A Perception-Based View of the Employee: A Study
of Employees’ Reactions to Change
DISSERTATION of the University of St. Gallen,
Graduate School of Business Administration, Economics, Law and Social Sciences (HSG)
to obtain the title of Doctor of Business Administration
submitted by
Chaiporn Vithessonthi
from
Thailand
Approved on the application of
Prof. Dr. Markus Schwaninger and
Prof. Dr. Günter Müller-Stewens
Dissertation no. 3040
D-Druck-Spescha, St. Gallen 2005
The University of St Gallen, Graduate School of Business Administration, Economics, Law
and Social Sciences (HSG) hereby consents to the printing of the present dissertation,
without hereby expressing any opinion on the views herein expressed.
St Gallen, January 20, 2005
The President:
Prof. Dr. Peter Gomez
i
Abstract
Drawing on several theoretical perspectives (e.g., individual motivation, behavioral
decision-making, social exchange theories, organizational justice theories, social cognition,
institutional theories and neoclassical economics theories) from different disciplines (e.g.,
organizational psychology, strategic management, and economics), this dissertation
developed a perception-based approach to examine a possibility that employees’ perceptions
and/or attitudes will be associated with their decisions in an organizational setting.
Specifically, this dissertation examined the effects of employees’ perceptions and/or
attitudes on their reactions to organizational change.
This dissertation addressed two major research questions relevant to organizational
change management, organizational behavior and applied psychology. First, it addressed a
question of what perceptions and/or attitudes influence employees’ resistance to change.
Second, it addressed a question of what perceptions and/or attitudes influence employees’
support for change? This was done by drawing on several theoretical perspectives and
examining relationships between perception and/or attitude variables and resistance to
change and support for change.
Based on data obtained from two samples of respondents from two different settings
(i.e., a downsizing in Study 1 and a privatization in Study 2), this dissertation found
significant relationships between perceptions and/or attitudes and resistance to change
and/or support for change. The findings provide some empirical support for the perception-
based view of the employee. Using multinomial ordered probit modeling, some perceptions
and/or attitudes were found to be significantly predictive of employees’ reactions to change.
The potential practical value of using perceptions and/or attitudes as predictors of
employees’ reactions to change is discussed, as are implications and suggestions for future
research.
ii
Acknowledgements
This dissertation began with a conversation with Professor Dr. Markus Schwaninger, a
professor of management at the University of St. Gallen, in the summer of 2003, when I was
about to finalize my master’s degree in international management at the same university.
During this conversation we discussed organizational change, and since I had thought that it
might make an interesting piece of research, I asked him about the possibility to write the
dissertation that lies before you today. As I expected, his response was clear, insightful,
interesting, and encouraging. He enthusiastically agreed to supervise my dissertation and
told me to proceed with my ideas. So it began.
I am reminded as I finalize these notes of my good fortune in being able to do
something I enjoy, and to complete my research. It is the rarest of privileges for me, with
my limited ability, to do that in a relatively short span of time; this seems tremendously
precious to me. But this work could not have been completed without support from many
people. I owe a debt of gratitude to the 315 respondents who took time out of their busy
schedules to complete and return the questionnaire. I am extremely grateful to Prof. Dr.
Markus Schwaninger, who has been not only the referee for this dissertation but also my
mentor throughout the past years, for offering his invaluable help, comments, perspectives,
and suggestions, and for showing great interest in my research. Undoubtedly, he has pointed
me in the direction of a fascinating landscape, not for the first time and, I hope, not for the
last.
I also want to express my sincere gratitude to Professor Dr. Günter Müller-Stewens,
who has magnanimously taken time out of his busy schedule to become the co-referee, for
offering his valuable insights and perspectives on the theoretical, methodological and
empirical aspects of my dissertation. I am very grateful to Dr. Klaus Edel as well, not only
for offering his valuable suggestions and solutions to statistical issues with enthusiasm, but
also for allowing me to use his computer and statistical applications. I am also grateful to
Silke Bucher, Bernd Beuthel, and Jasmina Hasanbegovic for their thoughtful and
constructive feedback on earlier versions of this dissertation. And, of course, I thank Linda
Roberts, my editor and proofreader, at Western Illinois University, who shouldered the
editorial and proofreading work on my unpolished lines of English. Last but not least, I
would like to thank my parents for their love, incredibly great confidence, and unbounded
support throughout the course of this journey and beyond.
Basel, January 2005 Chaiporn Vithessonthi
iii
Table of Contents
Abstract .....................................................................................................................................i
Acknowledgements ..................................................................................................................ii
List of Tables...........................................................................................................................vi
List of Diagrams and Figures ............................................................................................... viii
List of Abbreviations................................................................................................................x
1. Introduction .....................................................................................................................1
1.1. Research Issues ...........................................................................................................1
1.2. Research Questions.....................................................................................................3
1.3. The Importance of the Research Questions................................................................6
1.4. The Scope of the Dissertation.....................................................................................8
1.5. The Intended Contributions of this Dissertation.......................................................10
2. Core Concepts and Relevant Literature ........................................................................12
2.1. Theories of Change...................................................................................................12
2.2. Perceptions................................................................................................................16
2.3. Attitude .....................................................................................................................19
2.4. Emotion.....................................................................................................................21
2.5. Individual Decision-Making.....................................................................................23
2.6. Reactions to Change .................................................................................................27
3. Theoretical Development and Research Model ............................................................31
3.1. Perception-Based View of the Employee.................................................................32
3.2. Research Model and Hypotheses..............................................................................35
3.2.1. Perceived Organizational Support .....................................................................38
3.2.2. Perceived Procedural Justice..............................................................................40
3.2.3. Perceived Participation in Decision-making......................................................42
3.2.4. Perceived Need for Change ...............................................................................45
3.2.5. Attitude towards Organizational Change...........................................................48
3.2.6. Fear of Known Consequences of a Change .......................................................50
3.2.7. Fear of Unknown Consequences of a Change ...................................................52
3.2.8. Perceived Change in Power ...............................................................................54
3.2.9. Perceived Change in Status................................................................................56
3.2.10. Perceived Change in Pride .................................................................................58
3.2.11. Job Satisfaction ..................................................................................................60
3.2.12. Job Security........................................................................................................62
iv
3.2.13. Job Motivation ...................................................................................................64
3.2.14. Perceived Employability....................................................................................66
3.2.15. Self-Confidence for Career-Relevant Learning.................................................69
3.2.16. Affective Commitment ......................................................................................71
3.2.17. Trust in Management .........................................................................................73
3.2.18. Colleagues’ Reactions to Change ......................................................................75
4. Research Methodology..................................................................................................77
4.1. Context, Sample and Procedure................................................................................78
4.1.1. Study 1 – Context, Sample and Procedure ........................................................78
4.1.2. Study 2 – Context, Sample and Procedure ........................................................79
4.2. Alternative Methods of Data Analysis .....................................................................80
4.3. The Multinomial Ordered Probit Model...................................................................81
4.4. Measures of Theoretical Constructs .........................................................................83
4.4.1. Dependent Variables..........................................................................................83
4.4.2. Independent Variables .......................................................................................84
4.4.3. Control Variables ...............................................................................................87
4.5. Data Analysis Procedures .........................................................................................87
5. Results and Discussion..................................................................................................89
5.1. Study 1 – Results and Discussion.............................................................................89
5.1.1. Analyses of Correlations among Dependent Variables .....................................89
5.1.2. Analyses of Correlations among Independent Variables...................................90
5.1.3. Results for Hypotheses – The Multinomial Ordered Probit Models .................94
5.1.4. Discussion of Study 1 ......................................................................................106
5.2. Study 2 – Results and Discussion...........................................................................108
5.2.1. Analyses of Correlations among Dependent Variables ...................................109
5.2.2. Analyses of Correlations among Independent Variables.................................110
5.2.3. Results for Hypotheses – The Multinomial Ordered Probit Models ...............114
5.2.4. Discussion of Study 2 ......................................................................................127
5.3. General Discussion .................................................................................................131
5.3.1. Key Contributions of the Dissertation .............................................................131
5.3.2. Limitations to this Dissertation........................................................................136
5.3.3. Implications and Directions for Future Research ............................................138
5.3.4. Implications and Directions for Practice .........................................................139
6. Conclusions .................................................................................................................140
References ............................................................................................................................142
Appendices ...........................................................................................................................165
v
Appendix A: Questionnaire Survey Items for Studies 1 and 2.........................................165
Appendix B: Study 1 – Diagrams and Correlations .........................................................171
Appendix C: Study 2 – Diagrams and Correlations .........................................................195
Appendix D: Additional Regression Analyses for Study 2 ..............................................219
Curriculum Vitae..................................................................................................................236
vi
List of Tables
Table 1: Characteristics of Alternative Regression Models ...............................................81
Table 2: Study 1 – Correlations for All Final Variables.....................................................93
Table 3: Study 1 – Regression Results of Active Resistance to Change............................95
Table 4: Study 1 – Regression Results of Passive Resistance to Change...........................96
Table 5: Study 1 – Regression Results of Active Support for Change...............................97
Table 6: Study 1 – Regression Results of Passive Support for Change ..............................98
Table 7: Study 2 – Correlations for All Final Variables...................................................113
Table 8: Study 2 – Regression Results of Active Resistance to Change..........................115
Table 9: Study 2 – Regression Results of Passive Resistance to Change.........................116
Table 10: Study 2 – Regression Results of Active Support for Change.............................117
Table 11: Study 2 – Regression Results of Passive Support for Change ...........................118
Table 12: Summary of Results for Hypotheses in Study 1 and Study 2.............................132
Table 13: Study 1 – Correlations for All Dependent Variables..........................................182
Table 14: Study 1 – Correlations for Active Resistance.....................................................183
Table 15: Study 1 – Correlations for Active Resistance (cont.) .........................................184
Table 16: Study 1 – Correlations for Active Resistance (cont.) .........................................185
Table 17: Study 1 – Correlations for Passive Resistance ...................................................186
Table 18: Study 1 – Correlations for Passive Resistance (cont.)........................................187
Table 19: Study 1 – Correlations for Passive Resistance (cont.)........................................188
Table 20: Study 1 – Correlations for Active Support .........................................................189
Table 21: Study 1 – Correlations for Active Support (cont.)..............................................190
Table 22: Study 1 – Correlations for Active Support (cont.)..............................................191
Table 23: Study 1 – Correlations for Passive Support........................................................192
Table 24: Study 1 – Correlations for Passive Support (cont.) ............................................193
Table 25: Study 1 – Correlations for Passive Support (cont.) ............................................194
Table 26: Study 2 – Correlations for Dependent Variables................................................206
Table 27: Study 2 – Correlations for Active Resistance.....................................................207
Table 28: Study 2 – Correlations for Active Resistance (cont.) .........................................208
Table 29: Study 2 – Correlations for Active Resistance (cont.) .........................................209
Table 30: Study 2 – Correlations for Passive Resistance (cont.)........................................210
Table 31: Study 2 – Correlations for Passive Resistance (cont.)........................................211
Table 32: Study 2 – Correlations for Passive Resistance (cont.)........................................212
Table 33: Study 2 – Correlations for Active Support .........................................................213
vii
Table 34: Study 2 – Correlations for Active Support (cont.)..............................................214
Table 35: Study 2 – Correlations for Active Support (cont.)..............................................215
Table 36: Study 2 – Correlations for Passive Support........................................................216
Table 37: Study 2 – Correlations for Passive Support (cont.) ............................................217
Table 38: Study 2 – Correlations for Passive Support (cont.) ............................................218
Table 39: Summary of Regression Results of Indicators for Resistance to Change ..........223
Table 40: Summary of Regression Results of Indicators for Support for Change .............224
Table 41: Regression Results of Active Resistance to Change 1 .......................................225
Table 42: Regression Results of Active Resistance to Change 2 .......................................225
Table 43: Regression Results of Active Resistance to Change 3 .......................................226
Table 44: Regression Results of Passive Resistance to Change 1 ......................................227
Table 45: Regression Results of Passive Resistance to Change 2 ......................................228
Table 46: Regression Results of Passive Resistance to Change 3 ......................................229
Table 47: Regression Results of Active Support for Change 1 ..........................................230
Table 48: Regression Results of Active Support for Change 2 ..........................................231
Table 49: Regression Results of Active Support for Change 3 ..........................................232
Table 50: Regression Results of Passive Support for Change 1.........................................233
Table 51: Regression Results of Passive Support for Change 2.........................................234
Table 52: Regression Results of Passive Support for Change 3.........................................235
viii
List of Diagrams and Figures
Figure 1: Dimensions for Categorization of Reactions to Change ......................................29
Figure 2: A Categorization of Reactions to Change ............................................................30
Figure 3: Alternative Models Relating Perceptions and Reactions to Change ....................31
Figure 4: Conceptual Diagram of the ‘Direct Effects’ Model .............................................37
Figure 5: Five Stages of Organizational Decline .................................................................46
Figure 6: Summary of Measures of Reactions to Change....................................................84
Figure 7: Summary of the Sequence of Data Analysis ........................................................88
Figure 8: Study 1 - Indicators for Active Resistance to Change........................................171
Figure 9: Study 1 - Indicators for Passive Resistance to Change ......................................171
Figure 10: Study 1 - Indicators for Active Support for Change...........................................172
Figure 11: Study 1 - Indicators for Passive Support for Change .........................................172
Figure 12: Study 1 - Indicators for Perceived Organizational Support................................173
Figure 13: Study 1 - Indicators for Perceived Procedural Justice........................................173
Figure 14: Study 1 - Indicators for Perceived Participation in Decision-Making ...............174
Figure 15: Study 1 - Indicators for Perceived Need for Change..........................................174
Figure 16: Study 1 - Indicators for Attitude towards Organizational Change .....................175
Figure 17: Study 1 - Indicators for Fear of Known Consequences of a Change .................175
Figure 18: Study 1 - Indicators for Fear of Unknown Consequences of a Change .............176
Figure 19: Study 1 - Indicators for Perceived Change in Power .........................................176
Figure 20: Study 1 - Indicators for Perceived Change in Status ..........................................177
Figure 21: Study 1 - Indicators for Perceived Change in Pride ...........................................177
Figure 22: Study 1 - Indicators for Job Satisfaction ............................................................178
Figure 23: Study 1 - Indicators for Job Security ..................................................................178
Figure 24: Study 1 - Indicators for Job Motivation..............................................................179
Figure 25: Study 1 - Indicators for Perceived Employability ..............................................179
Figure 26: Study 1 - Indicators for Self-Confidence for Learning.......................................180
Figure 27: Study 1 - Indicators for Affective Commitment.................................................180
Figure 28: Study 1 - Indicators for Trust in Management ...................................................181
Figure 29: Study 1 - Indicators for Perceptions of Colleagues’ Resistance to Change .......181
Figure 30: Study 2 - Indicators for Active Resistance to Change........................................195
Figure 31: Study 2 - Indicators for Passive Resistance to Change ......................................195
Figure 32: Study 2 - Active Support for Change Indicators ................................................196
Figure 33: Study 2 - Indicators for Passive Support for Change .........................................196
ix
Figure 34: Study 2 - Indicators for Perceived Organizational Support................................197
Figure 35: Study 2 - Indicators for Perceived Procedural Justice........................................197
Figure 36: Study 2 - Indicators for Perceived Participation in Decision-Making ...............198
Figure 37: Study 2 - Indicators for Perceived Need for Change..........................................198
Figure 38: Study 2 - Indicators for Attitude towards Organizational Change .....................199
Figure 39: Study 2 - Indicator for Fear of Known Consequences of a Change...................199
Figure 40: Study 2 - Indicators for Fear of Unknown Consequences of a Change .............200
Figure 41: Study 2 - Indicator for Perceived Change in Power ...........................................200
Figure 42: Study 2 - Indicators for Perceived Change in Status ..........................................201
Figure 43: Study 2 - Indicators for Perceived Change in Pride ...........................................201
Figure 44: Study 2 - Indicators for Job Satisfaction ............................................................202
Figure 45: Study 2 - Indicators for Job Security ..................................................................202
Figure 46: Study 2 - Indicators for Job Motivation..............................................................203
Figure 47: Study 2 - Indicators for Perceived Employability ..............................................203
Figure 48: Study 2 - Indicators for Self-Confidence for Learning.......................................204
Figure 49: Study 2 - Indicators for Affective Commitment.................................................204
Figure 50: Study 2 - Indicators for Trust in Management ...................................................205
Figure 51: Study 2 - Indicators for Perceptions of Colleagues’ Resistance to Change .......205
x
List of Abbreviations
AR Active resistance to change
AR1 Indicator 1 for active resistance to change
AR2 Indicator 2 for active resistance to change
AR3 Indicator 3 for active resistance to change
AS Active support for change
AS1 Indicator 1 for active support for change
AS2 Indicator 2 for active support for change
AS3 Indicator 3 for active support for change
e.g. Exempli gratia; (for example)
etc. Et ectera (and so forth)
i.e. Id est; (that is)
IIA The independence of irrelevant alternatives
IPO Initial Public Offering
OLS Ordinary least square
PBV Perception-Based View (of the employee)
POS Perceived organizational support
PR Passive resistance to change
PR1 Indicator 1 for passive resistance to change
PR2 Indicator 2 for passive resistance to change
PR3 Indicator 3 for passive resistance to change
PS Passive support for change
PS1 Indicator 1 for passive support for change
PS2 Indicator 2 for passive support for change
PS3 Indicator 3 for passive support for change
S.E. Standard error
1
1. Introduction
1.1. Research Issues
The starting point for this research is the challenge of “managing change in organizations.”
Managing organizational change is problematic: situations in which changes are undertaken
are shifting, it is harder for organizations, and in particular top managers as well as change
agents, to prepare for and manage the change in ways that satisfy the demands of both the
organization and its employees.1 How do organizations go about making “structured” and
“unstructured” decisions concerning how to cope with resistance to change, so that they
achieve the goals of their organizational change efforts? It is not surprising that, over the
years, resistance to change has attracted increasing attention from researchers, practitioners,
and the general public. A great deal of research has focused on understanding the sources
and determinants of resistance to change. The media and the general public are generally
interested in various forms of active resistance to change such as strikes or protests. Other
forms of resistance such as passive resistance, although less observable, have not gone
unnoticed and thus have also warranted extensive research over the years.2 Not surprisingly,
resistance to change is frequently reported as being one of the sources of organizational
change failures (Coch and French, 1948; Kotter, 1995; Kotter and Cohen, 2002).
Broadly speaking, the concept of organizational change (e.g., Meyer, 1982; Nadler,
1998) refers to an effort or a series of efforts designed to modify certain aspects or
configurations of an organization: for example, identity, goals, structure, work processes or
human resources. Furthermore, ideas of organizational learning (e.g., Argyris, 1990; Argyris
and Schön, 1978; Fiol and Lyles, 1985; Crossan and Berddrow, 2003) or strategic flexibility
(e.g., Harrigan, 1985; Sanchez, 1995; Raynor and Bower, 2001) that emphasize the extent to
which a firm is capable of learning and adapting itself to changing environments are
associated with the antecedents and outcomes of organizational change. We can thus see
that the growing attention to these concepts has enhanced both the frequency and scale of
organizational change efforts. Hence, one can reason that the likelihood of employees facing
some type of organizational change is higher than ever before.
1 According to the institutional school of organizational thought, individuals in organizations have their own interests
and generally try to make use of organizations for their own interests. For a more detailed discussion of these
problems, see Selznick (1965) or Meyer and Rowan (1977). 2 To me it seems that we should distinguish between active resistance and passive resistance. This view is consistent
with those of Hultman (1998) and Judson (1991). For a more extensive discussion of reactions to change, see
Section 2.6 of this dissertation.
2
In addition to the greater level of exposure of employees to organizational change,
managers within most organizations are also experiencing greater internal and external
pressures to initiate change within their organization in order to maintain or improve firm
performance. These pressures include, for example, increased competitive pressures (Meyer,
Brooks and Goes, 1990), new government regulations (Meyer et al., 1990; Haveman, 1992;
Fox-Wolfgramm, Boal and Hunt, 1998), technological change (Haveman, 1992), or
declining firm performance (Bibeault, 1982).
Given the above-mentioned environments, research on organizational change has been
enriched by both empirical and theoretical studies investigating many aspects of
organizational change such as change strategies, change processes, or antecedents and
outcomes of different forms of change.3 To search for conditions that promote successful
change in organizations, it is crucial to know the implications or organizational change for
employees, and more importantly, the reactions employees will have. Much of the past
research on employees’ reactions to change seems to have been implicitly based on a
rational choice theory about employees’ behaviors4, thereby giving little attention to the
potential effects of perceptions, attitudes, or social influence on decisions and behaviors.
Indeed, rational choice theories5 have long dominated the research in organization theory,
which encompasses research on organizational change and development In their roughest
form, rational choice theories would assert that when organizational change efforts are
understood to be beneficial to a firm, employees in this firm should support such changes.
This raises the question of whether all employees do in fact share the same view on this
change. What are the implications for their decisions if they do not share the same view?
Within the large body of research on decision-making in the literature on strategic
management or management science, several concepts and underlying assumptions—for
example, cost-benefit analysis and human rationality—seem to have conditioned both the
theoretical and empirical research in organizational change and employees’ reactions to
3 Organizational change can be considered as a class of organization theory. 4 Note that it is important to understand choice theories and underlying assumptions about how people make choices
because any kind of reactions to change—for example, resistance to change and support for change—is an outcome
of choice-selection process. In its simplest form, the economic model of decision-making assumes that managers
have perfect information and thus could make decisions that maximize profits. For a critique of the economic model
of decision-making, see Simon (1957) and March and Simon (1958). For a more extensive discussion of the concept
of rationality, see Section 2.5 of this dissertation. 5 Simon (1978, 1985, 1986) pointed out that there are at least two main forms of human rationality in social science:
one of them is in an area of cognitive psychology; and the other is in an area of economics. In this dissertation,
unless stated otherwise, both rational choice theories and human rationality shall refer to the form of human
rationality in the field of neoclassical economics. It is important to note that in economics there are variations in the
concepts of rationality.
3
change. This view is consistent with that of Rumelt, Schendel, and Teece (1991), who have
suggested that the logic of economics has dominated the field of strategic management.
Only recently have researchers become aware of the limitations of decision-making models
in economics, and thus have applied a cognitive paradigm in their research on strategic
decision-making (e.g., Schwenk, 1984, 1995; Tversky and Kahneman, 1974).6
Employees who are confronted with changes in their organization face an inevitable
choice: whether they should support or resist such changes in order to still (or best) achieve
their personal goals and objectives. Despite a large body of normative literature on
techniques for managing change, for example, models of implementing change by Judson
(1991), Kotter (1995), Galpin (1996), and Kotter and Cohen (2002), empirical studies of
their application seem to be too sparse to indicate convincingly and conclusively whether
the techniques presented in those models have had significant influences on employees’
reactions to change. Because I do not share the views and assumptions of some prior
researchers7, this dissertation theoretically deviates from the mainstream research on change
management by introducing a perception-based view of the employee as an alternative
approach to understand employees’ reactions to change.
1.2. Research Questions
Researchers and practitioners alike posit that employees’ reactions to change have critical
implications for change implementation and firm performance (e.g., Kotter, 1995; Kotter
and Cohen, 2002). For instance, the issue of intraorganizational conflict as a serious
challenge for managers in making strategic asset decisions has been highlighted (Amit and
Schoemaker, 1993). The question of how firms, managers or consultants can minimize
employees’ resistance to change is a subject of debate and further research. There are a
number of theoretical and practical questions, some of which lie more in the area of
philosophy than in the area of change management or social science. In this dissertation I
am particularly concerned with the role of perceptions and attitudes and how these might
constitute determinants of employees’ reactions to change. These perceptions and attitudes
about change (e.g., perceived need for change, perceived change in power, and job security)
are theorized to be factors leading to subsequent conscious or unconscious decisions and/or
behaviors in response to changes in organizations, which may significantly impact the
6 For a more extensive discussion of decision-making, see Section 2.5 of this dissertation. 7 For a more extensive discussion of assumptions in prior studies and assumptions made in this study, see Section 3 of
this dissertation.
4
change implementation and firm performance. In particular, this dissertation attempts to
answer two research questions:
• What perceptions and/or attitudes influence employees’ resistance to change?
• What perceptions and/or attitudes influence employees’ support for change?
With the above research questions, I advance and test an argument that perceptions and/or
attitudes influence employees’ reactions to change. Rather than hindering or substituting for
current change management models where the main focus is on human rationality, well-
understood effects of perceptions and/or attitudes may actually promote more
comprehensive, effective and pragmatic change management models designed for
promoting employees’ support for change and/or for reducing employees’ resistance to
change. In response to seemingly limited empirical evidence on the effectiveness of most
change management models, well-understood effects of perceptions and attitudes on
reactions to change narrow the domain of potentially key factors influencing employees’
reactions to change to which an organization should pay attention. In addition, these
research questions are consistent with contemporary research on the role of psychological
factors in predicting employees’ behaviors in response to various types of decisions of
organizations, but the role of several psychological factors require empirical verification.
Thus, this dissertation attempts to fill a gap in current empirical research by empirically
examining relationships between several perceptions and/or attitudes on the one hand and
resistance to and support for change on the other hand.
Despite evidence that certain change management practices during organizational
change are related to employees’ resistance to and/or support for change rates (i.e., a
percentage of the total number of employees who support or resist a change to the total
number of employees) at the organizational level, it would be a fallacy to then assume that
such practices are similarly and/or directly related to employees’ resistance to and/or
support for change decisions at the individual level. Thus, it is critical to explain the
relationship between any type of change management practices and resistance to and/or
support for change at the individual level. The results in this dissertation may help scholars
explain such relationship by providing a connecting answer. Rather than answering the
question of the effect of change management practices on employees’ reactions to change
directly, empirical evidence of the role of perceptions and/or attitudes in predicting
employees’ reactions to change may promote a better understanding of psychological
factors influencing employees’ reactions to change. If certain change management practices
were found to influence these perceptions and/or attitudes, then such practices may thereby
5
have the effect on employees’ reactions to change. Thus, the findings in this dissertation add
to the change management literature by examining relationships between perceptions and/or
attitudes held by employees and their reactions to change. Given these research questions,
this dissertation has three major objectives.
• In order to provide foundations for developing a theoretical framework in this
dissertation, the first objective is to review prior research on perceptions, attitudes,
decision-making, theories of change, and employees’ reactions to change. It should
be noted that the literature review on decision-making focuses on the normative and
cognitive decision theories in the fields of management and economics.
• The second objective is to conceptualize a theoretical framework representing the
link between various perceptions and attitudes on the one hand, and resistance to
change and support for change, on the other hand. Here I propose to bring several
theoretical perspectives together, creating a more realistic model of employees’
reactions by combining different conceptions of human rationality. The main aim of
the research model is to investigate which perceptions and attitudes are associated
with resistance to change and/or support for change. Additionally, it aims to provide
theoretical and, perhaps, practical insights to organizations, top managers, as well as
change agents to assist them in developing tools that may detect and alter employees’
perceptions and attitudes in order to (minimize resistance to change and) optimize
support for change.
• The final objective is to empirically test the hypothesized relationships presented in
the research model by gathering and analyzing relevant empirical data in a systematic
way.
After having identified the main research questions, the next step is to decide the
appropriate level of analysis: employee, top manager, or firm level. To answer the research
questions above, the employee, not the firm, will be the unit of analysis in this dissertation.
Using the employee as the unit of analysis, one can explore a perception or attitude as a
predictor of employees’ reactions to change. Further, examination at the decision level of
analysis—that is to say, resistance to change and support for change—diminishes at least
two concerns. First by relating perceptions and attitudes rather than decision-making
process to reactions to change, casual ambiguity is not an issue since (1) the relationships
between perceptions and reactions to change are more direct; and (2) such analyses do not
have to deal with the extent to which an employee uses rational decision-making processes.
Second, to use the decision level of analysis, it is not necessary to assume that employees
6
consistently use specific processes across time or decisions, thereby allowing the notion that
different decision-making processes may be at work for each reaction to change.
Past research has posited that it is a key interest of a firm to appropriately deal with
resistance to change in order to achieve the goals of organizational change efforts (Coch and
French, 1948; Kotter, 1995; Kotter and Cohen, 2002). However, it is important to know
whether resistance to change always has a negative impact on change efforts and thus firm
performance, or whether there might at times be a counter-intuitive implication, i.e., a
positive effect, on change efforts and thus firm performance. Despite the claim that
resistance has a negative effect on change efforts and therefore should be minimized (e.g.,
Kotter, 1995; Kotter and Cohen, 2002), the question is, then, whether resistance to change
may be strategically valuable or positive when it acts as a means to ensure that the change is
indeed designed and implemented to promote an organization’s goals. Thus, one can
question the accuracy of the claim made by some researchers (e.g., Coch and French, 1948)
that resistance to change is always undesirable. This question seems to have gone unnoticed,
providing little recognition of the conditions under which resistance to change may result in
superior outcomes of organizational change. Although identifying conditions in which
resistance to change has positive or negative outcomes on change processes is not the goal
of this dissertation itself, it deserves mention so as to reflect on this issue.
In order to state that resistance to change always has negative implications for the
firm, one would have to show that such resistance can legitimately be considered negative at
any given moment and in any particular circumstance. If this same resistance does not
create a negative implication for the firm at another moment and in another similar
circumstance, one may not legitimately and precisely conclude that resistance to change is
always undesirable and negative. On the other hand, it is probable that resistance to change
may at times have a positive effect on the outcome of organizational change, and that it may
be strategically valuable to an organization. For example, it is imaginable that resistance to
change could be constructive by entailing a high degree of objective evaluation of the
change. This should suggest that researcher should not make the critical assumption that
resistance to change always has negative effects on the outcomes of organizational change.
Instead, they should investigate how to benefit from resistance to change.
1.3. The Importance of the Research Questions
Clearly, improved firm performance is one of the main objectives of organizational change,
but intermediate outcomes are more proximal indicators of its success or failure.
Employees’ performance can be considered as an immediate outcome or a path through
which changes in organizations affect firm performance. Therefore, one can also reason that
7
employees’ resistance to or support for change which are arguably predictive of their
performance at the time of the organizational change, can be seen as an indicator predicting
the probability of success of the change (Kotter, 1995; Kotter and Cohen, 2002). Thus, the
optimization of resistance to change and support for change may enhance the probability of
success of organizational change, thereby improving firm performance. In order to optimize
these levels of resistance to change or support for change, we need to understand the factors
that play an important role in creating or changing them. In this dissertation I focus on the
direct relationships between perceptions and attitudes on the one hand, and resistance to
change and support for change on the other hand. This perspective assumes that employees’
perceptions and attitudes are likely to influence their reactions to change. I take this a step
further by proposing that if we know which perceptions or attitudes affect levels of
resistance to change and support for change, we will then have opportunities to develop
tools to properly influence reactions to change.
Although individual decision-making processes are not programmed, they are
programmable (Mintzberg, Raisinghani and Theoret, 1976): the underlying basis of this
argument is that strong evidence indicates that a basic logic or structure underlies the
actions of a decision-maker and that this structure can be identified by a systematic study of
his or her behavior8. If individuals have patterns of decision-making processes, the study of
employees’ reactions to change may yield some valuable insight. That is, if certain
perceptions or attitudes are associated with certain decisions at a given moment and in a
particular setting, the same pattern of relationships may persist at other moments and in
other settings.
One assumption in this dissertation is that employees’ decisions are based on their
interpretation and evaluation of the data available to them. As this data is collected and
interpreted, different employees may arrive at different perceptions, interpretations and
understandings of the same data. Consistent with Simon’s (1957) concept of ‘bounded
rationality’ in decision-making processes9, I argue that there are potential gaps between the
object’s (e.g., organizational change’s) ‘objective’ (what they actually are) characteristics
and ‘perceived’ (what people believe or perceive them to be) characteristics, and that the
8 Note that in this dissertation, words like “decision”, “behavior”, or “reaction” are used interchangeably since they all
refer to an employee’s resistance to change and/or support for change. In its simplest form, one may find that
resistance to change and support for change can be considered as one kind of decision, and that both resistance to
change and support for change are expressed in terms of behaviors or reactions. 9 Simon (1957) has discussed the two main problems with the economic model of decision-making; first, managers
seldom have perfect information and thus often have to make decisions under uncertainty. Second, managers are not
cognitively capable of processing all of the information that they would need to make a profit-maximizing decision.
Therefore, Simon (1957) has introduced the concept of “bounded rationality” for the model of decision-making.
8
‘perceived’ characteristics rather than the ‘objective’ characteristics are used as inputs in the
decision-making processes determining decisions. Thus, perceptions of the object play an
important role in decision-making processes and result in decisions that at least partially
reflect these perceptions.
As I reflect on economic theories that seem to explain well the utilitarian side of
human behavior, but seem to fail to explain the side of human behavior that goes beyond
outcome-driven self-interest, I want to explore an alterative approach in understanding
employees’ reactions to change, and label this approach the “perception-based view of the
employee.” In short, using perception-based logic, this dissertation focuses on the role of
perceptions and attitudes as the driving forces leading employees to either support or resist
organizational change. Understanding the ways in which employees react to change will
certainly provide a potential avenue for developing new change management strategies that
may bring employees’ perceptions into alignment with ones desired, thereby eliciting
desired reactions to change.
1.4. The Scope of the Dissertation
Obviously, the field of organizational change and its scientific investigation is manifold. For
instance, archetypes of a firm’s organizational change can be neatly classified into five
groups or dimensions: (1) identity; (2) strategy; (3) business processes; (4) structure; and (5)
human resources. Each of these dimensions has different implications for an organization as
well as its employees.10
In view of the fact that organizational change can take on many forms, this dissertation
focuses on two aspects of organizational change: “downsizing,” which can be subsumed
into the “firm structure” dimension, and “privatization.” which is part of the “firm strategy”
dimension.11 In Study 1, a downsizing effort was chosen because this kind of change
typically has direct and significant implications for employees, who directly experience the
effects of these changes. For example, employees may have to increase their productivity
(Hambrick & Schecter, 1983) or risk losing their jobs. Further, downsizing has often been
employed as a means to improve firm performance (Freeman & Cameron, 1993).
Additionally, firms in a crisis situation often downsize as part of their turnaround strategies
(Robbins & Pearce, 1992; Appelbaum, Everard & Hung, 1999). Similarly, there were
10 Donaldson (1987) pointed out that organizational change can be thought of as an adjustment of strategy, structure,
or processes of an organization. For a more extensive discussion of organizational change, see Section 2.1 of this
dissertation. 11 It is noteworthy that from different perspectives, any kind of organizational change can be classified into more than
one category.
9
numerous reasons for choosing privatization as a context of the study. First, many state-
owned enterprises in several countries are, or will eventually be, in a process of
privatization, and this privatization has several implications for markets, other firms, and
their employees. Second, in addition to being a change in itself, privatization is also a source
of other changes within an organization—for example, changes in corporate strategies and
corporate structures. Consequently, it is important to note that a study of employees’
reactions to privatization not only has to deal inclusively with reactions to privatization but
also with reactions to a set of changes that come along with the privatization initiative in a
broader sense.
This dissertation aims to develop a research model which suggests relationships
between perceptions and attitudes on the one hand and resistance to change and support for
change on the other hand, and to empirically test it by using data gathered from employees
currently facing organizational change. The number of variables examined in this
dissertation is limited predominantly due to two key reasons: theoretical aspect (the greater
the number of variables in the model, the less the degree of parsimony of the model), and
practical aspect (the greater the number of variables in the model, the lower the response
rates in the survey).
This dissertation focuses on empirical evidence gathered at a particular point in time
from employees in two organizations. In Study 1, a survey was distributed to a random
sample of 100 teachers at a large private school in Thailand where the management has
recently decided to reduce the number of teachers. Of those sampled, 91 teachers returned
the surveys (91% response rate). In Study 2, a survey was distributed to 500 employees at a
large state-owned company in Thailand where top managers have attempted to privatize the
organization. Of those sampled, 224 employees returned the survey (44.8% response rate).
The focus of this dissertation is strictly limited to the examination of the relationships
between perceptions and attitudes on the one hand and reactions to change on the other hand
at the given moment in time rather than during different points in time. Thus, it is not a
longitudinal study. This implies that these studies did not investigate feedback-loops or a so-
called dynamic model12 that addresses: (1) the effects of employees’ resistance to and
support for change on the change efforts (e.g., the change goals and processes); and (2) the
perceptions of the modifications in organizational change efforts at time t1 as a consequence
of employees’ reactions at time t0 on their reactions to such modifications at time t1. One
12 As March (1955) pointed out problems in determining influence order, one may consider that the influence
relationships in this dissertation may represent closed-loop systems. For a detailed discussion of this issue, see
March (1955).
10
reason why this dissertation does not include the feedback-loops model concerns the casual
link between perceptions or attitudes, and reactions to change. If we were to find such a
relationship at one moment in time, then we might expect to find that relationship at another
moment in time. Another reason concerns the practical aspect of developing and validating
the feedback-loops model using data from the questionnaire surveys: this would require not
only comparing results of different surveys but also gathering data from the same
respondents at different times, which would be too problematic or beyond the scope of this
study.
It is important to note that the nature and magnitude of the impact of organizational
change on employees depends on, among other things, the type of change and the way in
which the change is introduced. For example, changes can be initiated either from top
management (a so-called top-down approach) or from employees (a so-called bottom-up
approach). Because I assumed that the strength of the impact of the change was inherently
expressed in the perceptions of the employees, it was not necessary to separately explore the
effects of the change on the employees, or distinguish how the changes were introduced.
However, because the changes studied in this dissertation entailed organization-specific,
situation-specific, time-specific, and relationship-specific contexts, the extent to which the
findings can be generalized to other contexts is limited. It is also useful to note that the
implications of cultural differences on reactions to change are not within the scope of this
dissertation. Thus, the examination of relationships between predictors and outcomes within
one culture (Thailand) is conducted.
1.5. The Intended Contributions of this Dissertation
The principal thesis that emerges from the research model is that employees who are
confronted with any form of organizational change tend to develop the initial and
subsequent reactions to this change through a variety of decision-making processes.
Consistent with the bounded rationality framework (Simon, 1957), this dissertation further
argues that certain perceptions and attitudes enhance or prohibit their choices of reactions to
change.
Specifically, this dissertation focuses on employees’ perceptions and attitudes in a
downsizing situation (in Study 1) and a privatization situation (in Study 2). These
perceptions and attitudes are theorized to be factors leading to subsequent conscious and/or
unconscious decisions and/or behaviors in response to the changes, which may significantly
impact the change implementation and firm performance. This dissertation attempts to
contribute to the research on organizational change, especially employees’ resistance to
change and support for change, in three ways.
11
First, this dissertation examines a variety of actions that employees may choose in
response to a change in the organization. Drawing upon prior research, it identifies two
primary types of employees’ reactions to change: resistance to change and support for
change. These are further divided into: active and passive resistance, and active and passive
support.
Second, using perception-based logic, this dissertation examines a number of
perceptions and attitudes that may influence employees’ choice (conscious or unconscious)
to support or resist change, thus shedding light on whether perceptions and attitudes impel,
impede or exert no effect on employees’ behavior and decisions. Although the
organizational change literature is rich, there seems to be a surprising gap in the literature
concerning the role and nature of employees’ perception of change in organizations. In
particular, this dissertation aims to contribute in this area by examining the link between
various perceptions and attitudes on the one hand and resistance to change and support for
change on the other hand. Consensus on these issues will allow theories of employees’
reaction to change to move forward in a systematic fashion.
Third, based on the findings in this dissertation, it is probable that we will be able to
develop a variety of tools for predicting employees’ reactions to change. More importantly,
understanding the ways in which employees establish certain reactions to change will
provide a potential avenue for developing a range of change management strategies that
may bring employees’ perceptions in alignment with those desired, thereby strengthening
the degree to which employees support organizational change. Specifically, the key findings
are mainly relevant to the design, implementation, and closing phases of change
management strategies in Thailand. Nonetheless, it goes without saying that part of the
knowledge derived from the present dissertation will be applicable and transferable to firms
in other geographical settings and industries wishing to introduce a change, any change, to
their organization.
The findings in this dissertation will also be informative for consultants, as a way to
improve the current change management practices in dealing with employees’ resistance to
change. As discussed earlier, employees’ resistance to change is reported to be a source of
problems for organizations and has subsequent negative effects on firm performance.
Understanding employees’ perceptions and attitudes before, during, and after the
implementation of organizational change may prove to be valuable to firms, managers, and
consultants.
12
2. Core Concepts and Relevant Literature
This section discusses the central tenets of theories of change, perception, attitude, emotion,
individual decision-making, resistance to change and support for change, focusing on the
core theoretical and empirical arguments. It is important to note that I neither seek to
provide an exhaustive literature review, nor seek to explicitly review an extended list of the
critiques of the core arguments previously made. This narrow focus is deliberate, for my
purpose is to concisely outline the main tenets of concepts and theories concerning these
topics, to assess how they are conceptualized, to provide a basis for establishing the link
between key concepts, and to develop my research model.
2.1. Theories of Change
There are several relevant questions concerning change. What is it? Why do firms need to
change? Under which conditions will firms initiate changes in their organization? What
kinds of outcome will a change bring to firms? Certainly, these questions already suffice to
show that there is need for research on organizational change.13 The wide range of past
research on organizational change has focused on four main categories. One category has to
do with content issues, and it mainly focuses on factors related to successful or unsuccessful
change attempts (e.g., Hofer 1980; Bibeault, 1982; Hambrick and Schecter, 1983; Barker
and Duhaime, 1997). Another category concerns process issues, mainly focusing on steps,
phases, or actions undertaken during the implementation of an intended change (e.g.,
Judson, 1991; Kotter, 1995; Galpin, 1996). An additional category deals with context issues,
focusing on internal or environmental forces or conditions affecting a change in an
organization (e.g., Schendel and Patton, 1976; Slatter, 1984; Robbins and Peace, 1992). The
final category concerns reaction issues, and it focuses on employees’ responses to
organizational change (e.g., Weiss and Cropanzano, 1996; DeWitt, Trevino, and Mollica,
1998; Patterson and Cary, 2002).
The literature suggests several internal and external factors that lead a firm to
commence a change. Examples of these factors include: (1) increased competitive pressure
(Meyer, Brooks and Goes, 1990); (2) new government regulation (Meyer et al., 1990;
Haveman, 1992; Fox-Wolfgramm, Boal and Hunt, 1998); (3) technological change
(Haveman, 1992); and (4) management team change (Castrogiovanni, Baliga and Kidwell,
1992).
13 As mentioned earlier, research on organizational change is one of the areas in organization theory research.
13
Firms that undertake change, any change, in their organization often aim to improve
their performance in terms of, for example, higher profits, better responsiveness to the
market, and long-term competitive advantage. For example, past studies on corporate
turnaround (e.g., Hofer 1980; Bibeault, 1982; Hambrick and Schecter, 1983; Barker and
Duhaime, 1997) have found several actions or strategies that can revive the troubled firms
through corporate turnaround. We can thus conclude that the real value of organizational
change rests on its ability to alter an organization’s identity, strategy, structure, operation or
human resources as a means to enhance firm performance.
Now let us consider the characteristics of change. Change is defined as a movement
away from a current state toward a future state (George and Jones, 1995). In the
organizational change literature, at the abstract level, there are two distinct modes of
change: first- and second-order change. The phrase “first-order change” is used to describe
organizational changes that occur within a relatively stable system that remains mostly
unchanged; and for a system to remain stable or unchanged, it requires frequent first-order
changes (Weick and Quinn, 1999).14 On the contrary, second-order change or so-called
episodic change modifies or transforms fundamental structures or properties of the system
(Weick and Quinn, 1999). The concept of first- and second-order change is very popular
and powerful, and its fruits have been many. To give but a brief sample of some of the
works that have benefited from this concept, it has advanced several theoretical models such
as Argyris and Schön’s (1979, 1996) single- and double-loop learning by individuals, Miller
and Friesen’s (1984) adaptation vs. metamorphosis by organizations, and Tushman and
Anderson’s (1986) competence-enhancing vs. competence-destroying changes in
technology. In summary, there are several patterns or types of change (Miller, 1980;
Johnson-Cramer, Cross and Yan, 2003): small or large (Ledford et al., 1989), planned or
emergent in nature (Johnson-Cramer et al., 2003), radical or incremental (Weick and Quinn,
1999).
Another aspect of change is that it can occur at differing organizational levels. First,
change can occur within a population of organizations. For example, changes occurring at
an industry level (e.g., changes in customers’ demands and preferences) have implications
for most, if not all, companies within the industry. Similarly, changes occurring at a country
level have implications for most, if not all, organizations within the country. In addition,
changes can occur in a single organization, having implications for the whole organization
14 As the phrase “continuous change” is used to describe organizational changes that tend to be ongoing, cumulative,
and evolving (Weick & Quinn, 1999), the terms “first-order change” and “continuous change” seem to be used
interchangeably.
14
or for specific parts of the organization. Last but not least, changes can occur at the level of
individuals within an organization—that is, at the level of employees or managers. The
important point for us to observe is that changes at differing levels may share some common
characteristics but may also possess certain unique characteristics.
One of the central issues of organizational change concerns the ability of the
organization to enact change.15 The ability may be partly limited by organizational inertia;
that is, the organization may not be inclined to search for new solutions (Meyer and Rowan,
1977; Zucker, 1987). This raises the question of whether organizations can change
themselves.16 That is a difficult question, and no single answer will adequately answer it.
My answer is that they cannot, due to the fact that from a legal perspective, an organization
is a non-human entity; therefore, we can argue that it is not the organization that changes
itself but rather the people in the organization that change themselves and thereby change
the organization. But this leads to the question of whether an organization’s capability to
adapt is conditioned by its employees’ capability to adapt, which may be determined by the
levels of inertia at the individual level.
Research has been done on organizational inertia, which examines the role and impact
of organizational inertia on organizational structure and design.17 In the organizational
inertia literature, it is argued that various factors generate several forms of inertia in the
organization (e.g., strategic, structural, or cultural inertia). Organizational change may be
limited by internal factors such as an organization’s investments18 in plant, equipment, and
specialized personnel (Hannan and Freeman, 1989). It is also possible that top managers or
decision makers may receive limited or insufficient information to the extent that they may
15 The question concerning the degree to which organizations or managers can change the ways organizations work in
response to changes in their operating environments is one of the main questions in the organization theory research.
There are two contrasting views: The first perspective is that organizations or individuals in organizations can
undertake a surveillance of their environments and change their internal properties to promote their survival. The
second view is that organizations or individuals in organizations are constrained by limitations to the possibility for
change. 16 It should be noted that this question is different from the question of whether organizations change or not. A key
difference between them concerns who is an actor or initiator of organizational change. The former question focuses
on whether organizations can be the ones who make organizational change, whereas the latter question focuses on
whether organizations, as an object, can be changed. To the latter question, prior research has suggested that
organizations do change certain aspects such as strategies or structures (Zajac and Shortell, 1989). 17 For an extensive discussion of organizational inertia, see Arrow (1974), Hannan and Freeman (1984, 1989), or
Perrow (1986). 18 In economics theory these investments can be considered sunk costs.
15
fail to make a decision on organizational change or adaptation.19 If internal politics exist in
an organization, they may also contribute to organizational inertia; that is, political
disequilibrium in an organization may lead to resistance towards certain proposed changes.
Indeed, most organizational changes are designed to benefit the organization as a whole;
and these benefits are likely to take time to be realized; however, any political resistance
within the organization generates short-run political costs that may either exceed the
potential benefits or be high enough that top executives may decide against the intended
change (Hannan and Freeman, 1989).20 Likewise, external factors such as the dynamics of
political coalitions, costly or limited information with regard to relevant environments, and
legal and other barriers to entry or exit from the market may also restrict the nature and
degree of organizational change or adaptation in organizations (Hannan and Freeman,
1984).
Research on organizational change has led to various views and perspectives.
However, there are at least three most prominent views on organizational change. The first
view, based on population ecology theory,21 argues that most of the variations in
organizational structures occur through the creation of new organizations and organizational
forms, and the demise of old ones (Hannan and Freeman, 1977, 1989; Freeman and Hannan,
1983). According to Hannan and Freeman (1989), this perspective, which may be called
“selection theory,” argues that existing organizations, particularly the largest and most
powerful ones, seldom change their strategy and structure quickly enough to keep up with
the demands of uncertain and changing environments. The second view, based on random
transformation theory, proposes that endogenous processes induce structural changes in the
organizations, but the changes are loosely associated with the goals of the organization and
the demands of the uncertain and changing environments (March and Olsen, 1976; Weick,
1976). The third view, based on the rational adaptation theory developed by March and
Simon (1958), argues that organizational variability generates changes in strategy and
structure of organizations in response to threats, opportunities, and environmental changes.
19 This proposition is consistent with Simon’s concept of bounded rationality. For more complete details, see Simon
(1957). 20 From the political and institutional perspectives, it is difficult to enact changes in organizations without a major
organizational crisis. For a detailed discussion on this issue, see Fligstein (1996) or Myer and Rowan (1977). 21 Population ecology theory, which is based on biological theory, especially Darwinian natural selection theory, was
developed in response to a growing dissatisfaction with and critiques on the adaptation and strategic contingency
models.
16
There are some variations in this view. For example, strategic contingency theories22 focus
on structural changes that match organizational structures (Thompson 1967), whereas
resource dependence theories23 focus on structural changes that neutralize sources of
environmental uncertainty (Pfeffer and Salancik, 1978).
In summary, as the review of the literature has shown, organizational change,
regardless of its form, will have implications for the organization as well as its employees.
Simon (1991: 32) noted that “employees, especially but not exclusively at managerial and
executive levels, are responsible not only for evaluating alternatives and choosing among
them but also for recognizing the need for decisions.” Accordingly, it is useful to understand
how employees view and react to organizational change. In support of this view, the main
focus of this dissertation is on the implications of organizational change for employees
rather than for organizations and, specifically, on how employees respond to organizational
change.
2.2. Perceptions
As this dissertation will deal to a high degree with perceptions and reactions to change, it is
especially important to elaborate on the nature and implications of perceptions on decisions.
Although research on perceptions is rich and comprehensive, the intent of this literature
review is not to present an exhaustive list of extant definitions of perception. Instead, my
intent is to establish two key points. First, perception, as a psychological construct, is
associated with other constructs such as attitude or emotion. Despite the differences among
these constructs, most, if not all, of them seem to share common properties that shall be
seen later. Second, perceptions influence the ways in which humans understand the world
around them and how they make decisions. With deeper insights into how people
understand the world, we can better comprehend the ways in which humans make decisions
and why they behave in certain ways.
First of all, what is perception? Perception can be defined as a “complex process by
which people select, organize, and interpret sensory stimulation into a meaningful and
coherent picture of the world” (Berelson and Steiner, 1964: 88). In the same vein,
perception is “about receiving, selecting, acquiring, transforming and organizing the
22 The strategic contingency theory assumes that owners and managers of organizations establish organizations that
allow them to monitor the goals and procedures in the organization so that they will be able to respond to external
problems. See Thompson (1967) for a theoretical approach along these lines. 23 Slightly different from the logic of the strategic contingency theory, the resource dependency theory argues that
managers strategically create organizational structures and procedures that help organizations mitigate the effects of
external environments on the organization. See Pfeffer and Salancik (1978) for more complete references.
17
information supplied by our senses” (Barber and Legge, 1976: 7). The research on
perceptions can be traced back to Bartlett’s (1932) influential works on the constructive
nature of cognition, which argues that schematic thinking dominates human perception in
ways that human generic beliefs about the world influence and shape information processes.
Several researchers (e.g., Allport, 1954) have extended Bartlett’s (1932) work and have
advanced our understanding of perception, attitude, judgment, and several other concepts.24
The preceding discussion has suggested that from a psychological perspective,
individuals’ perceptions have a directive influence upon their decision-making and the
outcome of their decisions; thus, it is not surprising that organization theorists are now
interested in relationships between perceptions and various aspects of organizations. For
example, a work by Anderson and Paine (1975) has posited the influences of the perception
of uncertainty in the environment on the perception of the need for change in a firm’s
strategies.
The research on the roles and effects of perceptions on people’s decisions and
behaviors is yet to be completed, and the search for a better understanding of various
perceptions on employees’ behaviors such as turnover or commitment in the field of human
resource management continues its momentum. However, empirical research has begun to
show that in organizational settings, certain perceptions such as the perception of
uncertainty are associated with people’s behaviors. An empirical study by Ashford and
colleagues (1989), for example, has shown evidence for a positive relationship between
perceived job insecurity and intention to quit. Another empirical study by Eisenberger,
Fasolo and Davis-LeMastro (1990) has demonstrated that employees’ perceived
organizational support is related to various attitudes and behaviors. In a more recent study,
Gopinath and Becker (2000) found that perceived procedural justice concerning the
divestment activities of the firm is positively related to post-divestment commitment to the
firm.
Thus far, I have dealt with a holistic review of perceptions. However, the discussion of
the general concept of perceptions would be incomplete without mentioning two other
related concepts – recognition and action. The concept of recognition deals with the ability
to discriminate among familiar classes of objects,25 and it is related to the concept of
categorization. Thus, at an abstract level, recognition is one’s ability to place objects in a
24 Note that the dominant assumption in much of human perception is that one’s schematic preconceptions drive his or
her evaluations of, and reactions towards, an object. We will come back to this issue in later chapters. 25 For a detailed discussion of the concept of recognition, see Langley and Simon (1981).
18
category.26 To understand the relationship between recognition and categorization, it is
necessary to consider how humans make sense of reality in a complex world. Perhaps the
key answer to this question is the assertion in psychology that in an attempt to make sense
of a complex world, humans often construct and use categorical representations to simplify
and streamline the perception process (Fiske and Taylor, 1984, 1991; Gilbert and Hixon,
1991). In psychology, the term “categorization” is typically regarded as a process in which
people group together objects and/or things (Zentall, Galizio, and Critchfield, 2002). Within
psychology literature, there are several theories of categorization, for example, exemplar
models (Brooks, 1978) and decision bound theory (Ashby and Gott, 1988).
The other relevant concept in connection with perception is “action.” Action refers to
one’s activities such as moving the body in response to the perceptual process. As pointed
out by Argyris (1999), humans possess certain kinds of mental programs on how to act
effectively in different types of interaction; and there are two theories of action that humans
hold. The first one is normally expressed in the form of stated beliefs and values. The
second one is actually used and can thus only be inferred from observing their behaviors.
Up to now, most people studied have a theory-in-use, which is called Model I (Argyris,
1999).27 Model I theory-in-use requires defensive reasoning (Argyris, 1999). In his view,
individuals tend to keep their premises and inferences tacit for fear that they may lose
control, and the use of defensive reasoning prevents questioning the defensive reasoning.28
The consequences of the model of the theory-in-use strategies are that defensiveness,
misunderstanding, and self-fulfilling and self-sealing processes are more likely (Argyris,
1999).
If perceptions are derived from or based on incomplete information and limited
observation, perceptual biases will occur, and thus affect a person’s decisions and actions.29
But what is the point of getting to know the concept of perception? Here, it is the contention
that several perceptions of change are acting as determinants of employees’ reactions to
26 The term “category” typically refers to the totality of information that one has in mind about various groups of
objects (Smith, 1998). 27 In short, Model I theory-in-use (Argyris, 1982, 1990, 1993, 1999; Argyris & Schön, 1996) has four governing
values: achieve your intended purpose; maximize winning and minimize losing; suppress negative feelings; and
behave according to what you consider rational. 28 This is because most people who follow Model I theory-in-use employ the following prevalent action strategies:
advocate your opinion; evaluate the thoughts and actions of others (and your own thoughts and actions); and
attribute causes for whatever you are trying to understand (Argyris, 1999). 29 Individuals do not see or receive everything that happens in a particular situation. More importantly, they tend to be
selective in what they attend to and what they perceive. This selectivity in the perceptual process leads to the
tendency or bias to perceive one thing and not another. This is called “perceptual bias.”
19
change. That is, humans usually try to make sense of what has happened, what is happening,
and what will happen. A number of researchers have noted a link between the perceptual
process and the interpretation of information; they have argued that the interpretation of
information is based on the perceptual process (e.g., Anderson and Pained, 1975). Further,
during organizational change processes, employees create their own perspectives and
interpretations of what is going to happen, what others are thinking, and how they
themselves are perceived. Additionally, if there is a lack of information about the change,
then evidence of employees’ own perspectives and interpretation of the change is more
likely to be observed (Coghlan, 1993).
2.3. Attitude
Like the preceding discussion of human perceptions that has given an overview of how
humans perceive and make sense of the world, this section discusses how research on
perceptions has advanced our understanding of attitude(s). In psychology, attitude has been
examined extensively for a long period of time. The main focus of research on attitudes
concerns the nature and function of attitudes and how individuals construct them. The
application of current knowledge on attitude to business settings and the implications of
attitude for individuals’ decisions and behaviors are of interest in this dissertation. This
dissertation asserts that employees’ attitudes can influence their predisposition to formulate
a pre-determined response to a change.
The definitions of attitudes have been many. In social psychology, the term “attitude”
refers to an individual’s preference for or disinclination toward an idea, issue, item or
object; it is subjective in nature, and can be positive or negative. There are three other
definitions that have influenced subsequent studies on attitude.30 One definition is that
attitude is “the affect for or against a psychological object” (Thurstone, 1931: 261). Another
definition that seems to be more comprehensive is that attitude is “a mental and neural state
of readiness, organized through experience, exerting a directive or dynamic influence upon
the individual’s response to all objects and situations with which it is related” (Allport,
1935: 8). A final definition that is slightly different from Thurstone’s (1931) is that attitude
is “a disposition to react favorably or unfavorably to a class of objects” (Sarnoff, 1960:
261). There are two important aspects of attitude: one of them is a belief aspect that uses
cognitive processes to describe an object and its relation to other objects, the other is an
affective aspect that leads to liking or disliking an object (Katz, 1960).
30 For a detailed review of attitudes, see Greenwald and Banaji (1995).
20
Another fundamental question in the research on attitudes is about how individuals
acquire attitude. In psychology, attitudes arise from concepts, which are constructed through
experience; and concepts become attitudes though a process in which an evaluative aspect is
added on to them (Rhein, 1958). To understand the role of attitude in human behavior, a
model by Fishbein and Ajzen (1975) has suggested that: first, an individual’s positive or
negative beliefs about an object form an attitude towards that object; second, this attitude
determines the individual’s intention to behave with respect to the object; and finally, this
intention to behave is related to the actual behaviors acted.
Given this observation, we may assume that attitudes towards organizational change
tend to result in pre-determined intentions to behave and then subsequent behaviors. In this
sense, managers and/or employees who have a negative attitude towards organizational
change are more likely to resist efforts to change. In the same way, it is probable that
managers or employees who have a positive attitude toward organizational change are more
likely to support efforts to change.
There are two basic assumptions guiding the directions of research on attitude. The so-
called traditional view assumes that attitudes are dispositional in nature. According to the
dispositional approach, the so-called traditional view, attitudes are seen as stable
dispositions that have developed within the individual. In its roughest form, this view
emphasizes the role of an individual’s disposition to the development of attitudes (Salancik
and Pfeffer, 1978). A more recent theory, developed in the late 1970s, can be seen as a
breakaway from the traditional view on how attitudes are formed is based on the assumption
that attitudes are situational in nature. According to this approach, attitudes are viewed as
reactions to social situations that change when social context changes (Salancik and Pfeffer,
1978). For instance, the social information processing perspective (e.g., Salancik and
Pfeffer, 1977, 1978) asserts the role of social information on the behavioral reactions of
individuals to situations. Both predictions may help us gain insights into how humans
acquire and change their attitudes. By considering the two different views, whether attitudes
are dispositional or situational in nature, my main conclusion is that the two views
complement one another. Attitudes may be stable dispositions, but may be influenced by
social situations.
There is also the question of whether attitudes are conscious or unconscious in nature.
Recent research, which has suggested that attitudes are conscious in nature, has been
implicitly embedded in much of the prior research on attitudes (Greenwald and Banaji,
1995); and most of the previous studies have focused on conscious cognitive involvement in
debate judgments and decisions. On the contrary, another group of researchers has begun to
recognize the unconscious aspect of attitude. The key proposition of this stream of research
21
is that there is an implicit operation of attitudes.31 By acknowledging both implicit and
explicit operations of attitudes, we can assert that humans’ attitudes can influence thinking,
decision-making and behaviors in situations in which people recognize the existence of their
attitudes as well as in situations in which they do not recognize the existence of their
attitudes.
2.4. Emotion
Because the human rationality approach to decision-making in economics has dominated
much of the research on organization theory for years (Ashkanasy, Härtel and Daus, 2002),
empirical research on the effects of emotion on decision-making and behavior in the field of
management has been limited. Therefore, we can reason that because of the predominance
of the rational choice models, the concept of emotion has been largely unnoticed or ignored
for some time in the mainstream research in management science. Whereas there is a
relatively sparse body of management literature dealing with emotion, research on emotion
in the field of psychology has been voluminous.
Research on emotion has a long history, perhaps starting with Charles Darwin’s book
The Expression of the Emotions in Man and Animal (1872). Since then, the development of
the literature on emotion has lead to at least four prominent perspectives: the Darwinian, the
Jamesian, the Cognitive, and the Social-Constructivist.32 All of these approaches have
attempted to provide answers to the same fundamental questions, for example, what is
emotion, and how does it evolve? This literature review will not discuss each of the key
questions in light of the different perspectives. In fact, it will only touch on certain aspects
of the last two. Since my objective is to give only a brief overview of the research on
emotion and underpin arguments for my research model, this literature review will take us
through the research on emotion in the simplest form.
The term “emotion” has been defined as “a relative short-term positive or negative
evaluative state that involves neurophysicological, neuromuscular, and cognitive
components” (Kemper, 1978). Although in the psychology and sociology literature, there
seems to be little consensus concerning the meaning of emotion and related terms such as
mood, feeling, and sentiments (Kemper, 1987), it is beyond scope of this paper to offer a
new definition. For that reason I shall simply review the role of and influence of emotion on
31 There has recently been some debate over the views on conscious or unconscious aspects of attitudes. The
traditional view does not make an explicit distinction as to whether attitudes operate in conscious mode or in
unconscious mode, while a recent view explicitly acknowledges that attitudes also operate in unconscious mode. For
a detailed discussion of this issue, see Greenwald and Banaji (1995). 32 For an overview of all four perspectives on emotion, see Cornelius (1996).
22
people’s decisions and behavior. Because emotions exert effects on people’s decisions and
behavior, it is important for this dissertation to recognize and understand how and why
emotions can exert such effects on employees’ decisions and behavior in the context of
organizational change.
Previous research on emotion has suggested that humans’ affective states, decisions
and behavior are influenced by how they process information. For example, a central theme
of the Affective Infusion Model (AIM) proposed by Forgas and George (2001) is that the
influence of affective states on individuals’ judgments and behaviors depends on the type of
information-processing strategies the individuals adopt in a particular situation. In its
roughest form, the basic idea is that affect (referring to both moods and emotions) impacts
organizational behavior because it influences both what people think (the content of
thinking) and how people think (the process of thinking); and most social thinking and
action occurs in naturally complex and ambiguous situations, and requires the use of active,
constructive information process strategies (Forgas and George, 2001).
According to Forgas (1995), affect infusion can be defined as the process whereby
affectively loaded information exerts influence upon and becomes incorporated into an
individual’s cognitive and behavioral processes, entering into their constructive
deliberations and eventually coloring the outcome in a mood-congruent direction. Basically,
the AIM model (Forgas and George, 2001) asserts that there are four information-
processing strategies based on different affect infusion potentials: (1) a direct access; (2) a
motivated processing; (3) a heuristic processing; and (4) a substantive processing. Both the
direct access and motivated processing strategies require little constructive processing,
limiting the extent of mood infusion. On the contrary, both the heuristic and substantive
processing strategies require a high degree of open and constructive thinking, allowing
greater mood infusion to occur, and resulting in the creation of new knowledge from the
combination of new information and stored information. Moreover, task characteristics,
personal variables, and situational features determine processing choices (Forgas and
George, 2001), implying that the influence of affect is context-dependent.
Central among issues of emotion is whether there is only one direction, either positive
or negative, for each relationship between emotions and the other variables. This is crucial
because it complicates and shapes how researchers conduct their research on emotions.
Based on numerous studies on emotions, it is obvious that there can potentially be inverse
relationships between moods and emotions on the one hand and behaviors and attitudes on
the other hand. For example, George and Zhou (2001) theorized that under certain
conditions, positive moods might hinder, and negative moods might enhance creative
performance. This is because when creativity is an objective for people and that they are
23
high on clarity of feeling, they may use their mood as input to determine the sufficiency of
their efforts. In this sense, negative moods may signal that things are not going well and that
additional effort is needed. Along similar lines, positive moods may signal that things are
going well and that an additional effort is not required. George and Zhou’s (2001) findings
were consistent with their theory, that is, positive mood was negatively associated with
creative performance; and negative mood was positively associated with creative
performance. In other conditions, there may be a positive relationship between positive
mood and creative performance (see, e.g., Isen, Daubman and Nowicki, 1987).
According to the literature on mood, its effects on work motivation are manifold. First,
positive moods may enhance spontaneity and helpfulness toward coworkers (George, 1991).
Second, positive moods may facilitate a flexible and open cognitive style in social situations
(Forgas, 1999a, 1999b). Last but not least, positive moods may influence the performance
of leaders (George 1995, 2000). In contrast, a negative mood has been linked to several
negative decisions and behaviors such as absenteeism and turnover. For example, empirical
research has shown an inverse relationship between employees’ positive moods and levels
of absenteeism (e.g., George, 1989). Another example is that the interaction between value
attainment, job satisfaction, and positive mood is likely to predict turnover intentions among
employees (George and Jones, 1996).
2.5. Individual Decision-Making
In economics, research on decision-making and judgment seems to have begun in 1950’s,
focusing on a rational approach.33 Since then, research on decision-making (e.g., strategic
decision-making in organizations) has been growing. Another stream of research on
decision-making in the field of psychology has also advanced our understanding of how
individuals make judgments and decisions. It is important to note that with regard to human
rationality, the forms of human rationality in the area of psychology, which differ from
those of theories of human rationality in neoclassical economics, have begun to receive
greater attention in strategic management research. Examples of works that have been
influential in strategic management or management science (e.g., Dean and Sharfman,
33 This by no means suggests that the concept of rationality is not being applied in other social sciences. Simon (1978,
1979, 1985, 1986) pointed out neatly that most social sciences implicitly or explicitly assume human rationality;
however, the forms of human rationality that they adopt may differ. Thus there is a point of agreement concerning
human rationality: that is, humans have reasons for what they do or for how they behave. The differences have to do
with the question of what constitutes rationality. For instance, economic theories take a special form of human
rationality – the rationality of the utility maximizer who will objectively aim for the best possible choice in terms of
the given utility function (Simon, 1978).
24
1996) are those of Simon (1957), March and Simon (1958), and Tversky and Kahneman
(1974). Central to these works are the arguments that there are several forms of human
rationality, and that human rationality is bounded to external and/or internal constraints.
A review of past research on strategic decision-making has shown that there are
several models of the strategic decision-making process.34 One example is Hofer and
Schendel’s (1976) model that outlines seven steps of the strategic decision-making process:
(1) strategy identification; (2) environmental analysis; (3) resource analysis; (4) gap
analysis; (5) strategic alternatives; (6) strategy evaluation; and (7) strategic choice. Another
is the model of Mintzberg et al. (1976), which suggests three phases and seven steps of the
strategic decision-making process: (1) identification phase consisting of decision
recognition and diagnosis steps; (2) development phase consisting of search and design
steps; and (3) selection phase consisting of screening, evaluation, and authorization steps.
Likewise, Fredrickson (1984) suggested that from the perspective of a managerial decision
maker, the rational decision-making process involves five interrelated cognitive stages: (1)
pay attention to a problem or opportunity; (2) gather information; (3) develop a series of
options; (4) value the options using expected costs and benefits; and (5) select the option
with the greatest utility.
Another key aspect in decision-making is learning, which involves developing new
understandings. The learning process involves the acquisition and interpretation of
knowledge (Linsay and Norman, 1977). Learning is the process of modifying one’s
cognitive map or understandings (Friedlander, 1983: 194), thereby altering the range of
one’s potential behaviors (Huber, 1991). So we may speculate that since learning capability
refers to individuals’ ability to develop a new understanding of the world around them, it
may promote or limit their understanding of a proposed change.
Past research has led to several concepts and theories to explain certain aspects of
decision-making with the goal of explaining decision-outcome deviations from normative
expectations of the rational decision-making approach. One such theory is Beach’s (1990)
image theory that incorporates Einhorm and Hogarth’s (1981) idea that humans make use of
mental simulation to evaluate options by applying strategies from known situations to new
situations.35 Another example is the model called framing effects that has suggested how
apparently irrelevant variables can influence decision-making. According to Kahneman and
Tversky (1979), framing or editing phases occurring during a process of choice concerns
34 For a detailed review of the literature on strategic decision-making, see Eisenhardt and Zbaracki (1992). 35 For a detailed discussion of image theory, see Einhorn and Hogarth (1981), Klein and Crandall (1995), and Beach
(1990).
25
with the preliminary analysis of alternatives, their outcomes and contingencies.36 Note that
the concept of framing effects is theoretically related to the concept of categorization
discussed in the previous chapter.
Most strategic decision-making models that have been influenced by economic
theories assert implicitly or explicitly that a manager as well as an employee, as an agent of
a firm, should arrive at a decision that will achieve the firm’s goals, one of which is the
maximization of the firm’s value. This observation suggests a key difference between
strategic decision-making models for firms and decision-making models for employees.
That is, decisions (e.g. reactions to change) of employees may be oriented towards the
individual-level maximization of certain objectives such as career advancement or social
status rather than towards the firm’s goals such as maximizing the value of the firm.
However, we may argue here that the ways in which different individuals arrive at decisions
(e.g., as a manager making a choice that achieves the firm’s goals or as an employee making
a choice that achieves his or her personal goals) may not be fundamentally different. That is,
as employees react to change, they are likely to carry out: (1) objective identification; (2)
decision/outcome alternatives; and (3) evaluation and selection. In this sense, employees are
assumed to be rational; however, their form of rationality does not necessarily correspond to
the form of rationality in economics or the form of rationality that the firm may wish its
employees to hold.
Let me now turn to a study leading to a model of reaction to change proposed by
Isabella (1990). In this empirical work, 40 executives from a medium-sized, urban, financial
services institution were asked to describe and discuss five events that had occurred in the
organization over the previous five years. The results showed that members of the
organization construe key events linked to the process of change and that there are four
stages that individuals go through as changes unfold. The four stages are anticipation,
confirmation, culmination, and aftermath. In the anticipation stage, people gather rumors,
scattered pieces of concrete data, to construct a construed reality. In the confirmation stage,
following the standardization of events into a conventional frame of reference, people
reflect or refer their frames of reference which have worked in the past. In the culmination
stage, people compare the conditions before and after an event, at which time they amend
their frame of reference to either include new information or omit invalid information. In
the aftermath stage, people review and evaluate the consequences of a change. From this
36 See Tversky and Kahneman (1981), John et al. (1993), and Paese, Bieser, and Tubbs (1993) for empirical research
on framing effects.
26
example we begin to better understand the process which individuals undergo when they are
confronted with a change in their organization.
At this point, I shall discuss how individuals interpret data and information. The term
“interpretation” has been defined as the process through which people give meaning to
information (Daft and Weick, 1994). The process of interpretation is important because it is
used to understand information. Accordingly, employees use the process of interpretation to
give meaning to, and to understand the information concerning a change. It is logical to
argue that different people may give differing meanings to the same information,37 and that
the differing meanings prompt differing decisions. Moreover, an individual’s emotions and
behaviors depend upon the way they structure their thoughts (Ellis and Harper, 1975). Thus,
one can reason that the processes of interpretation and decision-making may be related.
Indeed, the evaluation phase of a decision-making process requires interpreting information.
Past research on interpretation processes has suggested several models of the decision-
making processes. For example, Jaffe, Scott, and Tobe (1994) have proposed a four-stage
model of how employees interpret events as an organizational change unfolds. The four
stages are denial, resistance, exploration, and commitment. However, one may argue that
this general explanation is an incomplete view of real decision-making processes (Beach,
1993). For instance, personal biases, failures of memory, and misunderstood probabilities
have been found to cause decision mistakes (see, e.g., Kahneman, Slovic, and Tversky,
1982). In addition, several researchers have emphasized the existence of intuitive and
irrational decision-making (Isenberg, 1986; Fiske, 1992). That is, decision-making
processes sometimes involve experience-based mental routines, creating quick decisions
without rational thought.
Now let us have another look at mood theory. Forgas and colleagues have conducted
studies on mood theory concerning the manner whereby moods determine behaviors in
social (see, e.g., Forgas, 1995) and organizational (see, e.g., Forgas and George, 2001)
settings. In short, past empirical research on emotions such as positive or negative moods
has suggested that emotions may affect people’s attitudes, values, and behaviors toward
other objects and their world. This observation suggests that the effects of emotion on
judgments, thought processes, decision-making, and behaviors should not be neglected
when one wishes to study people’s decisions and behaviors.
37 Let us consider whether we always give the same meaning to the same information—that is to say, whether we
sometimes assign differing meanings to the same information in other circumstances. If this is the case, then we
might reason that it ought to be possible that different people may give a different meaning to the same information
as well.
27
2.6. Reactions to Change
Resistance to change has been identified as a negative and undesired response for
organizations because it can lead to failures of change efforts (Martin, 1975; Regar,
Mullance, and Gustafson, 1994; Spiker and Lesser, 1995). Indeed, studies of organizational
change often attribute outcomes of change efforts to behaviors of employees, especially
acceptance of change and resistance to change (e.g., Kotter, 1995; Galpin, 1996). Given the
frequent occurrence and persistence of resistance to change in most change initiatives, it is
not surprising that much research has been devoted to examining the problems of resistance
to change, especially the ways in which resistance to change can be minimized. It is
understandable that research on organizational change management has a pessimistic view
on resistance to change. After all, resistance to change may disrupt or suppress efforts to
change. However, little work has directly addressed the possibility of gaining a positive
effect from resistance to change. As discussed earlier, the question is whether resistance is
always negative. It might be that resistance to change can become strategically valuable.
If we are to understand why resistance to change has been considered the source of
organizational change failures, we need to examine closely the characteristics and role of
resistance to change itself. It appears that Kurt Lewin (1945, 1947, 1951) was the first
author who used the notion of resistance to change. According to his field theory38, the
status quo represents the equilibrium between the forces supporting change and the barriers
to change. Some difference between these forces is therefore required to generate the
“unfreezing” that initiates change. To make the change permanent, “refreezing” at the new
level is required. In this sense, resistance is a system phenomenon. It is part of the change
process and is not necessarily a negative factor.
Many studies have posited that resistance to change is negative and should be removed
or minimized. For example, Coch and French’s (1948: 521) view on resistance to change is
that it is a combination of an individual reaction to frustration with strong group-induced
forces. Similarly, Zander has defined resistance to change as “a behavior which is intended
to protect an individual from the effects of real or imaged change” (Zander, 1950: 9). In the
same view, Agócs (1997) has defined resistance as a process of refusal by decision-makers
to be influenced or affected by the views, concerns or evidence presented to them by those
who propose change. In summary, resistance to change generally refers to the behaviors of
individuals or groups of individuals who are opposed to or unsupportive of changes that top
executives want or decide to implement in the organizations.
38 For Lewin (1947), a change process consists of three phases: (1) unfreezing, (2) moving, and (3) refreezing.
28
Ford, Ford, and McNamara (2002) noted that, from a constructivist perspective,
resistance to change is a function of the socially constructed reality in which a person lives,
and that depending on the nature of that constructed reality, the form of that resistance will
vary. On the contrary, from a modernist perspective, with the assumption that the same
objective and homogeneous reality is shared by everyone, all people involved in a change
are believed to confront the same change within the same context. An important conclusion
to be drawn from these extremely different perspectives is that we need to develop a better
understanding of how individuals really construct reality or see the world. However, for the
purpose of this dissertation, I suggest that any difference between both perspectives is not of
a great concern since in any circumstance the reality that a person holds will ultimately be
expressed in terms of perceptions and/or attitudes.
According to Agócs (1997), a typology of forms of resistance consists of: (1) denial of
the legitimacy of the case for change; (2) refusal to recognize the responsibility to address
the change issue; (3) refusal to implement a change initiative that has been adopted by the
organization; and (4) the reversal or dismantling of a change initiative once implementation
has begun. Recently, some researchers (e.g., Dent and Goldberg, 1999) have argued that
people do not resist change, but rather losses of status, pay or comfort, and that this is not
the same as resisting change.
In the literature on organizational change, several factors are thought to be
determinants of resistance to change; they include fear of real or imagined consequences
(Morris and Raben, 1995), fear of unknown consequences (Mabin, Forgeson, and Green,
2001), a threat to the ways in which people make sense of the world (Ledford et al., 1989), a
threat to the status quo (Beer, 1980; Hannan and Freeman, 1988; Spector, 1989), a threat to
social relations (O’Toole, 1995), distrust toward those leading change (Bridges, 1980;
O’Toole, 1995), and different understandings or assessments of the situation (Morris and
Raben, 1995). Thus, it can be reasoned that a person does not resist organizational change
but rather the consequences of organizational change. However, it can also be reasoned that
the consequences of organizational change are part of change efforts and thus cannot be
clearly separated.
As discussed above, a central issue raised by previous research in change management
is the role and implications of resistance to change, that is, how resistance to change
evolves. At least one issue emerges from previous studies. Despite the seemingly extensive
research on resistance to change, with the exceptions of the aforementioned definitions,
seldom has previous research provided a definition of resistance to change. It seems that the
term ‘resistance to change’ is used as a given. Thus, it is useful, if not critical, to examine
29
the dimensions of “reaction to change” to better understand and conceptualize the term and
the concept of “resistance to change” as well as “support for change.”
Figure 1: Dimensions for Categorization of Reactions to Change
Discontent Contentment
Active Passive
Discontent ContentmentDiscontent Contentment
Active PassiveActive Passive
As illustrated in Figure 1, one dimension of reactions to change is whether a reaction
represents one’s contentment or discontent with the change. Resistance to change can be
described as a reaction that represents a high degree of one’s discontent with change. In
contrast, support for change can be described as a reaction that represents a high degree of
one’s contentment with change. Another dimension of reactions to change is whether it is
active or passive in nature. An active action refers to any action that is active in nature and,
thus, can be easily recognized, whereas a passive action refers to any action that is passive
in nature and, thus, cannot be easily observed.
I treat each dimension as a continuum along which any reaction can be located. The
position of the reaction along each continuous dimension affects the categorization and
nature of information required to detect it. That is, it is possible that one can easily observe
most active actions with relatively little effort. On the contrary, a relatively large amount of
efforts is required to detect passive actions. Likewise, the position of the reaction along each
continuous dimension affects the relative ease of interpretation of the reaction. To illustrate:
By seeing employees listening quietly to the announcement of organizational change, any
observers will find it relatively difficult to know whether they will support or resist the
change; therefore, addition information will be needed to develop a better understanding of
their position with regard to the change. On the contrary, by seeing employees acting in
ways that they oppose change efforts, any observer can easily determine that they resist the
change. Several researchers (e.g., Hultman, 1998; Judson, 1991) have already distinguished
between active and passive resistance.
Thus, it can be reasoned that these dimensions of reactions to change are capable of
creating the parameters in which the definitions of resistance to change and support for
change could be conceptually established. However, each dimension alone is insufficient to
constitute a reaction that can be considered as resistance or support for change. Therefore, I
suggest that a combination of the two dimensions can form the basis for defining and
30
categorizing various reactions to change. As illustrated in Figure 2, any reaction to change
can be neatly classified along two dimensions into one of four categories: (1) active
resistance; (2) passive resistance; (3) active support; and (4) passive support.
Figure 2: A Categorization of Reactions to Change
Passive Support Passive Resistance
Active SupportActive Resistance
Passive
Active
ContentmentDiscontent
Passive Support Passive Resistance
Active SupportActive Resistance
Passive
Active
ContentmentDiscontent
According to this classification, active resistance to change can be defined as a reaction that
is active in nature and represents discontent with the change. Consider, for example,
expressing opposition to a proposed change. It is an active action and reveals discomfort
with or disagreement with the change; therefore, it can be considered active resistance to
change. In contrast, passive resistance to change can be defined as a reaction that is passive
in nature and reveals discontent with the change. For example, the act of ignoring is passive
in nature and implicitly indicates one’s discomfort with change; thus, it can be called
passive resistance to change. Active support for change can be defined as a reaction that is
active in nature and reveals contentment with the change. Consider, for example, praise of
the change. This is an active action and reveals one’s comfort with or agreement with the
change; therefore, it can be considered active support for the change. In contrast, passive
support for change can defined as a reaction that is passive in nature and represents
contentment with the change. For example, expressing agreement is a passive action and
reveals one’s contentment with the change.
In summary, to explore the concept of resistance to change and support for change,
this dissertation proposes two dimensions that specify the properties that should be
considered the criteria for defining both resistance to change and support for change. It is
expected that these definitions will increase the level of clarity of the definitions of
resistance to change and support for change.
31
3. Theoretical Development and Research Model
Recall that the research questions of this dissertation are: What perceptions and/or attitudes
influence employees’ resistance to change? And, what perceptions and/or attitudes influence
employees’ support for change? A review of the literature suggests not only direct
relationships between perceptions/attitudes and reactions to change but also paths (indirect
relationships between them). Reflecting on the research questions, I first examine whether
there is a direct relationship between each perception and each reaction to change without
considering the potential moderating effects of other variables. This model is called a ‘direct
effects’ model in Figure 3.
Figure 3: Alternative Models Relating Perceptions and Reactions to Change
Perceptions / Attitudes Reactions to Change
Perceptions / Attitudes Perceptions / Attitudes Reactions to Change
Perceptions / Attitudes Perceptions / Attitudes Reactions to Change
1. Direct Effects Model
2. Partially Moderated Model
3. Fully Moderated Model
Perceptions / Attitudes Reactions to Change
Perceptions / Attitudes Perceptions / Attitudes Reactions to Change
Perceptions / Attitudes Perceptions / Attitudes Reactions to Change
1. Direct Effects Model
2. Partially Moderated Model
3. Fully Moderated Model
It is important to note that the main focus of this dissertation is on the direct effects model.
This narrow focus is deliberate, for my objective is to concisely develop and empirically test
the model of perception-based factors affecting employees’ reactions to change. If a
majority of hypothesized relationships in the direct effects model were to receive significant
support, I will also examine a set of intervening models to assess if inclusions of some
perceptions and attitudes improve the explanation of reactions to change, and, if so, which
intervening model is most appropriate to the data.
As suggested earlier, one reason to develop the degree of employees’ resistance to
change and support for change as the dependent variables in this research is that
organizational change may strongly affect work performance in some change efforts, affect
only average in others, and affect weakly in still others. To this point, one can reason that
resistance to change tends to have a negative relationship with work performance (Kotter,
1995). One can also reason that employees’ overall performance during organizational
32
change processes depends, among other things, on the net effect of organizational change on
employee’s reactions to change; that is to say, organizational change has a direct effect on
employee’s reactions to change, which in turn have a direct effect on work performance,
which subsequently affects firm performance. Thus, it is sensible to study what factors
enable resistance to change and support for change to emerge.
Indeed, employees’ resistance to change and support for change often depend on,
among other things, how employees construct numerous perceptions, and assign the degree
of importance to each perception. Each of these perceptions can lead to higher or lower
levels of resistance to change and/or support for change. Aggregating the outputs of these
numerous perceptions can impose a difficulty at examining whether a particular set of
perceptions and attitudes actually generates resistance to change and/or support for change.
In this setting, it is also useful to recognize the importance of employees’ ranking of level of
importance attached to each perception with regard to a decision choice.
3.1. Perception-Based View of the Employee
What is a perception-based view (PBV) of the employee? In contrast to the rational
decision-making approach commonly used in the mainstream research in management
science, an alternative approach which is labeled as ‘a perception-based view of the
employee’ in decision-making focuses on the use of perception, attitude or emotion for a
purpose of selecting a sensible alternative in pursuit of one’s goals. The main purpose of the
perception-based view of the employee is to explain variations in decision and/or behavior
among employees in the same context. That is, it attempts to answer two primary questions:
(1) why do individuals in the similar setting and facing the same object have differing
decisions; and (2) why do individuals make decisions that might seem irrational, and be
contradictory to those predicted by rational choice theories?
Perceptions are multi-dimensional and have behavioral implications for humans’
decision-making. What, then, are the implications of perceptions on decisions and
behaviors? Why is this related to reactions to change? First, let us consider a question of
whether perceptions are a source of input for making a decision. If we are to agree that
humans use perceptions as inputs for arriving at decisions, we face a question of whether we
perceive the world around us as others do. The central idea here is that a person may obtain
a different perception of a stimulus than others do,39 and each reacts to this stimulus
according to his or her interpretation process and is thereby motivated to make a decision
39 There is also the question of whether we assume that humans have an objective description of the world as it really
is; that is, whether their perception of the world corresponds to the world as it really is.
33
that is different to one another. This point emphasizes at least two implications. First, if
different people have different perceptions of a similar object at a given moment and in a
given circumstance, and if one perception, as a certain input for a process of choosing,
contributes to one decision and/or behavior rather than another, then one may conclude that
variations in decisions and behaviors can be explained by variations in perceptions. Second,
if, on the other hand, a perception varies across space and time—that is to say, a person’s
perception of a similar object does not hold true at another moment and in another
circumstance, then we may acknowledge consequences of time and space on humans’
perceptions. Here, it seems to me, if the concept of perceptions is to be applied in this
dissertation, it is important to recognize that one shall have to understand the basic elements
of this construct.
The PBV perspective deals with how perceptions, attitudes, and emotions are used by
individuals to solve a problem or to make a decision. At the abstract level, it deals with the
effects and implications of psychological factors on individuals’ decision-making in a
choice situation. In this sense, the central question concerns the extent to which
psychological and emotional factors exert an influence on humans’ decisions and behaviors.
By approaching humans’ decision-making with the PBV logic rather than with the rational
approach, one will observe at least three key differences between the two approaches.
A first difference is that the PBV perspective does not assume that decision-makers
focus on a choice that maximizes expected utility, which is at the heart of the rational choice
perspective, influenced by the neoclassical economic theory.40 Viewed from an economic
perspective, an individual is outcome-driven self-interested, thereby attempting to maximize
expected utility. More importantly, we should make a distinction between a rational choice
of an individual and a rational choice of the firm. This is important because one choice may
seem irrational to one person, but it may seem rational to another. For illustration, I can use
the logics of economics—the utility function. If two persons arrive at a rational choice that
maximizes expected utility of their utility function respectively, and if both do not have a
similar utility function, then both will not arrive at the same decision. If one of them
presumes the other to hold the similar utility function, it is possible that this person may
view the other’s choice as an irrational choice.41
40 In its simplest form, the economic model of decision-making assumes that managers have perfect information and
thus could make decisions that maximize profits. For a critique of the economic model of decision-making, see
Simon (1957) and March and Simon (1958). The logic of the economic model of decision-making may be extended
to employees’ decision-making. 41 Assume that he thinks such choice that the other has made gives a lower level of expected utility (according to his
own utility function).
34
A second difference is that although I tend to agree with prior research on decision-
making asserting that humans make rational decisions,42 I do not believe that humans
always arrive at a rational decision. Now consider a simple example of an angry man.
Should we assume that all decisions he makes at the moment of angriness are rational? If
your answer is “no”, then you are getting close to agreeing with my argument. As this
example illustrates, several psychological constructs such as emotion or attitude exert a
directive or influence on individuals’ decision-making process and outcomes, thereby
diminishing the use of rationality in the process of making a decision.
A third difference is that the PBV perspective does not assume that decision-makers
consistently use a rational decision-making process that focuses on analytical
comprehensiveness. According to Miller (1987), analytical comprehensiveness is a concept
that focuses on individuals’ systematic scanning and analysis of environments in decision-
making processes. Consider a situation in which people have to make quick responses; that
is, there is a time constraint for arriving at decisions. In these circumstances, they may not
go through all steps in decision-making process for making their decisions.
Most important for the PBV perspective is that the greater the existence of the
psychological factors for an individual in a choice selection situation, the stronger the
predictive power of the PBV logic; that is, the PBV posits that the nature and magnitude of
psychological factors existing at the time of decision-making will condition the effects of
these psychological factors on a decision choice, and moderate the extent to which
individuals make use of the rational-decision making process. In this dissertation,
perception-based predictions of employees’ behavior are tested using the degrees of
resistance to change and support for change of employees as dependent variables.
For the moment, to illustrate a potential limitation to the PBV logic, consider a case
that resistance to change of an employee only depends on two perceptions: perception A and
perception B. Suppose that each of these perceptions has a positive effect on an employee’s
resistance to change: that is, the greater the degree of perception A, the greater the degree of
resistance to change becomes. Similarly, the greater the degree of perception B, the greater
the degree of resistance to change becomes. Suppose that the firm has a change management
strategy that is effective at minimizing perception A, but is ineffective at minimizing
perception B. Suppose that this employee has a low level of perception A but a high level of
perception B. The net effect of these two perceptions on resistance to change may be that
42 Rational decisions in this sense are not limited to rational choices within a boundary of the rational choice theory in
economics. The notion of rational decisions here is in a broader sense and includes both a rational decision and a
decision that is derived from a rational decision-making process.
35
this employee only produces average levels of resistance to change, and subsequently
average levels of work performance. If researchers were to measure the degree of perception
A that influences this employee to resist a change, and correlate this perception with this
employee’s resistance to change, they might conclude that perception-based predictions
were not supported; i.e., resistance to change is higher than predicted by the perception-
based logic. On the other hand, if researchers were to measure the degree of perception B
that influences this employee to resist a change, and correlate this perception with this
employee’s resistance to change, they might conclude that perception-based predictions
were not supported, but in a different way; i.e., resistance to change is lower than predicted
by perception-based logic. Both of these findings apparently contradict the perception-based
logic which will be discussed in greater detail in the following section, although, at this
employee’s overall perceptions, perception-based logic may be strongly supported.
3.2. Research Model and Hypotheses
In view of research issues and research questions discussed earlier, the model of perceptual
and attitudinal factors exerting an influence upon employees’ resistance to change and
support for change presented here represents an attempt to develop a conception of the
directive influence of perceptions and attitudes on decisions of the employees in the context
of organizational change upon which to support the perception-based view of the employee.
As such, the research model links various perceptions and attitudes on the one hand and
resistance to change and support for change on the other hand. It is theorizing that, through
a decision-making process, a range of perceptions and attitudes may exert the effects upon
the nature and magnitude of resistance to change and support for change.
While prior empirical research has examined the role of some of these factors, much of
prior research has focused on a smaller set of variables than the one this dissertation
examines. Additionally, empirical research pertaining to the examination of factors
influencing employees’ support for change is relatively sparse. Here, it seems to me, much
of past empirical research has emphasized more on the examination of resistance to change
and less on the investigation of acceptance of change or support for change. An example of
empirical works on acceptance to change is an empirical study by Iverson (1996) examining
the relationships between various factors such as organizational commitment, job
satisfactory and job motivation on the one hand and employees’ acceptance of
organizational change on the other hand. Another example is an empirical study by Iverson
and Pullman (2000) investigating the determinants of voluntary and involuntary turnover in
a repeated downsizing environment. The final example is an empirical study by Erez,
36
Earley, and Hulan (1985) examining the impact of participation on goal acceptance and
performance.
The review of the literature on employees’ reactions to various organizational
decisions (e.g., layoff, turnaround strategy, and employee compensation plan) has identified
several perception variables that are expected to exert an influence upon their resistance to
change and support for change. Based on the results of the initial literature review, the
research model, as illustrated in Figure 4, was developed. The explanatory variables
proposed in this research model using the perception-based predictions can be neatly
categorized into four groups or dimensions: (1) factors concerning change processes; (2)
factors concerning real and expected consequences of change; (3) factors concerning
employees’ ability; and (4) factors concerning employees’ relationship with the firm and
their colleagues.
To summarize, this dissertation focuses on (1) the degree to which employees support
or resist organizational change and (2) whether direct relationships exist between various
perceptions and/or attitudes and reactions to change. In the following section, I will discuss
each of hypothesized relationships in greater detail.
37
Figure 4: Conceptual Diagram of the ‘Direct Effects’ Model
Factors concerning
Employees’
Relationships
with the Firm and
Colleagues
Factors concerning
Actual & Expected
Consequences
of the Change
Factors concerning
Change Processes
Perceived Change in Power
Perceived Change in Status
Perceived Change in Pride
Job Satisfaction
Job Security
Job Motivation
Fear of Unknown Consequence of Change
Fear of Known Consequence of Change
Perceived Organizational Support
Perceived Procedural Justice
Perceived Participation in Decision-Making
Perceived Need for Change
Attitude toward Organizational Change
Factors concerning
Employees’ Ability
Perceived Employability
Self-Confidence for Learning/Development
Trust in Management
Affective Commitment
Colleagues’ Reaction to Change
Employees’ Reactions to Change
Passive Resistance to Change
Active Resistance to Change
Active Support for Change
Passive Support for Change
Factors concerning
Employees’
Relationships
with the Firm and
Colleagues
Factors concerning
Actual & Expected
Consequences
of the Change
Factors concerning
Change Processes
Perceived Change in Power
Perceived Change in Status
Perceived Change in Pride
Job Satisfaction
Job Security
Job Motivation
Fear of Unknown Consequence of Change
Fear of Known Consequence of Change
Perceived Organizational Support
Perceived Procedural Justice
Perceived Participation in Decision-Making
Perceived Need for Change
Attitude toward Organizational Change
Factors concerning
Employees’ Ability
Perceived Employability
Self-Confidence for Learning/Development
Trust in Management
Affective Commitment
Colleagues’ Reaction to Change
Employees’ Reactions to Change
Passive Resistance to Change
Active Resistance to Change
Active Support for Change
Passive Support for Change
Employees’ Reactions to Change
Passive Resistance to Change
Active Resistance to Change
Active Support for Change
Passive Support for Change
38
3.2.1. Perceived Organizational Support
The variation in employees’ reactions to change – resistance to change and support for
change – may be systematically attributable to certain perceptions, attitudes and emotions
that employees form about a change. Previous studies have suggested that perceived
organizational support is related to a wide array of work-related attitudes and outcomes
(Eisenberger, Fasolo and Davis-LaMastro, 1990). Accordingly, if perceived organization
support is correlated with certain decisions of employees, we would then expect that
employees are more likely to take into account perceived organizational change when
making decisions regarding whether to resist or support organizational change.
Consider employees who search for a response to organizational change by
considering the extent to which their organization has supported them. The value of
subjective perceptions of organizational support comes from the possibility of avoiding
negative consequences of organizational change. Intuitively they would be willing to
support organizational change efforts to the value of perceived organizational support they
receive. On the contrary, they will be more likely to resist organizational change if they hold
a perception that their organization does not support them.
Based on the social exchange theory (Blau, 1964) and the norm of reciprocity
(Gouldner, 1960)43, which have been widely used for research on the relationship between
organizations and employees, it can be reasoned that employees’ perceived organizational
support affects their feeling of obligation to their organization. Based on the norm of
reciprocity, employees tend to respond positively to favorable treatments from their
employer, or they feel obliged to help those who helped them, implying a positive norm of
reciprocity (Gouldner, 1960). On the contrary, employees tend to respond negatively to
unfavorable treatments from their employer or feel obliged to retaliate against those who
injured them, implying a negative norm of reciprocity in which individuals retaliate to the
injuries or the negative benefits enacted by others (Gouldner, 1960).
Prior empirical studies (e.g., Eisenberger et al., 1986) have found a positive correlation
between perceived organizational support and feelings of obligation. The key to this idea is
that based on the organization’s procedures and policies employees form perceptions about
the organization’s intentions and attitudes towards them. Then, they assign certain human-
like attributes/characteristics to the organization on the basis of the treatment they receive.
43 Gouldner (1960) noted that, in a view that exchanges of benefits or favors among individuals induce the imbedded
obligation, there are three different components of the process that form the governance of the norm of reciprocity.
A first component is equivalence, which is the extent to which the amount of return almost equates to what was
received. A second component is immediacy, which is the time period between repayment and receipt of favors. A
final component is interest, which is the motive of the partner in making the exchange of benefits.
39
In this view, employees who perceive greater support from their organization feel obliged to
repay their organization (Eisenberger et al., 1986; Eisenberger et al., 1990). In one
empirical study, Allen, Shore and Griffeth (2003) have illustrated that perceived supportive
human resource practices contributed to the development of perceived organizational
support, of which mediated relationships with organizational commitment and job
satisfaction.
Likewise, the concept of the inducements-contributions framework of voluntary
turnover (March and Simon, 1958) has suggested that a balance between the inducements
offered by the organization and the contributions expected of employees is more likely to
determine employees’ decision to continue their participation in the organization. In this
view, employees who have a perception of greater inducements would be less likely to
desire to leave the organization than those who have a perception of fewer inducements.
Research on psychological contracts44 examining implications of psychological
contract breach45 on employees’ attitudes and behaviors (e.g., Robinson and Morrison,
1994; Robinson and Morrison, 1995; Robinson, 1996; Turnley, Bolina, Lester and
Bloodgood, 2003) has suggested that the breach of psychological contracts often results in a
wide range of negative consequences such as declined job satisfaction or declined trust in
the organization. Thus, it is possible that employees may consider organizational change as
the breach of psychological contracts committed by their organization, and this promotes
their negative reaction to change.
In summary, an organization that offers support to its employees, particularly during
change processes, may be seen as offering greater inducements to employees, thereby
promoting a sense of obligation for the employees to repay to the organization. In this sense,
we might expect that perceived organizational support would be correlated with reactions to
change. Specifically, it is positively correlated with support for change and is negatively
correlated with resistance to change. Accordingly, the following hypotheses are formulated:
H1a: Employees’ perceived organizational support will be negatively related to their
resistance to change.
H1b: Employees’ perceived organizational support will be positively related to their
support for change.
44 Psychological contract refers to an employee’s beliefs about the terms and conditions of the exchange agreement
between himself or herself and the organization (Robinson, Kraatz & Rousseau, 1994) 45 An employee feels that the organization breaches the psychological contract when the organization has failed to
fulfill one or more of the perceived obligations comprising the psychological contract (Morrison & Robinson, 1997).
40
3.2.2. Perceived Procedural Justice
An important question arises regarding the likelihood of interaction between perceived
procedural justice and reactions to change. Before considering whether, or in what sense,
perceived procedural justice can explain employees’ reactions to change, one must first ask
what fairness or justice can do. Several researchers in management science have indicated
that fairness of organizational policies and procedures exerts an impact on people in
organizations (e.g., Adams 1965; Thibaut and Walker, 1975, Gopinath and Becker, 2000).
By recognizing the role of fairness of organizational policies and procedures on employees’
decisions, it is possible to investigate if one facet of justice – perceived procedural justice –
has an effect on employees’ reactions to change.
The literature dealing with (1) how employees react to inequitable processes and
outcomes (e.g., Greenberg, 1982; Folger and Greenberg, 1985) and (2) how they try to
establish equitable conditions (e.g., Greenberg, 1982; Folger and Greenberg, 1985) has
suggested that perceptions of fairness of organizational decision-making processes have
significant effects on employees’ attitudes and behaviors.46 Moreover, empirical research
has shown that perceived justice of the organization’s decision-making process has been
found to have effects on employees’ reactions to strategy implementation (Kim and
Mauborgne, 1993) and pay raise decisions (Folger and Konovsky, 1989). In addition,
perceptions of fairness have been found to be positively associated with employees’
organizational commitment (McFarlin and Sweeney, 1992) and job satisfaction (Conlon and
Fasolo, 1990).
It should be noted that there are several forms of justice in the social psychology
literature: one of them is procedural justice; the other is distributive justice. What is
procedural justice? For Thibaut and Walker (1975), procedural justice refers to decision
control and process control in determining fairness. In a same vein, Tyler (1994) noted that
procedural justice deals with the fairness of a procedural or set of procedures. There are
several aspects of procedural justice: for example, consistency and bias suppression
(Leventhal, 1980). What is distributive justice? Distributive justice refers to the perceived
fairness of resource allocations or outcomes (Moorman, 1991). Rooted in the field of social
psychology, distributive justice theory has been used to study various organization
phenomena such as conflict resolution process (Karambayya and Brett, 1989) and work
group incentive pay plans (Dulebohn and Martocchio, 1998). In addition to its root in social
psychology literature, distributive justice is also grounded in equity theory, which states that
when outcomes are consistent with individuals’ inputs; they believe outcomes are fair
46 For a detailed review, see Lind and Tyler (1988)
41
(Folger and Crapanzano, 1998). Thus, one may reason that employees evaluate the fairness
of their own outcome by comparing it to a reference point (e.g., the outcome of their
colleagues).
Now let us cast an eye on empirical research on procedural justice in an organizational
setting in greater detail. A first example of empirical work on procedural justice is a study
by Brockner et al. (1994) which has found that perceptions of procedural justice
significantly influenced the reactions of employees who survive layoffs; that is, when
survivors of layoffs felt that procedural justice was high, the perception of negative
outcomes had no effect on their reactions, whereas survivors who felt that procedural justice
was low reacted more adversely to perceived negative outcomes.
Another example is an empirical study by Gopinath and Becker (2000) which has
found that high levels of perceived procedural justice are correlated with high levels of trust
in new ownership and high levels of post-divestiture commitment to the organization. This
study has also found that communications from management explaining the events helped
increase perceptions of the procedural justice of the divestiture and layoffs.
My final example of empirical study on procedural justice is a work by Korsgaard,
Sapienza and Schweiger (2002) which has found that procedural justice would moderate the
impact of planning change on employees’ obligations, trust in management, and intention to
remain in the organization. In light of previous theoretical and empirical research
aforementioned, extending these results to the context of organizational change by linking
perceived procedural justice to employees’ resistance to change and support for change
seems plausible.
If employees perceive a high level of procedural justice in organizational change
efforts, then consequences of organizational change may seem justifiable. Intuitively that
will promote the level of legitimacy of the change. Consequently, it may enhance
employees’ support for change, and reduce employee’s resistance to change. On the
contrary, if employees hold a perception that procedural justice regarding organizational
change is low, then consequences of organizational change may seem unjustifiable.
Intuitively that will reduce the degree of legitimacy of the change. Consequently, it may
reduce employees’ support for change, and increase employees’ resistance to change. In
sum, the following hypotheses are proposed:
H2a: Employees’ perceived procedural justice will be negatively related to their resistance
to change.
H2b: Employees’ perceived procedural justice will be positively related to their support
for change.
42
3.2.3. Perceived Participation in Decision-making
So far the argument that perceived procedural justice is likely to influence employees’
reactions to change has been made. The argument raises the issue of whether the extent to
which employees participate in decision-making might have an effect on their reactions to
change. It is clear that while perceived procedural justice and perceived participation in
decision-making may be parallel, they are not the same. Therefore, we should distinguish
between the two. Consider employees who hold a perception that procedural justice is high,
who seek to hedge or minimize the downside consequence of organizational change by
influencing decisions regarding the change. The perception of their participation in
decision-making is then not contingent upon their perception of procedural justice, implying
that one cannot assume that high levels of perceived procedural justice implies or equates
high levels of perceived participation in decision-making since they are two different
constructs.
Several researchers have emphasized the role of participation in decision-making for
promoting employees’ acceptance of change (e.g., Blumberg, 1976; Coch and French, 1948,
Lewin, 1951). Extending the logic of previous research, one might expect that employees
who perceive a low level of their participation in an organization’s decision-making
concerning organizational change tend to react more negatively to change than those who
perceive a high level of their participation in decision-making. Using the same logic, one
might expect that employees who perceive a high level of their participation in decision-
making process tend to react more positively to change than those who perceive a low level
of their participation in decision-making. The key to these propositions is that if employees
who face organizational change efforts evaluate their level of participation in decision-
making or the extent to which their organization allows them to participate in the decision-
making concerning organizational change or to express their opinions, concerns, or
suggestions, and if they correlate this perception of participation in decision-making to their
reactions to change, we may expect that a degree of perceived participation in decision-
making tends to be associated with employees’ resistance to change and support for change.
Empirical research on participation in decision-making has suggested that participation
in decision-making is related to a variety of work-related attitudes and decisions. For
example, a study by Ruh, Kenneth, and Wood (1975) has found a correlation between
participation in decision-making and job involvement. A more resent study by Allen, Shore
and Griffeth (2003) has found a significant negative and significant correlation between
participation in decision-making and turnover intentions and a significant positive
relationship between participation in decision-making and perceived organizational support.
However, prior empirical studies on participation in decision-making have shown mixed
43
results. For example, a study by Locke, Frederick, Lee, and Bobko (1984) has suggested
that participation in decision-making was less effective in production setting. Thus, findings
of this dissertation may help clarify these issues to some extent, and allow a theory to move
forward in a systematic fashion.
There are at least three reasons to support a proposition linking perceived participation
to change on the one hand and resistance to change and support for change on the other
hand. One reason is that according to the self-interest model (Thibaut and Walker, 1978),
which is based on social exchange theory (Blau, 1964), an organization’s decision has
implications for employees; therefore, employees will want to gain control (to some extent)
over the decision-making, and exert an influence on any major decision. This is because it is
possible that employees consider a control over decision-making as a means to mitigate the
magnitude of their own exposure to a potential negative effect. Consistent with the logic of
the self-interest model, I argue that if low levels of participation in a decision-making are to
promote uncertain feelings concerning a preferred outcome of organizational change, and if
employees perceive themselves as a decision-taker rather than a decision-maker because
they have a low level of participation in this decision-making process, and correlate this
perception with their subsequent decision, we might expect that perceived participation in a
decision-making is correlated with their reactions to change. Empirical evidence has
suggested the relationship between perceived participation in decision-making and reactions
to decisions of organizations. For example, a study by Erez, Earley and Hulin (1985) has
found that participative goal setting results in higher goal acceptance than goal assignment
and that when a variance in individual goal acceptance exists, the performance of
participative goal setting groups are higher than assigned goal setting group.
A second reason is that if perceived participation in decision-making is related to a
feeling of uncertainties in the organization due to the uncertainties surrounding
organizational change and its consequences, then employees who feel uncomfortable about
organizational change or a situation with which it is related may attempt to participate in
decision-making so that they may be able to obtain information about organizational change
(early enough and/or sufficient enough), and to have an opportunity to change it if needed.
By having a strong sense of control47 over a situation, especially decision-making,
employees may feel more secure about the situation regarding organizational change.
Empirical evidence has suggested that perceived control is negatively associated with
47 A sense of control has been defined as “a generalized belief on the part of the individual about the extent to which
important outcomes are controllable” (Parks, 1989: 21).
44
emotional distress (Spector, 1986) and negatively associated with burnout during a
downsizing process (Westmann, Etzion and Danon, 2001).
A final reason is that employees may view the merit of organizational change not only
on the content of organizational change (e.g., reasons for change and the expected
outcomes) but also on the process of organizational change (e.g., how a change is designed,
evaluated, selected and implemented). Specifically, a perception that an organization does
not allow employees to participate in a decision-making or express their opinion, concerns,
or suggestions may give a signal that an organization does not care about employees’
feelings.48 Based on the social exchange theory (Blau, 1964) and the norm of reciprocity
(Gouldner, 1960), employees may return in kind the favors of the organization; that is, they
may react negatively to the change.
Following the above discussion, two hypotheses regarding the effects of perceived
participation in decision-making on employees’ reactions to change are developed. In
developing the hypotheses, it is assumed that employees have a perception that a higher
level of participation in the decision-making they have, the higher a probability of receiving
a positive consequence of organizational change (at least for themselves) becomes or the
lower a probability of receiving a negative consequence of organizational change (at least
for themselves) becomes. It is also assumed that employees have the same preference of a
level of participation in decision-making as a baseline.49 In addition, it is assumed that
employees take on the same initial degree of exposure to organizational change.50 In
summary, the effects of the perception of participation in a decision-making process on
employees’ reactions to change can be expressed in the following hypotheses:
H3a: Employees’ perceived participation in decision-making processes regarding
organizational change will be negatively related to their resistance to change.
H3b: Employees’ perceived participation in decision-making processes regarding
organizational change will be positively related to their support for change.
48 In my view, despite the fact that participation in decision-making is regarded as one facet of procedural justice or
fairness, we should not assume that low perceived participation in decision-making implies low perceived
procedural justice. 49 The alternative would be to assume that employees have a different preference of a level of participation in decision-
making. 50 The alternative would be to assume that employees take on the different initial degree of exposure to a change.
45
3.2.4. Perceived Need for Change
For organizational change to emerge there must be some underlying causes or antecedents
of a change in an organization. For organizational and/or strategy theorists, a combination
of internal and external pressures influences an organization to undertake a certain
archetype of organizational changes. For any change to occur, one can expect that most
organizations that want to undertake organizational change will communicate their
compelling reasons for change to employees at one point in time.
Research on organizational change has suggested that a proper communication from
management tends to help employees understand a situation and a need for organizational
change, thereby facilitating change processes and reducing employees’ resistance to change
(see, e.g., Kotter 1995; Kotter and Cohen, 2002). One of purposes of communication
between organizations and their employees is to legitimize organizations’ decision to enact
organizational change, subsequently promoting employees’ acceptance of the change.
Empirical research on organizational change management seems to support the role of
communication during change processes. For example, an empirical study by Gopinath and
Becker (2000) has found that in contexts of divestiture, communications from management
that help employees understand the events relating to the sales of business units are
positively correlated with the perceived procedural justice of the divestiture and the absolute
justice of layoffs.
Up to this point, it raises a question of whether employees will share the similar view
of a situation with that of their organization.51 Starbuck and Milliken (1988) suggested three
reasons concerning why perceptual filters of managers might affect noticing changes in the
environment. First, individual habits and beliefs will exert an effect on what they notice.
Second, some stimuli that are not actively noticed must change significantly in order to get
noticed. Third, the organizational institutionalization may induce problems of noticing
because resources are assigned to track those stimuli that top managers have perceived as
important, while other stimuli that top mangers have not identified as important may not be
traced, and go unnoticed. Additionally, a study by Barr, Stimpert and Huff (1992)
attempting to investigate a relationship between changes in mental models of top managers
and changes in organizational action has suggested that top managers may not notice
changes in the environment because these changes are not central to existing mental models
51 Or, to be more precise, that of the organization’s top management. Note that, unless stated otherwise, the terms “top
management” and “organization or organizations” are used interchangeably, i.e. top management’s view refers to
the organization’s view, and vice versa.
46
of top managers, and it has also found that the organization that renewed its strategy and
still survives shows a definite succession in mental models.
Based on the preceding discussion, it raises a question of whether the concept of the
perceptual filters of managers may be applicable to employees. If employees have such
filters, we might reason that they may not notice changes in the environment because their
existing mental models do not focus on those changes. One possible implication of this is
that employees who have not noticed changes in their environment tend to have a differing
view on organizational change than those (e.g., top managers or other employees) who have
noticed these changes in the environment.
Figure 5: Five Stages of Organizational Decline
Source: Weitzel and Jonsson (1989), p. 102
But what is a perceived need for change? Anderson and Paine (1975: 815), from a strategic
formulation standpoint, defined a perceived need for change as “the perception by the
47
strategic formulator (boundary spanner) of a distinct lack of competence, capabilities, or
internal resource to carry out a planned program of action”. If organizations fail to perceive
a need for change and to carry out a corrective action, they may experience a decline. As
illustrated in Figure 5, Weitzel and Johnsson (1989) suggested a model that portrays five
stages of organizational decline from the early stage of decline to the demise of organization
as follows: the blinded stage, the inaction stage, the faulty action stage, the crisis stage, and
the dissolution stage.
One plausible interpretation on Anderson and Paine’s (1975) definition of a perceived
need for change and on Weitzel and Johnsson’s (1989) model of organizational decline is
that for organizational change to be perceived as needed, one condition must be fulfilled:
that is, a currently planned program of actions is less likely to be fulfilled, subsequently
resulting in lower performance. In this sense, it may suggest that people (e.g., top managers
and employees) may perceive that their organization needs to change when viewing that a
considerable threat to certain aspects of the organization exists. Hence, this definition of
perceived need for change does not take another important aspect of organizational change
into account. That is, organizational change may be initiated in order to capitalize on an
opportunity to enhance firm performance or to preempt competitors from taking
opportunities that may present a great threat to the firm. One may argue that for
organizations with good performance, there may not be a need for change to survive, but
there may be a need for change to take an advantage of available opportunities to perform
better. Similarly, one may argue that although organizations may perform well, they should
try to enact organizational change that may improve their performance. In this sense, we
clearly observe an ambiguity of the term “perceived need for change”, suggesting a
subjective nature of how one defines and quantifies a need for change.
It is useful to note that from employees’ point of view, the context in which
organizational change takes place tends to exert an effect on employees’ perceptions of need
for change. For example, organizational change in a turnaround situation tends to be
perceived of greater need than organizational change in a normal situation, demonstrating
the implication of the context in which organizational change occurs on employees’
perceived need for change. In summary, two hypothesize are proposed:
H4a: Employees’ perceived need for change will be negatively related to their resistance
to change.
H4a: Employees’ perceived need for a change will be positively related to their support for
change.
48
3.2.5. Attitude towards Organizational Change
Several researchers (e.g., Kirton and Mulligan, 1973) have suggested that there are effects
of employees’ attitudes towards organizational change on their reactions to change. As
discussed earlier, any attitude may register directive effects on a person’s predisposition to
formulate a certain type of pre-determined reaction to a wide range of objects, it ought to be
possible that employees’ positive or negative attitudes towards organizational change may
exert an effect on their perceptions of organizational change and a situation with which it is
related.
Much of the attitude literature has suggested that there is considerable consistency in
the underlying belief that an individual with attitudes about an idea, item or object is likely
to approach such idea, item or object with a set of pre-determined behaviors, essentially
demonstrating a distorted information processing and interpreting process and a form of
preference. As Allport (1935: 8) has defined an attitude as “a mental and neural state of
readiness, organized through experience, exerting a directive or dynamic influence upon the
individual’s response to all objects and situations with which it is related”, one can reason
that attitude induces not only pre-determined responses but also tendencies towards
performing of such responses. Prior research has shown that attitudes are related to a variety
of decisions of people in organizational setting. For example, Robey (1979) argued that
attitudes could affect the use of a computer based information system, and found that users’
attitudes are significantly related to management information system use.
Past research has suggested that employees’ experiences with other decisions of an
organization have an impact on their evaluation of the current decision of the organization.
For example, Davy, Kinicki, and Scheck (1991) found that the ways in which employees
evaluate an organization’s decision-making process (e.g., decision-making process
concerning a layoff) are undertaken in the context of their experiences with other decisions.
Therefore, it is logical to argue that prior evaluation of organizational change is likely to
exert a directive effect on the evaluation of a present organizational change effort. If a series
of the evaluations results in similar outcomes, one might reason that these outcomes,
through the attitude construction mechanism, may form or promote a positive or negative
attitude about organizational change.
What is attitude towards organizational change? Generally speaking, there is no
general agreement on the definition of attitude towards organizational change in the
literature. Grounding on Sarnoff’s (1960) definition of attitude, attitude towards
organizational change is defined here as a disposition to react favorably or unfavorably to a
change within an organization. It must be noted that there is no restriction on this definition
with regard to whether attitudes toward organizational change are conscious or unconscious
49
in nature. My position is that a question of whether employees recognize the existence of
their attitudes is of irrelevance to this dissertation so long as an influence of attitudes
towards organizational change on shaping employees’ reactions to change does in fact exist.
Parallel to the logic of hypotheses 4a and 4b, it is expected that there is a direct
relationship between employees’ attitude towards organizational change and their reactions
to change. Specifically, it is expected that a positive attitude towards organizational change
may result in greater positive perceptions of a current change and/or greater feelings of
comfort with the change and, through positive perceptions of a current change and/or
feelings of comfort with the change, lead to lower levels of resistance to change and/or
higher levels of support for change. Likewise, it is possible that a positive attitude towards
organizational change may result in a distortion of perceptual process. Thus, a positive
attitude towards organizational change may promote a positive perception of the change,
weaken any feeling of uneasiness with the presence of the change, and thus facilitate a
decision to accept or support a change.
On the other hand, a negative attitude towards change may create negative perceptions
of a current change and/or feelings of uncomfortable with a current change, which can result
in a distortion of perceptual process. In this sense, employees who have a negative attitude
towards organizational change may have a negative perception of organizational change that
promotes feelings of uneasiness with the presence of organizational change and, thus, leads
to higher levels of resistance to change and/or lower levels of support for change. In sum,
the effects of attitudes towards organizational on employees’ reactions to change can be
expressed in the following hypotheses:
H5: Employees’ (positive) attitude towards organizational change will be negatively
related to their resistance to change.
H5: Employees’ (positive) attitude towards organizational change will be positively
related to their support for change.
50
3.2.6. Fear of Known Consequences of a Change
One can question whether fear serves as a determinant of humans’ reactions. Or for that
matter interferes or hinders the process of arriving at any reaction. In either case, it is a
valuable moment to examine if there is an effect of fear on humans’ decision. For purposes
of discussing fear of known consequences of change, one must first note that fear is one
kind of emotional states (Ortony et al., 1988) that are capable of exerting influences on
humans’ decision. How can fear be conceptualized so as to make this concept useful for
management theory? Interestingly, it is relatively difficult to find a clear and precise
conceptualization of fear in the management literature. But according to Merriam-Webster’s
Collegiate Dictionary, fear refers to “an unpleasant often strong emotion caused by
anticipation or awareness of danger”. Due to a lack of empirical or theoretical knowledge of
fear in the management literature, this dissertation follows much of theories and frameworks
from other social sciences (e.g., psychology) to understand effects of fear in the
organizational setting, particularly in an organizational change situation. But what does this
fear of known consequences of a change effort have to do with employees’ reactions to
change?
Fear is often considered as a factor that triggers employees’ resistance to change
(Agócs, 1997, Kotter and Cohen, 2002). But why is this so? In the case before us, where the
organization is trying to undertake organizational change, which is intended to improve
organizational performance, fear of known consequences of a change becomes a barrier to
employees’ acceptance of change, because it exerts a negative effect on any person’s
rational thinking. If we accept the notion that fear can affect our thinking and reasoning, we
might expect that fear can also affect our decision-making in general and our decision-
making concerning a reaction to change in particular. Thus it is not hard to observe that
researchers have associated fear with resistance to change. For example, Dubrin and Ireland
(1993) noted that resistance to change is attributed to employees’ fear of poor outcomes, the
unknown, and realization of pitfalls with the change. In the same vein, Kotter and Cohen
(2002) posited that fear or panic drives self-protection or immobilization.
There are numerous explanations for a question of why we react negatively to an
object or idea while we fear such objective or idea. First, fear can suppress our rational
thinking and decision-making—that is to say, fear may shorten a person’ sequences of
thinking process or duration of such processes because it reduces a set of information
needed for making a decision and encourages impulsive decisions. Second, in circumstances
where fear exists, we may arrive at decisions that we may not have made in other
circumstances. In the extreme case, fear can force anyone to kill someone. Although we do
not expect that fear will force employees to kill managers, we must recognize that fear is
51
powerful and capable of invoking a person to do things unimaginable. Third, the known
consequences may be psychologically unbearable—that is to say, employees who view the
know consequences as psychologically unacceptable or as a threat to their psychologically
well-being may react negatively to ideas of experiencing this change. Finally, the known
consequences may be viewed as practically unattainable at the level of individual or firm.
For example, if employees who realize new demands of them and limitations of their
resources and/or abilities do not hold a belief that they could meet these new demands, then
they will be more likely to react negative to this change.
Through the fear-generating mechanisms and the effects of fear of known
consequences, employees tend to react negatively to change. The argument for employees
making resistance to change is relatively straightforward. To the extent that employees are
afraid of or fear the known consequences, they will feel that this change is not good, at least
not good for them. Or is it the other way around? In either case, fear will drive them into
protection mode. In order to get rid of feelings of fear, they either (1) accept the situation as
it is and live with it or (2) remove a source of fear—that is to alter the change. Using the
logic of social exchange theory (Blau, 1964) and the norm of reciprocity (Gouldner, 1960),
it is argued that feelings of fear are likely to result in a more negative evaluation of the
organization making organizational change and of the change because this change is viewed
as a negative treatment a person receives from the organization. Therefore, if they are afraid
of or fear the known consequences, and they feel that the organization treats them badly
with this change, they return the organization a negative treatment—they resist the change.
Although much of prior research on resistance to change has suggested that, under an
underlying assumption that employees’ fear tends to recede when they are well aware of
what is going on (e.g., Kanter, 1995), the positive effects of communication in various
phases of the change process may minimize their resistance to change. However, the
organization’s communication of organizational change alone may not be sufficient to
reduce employees’ resistance to change because fear induced by knowing the content (e.g.,
the consequences of the change) may be responsible for their resistance to change. In
summary, to test the potential effect of fear of known consequences of a change on
employees’ reactions to change, the following hypotheses are formulated:
H6a: Employees’ fear of known consequences of a change will be positively related to
their resistance to change.
H6b: Employees’ fear of known consequences of a change will be negatively related to
their support for change.
52
3.2.7. Fear of Unknown Consequences of a Change
As the preceding discussion of fear of known consequences of a change concerns primarily
the effects of fear induced by knowing consequences of a change on employees’ reactions to
change, I now turn my attention to a related-but-distinct factor—fear of unknown
consequence of a change. Specifically, I examine whether there is any relationship between
employees’ fear of unknown consequences of a change and their reactions to change. From
a practical perspective, shifting attention from explaining employees’ reactions to fear of
known consequences to explaining their reactions to fear of unknown consequences allows
an organization to decide on the extent to which the information on organizational change
should be communicated to its employees.
In the organizational change literature, there are suggestions that change
communications are more likely to reduce employees’ resistance to change (Kanter, 1995;
Cobb, Wooten and Folger, 1995) because these communications will reduce anxiety about
change (Kanter, 1995), and increase a perception of fairness of change (Cobb et al., 1995).
Because past research has found that organizational change is related to anxiety and stress
(Jick, 1985; Leana and Feldman, 1992), most change management models and frameworks
(Judson, 1991; Kotter, 1995; Galpin, 1996) have emphasized the roles and effects of
communication during the change process.
Anticipating the effect of fear of unknown consequences of a change on employees’
resistance to change is supported by two reasons. One reason is that the majority of people
tend to be afraid of moving from the known to the unknown—that is to say, if
organizational change entails moving employees from the known sphere to the unknown
sphere, and if employees are afraid of the unknown, then we might expect that employees
who do not know the consequences of a change tend to have a negative response to that
change (Steinburg, 1992; Coghlan, 1993).
Another reason is that if the majority of people tend to form a negative perception
about the unknown, we might expect that employees may form a negative perception about
the unknown consequence, leading to fear of not knowing consequences of change. This
fear of unknown consequences of a change then contributes to resistance to change. As
Mabin, Forgeson and Green (2001) noted that fear of unknown may be defined as being
uncertain about the nature of change, feeling that he or she does not know what is going on,
and what the future is likely to hold, it is possible that employees may have a rather dark
image of the unknown consequences of a change.
As discussed earlier, most people do not want to experience a feeling of fear. If
employees decide to direct their fear of unknown consequences of a change towards the
organization because they feel that such change is a bad treatment of the organization for
53
them, using the logic of the social exchange theory (Blau, 1964) and the norm of reciprocity
(Gouldner, 1960), we might expect that they will react negatively to organizational change
that has induced fear to them. However, past research has not discussed the likelihood that
without fear employees will support the change. Therefore I also examine whether there is a
relationship between fear of unknown consequence of a change and support for change—
that is to say, if employees have a low level fear of unknown consequence of change, then
they may support such change. Although this prediction does not directly address a question
of whether communication during the change process will enhance employee’s support for
change, it will indirectly address a question of whether communication that minimizes
employees’ fear of unknown consequence of a change will promote their support for
change.52
To summarize, the above discussion suggests two hypothesized relationships. On the
one hand, I predict a negative relationship between fear of unknown consequence of a
change and resistance to change. Using the same theoretical lens, I examine whether there is
a negative relationship between fear of unknown consequences of a change and support for
change. Accordingly, the following hypotheses are formulated:
H7a: Employees’ fear of unknown consequences of a change will be positively related to
their resistance to change.
H7b: Employees’ fear of unknown consequences of a change will be negatively related to
their support for change.
52 Many researchers (e.g., Kotter, 1995; Galpin, 1996; and Kotter and Cohen, 2002) have argued that organizations’
communication to employees during organizational change processes will lower employees’ fear of unknown
consequences, and increase employees’ support for change.
54
3.2.8. Perceived Change in Power
Research in a variety of setting has revealed a consistent view of power. In particular,
several studies have noted that loss of power is associated with resistance to change (e.g.,
Agócs, 1997; Trader-Leigh, 2002). This dissertation therefore examines if there is a
relationship between perceived change in power and reactions to change. What is power?
The term “power” can be seen in a wide range of disciplines: for example, political science,
organization theory, sociology and psychology. Several definitions of power have been
offered and adopted in research over year. One of influential definitions of power is French
and Raven’s definition. That is, power has been defined as “the perception by P that O has a
legitimate right to prescribe behavior for him” and that P accepts “that O has a legitimate
right to influence P and P has an obligation to accept that influence” (French and Raven,
1959: 151). Another example of definitions is the one offered by Pierce and Newstrom
(1995: 21), defining power as “the ability to change one’s environment”.
A review of literature on power has suggested that the concepts of power, influence,
and control have been used almost interchangeably. For example, legitimated power is one
form of influence, and individuals develop power to have a control in order to meet
organizational and personal objectives (Pfeffer, 1981). Similarly, influence refers to “the
process whereby one party changes the views or preferences of another so that they now
conform to their own” (Dawson, 1996: 170). In addition, a concept of power distance,
which refers to the extent to which less powerful members of an organization or a society
accept an unequal or hierarchical distribution of power within an organization or in a society
(Hofstede, 1980), has been as a key explanation to various studies. Here, it seems to me,
concepts of power, influence and control are, at least, overlapping each other.
In organizational setting, power is generally associated with a position in an
organization; that is, a higher level of a hierarchical position in an organization, a higher
level of power is associated with it. In this view, any change in an organization that affects a
power or hierarchical structure in an organization may result in creating a combination of
three distinct groups of employees. A first group consists of any employee who will receive
or gain greater power in this organization as a consequence of this change. A second group
consists of any employee who will have lesser power in this organization as a consequence
of this change. A final group consists of any employee who will experience no change of
their power in this organization. It is not surprising that employees who will have less power
in an organization as a result of this change may react to this change differently than those
who will have more power as a result of this change or than those who will maintain their
current level of power. One important aspect requires attention here. That is, there is a
question of whether employees’ goals and an organization’s goals are always aligned. To
55
this question, we may reason that both managers and employees regarded as an agent of an
organization may have a set of personal goals (e.g., career goals) that is not necessarily
coherent or aligned with that of an organization.53 The key here is that an effort to achieve
the organization’s objectives by inducing organizational change may affect the attainment
of employees’ personal goals. Thus, employees whose personal goals have been negatively
affected by organizational change may attempt to defend their personal goals through
various means.
A perceived negative change in power as a consequence of a change can lead to
aversive psychological outcomes. Using logics of the social exchange theory (Blau, 1964)
and the norm of reciprocity (see, e.g., Blau, 1964; Eisenberger et al, 1986; Fasolo and
Davis-LaMastro, 1990), one can reason that employees’ strong feelings of deterioration in
power may result in their resistance to change because they may feel that their organization
has mistreated them. If a perceived change in power is considered as an injury or
mistreatment committed by the organization, then employees may have a negative response
to the change. On the other hand, employees who have a perception that they have, or will
have, more power as a consequence of a change may have a more positive response to the
change because they may view this perceived gain in power as a benefit provided by the
organization, and feel obliged to repay the organization by providing support for change.
Based on the social exchange theory and the norm of reciprocity, it can be argued that
employees in a change situation will have a normative expectation about the likelihood of
various outcomes regarding their power position in an organization that might occur in that
setting. The actual outcomes that occur in a change setting do not necessarily conform to
these expectations for a variety of reasons. Suppose that the least employees expect is to
maintain the current level of their power. Any such deviation of actual outcomes from
expectation has an effect on their reactions to change. Employees may reduce negative
deviations (loss in power) by resisting such change (with an attempt to alter the change so
that their power will not be reduced). On the contrary, employees may not reduce positive
deviations (gains of power), and thus support the change. Thus, the following hypotheses
are proposed:
H8a: An employee’s perceived rise (fall) in power resulting from a change will be
negatively (positively) related to their resistance to change.
H8b: An employee’s perceived rise (fall) in power resulting from a change will be
positively (negatively) related to their support for change.
53 In economics, this kind of problem is known as a principal-agent issue, see Fama (1980) for a detailed discussion.
56
3.2.9. Perceived Change in Status
Does it bother you when you get a lower status in your social group? Or when your friend or
colleague rejects, neglects, or ignores your request that was once easily accepted? Or for
that matter disagrees or argues with you? Of course, you are left feeling hurt, upset, and
angry, but the question is why? Why does that bother us? Why do you care if you get a
lower status in a society?54
So often we throw around the words like status, ranking, and position. But what do
they all mean and how are they connected to our decision? In general, status indicates the
relative standing of a person in his or her social group. But what does this have to do with
being upset, hurt, or angry? Researchers have argued that a person’s status is based on the
prestige, honor and deference accorded him or her by other members of the group (Lovaglia
and Houser, 1996).55 When we talk about the concept of status, we refer to two interrelated
concepts: (1) the creation of status ranking, and (2) the attempt to achieve high status
ranking (Waldron, 1998). That would be great if we could get it ourselves directly, but
status is a by-product of how we behave or live our life. It cannot be gained directly.
Notice that I say “by other members of the group”. In order to gain the prestige, honor
and deference accorded by other members, we must do what is right, and more importantly
be perceived to do something right, meaning that we must be able to behave for a period of
time that can be weeks, months, or even years. This is why any situation that takes away our
status in effect harm our self-esteem, because when we feel being demoted in status, we
think we do something wrong. Therefore we find that our self-esteem is intertwined. And
that is the key. A change in anyone’s status implies a change in a set of relationship
between this person and other people in the social group. As we will see, it is the loss of
status that exerts effects on our decision. When we see our status in a society is declining,
we will often see ourselves fighting back against whatever seems to cause that change. We
become defensive and that is understandable. For instance, when we are ordered to take up a
position that is considered to be lower than the one we are currently occupying, we do not
feel good about ourselves, and we may even feel guilty and fight back. Any situation that
robs us of our status forces us consciously or unconsciously to react negatively. Prior
research on organizational change management has suggested that employees’ status quo in
54 Research on status has been undertaken in at least three disciplines: (1) sociology, (2) anthropology, and (3)
psychology. Arguments made in this dissertation are mainly from theories and frameworks from sociology and
psychology. 55 Note that we should distinguish between status in organizational contexts and the formalized positions in the
organizations. As Waldron (1998) points out, formalized positions and status rankings may often be parallel, but
they are not identical.
57
an organization induces resistance to change, particularly when a change negatively affects
their status quo (e.g., Smith, 1982; Spreitzer and Quinn, 1996). Additionally, Spreitzer and
Quinn (1996) discovered that middle managers claimed that higher-ranked executives
resisted change efforts. Similarly, Smith (1982) found that people in power often try to
maintain the status quo rather than change it and that when a proposed change is perceived
of having a negative impact on their power, such perceived loss of power enacts a defense
mechanism, leading to resistance to change. Research has also shown that the achievement
of status is one of the important concerns of employees (e.g., Kovach, 1987).
Many people tend to associate power with social status, maintaining that the greater
the power, the higher the rank of social status becomes. When organizational change affects
our status in a negative way, it causes us to question ourselves as a person, and we have a
tendency, conscious or unconscious, to behave in ways that may maintain our status. Do
you feel that words like power and status sound similar to us? Although power and status
may often be parallel, they are not the same. Therefore it is important to distinguish between
the two, and that will allow us to study the effects of perceived change in status.
There is also another aspect to consider. Based on the social exchange theory (Blau,
1964) and the norm of reciprocity (Gouldner, 1960), it is argued that employees will view a
decline in their status in an organization as a negative treatment they receive from an
organization, and feel obliged to return a negative treatment to the organization (Gouldner,
1960). This is why people are easily annoyed and upset when something demotes their
status. And this is exactly why, when a change affects employees’ status, they tend to have a
negative response to such change. On the other hand, one can argue that employees facing
organizational change will react positively when they feel that such change will provide
them a higher status in an organization. This is because employees may perceive a higher
status as a positive treatment they receive from an organization, and feel obliged to return a
positive favor or benefit to the organization, leading them to support the change.
In line with this discussion, it can be reasoned that there may exist the relationship
between employees’ perceptions of change in status resulting from organizational change
and their reactions to change. Thus, the following hypotheses are proposed:
H9a: An employee’s perceived rise (fall) in status resulting from a change will be
negatively (positively) related to their resistance to change.
H9b: An employee’s perceived rise (fall) in status resulting from a change will be
positively (negatively) related their support for change.
58
3.2.10. Perceived Change in Pride
An idea that employees’ perceived change in pride affects their reactions to change has yet
become well studied. A question in this context is: Does a perceived change in pride
resulting from organizational change exert an effect on a choice of reactions to change and
the magnitude of any chosen reaction? Based on the social exchange theory (Blau, 1964)
and the norm of reciprocity (Gouldner, 1960), a general hypothesis is that any modification
to a person’s pride will be the major driver of his or her subsequence reactions to a cause of
such modification.
It is argued that employees facing organizational change will have a normative
expectation about the likelihood of various outcomes of a change that might occur in that
setting. Any outcome of a change that robs or decreases employees’ pride forces them to
react negatively to such change—that is to say, they will resist such change. On the other
hand, any outcome of a change that promotes or increases employees’ pride encourages
them to react positively to such change—that is to say, they will support such change.
What is pride? In general, pride is “the quality or state of being proud”. In the
organizational setting, pride can be defined here as the quality or state of being proud about
oneself in one’s social group (e.g., in one’s workplace). A question then is why any change
in pride has an effect on employees’ reactions to change. Initial answers to this question
focus on the psychological motivations for reacting to any change in pride. It is logical to
expect that any person who feels being robbed of his or her pride will feel hurt and upset,
and try to regain his or her pride. This is because we, as a human being, socialize with other
member of our social group. Interactions with other members and the group’s acceptance of
us in a social group are the key to our psychological well-being. When a person is left
feeling a loss of pride, these emotions or feelings tear away at his or her self-esteem.56
Loss of pride can lead to embarrassment and disruptive modifications of ties or
linkages between people and their social group. Thus, they will try to regain their pride, and
remove their embarrassment. One of possible cures for this loss of pride is to remove its
cause—the change. Thus, if employees perceive organizational change accountable for their
loss of pride, and feel that removing such change will bring back their pride, they will try to
remove such change, meaning that they will resist the change.
As mentioned earlier, the social exchange theory (Blau, 1964) and the norm of
reciprocity (Gouldner, 1960) can be used to explain the possible relationship between
perceived change in pride on the one hand and resistance to change and support for change
on the other hand. Consider organizational change that decreases employees’ pride. Suppose
56 See Maslow (1954, 1970) for a detailed discussion of the hierarchy of need’s theory.
59
that employees’ pride is based on how they are proud of themselves in their social group. If
employees have a feeling that organizational change causes a negative change in their pride
(that they have in their workplace), and perceive this negative shift in pride as a negative
treatment or injury they receive from an organization, we might expect that they will want
to return in kind this injury to the organization—that is to say, they will resist the change.
On the contrary, if employees have a feeling that organizational change causes a positive
change in their pride (that they have in their workplace), and perceive that this positive
change in pride as a positive treatment or favor they receive from an organization, we might
expect that they will feel obliged to return in kind this benefit to the organization—that is to
say, they will support the change. This view is consistent with past research that has
suggested that pride is related with humans’ decision. For example, Kotter and Cohen
(2002) found that false pride or arrogance drives complacency, and that prevents the
implementation of planned change. This means that when employees perceive that their
pride may be obstructed or negatively affected by organizational change, they tend to
behave in such a way that may maintain the current state of pride, meaning that they will
resist the change.
It is important to note that pride is often associated with power; that is, the greater the
power, the greater the pride becomes. But it is crucial that we distinguish between the two
because even if power and pride may often be parallel, they are not the same. To illustrate
this point, consider whether employees who are proud of their contribution to the firm’s
success will always have more power in the organization. Of course their contribution may
lead them to be promoted to a higher position within the firm. A question is then whether
we can firmly conclude that pride and power are parallel in a situation where the
contribution does not lead to any promotion or more power57, and they are still proud of
themselves for what they have achieved for the organization. Thus, we should not assume
that pride and power are the same in this context. In sum, the following hypotheses are
proposed:
H10a: An employee’s perceived rise (fall) in pride resulting from a change will be
negatively (positively) related to their resistance to change.
H10b: An employee’s perceived rise (fall) in pride resulting from a change will be positively
(negatively) related to their support for change.
57 Note that I focus only the power associated with a position in an organization. For simplicity, other kinds of power
or how others’ perceptions of his power are not taken into account.
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3.2.11. Job Satisfaction
Now I should like to discuss another factor in my model—job satisfaction. The question is
whether there is a direct relationship between job satisfaction and reactions to change. Past
studies have tried to explain relationships between job satisfaction and a variety of decisions
and behaviors. For example, Mobley (1977) noted that job dissatisfaction often leads
employees to quit the organization due to the effect of the expectation that leaving an
organization will result in getting a more satisfying job. Therefore, it seems logical to argue
that job satisfaction may place considerable condition on an exchange relationship between
employees on the one hand and the organization and their reactions to change on the other
hand.
To fully understand what is going on, we have to answer the question: what is job
satisfaction? Research on job satisfaction has generated several definitions of job
satisfaction. I can only mention a few definitions here. First, Smith, Kendall and Hulin’s
(1969: 6) defined job satisfaction as “the extent to which an employee has a positive
affective orientation or attitude toward their job, either in general or towards particular
facets of it”. Second, Locke (1976: 1300) defined job satisfaction as “a pleasurable or
positive emotional state resulting from the appraisal of one’s job or job experiences”.
Finally, Dorman and Zapf (2001: 486) defined job satisfaction as “a pleasurable emotional
state resulting from the appraisal of one’s job”. In a nutshell job satisfaction tells us about
how a person feels about his job—for example, whether he is happy or unhappy with his
job.
When employees are satisfied with their job, they may be happy because it satisfies
how they want to see themselves. And this helps them establish their ability to feel in
control. On the other hand, when they are not satisfied with their job, they may not be happy
because it hurts how they see themselves. It robs them of their ability to feel in control.
When they are not satisfied with their job, they feel uncomfortable. When they are told
doing wrong things at work, they go into protection mode—they try to defend themselves of
what they did, and more importantly, of a person they are.
This is why organizational change that changes the degree to which they are satisfied
with their job may bother them. A person with a perception that this change means he has
performed not well enough will fell uncomfortable, hurt, and upset. Because these feelings
eat away at his self-respect and self-esteem, he feels less good about himself. So he
becomes defensive and wants to protect his self-respect and self-esteem. He will react
negatively to this change. On the other hand, when a person thinks that this change indicates
that he has worked well, he will feel good, happy, and joyful. Because these feelings
enhance his self-respect and self-esteem, he feels better about himself. So he becomes more
61
open and wants to gain even more self-respect and self-esteem. Therefore he will react
positively to this change.
Prior research on job satisfaction has suggested that job satisfaction is positively
correlated with attitude towards change (Gardner et al., 1987). Moreover, it has been
empirically confirmed that low job satisfaction is related to high turnover (e.g., Mobley,
Horner and Hollingsworth, 1978; Porter and Steers, 1973). Another empirical study by
Farrell (1983) has found that low job satisfaction is related to four categories of behaviors—
exit, voice, loyalty and neglect. Past studies have also suggested that job satisfaction is
sigificnatly correlated with organizational commitment (e.g., Brooke, Russell and Price,
1988, Davy et al., 1991). A more recent study by Iverson (1996) has found that employees
with high levels of job satisfaction will have higher levels of acceptance of organizational
change.
In addition, it should be noted that despite a general tendency to measure job
satisfaction at the overall job, several researchers have started to measure satisfaction with
job facets such as pay or promotion opportunities (e.g., Smith et al., 1979; Taber and
Alliger, 1995). In addition, some searchers (e.g., Weiss et al., 1967; Davy, Kinicki, and
Scheck, 1997) have started to distinguish between intrinsic job satisfaction and extrinsic job
satisfaction. Intrinsic job satisfaction denotes a pleasurable emotional state resulting from
the appraisal of one’s intrinsic aspects of the job, whereas extrinsic job satisfaction denotes
a pleasurable emotional state resulting from the appraisal of one’s extrinsic aspects of the
job.
As the above discussion suggests, employees who perceive lower levels of job
satisfaction as a direct or indirect consequence of a change are more likely to react
negatively to change. Likewise, employees who have high levels of job satisfaction as a
direct or indirect consequence of a change are more likely to react positively to change. In
summary, the following hypotheses are formulated:
H11a: Employees’ job satisfaction will be negatively related to their resistance to change.
H11b: Employees’ job satisfaction will be positively related to their support for change.
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3.2.12. Job Security
Is it possible that job security or insecurity might exert an influence on employees’ reactions
to change? The big question here is whether employees can make their decision properly
and correctly when they do feel insecure about their job situation. A variety of studies have
shown some consistency in the strength or even the direction of the relationships between
job security and several work-related decisions observed. For example, an empirical study
by Westman et al. (2001) has found that there is a relationship between job security and
burnout, whereas an empirical study by King (2000) has found that job security has a
significant impact on work efforts, organizational loyalty as well as on citizenship behavior.
Another empirical study by De Witte (1999) has also found that job security has effects on
psychological well-being. As a result, it ought to be possible that perceptions of job security
may have effects on employees’ reactions to change.
What is job security? Unlike job satisfaction, job security reflects the perceived
continuity in a job a person receives for his or her contribution to the organization. Job
security has been defined as “one’s expectations about continuity in a job situation” (Davy
et al., 1997: 323). What is job insecurity? Job insecurity has been referred to the degree of
uncertainty an individual has about his or her job continuity (see e.g., Greenhalgh, 1982).
Job insecurity has been defined as “the lack of control to maintain desired continuity in a
threatened job situation” (Hui and Lee, 2000: 216).
But how does job security or insecurity have to do with reactions to change? We all
know that for a change, any change, in an organization, we might sense its impact in one
way or another. If we do not feel anything about this change with regard to job security,
then it is fine. But if we feel that this change affects our job security, it causes us to question
our own self-worth and react on it. This is why employees with a perception of job
insecurity are highly sensitive—because they question themselves of their ability to work
and remain with the organization. When we feel insecure about our job situation, we feel
less good about who we are and what we do. The greater our feeling of job insecurity, the
greater hurt we feel. Therefore we go into protection mode—we react negatively. Resistance
to change is the impulsive response to this hurt feeling because we direct our resistance
toward the source that we feel responsible for eating away at our self-respect and self-
esteem. In sociology and psychology, the literature on trust suggests that trust lowers
transaction costs by ‘replacing contracts with handshakes’ (Adler, 2001). Therefore, we may
expect that both parties—employees and employers—would try to honor both formal and
informal contracts because withdrawing from the contacts is usually costly, and parties are
willing to accept such costs which can be in monetary and/or non-monetary forms only if
positive consequences of a contractual cancellation are considerable. Has there ever been a
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time in your life when you had implicit expectations about your job security? Prior studies
have insisted that we do have implicit expectation about our job security (Rousseau, 1989).
Researchers have suggested that any perceived threat to the job security represents a
possible violation of the informal or psychological contract, and that leads to withdrawal
cognitions (Davy et al., 1997).
Feelings or perceptions of job insecurity during change processes can lead to aversive
psychological outcomes. This occurs through a complex process (e.g., interpretation), which
tends to weaken a person’s rational thinking mechanism. Strong feelings of job insecurity
that stem from organizational change can result in resistance to change because employees
may view resistance to change as a means to reverse the change. Why is this so? By
focusing on the negative aspects of change (e.g., job insecurity), employees will feel less
good about the change. When their feeling of job insecurity becomes so strong, they become
very emotional and tend to forget about other potentially good aspects of the change. In
addition, perceptions of uncertainty regarding the existence of one’s current job may be as
damaging as actual job losses (Latack and Dozier, 1986).
Another question is whether employees who feel secure at their job during change
processes are likely to be less emotionally affected by the change, thereby decreasing a
tendency to engage in such behaviors that opposes the change. Intuitively the magnitude of
perceptions of job security or insecurity is likely to influence how employees will react. It is
noteworthy that it may occur that a negative shift along a continuum—from job security to
job insecurity—tends to have a far greater effect on employees’ response than a positive
shift along the same continuum—from job insecurity to job security.
But do you feel that traditional notions of job security remain in many workplaces
nowadays? Rousseau (1995) posited that in some workplace settings employees tend to
focus on employability rather than job security. Thus, the extent to which employees value
job security may mediate the effect of job security on reactions to change. Additionally, a
notion of work-life balance58 was found positively correlated with organizational
commitment (Scandura and Lankau, 1997). This may also condition the effects of feelings
of job security on reactions to change. In sum, the following hypotheses are proposed:
H12a: Employees’ job security will be negatively related to their resistance to change.
H12b: Employees’ job security will be positively related to their support for change.
58 The concept of work-life balance concerns with career advancement and family responsibilities (Wolfe & Kolb,
1980)
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3.2.13. Job Motivation
Recent developments in the management literature, and particularly in the field of
organizational behavior, have raised great interests as to how organizations can raise the
extent to which employees are motivated to perform their job (e.g., Herzberg, 1968).
However, it is not the purpose of this dissertation to discuss these interests, or to determine
whether organizations can motivate employees, or to examine what they should do to
motivate their employees.59 Rather, I shall assume that most, if not all, actions of an
organization affect employees’ job motivation, and shall put forth some proposition as to the
effect of job motivation on employee’s reactions to change might be.
Broadly speaking, an organization’s actions are expected to affect employees’ job
motivation because these actions may lead to significant changes at the employee level such
as new job characteristics, new hiring, or even dismissal (Korsgaard et al., 2002). Because
past research has suggested that job motivation tends to affect work performance (e.g.,
Herzberg, 1968), it can be reasoned that organizational changes may have an effect on
employees’ job motivation, and that job motivation may in turn determine not only the
choice of reactions to change but also the strength of such reaction. In this respect, this
dissertation focuses on examining if there is a direct relationship between job motivation on
the one hand and resistance to change and support for change on the other hand.
What is job motivation? Or for that matter, what is motivation? In psychology,
motivation has long been defined in relation to need strength. For example, McClelland’s
need theory has posited that humans are motivated by need for power, achievement and
affiliation (McClelland and Boyatizis, 1984). Prior research on job motivation in the
management literature seems to follow the frameworks of research on motivation in
psychology. For instance, the motivation-hygiene theory of job attitude (Herzberg, 1968)
has suggested that there are two sets of different needs of humans: one of which relates to
animal nature; another relates to unique characteristic of human—the ability to achieve and
to experiment with psychological growth.
Research on job motivation has distinguished between intrinsic motivation and
extrinsic motivation (Herzberg, 1968; Hui and Lee, 2000; Sansone and Harackiewicz,
2000). Intrinsic motivation represents “the relationship between a person and his/her job
itself” (Hui and Lee, 2000: 216) and is derived from within the person or form the activity
related to the job itself (Sansone and Harackiewicz, 2000). Research on intrinsic motivation
has suggested that task variety, task significance, task identity, and feedback from the task
59 In the research on job motivation, there are several theories: for example, Kanfer’s taxonomy of motivation theories
(1990) and Vroom’s expectancy theory (1964).
65
are the key characteristics that induce intrinsic motivation (Hackman and Oldham, 1976).
On the other hand, extrinsic motivation represents the relationship between a person and
externally administered rewards such as pay or prestige from others (Komaki, 1982).
An empirical study by Stumpf and Hartman (1984) has found that there is a positive
relationship between work motivation and perceived work performance and that work
motivation has a moderate correlation with intention to quit. Thus, it can be reasoned that if
there is a considerable relationship between job motivation and intention to quit, then, it
ought to be possible that there may be a relationship between job motivation and resistance
to change or support for change. It can be argued that employees who have a low level of
job motivation60 are less likely to provide support for organizational change than those who
have a high level of job motivation. In the same vein, employees who have a high level of
job motivation may be less likely to provide resistance to change than those who have a low
level of job motivation. Why is this so?
Drawing upon research on job motivation (e.g., Herzberg, 1968) suggesting that
employees seek to align motivation levels with efforts and that alignment processes have
certain implications for their decision, one may expect that the nature and magnitude of
employees’ reactions to change may also be influenced by their job motivation. In addition,
one may also reason that if past actions of organizations influence employees’ job
motivation, then organizational change may also influence their job motivation.
Suppose that organizational change has negative consequences for employees: for
example, greater levels of workloads or lower compensation. In this situation, employees
will be less motivated to work and, thus, more likely to provide resistance to change. On the
other hand, suppose that organizational change has positive consequences for employees:
for example, higher compensation or better job conditions. Then, they will be greater
motivated to work and, thus, more likely to render support for change. It must be noted that
in this dissertation, it is assumed that any effect of consequences of organizational change
on employees will be subsumed to a level of job motivation. In summary, it is hypothesized
that:
H13a: Employees’ job motivation will be negatively related to their resistance to change.
H13b: Employees’ job motivation will be positively related to their support for change.
60 For simplicity, I assume that the degree of job motivation of employees during organizational change represents the
net degree of job motivation after any effect of organizational change that may have on him.
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3.2.14. Perceived Employability
As discussed earlier, a general attitude towards an idea, issue or object formed by an
individual is more likely to promote a positive or negative inclination on the perceptual
process and decision-making process.61 If employees form a perception about their
employability, which refers to how employable they are for another identical or better job in
the market, perceived employability may play a role in determining a kind of reactions to
change.
In contrast to a relative large body literature in the area of human resource
management dealing with a wide array of job characteristics such as job motivation (e.g.,
Herzberg, 1968), job security (e.g., Westman et al., 2001), or job satisfaction (e.g., Mobley
et al., 1978; Porter and Steers, 1973), research on employability has been extremely scant.
Indeed, I have found no theoretical or empirical work focusing on employability. The path I
propose to follow in theorizing the effect of perceived employability on reactions to change
is by using arguments of the concept of sense of control (e.g., Parks, 1989; Westman and
Etzion, 1995; Westman et al., 2001).
Sense of control is “a generalized belief on the part of the individual about the extent
to which important outcomes are controllable” (Parks, 1989:21). Following from this, I
propose that employees may consider “employability” as an important outcome and that
they may have a certain degree of sense of control over their employability—that is to say,
they may hold a certain belief about the extent to which acquiring new jobs are controllable.
In this view, it can be reasoned that perceived employability, at its core, has at least one
similar property as that of sense of control: that is to say, both constructs concern the extent
to which important outcomes are perceived to be controllable. Thus, I maintain that one may
extent the concept of sense of control to develop a better understanding of perceived
employability.
Empirical evidence has shown that sense of control exerts effects on several work-
related outcomes of employees. For example, an empirical study by Westman and Etzion
(1995) has found a negative relationship between sense of control and burnout of
employees: that is, sense of control helps reduce degrees of burnout. In a more recent study,
Westman et al. (2001) also found that employees’ burnout is associated with their feelings
of job insecurity as well as self-control. Thus, if sense of control has the effects on one’s
attitudinal and work outcomes, so has sense of perceived employability, and the prediction
that perceived employability may influence employees’ reactions to change will seem
plausible.
61 For a detailed discussion of the concept of attitudes, see Section 2.4 of this dissertation.
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The nature and magnitude of perceived employability may arise from several sources
such as self-confidence (e.g., self-efficacy for performing), career aspiration, and current
characteristics of job market. Specifically, factors such as a high level of self-confidence, a
booming job market, good economic conditions or a high degree of knowledge possessed
and demanded by the market may promote a positive perception of one’s employability
which can be defined as a perception of having no difficulty for getting an identical or better
job if needed. On the other hand, factors such as a low level of self-confidence, a poor job
market, poor economic conditions or a low degree of knowledge possessed and demanded
by the market may promote a negative perception of one’s employability which can be
defined as a perception of having some difficulty in getting an identical or better job than
the current one if needed.
The important for us to observe is that the perceived employability construct also has
one property of the concept of self-confidence: that is, to say, for employees to form their
perceived employability, they need to form a level of confidence that they will achieve a
certain goal, of which is getting a new job. Thus, one may also extend the logic of the
concept of self-confidence to explain potential effects of perceived employability for
employees’ resistance to change and support for change.62
Here, it is argued that employees’ perceived employability might affect their
perceptual process and decision-making process when dealing with how to react to
organizational change. Suppose that employees have already established a perception of
their employability, it is possible that their perception may moderate a relationship between
them and their organization. That is, perceived employability may determine the extent to
which employees depend on the organization in terms of employment. Is it possible to
expect that employees who feel capable of having a new job easily will feel less dependent
on their current employment than those who feel less capable of getting a new job?
Up to this point, a key assumption in this discussion is that the degree to which
employees value the employment contract with their current employer can be explained by
the degree of their employability in the job market they hold. One can also reason that
employees’ perception of their dependency on the organization may be determined by
perceived employability. Then, it is probable that employees who have a low level of
perceived employability may be motivated to behave in ways to remain with their
organization than those who have a high level of perceived employability.
One key question remains: how does perceived employability shape or affect
employees’ reactions to change? It remains unclear whether a positive perception of
62 For a detailed discussion of self-confidence, see Section 3.2.15 of this dissertation.
68
employability will have a positive or negative relationship with resistance to change and/or
support for change. Similarly, it remains unclear whether a negative perception of
employability will have a positive or negative relationship with resistance to change and/or
support for change. To illustrate this point, let us consider, for example, a simple case where
employees are afraid of losing their job, and they do not expect to get a new job easily. One
possible scenario is that they will strongly resist the change because keeping their current
job is very important. On the other hand, it is also possible that they will accept the change
because they are afraid that their resistance to change may cause their job.
Similar to the above case, let us consider whether employees will support or resist
organizational change when they have a high degree of perceived employability. Certainly
we cannot answer this question outright because this perception seems to mediate
relationships between other variables and reactions to change rather than to have a direct
effect on reactions to change. In addition, because employees who have a high degree of
perceived employability may not be dependent on their current job, they may have more
options regarding reactions to change, and feel relatively free to make a reaction.63 The
important point for us to observe is that both high and low levels of perceived employability
can lead to different reactions to change. However, because there is no prior study
examining the effect of perceived employability on reactions to change, I shall first focus on
examining direct relationships between them. Thus, I propose the following hypotheses:
H14a: Employees’ perceived employability will be positively related to their resistance to
change,
H14b: Employees’ perceived employability will be negatively related to their support for
change.
63 Note that I assume that an employee with a high degree of perceived employability is not afraid of choosing a
decision that he feels is right (for him). In contrast, an employee with a low degree of perceived employability tends
to be afraid of choosing a reaction that may eventually cause his job even if that choice may be his preferred
reaction.
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3.2.15. Self-Confidence for Career-Relevant Learning
Individuals have different beliefs or perceptions about the factors responsible for what
happens to them. Individuals with an internal locus of control consider what happens to
them as determined by factors under their control, whereas those with an external locus of
control consider what happens to them as determined by factors outside their control
(Rotter, 1966; Elangovan and Lin Xie, 1999). A question is then whether it is possible that
one’s self-confidence exerts an influence on his or her decision? Specifically, does
employees’ self-confidence for career-relevant learning and competent development exert
effects on their reactions to change? In exploring a direct effect of self-confidence for
career-relevant learning and competent development (or in short ‘self confidence for
learning and development’) on employees’ reactions to change, this dissertation focuses on
resistance to change and support for employee of employees as (dependent) variables of
interest.
There has been a growing awareness in the organizational psychology literature (e.g.,
Bandura, 1977) that self-efficacy is a key determinant of individuals’ intention and choice to
pursue an activity. Self-efficacy has been defined as the belief that one possesses the ability
to complete a certain task (Foley, Kidder and Powell, 2002). Moreover, Bandura (1997)
suggested three levels of self-efficacy: (1) task specific self-efficacy; (2) domain self-
efficacy; and (3) general self-efficacy. Consistent with the definition of self-efficacy, self-
confidence for career-relevant learning and competence development can be categorized at
the task specific self-efficacy, which is self-confidence for dealing with performance of a
specific task, and at the domain self-efficacy level, which is self-confidence for dealing with
performance within a certain domain of tasks. In addition, competence development should
encompass learning of new skills or new level of existing skills. Consequently, self-
confidence for learning and development, at its core, refers to one’s confidence in learning
new things and developing new skills.
It has been argued that self-efficacy for development and learning and self-efficacy for
performance should be distinguished (Maurer, 2001). According to Maurer (2001), self-
efficacy for development and learning refers to one’s confidence in developing skills and
learning new things, whereas self-efficacy for performance refers to one’s confidence in
performing a task that one already possesses the skills required to perform that task. It is
useful to note that research has suggested that a decline in older employees’ self-confidence
in their ability to learn and develop may contribute to the age effect on participation in
learning and development (see e.g., Fossum, Arvey, Paradise and Robbins, 1986).
Another question is whether it is plausible to expect that employees who have a high
level of self-confidence for learning and development tend to feel more comfortable with
70
organizational change than those who have a low level of self-confidence for learning and
development. One may speculate that employees who have a high level of self-confidence
for learning and development will feel more comfortable than those who have a low level of
self-confidence for learning and development. One plausible reason to support this
proposition is that the degree to which a knowledge, skill or competence is obtainable may
be influenced by self-confidence for learning and development. Another possible reason is
that a work performance may be influenced by a result of learning new knowledge and
skills; therefore, employees who have a low level of self-confidence for learning and
development may be afraid of having a poorer work performance because they fail to learn
new knowledge or skills. Likewise, those who have a high level of self-confidence for
learning and development may consider learning new skills as an interesting challenge
sufficient so as to enjoy doing it, whereas those who have a low level of self-confidence for
learning and development may have a negative view on learning new skills. Last but not
least, it is also possible that employees who have a high level of self-confidence for learning
and development may consider learning new skills (as part of organizational change) as an
opportunity to boost their career prospect rather than as a threat to their work performance
or career advancement, whereas those who have a low level of self-confidence for learning
and development may have another idea.
In sum, this dissertation examines whether there is a negative relationship between
self-confidence for learning and development and resistance to change and whether there is
a positive relationship between self-confidence for learning and development and support
for change. To test these hypothesized relationships, the following hypotheses are proposed:
H15a: Employees’ self-confidence for career-relevant learning and competence
development will be negatively related to their resistance to change.
H15b: Employees’ self-confidence for career-relevant learning and competence
development will be positively related to their support for change.
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3.2.16. Affective Commitment
Despite the general agreement on the effect of affective commitment—that is to say, the
relationship between affective commitment and various work-related variables such as
willingness to turnover (Parker et al., 2003) or trust in management (Kim and Mauborgne,
1993; Pearce, 1993) have been found, there seems to be no prior empirical studies
examining effects of affective commitment on reactions to change, especially resistance to
change and support for change. Following from this, one might expect that employees who
are committed to their organization are not only less likely to behave in ways that resist
organizational change but also more likely to behave in ways that support organizational
change because they want their organization to be successful. Therefore, this dissertation
examines whether there is a relationship between affective commitment and resistance to
change and support for change.
A review of the literature dealing with organizational commitment has revealed
several terms such as affective commitment (Porter, Steers, Mowday and Boulian, 1974;
Allen and Meyer, 1990), normative commitment (Weiner, 1982), organizational
commitment (Mowday, Steers and Porter, 1979), and affective organizational commitment
(Mowday, Porter and Steers, 1982). Affective commitment refers to emotional attachment
to, identification with, and involvement in organization (Meyer and Allen, 1997), whereas
organizational commitment refers to identification with organizational goals, willingness to
exercise effort on behalf of the organization, and interest in remaining with the organization
(Mowday et al., 1979). There is one issue here to which I would like to draw attention.
Although these terms seem to have been used interchangeably across much of research,
there is still some disagreement concerning the definitions of organizational commitment
(Iverson and Roy, 1994). The point of departure amongst researchers over the definitions of
organizational commitment centers on an issue about whether commitment is attitudinal or
behavioral in nature. However, this is not of a great concern to this dissertation because one
can take either perspective or both of them for the purpose of studying the effect of
employees’ commitment to their organization on their decisions. In spite of their
differences, however, I tend to follow the “attitudinal commitment” perspective because it
can be argued that humans tend to follow what their heart tells to do.64
While researchers seem to disagree on the definitions, they have provided empirical
evidence supporting the notion that commitment, regardless of whether it is attitudinal (or
64 Note that to be more specific and correct on this point, one has to assume that actions that the mind or heart tells one
to do are actionable. For example, if someone intends to quit his job for whatever reason, he might not actually do so
when he does not think he can get another comparable job in a reasonable time period.
72
affective) commitment or behavioral commitment, has the effects on employees’ decisions
(e.g., Kim and Mauborgne, 1993; Parker et al., 2003). Additionally, research on
organizational commitment has pointed out that a degree of the organization’s commitment
to its employees is one of predictors of organizational commitment. This argument is
supported by an argument that employees’ perception of their organization’s actions will
induce the reciprocity in their attitudes or behaviors (Shore and Tetrick, 1991). Moreover,
empirical evidence has also suggested that perceived organizational support is significantly
correlated with organizational commitment (e.g., Shore and Tetrick, 1991), and
organizational commitment is significantly related to trust in management (e.g., Kim and
Mauborgne, 1993; Pearce, 1993; Gopinath and Becker, 2000; Whitener, 2001).
Based on past theoretical underpinning and empirical evidence, linking employees’
affective commitment to their reactions to change (e.g., resistance to change and/or support
for change) is supported by at least two reasons. A first reason is that based on the norm of
reciprocity (Gouldner, 1960), employees who have a low level of affective commitment
may hold a perception that they are under no obligation to return certain benefits to their
organization because a low level of affective commitment indirectly implies a low level of
perceived organizational support (Shore and Tetrick, 1991). On the other hand, employees
who have a high level of affective commitment may hold a perception that they have an
obligation to return benefits to their organization. Following from this, organizational
change that shifts levels of affective commitment tends to have altered perceptions of an
obligation to the organization. Employees who have a perception that they are under an
obligation to return a favor to their organization are more willing to repay their organization
in one or more ways than those who have a perception that they are under no obligation to
their organization. On the other hand, employees who have a perception that they are under
no obligation to their organization are unlikely to refrain themselves from resisting the
change, if it deems appropriate. It can be reasoned that if employees were to consider
support for change as a means to repaying his organization, those who have a perception
that they are under an obligation to repay their organization will provide higher levels of
support for change.
A second reason to support the potential relationship between affective commitment
and resistance to change and support for change is that if levels of affective commitment
play a role in determining levels of work performance (Parker et al., 2003), employees who
have a high level of affective commitment tend to perform their work better than those who
have a low level of affective commitment. If employees have a low level of affective
commitment during organizational change, then we might expect that they will tend to have
a lower level of work performance. Intuitively, changes in work performance may be
73
influenced by resistance to change. Similarly, if employees have a high level of affective
work performance, then we might expect that they will tend to have a higher level of work
performance. Changes in work performance may be influenced by support for change. This
position is then supported by an empirical study by Parker and colleagues (Parker et al.,
2003), which has found that effects of work attitudes (job involvement and commitment) on
work performance are partially mediated by motivation. If support for change is positively
correlated with work effort devoted to an organization, and if resistance to change is
negatively correlated with work efforts, then affective commitment differences among
employees will result in a variation in the nature and the degree of reactions to change.
Specifically, it is expected that there is a positive relationship between affective
commitment and support for change, and there is a negative relationship between affective
commitment and resistance to change. Thus, the following hypotheses are formulated:
H16a: Employees’ affective commitment will be negatively related to their resistance to
change.
H16b: Employees’ affective commitment will be positively related to their support for
change.
3.2.17. Trust in Management
Parallel to the logic of H16a and H16b, this dissertation predicts that there is a relationship
between trust in management and reactions to change. An important question is concerned
with whether employees will make a different decision between when having a high degree
of trust in management and when having a low degree of trust in management. Past research
has recognized the significance of trust in management or leadership (e.g., Argyris, 1962;
McGregor, 1967). Not only has the concept of trust in management lead to several
leadership theories—for example, trust is a key element of leader-member exchange theory
(Schriesheim, Castro and Cogliser, 1999) and employees’ trust in management as an
important factor for leader effectiveness (Bass, 1990)—but it has been emphasized in other
concepts such as psychological contracts, organizational relationships, or change
management. It has been suggested that trust in management would inevitably become one
of key concepts in organizational theory (Kramer, 1999).
Trust, which is a social construct, has been defined as a “psychological state
comprising the intention to accept vulnerability based upon positive expectations of the
74
intention or behavior of another (Rousseau, Sitkin, Burt and Camerer, 1998: 395).65 Trust in
management refers to employees’ attitude towards top management that indicates their
willingness to be vulnerable to top management (Whitener, Brodt, Korsgaad and Werner,
1998). Similarly, the trustworthiness has been defined as “an individual belief that top
management can be trusted” (Spretizer and Mishra, 2002: 710).
Prior research on organizational change management has noted that when top
managers attempt to undertake changes within their organization, they should build trust
among their employees in order to facilitate and sustain effective change (Webb, 1996).
Indeed, top managers should build trust among employees so as to increase organizational
effectiveness (Argyris, 1962). In addition, perceptions of legitimacy of organizational
change can be enhanced by trust in management (Rousseau and Tijoriwala, 1999). Several
researchers (e.g., Bridges, 1980; O’Toole, 1995) have noted that distrust towards those
leading changes is one of factors that lead to employees’ resistance to change.
Empirical research examining the role of trust in management has shown that there are
certain relationships between employees’ trust in management and their attitudinal
outcomes (Dirks and Ferrin, 2001). For example, Kim and Mauborgne (1993) and Pearce
(1993) found a relationship between trust in management and affective commitment. More
recently, Spreitzer and Mishra (2002) also found a positive correlation between the
trustworthiness of management and affective commitment. In addition, empirical evidence
has suggested that trust in management has a positive effect on group performance
(Klimoski and Karol, 1976) and business unit performance (Davis, Shoorman, Mayer and
Tan, 2000). Although prior research on trust has suggested that employees’ trust in
management develops through a social exchange process over time; that is, a process of
social exchange generates trust (Blau, 1965), there are different explanations about the
process through which trust forms as well as the process through which trust affects work-
related outcomes (Dirks and Ferrin, 2002).66
There is another issue here deserves attention. The issue is that there is a great
diversity in constructs of trust across much of past studies. Not only have researchers
provided many definitions of trust in management but also they have specified the construct
with different leadership referents (Dirks and Ferrin, 2002). For example, some researchers
have given attention to trust in a direct leader, whereas others have given attention to trust in
top management. Clarification on this issue is very important not only for theoretical
65 For Kim and Mauborgne (1993), this definition suggests that employees’ trust in management reflects two important
aspects: (1) an employee’s faith in organizational goal attainment and an organizational leader; and (2) an
employee’s belief that he or she will receive benefits from an organizational action. 66 For a more detailed discussion of this issue, see Dirks and Ferrin (2002).
75
reasons, but also for practical reasons, as it may provide guidance on whether this
dissertation should focus on trust in a direct leader or trust in leadership. Considering that
the forms of organizational change studied in this dissertation are a downsizing and a
privatization that have been originated by top managers,67 I therefore propose that the
theoretical construct of trust in management in this dissertation rests on trust in top
management rather than on a direct leader.
In light of this discussion, it can be reasoned that employees who have high levels of
trust in management are likely to provide higher levels of support for change and lower
levels of resistance to change. Accordingly, the following hypotheses are proposed:
H17a: Employees’ trust in management will be negatively related to their resistance to
change.
H17b: Employees’ trust in management will be positively related to their support for
change.
3.2.18. Colleagues’ Reactions to Change
Research on the effect of group and organizational context on attitudes and behaviors of
employees has attracted growing attention in the field of management (Kidwell, Mossholder
and Bennett, 1997). The social context has been described by relational phenomena that
cannot be understood in terms of individual separately but rather in terms of characteristics
of the environment, organization, and work group together, of which have an impact on
attitudes or behaviors of individual members of the group (Kidwell et al., 1997). Both the
social exchange theory (Blau, 1964) and the norm of reciprocity (Gouldner, 1960) can
explain the interactions and interpersonal relationships between members of the group and
the influence of the group’s norms on individual members of the group. In addition, social
network theory (Alderfer, 1986), which suggests that social relationships are embedded
within a larger structural context that encourages or precludes various kinds of social
contact, can also be used to explain the effect of the social group’s actions on members of
the group.
In the organizational behavior literature, the influence of social factors on individuals’
behavior has been demonstrated in several studies. Social identity theory and social
comparison research have demonstrated how other people exert an influence on individuals’
67 Note that middle-level managers were not the one who initiated the change (both for a case of downsizing at the
private school and for a case of privatization at EGAT); therefore, trust in middle-level manager (or in a direct
leader) is of less relevance to employees.
76
behavior (Festinger, 1954; Terry and Hogg, 2000). According to a social identity theory
(Capazza and Brown, 2000; Tajfel and Turner, 1986) people tend to classify others and
themselves into social categories/groups and identify more with members of their own
categories (in-group) than with members of other categories (out-group). People may have
multiple social identities along several dimensions: for example, gender, ethnicity, and
sexual orientation (Frabble, 1997). In addition, the social learning theory (Bandura, 1977)
postulates that role models for behavior have the effects on individuals’ behavior; that is,
individuals obtain a collection of certain behaviors by observing others’ behaviors and the
consequences in their social environment. According to the social information processing
theory (Salancik and Pfeffer, 1978), individuals use information about norms, values,
expectations, and behavior outcome contingencies derived from others in their social
environment to steer behavior. Moreover, the attraction-selection-attrition perspective
(Schneider, 1975) suggests that a group attracts, selects, and retains individuals with
characteristics or traits similar to those of other members of the group. For example,
individuals with easy-going tendencies would be more likely to be attracted to, selected by,
and stay with groups with similarly easy-going members, resulting in the establishment of a
group with relatively easy-going characteristics.
According to Hackman (1992), characteristics of a work environment may be
conceived of as either (1) discretionary stimuli that are transferred to individual members of
the group differently or (2) ambient stimuli that are diffused throughout the group setting
and are possibly available to all members of the group. In a conflicting social identities
situation, people tend to identify more with those who are similar along the dimension of
social identity that is most salient to them. Brewer (1991) has also noted that the value of
group identification comes from distinctiveness and shared identity.
In light of the above discussion, the social group’s decision is expected to exert an
effect on individual members’ decision. That is, colleagues’ resistance to change may
promote employees’ resistance to change, and weaken employees’ support for change
because employees, as a member of the group, tend to feel obliged to follow their group’s
decision so that they are not excluded from the group. On the other hand, colleagues’
support for change may weaken employees’ resistance to change, and promote employees’
support for change. In line with this reasoning, this dissertation hypothesizes that:
H18a: Employees’ perceptions of colleagues’ resistance to change will be positively related
to their resistance to change, and be negatively related to their support for change
H18b: Employees’ perceptions of colleagues’ support for change will be negatively related
to their resistance to change, and be positively related to their support for change.
77
4. Research Methodology
The overall objective of this dissertation is to examine if perceptions and/or attitudes effect
employees’ reactions to change. To achieve this objective, this dissertation seeks to test the
hypothesized relationships between perceptions and/or attitudes on the one hand and
employees’ resistance to change and support for change on the other hand. If one wishes to
understand the implications of employees’ perceptions and attitudes for their reactions to
change, and if one postulates a direct relationship between perceptions and reactions to
change, then two important consequences follow. First, the understanding of different
research methodologies that have been used in social science in general and management
science in particular was required. Second, a research strategy that was capable of providing
answers to the research questions in this dissertation had to be determined.
It is understandable that empirical research has many variants. Three of which are the
most prominent: (1) empirical experimental research; (2) empirical statistical research; and
(3) empirical case study (Wacker, 1998). According to Wacker (1998), each type of
research strategies seeks to address different research objectives: for the empirical
experimental research, the focus is on examining the relationships between variables by
manipulating controlled treatments to determine the exact effect on specific dependent
variables; the purpose of the empirical statistic research is to empirically validate the
assumed relationships between variables in a large sample from actual environments; and
the purpose of the empirical case study is to develop insightful relationships within smaller
or limited samples. For the moment, one can consider this dissertation to be the empirical
statistic research as it was to empirically test the hypothesized relationships between
predictors and outcomes.
Reflect on my research questions: what perceptions and/or attitudes influence
employee resistance to change? And what perceptions and/or attitudes influence employees’
support for change? Quantitative research seems to better address these research questions
than qualitative research. One plausible reason to lend strong support for the use of
quantitative research in this dissertation is that quantitative research is better suited than
qualitative research where the purpose of the study is to investigate relationships as pairs of
variables. In particular, quantitative research provides an opportunity to generalize the
results statistically to the population.
To address the research questions, this dissertation follows a positivistic tradition that,
as Schwaninger (2004) has described, focuses on facts, adopts an objectivist worldview, and
relies on quantification. Another issue to be considered is concerned with research design
78
choices which imply trade-offs between three dimensions: (1) generalization to the
population that supports the external validity; (2) precision in measurement and control of
the behavioral variables that affect internal and external validity; and (3) realism of context.
It is also useful to note that this dissertation was primarily concerned with statistical
generalization and precision in measurement.
The following sections address sampling criteria with the emphasis on the method
used for selecting the original population for studies 1 and 2, for selecting a sample size, and
for collecting data. Different methods of data analysis and model specification for the main
research model will be discussed. This dissertation proceeds by discussing measures of
study variables: dependent variables, independent variables and control variables. Finally,
the overall sequence of data analysis will be discussed in detail.
4.1. Context, Sample and Procedure
4.1.1. Study 1 – Context, Sample and Procedure
The setting for Study 1 was a private school in Thailand employing 120 employees at the
time of the survey. Declining numbers of enrolled (both new and retained) students over
past few years (e.g., from approximately 200 students per class in 1990 to 100 students per
class in 2004) had caused the management team to make multiple efforts to improve the
school’s efficiency and profitability. However, the numbers of enrolled students still
continue to decline every year, pressurizing the management team to engage in workforce
reductions. The downsizing program was initially aimed to reduce approximately 10
teachers by the start of the next academic year (i.e., 2005-2006) so as to improve the
student/teacher ratio and to remain profitable. Teachers were informed about the downsizing
decision in August 2004. It is useful to note that at the time of the survey (during the first
two weeks of September 2004), teachers did not have the full details of the downsizing
program (e.g., the details of the involuntary workforce reductions program).
A multiple-item survey in Thai was administered during working hours to a random
sample of 100 teachers at the school. In order to determine the clarity and the readability of
the original questionnaire written in the English language, the referee and the co-referee
conducted a review of the questionnaire items. Then, I whose first language is Thai
translated the questionnaire into the Thai language. Then, a professional Thai-English
translator back-translated the questionnaire into the English language and I examined each
item for translation error. The inspection did not find any instances where an item’s
meaning had significantly changed due to the translation. Survey instructions stressed that
participation in this survey was voluntary and confidential and that this survey was
undertaken for the purpose of writing a doctoral dissertation. Ninety-one surveys were
79
returned, presenting a response rate of 91%. Of these, 3 surveys were removed from the
analysis due to missing values in the main part of the returned questionnaire. Thus, the
sample comprised 88 cases. Respondents were representative of the larger population (25%
male, 80 % of respondents had a bachelor degree or equivalent, mean age = 44.1 years,
mean position tenure = 14.8 years, mean organizational tenure = 17.8 years). Listwise
deletion of missing values of the remaining sample reduced the sample to 86 cases (for
further data analysis with three control variables: age, education, and gender).
4.1.2. Study 2 – Context, Sample and Procedure
The setting for study 2 was a stated-own company in Thailand employing around 63,700
employees. Since 1992 this organization has started to form subsidiaries with the
government’s privatization policy to increase private sector participation in this industry and
reduce investment burden of both the organization and the government. Since 2003 the
organization has been in the final phrase of the privatization process; that is, the
management team has planned to list the company on the Stock Exchange of Thailand.
Although the initial public offering (IPO) was scheduled in mid-2004, this has yet been
materialized due to the fact that a final decision on the IPO has yet been made as a result of
disagreement between four main stakeholders (i.e., employees, top management, the
government and the public) on the details of the IPO. It should be noted that at the time of
the survey (during the first two weeks of September 2004), the final decision on the IPO
was still pending.
A multiple-item survey in Thai was administered during working hours to a random
sample of 500 employees at four offices located in Bangkok. It is useful to note that the four
offices had about 900 employees in total. For the purpose of comparability, the
questionnaire items in Study 2 were similar to those of in Study 1. As with Study 1, survey
instructions stressed that participation in this survey was voluntary and confidential and that
this survey was undertaken for the purpose of writing a doctoral dissertation. Two hundred
and twenty-four questionnaires were returned, presenting a response rate of 44.8%. Of
these, 17 surveys were removed from the analysis due to those respondents not completing
the main part of the questionnaire survey. The final sample comprised 207 cases.
Respondents were representative of the larger population (64.7% male, 40.5 % of
respondents had a bachelor degree or equivalent, mean age = 39.1 years, mean position
tenure = 9.0 years, mean organizational tenure = 14.9 years). Listwise deletion of missing
values of the remaining sample reduced the sample size to 197 respondents (for further data
analysis with three control variables: age, education, and gender).
80
4.2. Alternative Methods of Data Analysis
In this section, several methods of data analysis for the research model are discussed in
great details. Let us first consider an ordinary regression analysis since it is often used in
many, if not most, studies in management science. Given that dependent variables were
measured with six items on a five-point scale, which indicate the ordinal nature of the
dependent variable, using the ordinary regression analysis (ordinary least square or OLS) as
an analytical tool for estimation may be inappropriate.
In the tests of employees’ resistance to change (which was divided into two subsets:
active and passive resistance to change) and support for change (which was divided into two
subsets: active and passive support for change) as dependent variables, an ordinary
regression analysis (OLS) would be inadequate because it would fail to account for the
ordinal nature of the dependent variable. The ordinary regression analysis would treat the
difference between a level of scales (e.g., resistance to change) 4 and 5 as the same as the
difference between a level of scales (e.g., resistance to change) 1 and 2 (McKelvey and
Zavoina, 1975; Goodstein, 1994). Given a view that the differences between the levels of
resistance to change need not be similar, the parallel regression assumption may not be true,
implying that with the ordinary regression model, the estimates of the effects of independent
variables would be wrong, i.e., biased and inconsistent.
Let us then consider a multinomial logit or probit model. From the outset, both logit
and probit models seem to be more appropriate than the ordinary regression model.
However, the examination of these models suggests a key issue concerning the use of these
models in this dissertation. For both multinomial logit and probit regression models, there is
no order in the different categories that dependent variable can take; these models would not
take the existence of a ranking into account. Therefore, both models are also inefficient in
this dissertation. It is also important to note that the multinomial logit regression model
makes an implicit assumption, which is known as the independence of irrelevant
alternatives (IIA) property. The independence of irrelevant alternative property implies that
the ratio of the probability of choosing one choice to the probability of choosing a second
choice unchanged for individual decision-makers if a third choice enters the race (for
review, see Alvarez and Nagler, 1998). On the contrary, as the multinomial probit
regression model allows for correlations between the disturbances for difference choices, it
does not assume the independence of irrelevant alternative property (see Alvarez and
Nagler, 1998).
Based on the limitations to several regression models discussed here, the multinomial
ordered probit regression model seems to be the most appropriate tool for estimation in this
81
context because (1) it takes the existence of a ranking into account, (2) it assumes that the
difference between any two adjacent levels is not known, and (3) it does not assume the
independence of irrelevant alternative property. To test hypotheses, I therefore conducted
the multinomial ordered probit regression model, which does not violate the independence
of irrelevant alternative property. But it must be noted that due to a computation difficulty,
the estimation of large choice multinomial probit models is almost impossible using the
numerical integration of bivariate normal distributions (Alvarez and Nagler, 1998). A
comparison of the key properties of several regression models, which have been discussed
here, is illustrated in Table 1.
Table 1: Characteristics of Alternative Regression Models
Ordinary
Regression
(OLS)
Multinomial
Logit
Conditional
Logit
Multinomial
Probit
Multinomial
Ordered
Probit
Dependent Variable Interval or
Ratio
Ordinal or
Nominal
Ordinal or
Nominal
Ordinal or
Nominal
Ordinal or
Nominal
Independent Variable A linear function of interval/ratio of binary variables
Method e.g.,
Moment-
based
Method
e.g., Maximum Likelihood Method
Type of Distribution Normal
Distribution
Binomial
Distribution
Binomial
Distribution
Cumulative
Normal
Distribution
Cumulative
Normal
Distribution
Correlated Disturbances No No No Yes Yes
Includes Position of Choice No No Yes Yes Yes
Assumes the IIA Property No Yes Yes No No
Can Correctly Measure
Omission of a Choice
No No No Yes Yes
Source: Adopted from Alvarez and Nagle (1998: 59).
4.3. The Multinomial Ordered Probit Model
Let us define two categorical variables y1 ∈ {1…m} and y2 ∈ {1…m} indicating the
observed degree of resistance to change and support for change, respectively. As discussed
earlier, the explanatory variables include (1) five that are related to change process; (2) eight
that are related to actual and expected consequences of change; (3) two that are related to
employees’ ability; and (4) three that are related to the relationships between employees and
their organization and colleagues. The discrete probability function of y conditioned on all
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explanatory variables is commonly known as an ordered probit model. It is based on a latent
variable intended to present the employees’ reactions to change.
Let us assume that the unobserved continuous measures, resistance to change (Y1*), is
a linear function of a set of explanatory variable X, with the corresponding parameter vector
β, and a normally distributed error term ε:
Y1* = β’X + ε,
Although Y1* is unobserved, it is related to an observed discrete variable y1, whose value is
dependent upon the value that Y1* takes. It is assumed that employees’ resistance to change
is measured in one of three alternatives (y1 = 1, 2 or 3, where 1 = low, 2 = medium, and 3 =
high) corresponding to the range of observed ratings assigned by employees.
y1 = 1 if 0 < Y1* ≤ µ11,
= 2 if µ11 < Y1* ≤ µ12,
= 3 if µ12 ≤ Y1*,
Where µ11 and µ12 (0 < µ11 < µ12) are unknown threshold parameters of Y1* that define the
range of resistance to resistance; these parameters will be estimated in conjunction with the
β vector by maximizing the joint probability or likelihood function. Let us assume that ε is
normally distributed across observations, and the mean and variance of ε are normalized to
zero and one. With the normal distribution, the multinomial ordered probit model suggests
the following probabilities, where Ф denotes the cumulative normal distribution function.
Pr (Y1 = 1|X1, X2, …, Xk) = Ф(µ11 - β’X) ,
Pr (Y1 = 2|X1, X2, …, Xk) = Ф(µ12 - β’X) - Ф(µ11 - β’X) ,
Pr (Y1 = 3|X1, X2, …, Xk) = 1 - Ф(µ12 - β’X), and
Pr (Y1 = 1) + Pr (Y1 = 2) + Pr (Y1 = 3) = 1
Similarly, let us assume that the unobserved continuous measures, support for change (Y2*),
is a linear function of a set of explanatory variable X, with the corresponding parameter
vector β, and a normally distributed error term ε:
Y2* = β’X + ε,
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Although Y2* is unobserved, it is related to an observed discrete variable y2, whose value is
dependent upon the value that Y2* takes. It is assumed that employees’ support for change
is measured in one of three alternatives (y2 = 1, 2 or 3, where 1 = low, 2 = medium, and 3 =
high) corresponding to the range of observed ratings assigned by employees.
y2 = 1 if 0 < Y2* ≤ µ21,
= 2 if µ21 < Y2* ≤ µ22,
= 3 if µ22 ≤ Y2*,
Where µ21 and µ22 (0 < µ21 < µ22) are unknown threshold parameters of Y2* that define the
range of support for change; these parameters will be estimated in conjunction with the β
vector by maximizing the joint probability or likelihood function. Let us assume that ε is
normally distributed across observations, and the mean and variance of ε are normalized to
zero and one. With the normal distribution, the multinomial ordered probit model suggests
the following probabilities, where Ф denotes the cumulative normal distribution function.
Pr (Y2 = 1|X1, X2, …, Xk) = Ф(µ11 - β’X) ,
Pr (Y2 = 2|X1, X2, …, Xk) = Ф(µ12 - β’X) - Ф(µ11 - β’X) ,
Pr (Y2 = 3|X1, X2, …, Xk) = 1 - Ф(µ12 - β’X),
Pr (Y2 = 1) + Pr (Y2 = 2) + Pr (Y2 = 3) = 1
Thus, we can calculate the probability of levels of both resistance to change and support for
change conditioned on all explanatory variables. For parameter estimation, I used the SPSS
package version 12. Specifically, parameters were estimated by maximum likelihood
function using the command PLUM (PoLytomous Universal Model procedure) with a
probit link function in the SPSS package (see e.g., Borooah, 2002). The size of sample and
number of parameters being estimated can impose a potential estimation problem for both
models: that is, the greater the number of parameters, the larger is the sample size needed.
4.4. Measures of Theoretical Constructs
4.4.1. Dependent Variables
Resistance to change was measured using a newly developed six-item scale. Three newly
developed items were used to measure degrees of behaviors that were believed to represent
employees’ active resistance to change. Specifically, three types of behaviors, i.e., opposing,
arguing, and objecting, were measured. In the same vein, three newly developed items were
used to measure degrees of behaviors that were believed to represent employees’ passive
84
resistance to change. Specifically, two types of reaction, i.e., withdrawing and ignoring,
were measured. Respondents were asked to report the degree to which they agree with each
of items using a five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree).
Support for change was measured using a six-item scale. Three newly developed items
were used to measure degrees of behaviors that were believed to represent employees’
active support for change. Specifically, three types of reactions, i.e., embracing,
cooperating, and supporting, were measured. Similarly, three newly developed items were
used to measure degrees of behaviors that were believed to represent employees’ passive
support for change. That is, three types of reactions, i.e., agreeing, accepting, and
complying, were measured. Respondents were asked to report the degree to which they
agree with each of three items using a five-point scales ranging from 1 (strongly disagree) to
5 (strongly agree). Figure 6 presents an overview of measures of behaviors classified into
four categories of reactions to change in this dissertation.
Figure 6: Summary of Measures of Reactions to Change
Opposing a change
Arguing against a change
Objecting a change
Active Resistance to Change
Embracing a change
Cooperating with the firm
Giving support for a change
Active Support for Change
Withdrawing support
Ignoring a change
Passive Resistance to Change
Agreeing to a change
Accepting a change
Complying with a change
Passive Support for Change
ContentmentDiscontent
Active
Passive
Opposing a change
Arguing against a change
Objecting a change
Active Resistance to Change
Embracing a change
Cooperating with the firm
Giving support for a change
Active Support for Change
Withdrawing support
Ignoring a change
Passive Resistance to Change
Agreeing to a change
Accepting a change
Complying with a change
Passive Support for Change
ContentmentDiscontent
Active
Passive
4.4.2. Independent Variables
Perceived organizational support was measured using a three-item measure reflecting
perceived organizational support. These items were adapted from Eisenberger et al.’s (1986,
85
1990). Respondents were asked to indicate the degree to which they agreed with these items
using a five-point scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Perceived procedural justice was measured using a three-item perceived procedural
justice scale adapted from the 31-item measuring perceptions of the procedure justice of the
sale and layoffs developed by Gopinath and Becker (2000). Respondents indicated the
degree to which they agreed with these items using a five-point scale ranging from “1
(strongly disagree)” to “5 (strongly agree)”.
Perceived participation in decision-making process was measured using a three-item
measure reflecting perceived participation in decision-making. Respondents are asked to
indicate the degree to which they agreed with these items using a five-point scale ranging
from “1 (strongly disagree)” to “5 (strongly agree)”.
Perceived need for change was measured using a newly developed three-item measure
reflecting employee’s perception of need for a change in the organization. Respondents
were asked to indicate the degree to which they agreed with the items using a five-point
scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Attitude towards organizational change was measured using a newly developed three-
item scale reflecting employees’ attitude towards organizational change. Respondents
indicated the degree to which they agreed with the items using a five-point scales ranging
from “1 (strongly disagree)” to “5 (strongly agree)”.
Fear of known consequence of change was measured using a newly developed three-
item scale. Respondents indicated the degree to which they agreed with these items using a
five-point scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Fear of unknown consequence of change was measured using three newly developed
items. Respondents were asked to report the degree to which they agreed with these items
using a five-point scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Perceived change in power was measured using a newly developed three-item
measure reflecting perceived change in power. Respondents indicated the degree to which
they agreed with these items using a five-point scale ranging from “1 (strongly disagree)” to
“5 (strongly agree)”.
Perceived change in status was measured using a newly developed three-item scale
reflecting perceived change in status. Respondents were asked to indicate the degree to
which they agreed with these items using a five-point scale ranging from “1 (strongly
disagree)” to “5 (strongly agree)”.
Perceived change in pride was measuring using a newly developed three-item scale
reflecting perceived change in pride. Respondents indicated the degree to which they agreed
86
with these items using a five-point scale ranging from “1 (strongly disagree)” to “5 (strongly
agree)”.
Job satisfaction was measured using a three-item scale adopted from those used by
Weiss et al. (1967) and Davy et al. (1997). As job satisfaction items were found to indicate
two sub-dimensions: intrinsic and extrinsic satisfaction (Weiss et al, 1967), I used three
items to measure the indicators of extrinsic job satisfaction. These items include: (1) pay
and amount of work; (2) chances for advancement; and (3) working conditions.
Respondents indicate the degree to which they agreed with the items using a five-point scale
ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Job security was measured using a three-item scale adopted from those used by Caplan
et al.’s (1975) and by Hui and Lee (2000). These items consisted of: (1) ‘I am certain about
what my future career picture looks like in this company’, (2) ‘I am certain about what my
responsibilities will be six months from now’, and (3) ‘I am certain about my job security in
this company’. Respondents were asked to indicate the degree to which they agreed with the
items using a five-point scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Job motivation was measured using a three-item measure adopted from those used by
Hui and Lee (2000). These items measured extrinsic job motivation. Respondents were
asked to indicate the degree to which they agreed with the items using a five-point scale
ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Perceived employability was measured using a newly developed three-item measure
reflecting employees’ perceptions their ability to find a new job. Respondents were asked to
indicate the degree to which they agreed with the items using a five-point scale ranging
from “1 (strongly disagree)” to “5 (strongly agree)”.
Self-confidence for learning and development was measured using two newly
developed items and one item adopted from a study by Maurer et al (2003) reflecting
employees’ perceptions of their ability to learn new knowledge and develop new skills.
Respondents were asked to indicate the degree to which they agreed with the items using a
five-point scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Affective commitment, a psychological attachment to the organizational, was measured
using a three-item sale adopted from a 10-item scale used by Gopinath and Becker (2000).
Respondents were asked to indicate the degree to which they agreed with the items using a
five-point scale ranging from “1 (strongly disagree)” to “5 (strongly agree)”.
Trust in management was measured with a three-item scale adopted from those used
by Gapinath and Becker (2000) and Robinson and Rousseau (1994). Respondents indicated
the degree to which they agreed with the items using a five-point scale ranging from “1 =
strongly disagree” to “5 = strong agree”.
87
Perceptions of colleagues’ reactions to change were measured using a newly
developed three-item scale reflecting employees’ perceptions about colleagues’ resistance to
change and/or support for change. Respondents were asked to indicate the degree to which
they agreed with the items using a five-point scale ranging from “1 (strongly disagree)” to
“5 (strongly agree)”.
4.4.3. Control Variables
In addition to the endogenous and predetermined variables discussed above, this dissertation
aimed to control for an influence of age (in years), gender (male = 0, female = 1), education
(below a bachelor level = 0, a bachelor level = 1, a master level = 2, higher than a master
level = 3), position tenure (in years), organizational tenure (in years), family status (single =
0, married/co-habiting = 1, divorced = 2), a number of children when conducting analyses
to separate individual differences in age, gender, position tenure, organization tenure, family
status and a number of children. Data for all control variables were obtained from the
questionnaires completed by the respondents.
4.5. Data Analysis Procedures
In this section, the sequence of data analysis conducted in both Studies 1 and 2 that were
designed to test all hypotheses presented in this dissertation is presented. The overview of
the sequence of data analysis is illustrated in Figure 7. First, descriptive statistics (e.g., value
range, minimum and maximum values) for all variable indicators were examined. Second,
histograms illustrating distributions of all variable indicators were examined. In a third step,
for the purpose of reducing the number of indicators, the patterns of directions of indicators
for each variable were examined. To see this, I first averaged all indicators for each
variable, plotted this aggregate indicator along with original indicators in a graph, and
examined the pattern of directions. If the results did not reveal a satisfactory level of internal
consistency, I removed an indicator that appeared to have a different pattern of directions
from the model and conducted the same sequence of analyses until the aggregate indicator
that seemed to provide the highest level of internal consistency was found. As the Spearman
correlations also indicate the pattern of directions between indicators, I also examined the
correlation coefficients among indicators for each variable for the purpose of reducing the
number of indicators. Upon the completion of steps 3 and 4, I reduced the number of
indicators for both dependent and independent variables.
88
Figure 7: Summary of the Sequence of Data Analysis
Examine patterns of directions of indicators for each variable
Examine correlations for indicators for each variable
Reduce the number of indicators for each variable
Examine correlations among final variables
Recode scales of variables measurement
Conduct restricted ordered probit models
Conduct unrestricted (multinomial) ordered probit models
Examine descriptive statistics for all indicators
Examine histograms for all indicators
Examine patterns of directions of indicators for each variable
Examine correlations for indicators for each variable
Reduce the number of indicators for each variable
Examine correlations among final variables
Recode scales of variables measurement
Conduct restricted ordered probit models
Conduct unrestricted (multinomial) ordered probit models
Examine descriptive statistics for all indicators
Examine histograms for all indicators
Upon this point, there was only one indicator (the aggregate indicator) for each variable for
further analyses. Then, correlation analyses for the aggregate indicators were conducted.
Due to the sample size and number of parameters being estimated (for the multinomial
ordered probit models), I recoded levels of measurement for both dependent and
independent variables. That is, the items using a five-point scale ranging from “1 (strongly
disagree)” to “5 (strongly agree)” were recoded to a three-point scale ranging from “1
(low)” to “3 (high)” as follows: “1” and “2” = “1 = low”; “3” = “2 = medium”; and “4” and
“5” = “3 = high”. Next, 76 separate restricted models that included only one of the
independent variables and only one of the dependent variables at a time were conducted.
Then, I ran four separate full multinomial ordered probit models that included all
independent variables, one of the dependent variables, and three control variables (age,
education, and gender). However, the results indicate that the size of sample in Studies 1 (n
= 86) and 2 (n = 197) did not allow for conducting models that had more than one
independent variable. That is, multiple-variables models with the sample size of 86 and 197
cases (for Studies 1 and 2, respectively) inevitably produced a large number of empty cells.
Thus, I did not include control variables in the models and, indeed, ran only two-variable
models to test Hypotheses 1a-18b for both studies.
89
5. Results and Discussion
5.1. Study 1 – Results and Discussion
In Study 1, the first step was to examine whether the indicators for each variable were
internally consistent, i.e., whether it was possible to reduce the number of indicators. To
examine this possibility, I first averaged the indicators to form an aggregate indicator,
plotted the aggregate indicator along with the original indicators in a graph, and examined
the pattern of directions (see the Appendix B for further information). Using this procedure,
it could be seen whether the indicators for each variable followed the same pattern of
directions. It is important to note that the method in this study differs from other studies
(e.g., Mathieu and Farr, 1991; Hui and Lee, 2000) due predominantly to the ordinal nature
of the data in this study. Thus, this dissertation did not follow the procedure used in prior
studies that treated the ordinal data as the matrix data. Therefore, a factor analysis was not
conducted.68 The results of the procedure conducted in the present study indicate that it was
possible to reduce the number of indicators for each construct by either averaging all three
indicators to an aggregate level or averaging a pair of indicators to an aggregate level; thus,
I reduced the number of indicators for each variable, and conducted the testing of
hypotheses using the aggregate indicators in the multinomial ordered probit regression. In
addition to the use of graphs to examine the possibility of reducing the number of indicators,
analyses of the Spearman correlation coefficients were also conducted.
5.1.1. Analyses of Correlations among Dependent Variables
Tables in the Appendix B provide the Spearman correlation coefficients among all
indicators for dependent variables: namely, active and passive resistance to change, and
active and passive support for change. It is noteworthy that all correlations typed in bold
were statistically significant at the 0.01 level or at the 0.05 level.
As can be seen in the Appendix B, Active Resistance 1 was positively and
significantly correlated with Active Resistance 2 (r = .34, p < .01), suggesting that the
aggregate indicator between Active Resistance 1 and Active Resistance 2 would be used for
active resistance to change. As Passive Resistance 1 was positively and significantly
correlated with Passive Resistance 2 (r = .23, p < .05), the aggregate indicator between them
would be used for passive resistance to change. There were significant correlations among
all indicators for active support for change; thus, all of them were aggregated to a super
68 For a more detailed discussion of the methods of analyses, see the research methodology section.
90
level. Similarly, the number of indicators for passive support for change was reduced by
aggregating all indicators for passive support for change to a super level.
Further, Active Resistance 1 was positively and significantly correlated with Passive
Resistance 1 (r = .25, p < .05) and Passive Resistance 2 (r = .26, p < .05); and Active
Resistance 2 was positively and significantly correlated with Passive Resistance 2 (r = .27, p
< .05). Unexpectedly, Passive Resistance 3 was positively and significantly correlated with
Passive Support 2 (r = .26, p < .05) and Passive Support 3 (r = .26, p < .05). This raises a
question of whether Passive Resistance 3 could be categorically considered as resistance to
change. The results also indicate that Active Resistance 3 was negatively and significantly
correlated with Active Support 1 (r = -.33, p < .01), Active Support 2 (r = -.44, p < .01),
Active Support 3 (r = -.38, p < .01), and Passive Support 1 (r = -.34, p < .01).
In addition, there is observable evidence that there was a relationship between active
support for change and passive support for change. For instance, Active Support 1 was
positively and significantly correlated with Passive Support 1 (r = .37, p < .01), Passive
Support 2 (r = .25, p < .05), and Passive Support 3 (r = .24, p < .05). Moreover, Active
Support 2 was positively and significantly correlated with Passive Support 1 (r = .58, p <
.01), Passive Support 2 (r = .32, p < .01), and Passive Support 3 (r = .30, p < .01).
Of the correlations between the indicators for dependent variables and control
variables, only one significant correlation existed; that is, Active Resistance 3 was
positively and significantly correlated with organizational tenure (r = .22, p < .05),
suggesting that duration of employment with the organization may lead employees to make
objections to organizational change.
5.1.2. Analyses of Correlations among Independent Variables
Tables in the Appendix B provide the Spearman correlation coefficients between active
resistance to change indictors and all independent indicators. As with analyses of
correlations among the indicators for dependent variables, I examined correlations among
indicators for each independent variable for the purpose of reducing the number of
indicators.
Though Perceived Organizational Support (POS) 1 was negatively and significantly
correlated with Perceived Organizational Support (POS) 2 (r = -.22, p < .05), an aggregate
indicator between both of them was used for this construct.69 Next, since positive and
69 Although the correlation between POS 1 and POS 2 was negative, as can be seen in Figure 12 in the Appendix B,
POS 1, POS 2, and the aggregate indicator (of the two) had the same pattern of directions, suggesting that it was
reasonable to use the aggregate indicator for this construct.
91
significant correlations existed between Procedural Justice 1 and Procedural Justice 2 (r =
.34, p < .01) and Procedural Justice 2 and Procedural Justice 3 (r = .34, p < .05), all three
indicators were aggregated to a super level for perceived procedural justice.
The results show that positive correlations existed between Perceived Participation 1
and Perceived Participation 2 (r = .22, p < .05) and Perceived Participation 2 and Perceived
Participation 3 (r = .24, p < .05); however, the aggregate indicator between Perceived
Participation 2 and Perceived Participation 3 would be used for perceived participation in
decision-making since it provided a relatively higher level of internal consistency. As
Perceived Need for Change 2 was positively and significantly correlated with Perceived
Need for Change 3 (r = .56, p < .01), the aggregate indicator between Perceived Need for
Change 2 and Perceived Need for Change 3 would be used for this construct.
A positive and significant correlation existed between Attitude towards organizational
1 and Attitude towards organizational change 2 (r = .44, p < .01). Thus, these results support
an idea that the aggregate indicator between both of them would be used for attitude
towards organizational change. As Fear of Known Consequences 1 was positively and
significantly correlated with Fear of Known Consequences 2 (r = .52, p < .01), the
aggregate indicator between both of them would be used for fear of known consequences of
a change. As a positive and significant correlation existed between Fear of Unknown
Consequences 2 and Fear of Unknown Consequences 3 (r = .44, p < .01), the aggregate
indicator between both of them would be used for fear of unknown consequences of a
change.
The results also indicate that all indicators for perceived change in power were
positively and significantly correlated with each other: that is, Change in Power 1 was
positively and significantly correlated with Change in Power 2 (r = .27, p < .05), and
Change in Power 3 (r = .42, p < .01); and Change in Power 2 was positively and
significantly correlated with Change in Power 3 (r = .31, p < .01). Thus, all indicators for
perceived change in power were aggregated to a super level. Further, a positive and
significant correlation existed between Change in Status 1 and Change in Status 2 (r = .41, p
< .01), and a negative and significant correlation existed between Change in Status 2 and
Change in Status 3 (r = -.24, p < .05). Thus, the aggregate indicator between Change in
Status 1 and Change in Status 2 would be used for perceived change in status.
A negative and significant correlation existed between Change in Pride 1 and Change
in Pride 2 (r = -.44, p < .01), but a positive and significant correlation existed between
Change in Pride 2 and Change in Pride 3 (r = .25, p < .05). Consequently, Change in Pride 2
and Change in Pride 3 were aggregated to a super level. Further, as a positive and
significant correlation existed between Job Satisfaction 1 and Job Satisfaction 3 (r = .21, p <
92
.05), the aggregate indicator between both of them would be used for job satisfaction.
Similarly, Job Security 2 was positively and significantly correlated with Job Security 3 (r =
.38, p < .01); thus, both of them were aggregated to a super level for job security. As
positive and significant correlations existed among all three indicators for job motivation,
the aggregate indicator of all three indicators would be used for this construct. As Perceived
Employability 2 was positively and significantly correlated with Perceived Employability 3
(r = .25, p < .05), both of them were aggregated to a super level for perceived employability.
All three indicators for self-confidence for learning and development were positively
and significantly correlated with each other; therefore, all of them were aggregated to a
super level for this construct. Though all three indicators for affective commitment were
positively and significantly correlated with each other, the aggregate indicator between
Affective Commitment 1 and Affective Commitment 2 would be used for this construct
because removing Affective Commitment 3 from the aggregate indicator resulted in a
relatively higher level of internal consistency. Similarly, though all indicators for trust in
management were significantly correlated with each other, Trust in Management 1 and
Trust in Management 2 were aggregated to a super level for this construct. As also shown in
Table 2, a positive and significant correlation existed between Colleagues’ Resistance 1 and
Colleagues’ Resistance 2 (r = .60, p < .01); therefore, both were aggregated to a super level
for perceptions of colleagues’ resistance to change. Last but not least, it is noteworthy that
Change in Pride 1 was negatively and significantly correlated with Gender (r = -.22, p <
.05).
93
Table 2: Study 1 – Correlations for All Final Variables
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
1.
AR
.49
2.
PR
.31†
.41
3.
AS
-.12
.12
.67
4.
PS
-.12
.08
.49†
.70
5.
POS
-.01
.23*
.17
.34†
.41
6.
Justice
.08
.19
.67†
.39†
.25*
.51
7.
Participation
-.09
-.08
.21
.26*
-.03
-.01
.41
8.
Need
.03
.14
.18
.28†
.55†
.18
.10
.68
9.
Attitude
-.22*
.02
.16
.39†
.07
.05
.38†
.35†
.58
10. Fear Known
.54†
.45†
.03
-.02
.03
.17
-.13
.03
-.26*
.67
11. Fear Un
.24*
.44†
-.09
-.06
-.08
-.02
.11
.03
.04
.23*
.58
12. Power
.03
.29†
.28†
.21*
.27*
.38†
-.14
.24*
-.01
.15
.05
.63
13. Status
-.04
.10
.45†
.49†
.26*
.54†
.11
.26*
.08
.06
-.04
.45†
.57
14. Pride
.00
.09
.20
.41†
.41†
.32†
-.05
.26*
.09
.14
-.06
.59†
.46†
.42
15. Job Sat
.26*
.21
.10
.26*
.40†
.26*
.00
.02
-.07
.21
.06
.20
.22*
.32†
.38
16. Job Security
.13
.24*
.10
.34†
.44†
.15
-.01
.48†
.24*
.20
.00
.28†
.27*
.23*
.22*
.52
17. Job M
ot
.21
.12
.02
.22*
.13
-.02
.38†
.35†
.39†
.09
.18
-.17
-.11
-.05
.14
.32†
.81
18. Employ
-.06
-.10
.07
.02
.06
.13
-.09
.19
.01
.01
-.18
.12
.15
.12
-.01
.10
-.03
.41
19. Learning
.11
.07
.07
.28†
.23*
-.09
.43†
.38†
.39†
-.06
.15
-.11
-.11
.11
.11
.27*
.65†
.10
.83
20. Commitment
.26*
.10
-.08
.23*
.11
-.16
.24*
.20
.23*
.05
.11
-.26*
-.17
.09
.28†
.16
.57†
-.16
.60†
.59
21. Trust
.08
.01
.27*
.41†
.44†
.19
.14
.28†
.19
.10
.01
.08
.14
.45†
.48†
.32†
.24*
-.11
.42†
.46†
.93
22. Col Resist
.28†
.31†
-.20
.04
-.06
-.12
.18
-.03
.21
.02
.43†
-.05
-.29†
-.05
.17
.04
.44†
-.30†
.29†
.53†
.15
.73
23. Col Support
.01
-.09
.43†
.40†
.22*
.39†
.17
.19
.11
-.08
-.04
.43†
.55†
.43†
.16
.28†
-.10
.08
.00
-.04
.26*
-.12
-
24. Age
.07
-.02
-.18
-.15
.05
-.07
-.05
-.01
-.16
-.16
.11
.04
-.11
.05
.11
-.02
-.02
-.06
.04
.19
.05
.24*
.01
-
25. Education
-.01
-.02
-.05
.10
.02
-.02
.07
.09
.16
.06
.05
.04
.07
.10
-.01
.04
.06
-.09
.14
.07
.03
-.08
-.01
-.03
-
26. Gender
-.08
.01
.00
.14
-.05
.03
.08
-.01
.09
-.07
.13
.06
.15
.09
.08
-.07
.08
.02
.02
.03
-.07
.16
-.08
-.11
-.19
Notes:
N = 86. Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed). † p < .01, * p < .05. Scale
reliabilities (Cronbach’s alpha) are shown along the diagonal.
94
5.1.3. Results for Hypotheses – The Multinomial Ordered Probit Models
After the number of indicators for the variables had been reduced, a correlation analysis for
the final variables was conducted. Table 2 provides the Spearman correlations for all the
variables for Study 1. For ease of interpretation of all the data, results relevant to
correlations analyses and regression analyses will be interpreted together rather than in
sequentially separate results sections.
To test the study hypotheses, a series of ordered probit regressions was conducted. As
discussed earlier, the multinomial ordered probit model was used because it is able to
account for the discrete and ordered nature of dependent variables. Due to the sample size
and number of parameters being estimated, measurement scales for each variable were
recoded (i.e., “1” and “2” = “1”; “3” = “2”; and “4” and “5 = “3”). First, restricted models
that included only one of the independent variables and only one of the dependent variables
were conducted. Then, full models that included all independent variables, one of the
dependent variables, and three control variables were conducted. However, the regression
results of the full models indicate that the size of sample in Study 1 (n = 86) did not allow
for conducting models that had more than one independent variable. That is, multiple-
variables models with a sample size of 86 cases inevitably produced a large number of
empty cells. Thus, I did not include control variables in my analyses and, indeed, ran only
two-variable models to test Hypotheses 1a-18b for Study 1.
It is important to note that the regression results were considered as supportive of any
of the study hypotheses only when all four parameters (i.e., two parameters for dependent
variable threshold and two parameters for independent variable location) were statistically
significant. Additionally, the regression results were considered as partially supportive of
any hypothesis only when both (two) parameters of independent variable location and one
parameter of dependent variable threshold were statistically significant. Tables 3, 4, 5 and 6
report the results of the multinomial ordered probit models; significant coefficients are
typed in bold. Surprisingly, the results do not indicate general support for the hypotheses
that perceptions and/or attitudes would be significantly related to reactions to change.
Hypothesis 1a predicted that perceived organizational support would be negatively
related to resistance to change. As shown in Table 2, perceived organizational support was
not significantly correlated with active resistance to change but was positively and
significantly correlated with passive resistance to change (r = .23, p < .05). Further, as can
be seen in Tables 3 and 4, the levels of perceived organizational support were not
significantly predictive of the levels of active resistance to change or passive resistance to
change. Thus, Hypothesis 1a was not supported by the data.
95
Table 3: Study 1 – Regression Results of Active Resistance to Change
Dependent Variable Threshold Independent Variable Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-.730† .236 .282 .229 -.165 .317 -.302 .288 1.099
Perceived Procedural Justice -.863† .290 .150 .280 -.356 .335 -.396 .333 1.497
Perceived Participation in
Decision-Making
-.353* .198 .667† .204 .350 .344 .364 .266 2.167
Perceived Need for Change -.605† .190 .401* .186 -.031 .303 -.161 .286 .329
Attitude towards Organizational
Change
-.414* .179 .603† .183 .509 .381 .237 .265 2.054
Fear of Known Consequences
of a Change
-1.166† .220 -.018 .192 -1.275
† .314 -.714* .296 17.798
†
Fear of Unknown
Consequences of a Change
-.803† .211 .227 .200 -.613** .328 -.288 .272 3.605
Perceived Change in Power -.943* .441 .066 .434 -.438 .467 -.404 .466 .865
Perceived Change in Status -.659† .224 .360** .218 .071 .302 -.333 .289 2.185
Perceived Change in Pride -.506* .227 .506* .227 -.209 .369 .157 .272 1.200
Job Satisfaction -.786† .195 .242 .184 -.370 .337 -.471** .272 3.326
Job Security -.677† .212 .332 .206 -.295 .377 -.173 .261 .758
Job Motivation -.729† .166 .320* .155 -1.145* .489 -.389 .321 6.523*
Perceived Employability -.226 .233 .801† .243 .476 .325 .476 .290 3.189
Self-Confidence for Learning
and Development
-.717† .179 .322** .170 -.978* .452 -.198 .266 4.905**
Affective Commitment -.732† .168 .313* .157 -1.252* .585 -.436 .295 6.190*
Trust in Management -.604† .190 .402* .186 -.165 .290 -.035 .298 .325
Colleagues’ Resistance to
Change
-.836† .210 .194 .197 -.444 .374 -.471** .262 3.579
Colleagues’ Support for Change -.742† .278 .266 .272 -.238 .336 -.238 .319 .644
Notes: N = 86. Variables have 3 Levels: 1 = Low; 2 = Medium; 3 = High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
96
Table 4: Study 1 – Regression Results of Passive Resistance to Change
Dependent Variable Threshold Independent Variable Location
Level 1 Level 2 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-.763† .237 .425* .230 -.424 .317 -.127 .287 1.888
Perceived Procedural Justice -.694* .284 .517** .281 -.404 .332 .170 .329 4.621**
Perceived Participation in
Decision-Making
-.503* .200 .672† .204 .182 .342 .126 .264 .372
Perceived Need for Change -.658 .191 .516 .188 -.147 .302 -.132 .285 .336
Attitude towards Organizational
Change
-.524 .181 .654 .184 .337 .376 .065 .264 .811
Fear of Known Consequences
of a Change
-1.137† .218 .157 .191 -1.054
† .307 -.742* .296 13.595
†
Fear of Unknown
Consequences of a Change
-1.223† .232 .109 .201 -1.388
† .350 -.698* .277 17.255
†
Perceived Change in Power -1.292† .456 -.084 .442 -.923* .478 -.576 .475 4.550
Perceived Change in Status -.645† .223 .541* .221 -.288 .301 .090 .287 1.711
Perceived Change in Pride -.543* .228 .654† .230 -.392 .371 .221 .271 3.209
Job Satisfaction -.733† .193 .452* .187 -.141 .335 -.350 .270 1.683
Job Security -.876† .218 .327 .206 -.274 .376 -.494** .263 3.564
Job Motivation -.587† .160 .587
† .160 -.209 .444 .098 .319 .369
Perceived Employability -.113 .234 1.117† .254 .631** .327 .743* .294 6.850*
Self-Confidence for Learning
and Development
-.646† .177 .529
† .174 -.248 .424 -.113 .265 .434
Affective Commitment -.689† .165 .496
† .160 -.400 .521 -.334 .293 1.686
Trust in Management -.623† .190 .552
† .188 -.166 .289 .037 .297 .444
Colleagues’ Resistance to
Change
-1.018† .217 .229 .198 -1.075
† .389 -.551* .263 9.048*
Colleagues’ Support for Change -.590* .274 .590* .274 .159 .334 -.112 .317 .981
Notes: N = 86. Variables have 3 Levels: 1 = Low; 2 = Medium; 3 = High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
97
Table 5: Study 1 – Regression Results of Active Support for Change
Dependent Variable Threshold Independent Variable Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-.445* .231 .554* .233 -.367 .320 -.106 .288 1.406
Perceived Procedural Justice -1.317† .317 -.004 .286 -1.958
† .380 -.439 .339 36.924
†
Perceived Participation in
Decision-Making
-.487* .201 .568† .203 -1.075
† .383 .000 .264 9.500
†
Perceived Need for Change -.581† .190 .444* .187 -.503 .308 -.561** .292 4.811**
Attitude towards Organizational
Change
-.517† .182 .517
† .182 -1.053* .419 -.240 .266 6.690*
Fear of Known Consequences
of a Change
-.310 .191 .681† .198 -.128 .296 .070 .290 .380
Fear of Unknown
Consequences of a Change
-.257 .200 .741† .209 -.168 .328 .199 .272 1.301
Perceived Change in Power -.312 .428 .704 .432 -.256 .461 .232 .459 3.661
Perceived Change in Status -.802† .230 .296 .219 -1.182
† .323 -.347 .289 14.271
†
Perceived Change in Pride -.668† .232 .354 .226 -.702** .377 -.478** .274 4.507
Job Satisfaction -.396* .186 .597† .190 -.203 .338 -.190 .271 .644
Job Security -.461* .208 .551† .210 -.748** .398 -.124 .261 3.579
Job Motivation -.389 .156 .613 .162 -.488 .461 -.277 .325 1.701
Perceived Employability -.145 .234 .867† .245 -.074 .328 .398 .290 3.217
Self-Confidence for Learning
and Development
-.449† .173 .562
† .175 -.667 .448 -.261 .268 2.801
Affective Commitment -.362* .158 .636† .164 .137 .519 -.333 .299 1.407
Trust in Management -.594† .191 .459* .188 -.877
† .306 -.210 .298 8.538*
Colleagues’ Resistance to
Change
-.066 .198 .944† .214 .439 .374 .402 .263 2.774
Colleagues’ Support for Change -.940† .286 .139 .273 -1.148
† .351 -.513 .322 11.555
†
Notes: N = 86. Variables have 3 Levels: 1 = Low; 2 = Medium; 3 = High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
98
Table 6: Study 1 – Regression Results of Passive Support for Change
Variable Threshold Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-1.353† .268 -.418** .244 -.823* .334 -.960
† .308 10.823
†
Perceived Procedural Justice -1.254† .313 -.313 .295 -1.040
† .353 -.340 .350 10.970
†
Perceived Participation in
Decision-Making
-.988† .217 -.072 .199 -1.015
† .358 -.295 .271 8.112*
Perceived Need for Change -.965† .203 -.072 .186 -.590** .309 -.519** .291 5.016**
Attitude towards Organizational
Change
-.926† .195 -.035 .178 -.726** .382 -.434 .269 4.919**
Fear of Known Consequences
of a Change
-.720† .200 .150 .191 -.285 .296 .056 .295 1.255
Fear of Unknown
Consequences of a Change
-.803† .212 .064 .201 -.221 .328 -.245 .275 .899
Perceived Change in Power -1.058* .456 -.184 .447 -.549 .480 -.311 .480 1.745
Perceived Change in Status -1.657† .279 -.595* .241 -1.652
† .339 -.985
† .316 25.420
†
Perceived Change in Pride -1.281† .260 -.309 .235 -1.568
† .402 -.576* .287 15.796
†
Job Satisfaction -.885† .200 .015 .185 -.826* .346 -.195 .274 5.664**
Job Security -1.037† .227 -.126 .209 -1.080
† .393 -.415 .269 7.732*
Job Motivation -.855† .170 .043 .153 -.594 .450 -.672** .326 5.532**
Perceived Employability -.542* .237 .323 .234 .074 .325 .219 .291 .613
Self-Confidence for Learning
and Development
-.868† .185 .016 .169 -.597 .430 -.426 .270 3.649
Affective Commitment -.871† .173 .038 .155 -.140 .526 -.780* .301 6.916*
Trust in Management -1.096† .210 -.167 .187 -.885
† .300 -.632* .305 9.836
†
Colleagues’ Resistance to
Change
-.755 .208 .116 .198 .150 .383 -.248 .263 1.516
Colleagues’ Support for Change -1.691† .342 -.743 .318 -1.315
† .383 -1.110
† .367 13.410
†
Notes: N = 86. Variables have 3 Levels: 1 = Low; 2 = Medium; 3 = High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
99
Hypothesis 1b was that perceived organizational support would be positively related to
support for change. As can be seen in Table 2, perceived organizational support was not
significantly correlated with active support for change but was positively correlated with
passive support for change (r = .34, p < .01). The results shown in Table 5 indicate that the
levels of perceived organizational support were not significantly predictive of the levels of
active support for change. The negative coefficients for perceived organizational support
(see Table 6) imply that the lower the level of perceived organizational support, the greater
the likelihood of having passive support for change (b1 = -.823, p < .05; b2 = -.960, p < .01).
Thus, Hypothesis 1b was not supported.
Hypothesis 2a predicted that perceived procedural justice would be negatively related
to resistance to change. Perceived procedural justice was not significantly correlated with
active resistance to change and passive resistance to change (see Table 2). The results
shown in Tables 3 and 4 also indicate that the levels of perceived procedural justice were
not significantly predictive of the levels of active support for change or passive support for
change. Thus, Hypothesis 2a was not supported.
Hypothesis 2b predicted that perceived procedural justice would be positively related
to support for change. As can be seen in Table 2, perceived procedural justice was
positively correlated with active support for change (r = .67, p < .01) and passive support
for change (r = .39, p < .01). However, as can be see in Tables 5 and 6, the levels of
perceived procedural justice were not significantly predictive of the levels of active support
for change or passive support for change. Thus, Hypothesis 2b was not supported.
Hypothesis 3a was that perceived participation in decision-making regarding
organizational change would be negatively related to resistance to change. This hypothesis
was not supported, as perceived participation in decision-making was not significantly
correlated with active resistance to change or passive resistance to change (see Table 2). As
also shown in Tables 3 and 4, the levels of perceived participation in decision-making were
not significantly predictive of the levels of active resistance to change or passive resistance
to change.
Hypothesis 3b, which predicted that perceived participation in decision-making
regarding organizational change would be positively related to support for change, was not
supported by the data. As illustrated in Table 2, perceived participation in decision-making
was not significantly correlated with active support for change but was positively correlated
with passive support for change (r = .26, p < .05). The findings indicate that the levels of
perceived participation in decision-making were not significantly predictive of the levels of
active support for change or passive support for change (see Tables 5 and 6).
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Hypothesis 4a was that perceived need for change would be negatively related to
resistance to change. As can be seen in Table 2, neither a correlation between perceived
need for change and active resistance to change nor a correlation between perceived need
for change and passive resistance to change was significant. Moreover, as shown in Tables 3
and 4, the levels of perceived need for change were not significantly predictive of the levels
of active resistance to change or passive resistance to change. Therefore, Hypothesis 4a was
not supported.
Hypothesis 4b predicted that perceived need for change would be positively related to
support for change. This hypothesis was not supported. As shown in Table 2, perceived
need for change was not significantly correlated with active support for change but was
positively correlated with passive support for change (r = .28, p < .01). The regression
results indicate that the levels of perceived need for change were not significantly predictive
of the levels of active support for change (see Table 5) or passive support for change (see
Table 6).
Hypothesis 5a suggested that attitude towards organizational change would be
negatively related to resistance to change. As can be seen in Table 2, attitude towards
organizational was negatively and significantly correlated with active resistance to change (r
= -.22, p < .05), but it was not significantly correlated with passive resistance to change.
Furthermore, the degrees of attitude towards organizational were not significantly predictive
of the levels of active resistance to change (see Table 3) or passive resistance to change (see
Table 4). Thus, Hypothesis 5a was not supported.
Hypothesis 5b predicted that attitude towards organizational change would be
positively related to support for change. As illustrated in Table 2, attitude towards
organizational change was not significantly correlated with active support for change but
was positively correlated with passive support for change (r = .39, p < .01). Moreover, the
results of the ordered probit analyses indicate that degrees of attitude towards organizational
change were not significantly predictive of the levels of active support for change (see Table
5) or passive support for change (see Table 6). Thus, Hypothesis 5b was not supported.
Hypothesis 6a was that fear of known consequences of a change would be positively
related to resistance to change. As shown in Table 2, fear of known consequences of a
change was positively correlated with active support for change (r = .54, p < .01) and
passive support for change (r = .45, p < .01). However, as can be seen in Tables 3 and 4, the
levels of fear of known consequences of a change were negatively and significantly
predictive of active resistance change (b1 = -.1.275, p < .01; b2 = -.714, p < .05; note that
one parameter of dependent variable threshold was not significant) and passive resistance
change (b1 = -1.054, p < .01; b2 = -.742, p < .05; note that one parameter of dependent
101
variable threshold was not significant). The negative coefficients imply that the likelihood
of having higher levels of active resistance to change or passive resistance to change did
decrease with higher levels of fear of known consequences of a change, which was
inconsistent with expectations. Thus, Hypothesis 6a was not supported.
Hypothesis 6b, which predicted that fear of known consequences of a change would be
negatively related to support for change, was not supported. As results in Table 2 show, fear
of known consequences of a change was not significantly correlated with active support for
change or passive support for change. Furthermore, as the results in Tables 5 and 6 indicate,
the levels of fear of known consequences of a change were not significantly predictive of
the levels of active support for change or passive support for change.
As Hypothesis 7a suggested that fear of unknown consequences of a change would be
positively related to resistance to change, the findings in Table 2 show that fear of unknown
consequences of a change was positively correlated with active resistance to change (r =
.24, p < .05) and passive resistance to change (r = .44, p < .01). However, the levels of fear
of unknown consequences of a change were not significantly predictive of the levels of
active resistance to change (see Table 3). Indeed, the negative coefficients for fear of
unknown consequences of a change (b1 = -1.054, p < .01; b2 = -.742, p < .05; note that one
parameter of dependent variable threshold was not significant) mean that the likelihood of
having higher levels of passive resistance to change did decrease with higher levels of fear
of unknown consequences of a change (see Table 4). Thus, Hypothesis 7a was not
supported.
Hypothesis 7b predicted that fear of unknown consequences of a change would be
negatively related to support for change. This hypothesis was not supported. As shown in
Table 2, fear of unknown consequences of a change was not significantly correlated with
active support for change or passive support for change. Furthers, as can be seen in Tables 5
and 6, the levels of fear of unknown consequences of a change were not significantly
predictive of the levels of active support for change or passive support for change.
Hypothesis 8a, which predicted that perceived change in power resulting from a
change would be negatively related to resistance to change, was not supported. As can be
seen in Table 2, perceived change in power resulting from the downsizing was not
significantly correlated with active resistance to change but was positively correlated with
passive resistance to change (r = .29, p < .01). Further, as shown in Tables 3 and 4, the
levels of perceived change in power resulting from the downsizing were not significantly
predictive of the levels of active resistance to change or passive resistance to change.
Hypothesis 8b suggested that perceived change in power resulting from a change
would be positively related to support for change. As can be seen in Table 2, perceived
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change in power resulting from the downsizing was positively correlated with active support
for change (r = .28, p < .01) and passive support for change (r = .21, p < .05). However, the
results shown in 5 and 6 indicate that the levels of perceived change in power resulting from
the downsizing were not significantly predictive of the levels of active support for change or
passive support for change. Thus, Hypothesis 8b was not supported.
Hypothesis 9a suggested that perceived change in status resulting from a change would
be negatively related to resistance to change. As can be seen in Table 2, perceived change in
status resulting from the downsizing was not significantly correlated with active resistance
to change or passive resistance to change. Further, the results shown in Tables 3 and 4
indicate that the levels of perceived change in status resulting from the downsizing were not
significantly predictive of the levels of active resistance to change or passive resistance to
change. Thus, Hypothesis 9a was not supported.
Hypothesis 9b predicted that perceived change in status resulting from a change would
be positively related to support for change. On the one hand, as shown in Table 2, perceived
change in status resulting from the downsizing was positively correlated with active support
for change (r = .45, p < .01) and passive support for change (r = .49, p < .01), suggesting
that this hypothesis is supported. On the other hand, as shown in Table 5, the levels of
perceived change in status resulting from the downsizing were not significantly predictive
of the levels of active support for change. The results shown in Table 6 also show the
negative coefficients for perceived change in status resulting from the downsizing (b1 = -
1.652, p < .01; b2 = -.985, p < .01), implying that the likelihood of having higher levels of
passive support for change did decrease with higher levels of perceived change in status.
Thus, Hypothesis 9b was not supported.
Hypothesis 10a suggested that perceived change in pride resulting from a change
would be negatively related to resistance to change. This hypothesis was not supported. As
can be seen in Table 2, perceived change in pride was not significantly correlated with
active resistance to change or passive resistance to change. Furthermore, the findings shown
in Tables 3 and 4 also indicate that the levels of perceived change in pride resulting from the
downsizing were not significantly predictive of the levels of active resistance to change or
passive resistance to change.
Hypothesis 10b predicted that perceived change in pride resulting from a change
would be positively related to support for change. As shown in Table 2, perceived change in
pride resulting from the downsizing was positively correlated with passive support for
change (r = .41, p < .01) but was not significantly correlated with active support for change.
As shown in Tables 5 and 6, the levels of perceived change in pride resulting from the
downsizing were significantly predictive of the levels of active support for change (b1 = -
103
.702, p < .10; b2 = -.478, p < .10; note that one parameter of dependent variable threshold
was not significant) and passive support for change (b1 = -1.568, p < .01; b2 = -.576, p < .01;
note that one parameter of dependent variable threshold was not significant). The negative
coefficients imply that the higher the level of pride as a result of the downsizing, the lower
the likelihood of having active support for change and passive support for change. Thus,
Hypothesis 10b was not supported by the data.
Hypothesis 11a predicted that job satisfaction would be negatively related to resistance
to change. This Hypothesis was not supported. As can be seen in Table 2, job satisfaction
was positively correlated with active resistance to change (r = .26, p < .01) but was not
significantly correlated with passive resistance to change. The regression results indicate
that the levels of job satisfaction were not significantly predictive of the levels of active
resistance to change (see Table 3) or passive resistance to change (see Table 4).
Hypothesis 11b predicted that job satisfaction would be positively related to support
for change. As can be seen in Table 2, job satisfaction was not significantly correlated with
active support for change but was positively correlated with passive support for change (r =
.26, p < .05). Furthermore, the levels of job satisfaction were not significantly predictive of
the levels of active support for change (see Table 5) or passive support for change (see
Table 6). Thus, Hypothesis 11b was not supported.
Hypothesis 12a predicted that job security would be negatively related to resistance to
change. As shown in Table 2, job security was not significantly correlated with active
resistance to change but was positively correlated with passive resistance to change (r = .24,
p < .05). The regression results illustrated in Tables 3 and 4 indicate that the levels of job
security were not significantly predictive of the levels of active resistance to change or
passive resistance to change. Thus, Hypothesis 12a was not supported.
Hypothesis 12b was that job security would be positively related to support for change.
As can be seen in Table 2, job security was not statistically correlated with active support
for change but was positively correlated with passive support for change (r = .34, p < .01).
However, as shown in Tables 5 and 6, the levels of job security were not significantly
predictive of the levels of active support for change or passive support for change. Thus,
Hypothesis 12b was not supported.
Hypothesis 13a predicted that job motivation would be negatively related to resistance
to change. This hypothesis is not supported. As can be seen in Table 2, job motivation was
not significantly correlated with active resistance to change or passive resistance to change.
Moreover, as can be seen in Tables 3 and 4, the levels of job motivation were not
significantly predictive of the levels of active resistance to change or passive resistance to
change.
104
Hypothesis 13b, which suggested that job motivation would be positively related to
support for change, was not supported. As can be seen in Table 2, job motivation was not
statistically correlated with active support for change but was positively correlated with
passive support for change (r = .22, p < .05). However, as illustrated in Tables 5 and 6, the
levels of job motivation were not significantly predictive of the levels of active support for
change or passive support for change.
Hypothesis 14a was that perceived employability would be positively related to
resistance to change. As shown in Table 2, perceived employability was not significantly
correlated with active resistance to change or passive resistance to change. The results
shown in Tables 3 and 4 indicate that degrees of perceived employability were not
significantly predictive of the levels of active resistance to change but were partially
predictive of the levels of passive resistance to change (b1 = .631, p < .10; b2 = .743, p < .05;
note that one parameter of dependent variable threshold was not significant). Thus,
Hypothesis 14a was partially supported for only one of the two indicators for resistance to
change: passive resistance to change.
Hypothesis 14b, which predicted that perceived employability would be negatively
related to support for change, was not supported in that, as shown in Table 2, perceived
employability was not significantly correlated with active support for change or passive
support for change. Moreover, as shown in Tables 5 and 6, the degrees of perceived
employability were not significantly predictive of the levels of active support for change or
passive support for change.
Hypothesis 15a predicted that self-confidence for career-relevant learning and
competence development would be negatively related to resistance to change. This
hypothesis was not supported. As can be seen in Table 2, self-confidence for career-relevant
learning and competence development was not significantly correlated with active
resistance to change or passive resistance to change. Furthermore, the degrees of self-
confidence for career-relevant learning and competence development were not significantly
predictive of the levels of active resistance to change (see Table 3) or passive resistance to
change (see Table 4).
Hypothesis 15b predicted that self-confidence for career-relevant learning and
competence development would be positively related to support for change. As can be seen
in Table 2, self-confidence for career-relevant learning and competence development was
not significantly correlated with active support for change but was positively correlated with
passive support for change (r = .28, p < .01). Furthermore, degrees of self-confidence for
career-relevant learning and competence development were not significantly predictive of
105
the levels of active support for change or passive support for change. Thus, Hypothesis 15b
was not supported.
Hypothesis 16a, which predicted that affective commitment would be negatively
related to resistance to change, was not supported. As shown in Table 2, affective
commitment was positively correlated with active resistance to change (r = .26, p < .01) but
was not significantly correlated with passive resistance to change. In addition, the levels of
affective commitment were not significantly predictive of the levels of active resistance (see
Table 3) to change or passive resistance to change (see Table 4).
Hypothesis 16b suggested that affective commitment would be positively related to
support for change. This hypothesis was not supported. As shown in Table 2, affective
commitment was not statistically correlated with active support for change but was
positively correlated with passive support for change (r = .23, p < .05). However, as can be
seen in Tables 5 and 6, the levels of affective commitment were not significantly predictive
of the levels of active support for change or passive support for change.
Hypothesis 17a, which predicted that trust in management would be negatively related
to resistance to change, was not supported. As shown in Table 2, trust in management was
not significantly correlated with active resistance to change or passive resistance to change.
In addition, the levels of trust in management were not significantly predictive of the levels
of active resistance to change (see Table 3) or passive resistance to change (see Table 4).
Hypothesis 17b was that trust in management would be positively related to support
for change. As shown in Table 2, trust in management was positively correlated with active
support for change (r = .27, p < .05) and passive support for change (r = .41, p < .01).
However, as shown in Tables 5 and 6, the levels of trust in management were not
significantly predictive of the levels of active support for change but were negatively and
partially predictive of the levels of passive support for change (b1 = -.885, p < .01; b2 = -
.632, p < .01; note that one parameter of dependent variable threshold was not significant).
Thus, Hypothesis 17b was not supported by the data.
Hypothesis 18a suggested that perceptions of colleagues’ resistance to change would
be positively related to resistance to change, and be negatively related to support for change.
As shown in Table 2, a perception of colleagues’ resistance to change was positively
correlated with active resistance to change (r = .28, p < .01) and passive resistance to
change (r = .31, p < .05), but it was not significantly correlated with active support for
change or passive support for change. As shown in Tables 3 and 4, the degrees of
perceptions of colleagues’ resistance to change were not significantly predictive of the
levels of active resistance to change but were negatively and partially predictive of the
levels of passive resistance to change (b1 = -1.075, p < .01; b2 = -.551, p < .05; note that one
106
parameter of dependent variable threshold was not significant). The results also indicate that
the degrees of perceptions of colleagues’ resistance to change were not significantly
predictive of the levels of active support for change (see Table 5) or passive support for
change (see Table 6). Thus, Hypothesis 18a was not supported.
Finally, Hypothesis 18b predicted that perceptions of colleagues’ support for change
would be negatively related to resistance to change, and be positively related to support for
change. As shown in Table 2, a perception of colleagues’ support for change was not
significantly correlated with active resistance to change or passive resistance to change, but
it was positively correlated with active support for change (r = .43, p < .01) and passive
support for change (r = .40, p < .05). However, as shown in Tables 3 and 4, the degrees of
perceptions of colleagues’ support for change were not significantly predictive of the levels
of active resistance to change or passive resistance to change. As also shown in Tables 5
and 6, the degrees of perceptions of colleagues’ support for change were not significantly
predictive of the levels of active support for change but was partially predictive of the levels
of support for change (b1 = -1.315, p < .01; b2 = -1.110, p < .01; note that one parameter of
dependent variable threshold was not significant). Thus, Hypothesis 18b was not supported.
5.1.4. Discussion of Study 1
The purpose of Study 1 was to extend our understanding of the relationships between
perceptions and reactions to change in an environmental context of the downsizing in
Thailand, where many, if not most, of the employees were under pressure to radically
transform themselves or risk losing their job. Toward this end, I examined perceptions
and/or attitudes and reactions of teachers in one private school in Thailand to a relatively
large-scaled forthcoming layoff that fundamentally altered the practice and policy of the
school and teachers.
Important aspects of Study 1 are that (1) it examined a relatively large set of predictors
and outcomes variables, (2) it received a high response rate (91%) to the survey which is
very rare, and (3) it offered some insights into employees’ reactions to change in the
downsizing situation in the private school in Thailand where research on organizational
change is extremely sparse. Before going further with this discussion, two important
cautions to the interpretation of the findings must be made. First, it must be noted that it was
not possible to control for the effects of age, education, gender and other control variables
for the ordered probit regressions due predominantly to a relatively small sample size (n =
86). It is entirely possible that a relatively larger sample size would improve the results of
these regressions. Second, it is also important to note that given the small sample size in
107
Study 1, response scales of variable measurements were recoded for the purpose of
conducting the ordered probit analyses.
Overall, the results of the analyses concerning the prediction of employee’s reactions
to change in this study are not clear-cut. That is, some significant correlations existed
between certain predictors and outcomes, but the sign of some of those significant
correlations was not consistent with expectations and the strength of some of those
significant correlations was low. In general, the results of the ordered probit models offer
little empirical support for the study hypotheses. Surprisingly only one of the 36 hypotheses
was supported: that is, Hypothesis 14a was supported in that most respondents having
higher degrees of passive resistance to change when they believed that they had higher
levels of employability, and those having lower levels of passive resistance to change when
they believed that they had lower levels of employability.
Although most hypotheses tested in Study 1 were not endorsed, there are some
interesting and surprising results. The findings indicate that employees who perceived
higher levels of organizational support had lower degrees of passive support for change.
Clearly, these findings are contradictory to the literature on perceived organizational support
(e.g., Eisenberger, Huntington, Hutchison and Sowa, 1986; Allen, Shore and Griffeth,
2003), the social exchange theory (Blau, 1964) as well as the norm of reciprocity (Gouldner,
1960).
Unexpectedly, higher degrees of fear of known consequences of a change decreased
the likelihood of having higher levels of active resistance to change and passive resistance
to change. In the same vein, the results also indicate that the likelihood of having higher
levels of passive resistance to change did decrease with higher levels of fear of unknown
consequences of a change. This is certainly a surprise as it demonstrates that the
commonsense belief that fear of known and/or unknown consequences of a change will
promote employees’ resistance to change is now known to be (e.g., Morris and Raben,
1995; Mabin et al., 2001), is not correct.
The findings that indicate that the greater the level of perceived need for change, the
lower the likelihood of having higher levels of passive support for change contradict the
argument that when employees perceive a need for change, they will be more ready to
provide support for change (e.g., Kotter 1995; Kotter and Cohen, 2002). While only
partially significant, this unexpected relationship calls into a question as to whether
perceptions of need for change will always promote employees’ support for change.
The evidence that perceptions of having greater pride resulting from the downsizing
decreased the likelihood of having higher levels of active support for change or passive
support for change is surprising. One plausible to these results is that in the context of
108
downsizing where some employees will inevitably have to leave the school, those who may
benefit directly or indirectly from this downsizing may not want to appear to be actively
supportive of the downsizing because they did not want to irritate their colleagues. The
findings that perceptions of having greater degrees of status resulting from downsizing
decreased the likelihood of having higher levels of passive support for change are
unexpected, but it is valuable as it lends support for my interpretation on the findings
concerning perceived change in pride. It is entirely possible that those who had gained some
pride from this downsizing may feel that showing support for this decision will cause
interpersonal problems with their colleagues, thereby reporting low levels of passive support
for change.
In the case of trust in management, the results indicate that higher levels of trust in
management decreased the likelihood of having passive support for change. One caveat to
the findings is that not all parameters were significant. Thus, firm conclusions about these
findings could not be drawn. Furthermore, the results also indicate that the stronger the
degree of perceptions of colleagues’ support for change, the lower the likelihood of having
passive support for change becomes.
In sum, from the point of view of observers expecting rational decisions or behaviors,
this is certainly a surprise as the abovementioned results lend empirical support for the
dispositional argument in this dissertation, or at least weaken the argument that humans are
rational or make rational decisions. However, the conclusions drawn from these results must
be treated with caution since they may not be generalized to other employees in other
organizations due predominantly to the small sample size (n = 86). Therefore, a sample in
Study 2, where another type of organizational change occurs and a sample size is relatively
larger (n = 197), was analyzed. Further analyses in Study 2 will suggest whether the
hypotheses proposed would be endorsed in another sample.
5.2. Study 2 – Results and Discussion
As with Study 1, the purpose of stage 1 was to examine whether the indicators for each
variable were internally consistent, i.e., whether the numbers of indicators for each construct
could be reduced. The same sequence of analysis was completed, starting first with an
assessment of the patterns of directions of the aggregate indicators and the original
indicators in graphical forms (see the Appendix C for further information). As with Study 1,
the results of the procedure used in Study 2 suggest that it was possible to reduce the
number of indicators for each construct (e.g., by either aggregating all three indicators to a
super level or aggregating a pair of indicators to a super level); thus, I reduced the number
of indicators for each variable and conducted the testing of hypotheses using the aggregate
109
indicators. In addition to the use of graphs (see the Appendix C for further information) to
examine the possibility of reducing the number of indicators, I also examined whether the
indicators for each variable were internally consistent using the Spearman correlation
coefficients. Based on the results of both approaches, a selection of indicators (e.g., the
original indicators or the aggregate indicator) to be used for each variable was undertaken.
5.2.1. Analyses of Correlations among Dependent Variables
Tables in the Appendix C provide the Spearman correlation coefficients for all dependent
indicators in Study 2. As can be seen, Active Resistance 1 was positively and significantly
correlated with Active Resistance 2 (r = .28, p < .01) and with Active Resistance 3 (r = .36,
p < .01). In graphs the aggregate indicator between Active Resistance 1 and Active
Resistance 3 visually provided a higher level of internal consistency than the aggregate
indicator between Active Resistance 1 and Active Resistance 2. Thus, I used the aggregate
indicator between Active Resistance 1 and Active Resistance 3 for active resistance to
change.
Further, the number of indicators for passive resistance to change could be reduced
since Passive Resistance 2 was positively and significantly correlated with Passive
Resistance 3 (r = .38, p < .01), and the plotted diagram indicated that they had the same
pattern of directions. Therefore, the aggregate indicator between Passive Resistance 2 and
Passive Resistance 3 would be used for passive resistance to change.
Similarly, I reduced the number of indicators for active support for change by
aggregating Active Support 1 and Active Support 2 to a super level for this construct
because Active Support 1 was positively and significantly correlated with Active Support 2
(r = .43, p < .01), and the plotted diagram indicated that they had the same pattern of
directions. Note that negative and significant correlations existed between Active Support 1
and Active Support 3 (r = -.42, p < .01) and between Active Support 2 and Active Support 3
(r = -.46, p < .01), suggesting that these combinations could not be used for this construct.
Next, Passive Support 1 was positively and significantly correlated with Passive
Support 2 (r = .45, p < .01) and with Passive Support 3 (r = .28, p < .01), but Passive
Support 2 was not significantly correlated with Passive Support 3. Graphically, the
aggregate indicator between Passive Support 1 and Passive Support 2 appeared to provide a
higher level of internal consistency than the aggregate indicator between Passive Support 1
and Passive Support 3; therefore, I reduced the number of indicators for passive support for
change by aggregating Passive Support 1 and Passive Support 3 to a super level.
Concerning relationships among indicators for active resistance to change and passive
resistance to change, there were eight positive and significant correlations among them;
110
moreover, there were three negative and significant correlations among them. On the
contrary, there were five positive and significant correlations but six negative and
significant correlations among the indicators for active support for change and the indicators
for passive support for change. Concerning the correlations between dependent indictors
and control variables, unlike in Study 1, there were several significant correlations among
them.
5.2.2. Analyses of Correlations among Independent Variables
Tables in the Appendix C provide the Spearman correlation coefficients for active resistance
to change indictors and all independent indicators. As with Study 1, I first examined
whether the indicators for each variable were significantly correlated with each other.
Concerning perceived organizational support (POS), POS 1 was positively and
significantly correlated with POS 2 (r = .50, p < .01), whereas POS 2 was negatively and
significantly correlated with POS 3 (r = -.25, p < .01). Thus, I reduced the number of
indicators for perceived organizational support by aggregating POS 1 and POS 2 to a super
level. Since Perceived Procedural Justice 1 was positively and significantly correlated with
Perceived Procedural Justice 3 (r = .15, p < .05), the aggregate indicator between Perceived
Procedural Justice 1 and Perceived Procedural Justice 3 would be used for perceived
procedural justice. Participation 1 was significantly correlated with Perceived Participation
2 (r = .37, p < .01) and Perceived Participation 3 (r = .38, p < .01), but Perceived
Participation 2 was not significantly correlated with Perceived Participation 3. Therefore,
Perceived Participation 1 and Perceived Participation 2 would be aggregated to a super level
for perceived participation in decision-making.
Perceived Need for Change 1 was positively and significantly correlated with
Perceived Need for Change 2 (r = .18, p < .05), and Perceived Need for Change 2 was
positively and significantly correlated with Perceived Need for Change 3 (r = .33, p < .01).
Comparing between two aggregate indicators (the one between Perceived Need for Change
1 and Perceived Need for Change 2 and the one between Perceived Need for Change 2 and
Perceived Need for Change 3) in diagrams, the latter combination seemed to provide a
higher level of internal consistency. Thus, Perceived Need for Change 2 and Perceived
Need for Change 3 were aggregated to a super level for perceived need for change. Since
Attitude towards Organizational Change 1 was significantly and significantly correlated
with Attitude towards Organizational Change 2 (r = .24, p < .01), the aggregate indicator
between Attitude towards Organizational Change 1 and Attitude towards Organizational
Change 2 would be used for attitude towards organizational change. Fear of Known
Consequences 3 was negatively and significantly correlated with Fear of Known
111
Consequences 1 (r = -.19, p < .01) but was positively and significantly correlated with Fear
of Known Consequences 2 (r = .17, p < .05). Therefore, Fear of Known Consequences 2
and Fear of Known Consequences 3 would be aggregated to a super level for this construct.
As a positive and significant correlation existed between Fear of unknown
Consequences 2 and Fear of Unknown Consequences 3 (r = .22, p < .01), Fear of Unknown
Consequences 2 and Fear of Unknown Consequences 3 would be aggregated to a super
level for fear of unknown consequences of a change. The results also suggest that all
indicators for perceived change in power were positively and significantly correlated with
each other; however, further graphical analyses suggested that only two indicators for this
construct should be aggregated to super level: that is, Change in Power 2 and Change in
Power 3 (r = .46, p < .01).
Concerning perceived change in status, Change in Status 1 was positively and
significantly correlated with Change in Status 2 (r = .31, p < .01) but was negatively and
significantly correlated with Change in Status 3 (r = -.16, p < .05); and Change in Power 2
was negatively and significantly correlated with Change in Status 3 (r = -.49, p < .01). To
reduce the number of indicators for this construct, I aggregated Change in Status 1 and
Change in Status 2 to a super level. Next, a negative and significant correlation existed
between Change in Pride 1 and Change in Pride 3 (r = -.34, p < .01), suggesting that I could
not aggregate the two indicators. To reduce the number of indicators for perceived change in
pride, I plotted the aggregate indicators between all possible pairs of indicators for
perceived change in pride. The results (see the Appendix C for further information) partially
supported the idea that the aggregate indicator between Change in Pride 1 and Change in
Pride 2 could be used for this construct.
Job Satisfaction 2 was positively and significantly correlated with Job Satisfaction 3 (r
= .20, p < .01); thus, Job Satisfaction 2 and Job Satisfaction 3 would be aggregated to a
super level. Though all indicators for job security were positively and significantly
correlated with each other, Job Security 1 and Job Security 2 would be aggregated to a super
level because it provided a higher level of internal consistency. With regard to job
motivation, Job Motivation 2 was positively and significantly correlated with Job
Motivation 1 (r = .20, p < .01) and Job Motivation 3 (r = .53, p < .01). To reduce the
number of indicators for this construct, I aggregated Job Motivation 2 and Job Motivation 3
to a super level as a unit of analysis.
Next, all indicators for perceived employability were significantly correlated with each
other, but with different signs. That is, Perceived Employability 2 was negatively and
significantly correlated with Perceived Employability 1 (r = -.14, p < .05) and Perceived
Employability 2 (r = -.23, p < .01); and Perceived Employability 1 was positively and
112
significantly correlated with Perceived Employability 2 (r = .16, p < .05). Thus, Perceived
Employability 1 and Perceived Employability 2 were aggregated to a super level for this
variable.
All correlations among the indicators for self-confidence for learning and development
were positive and significant. However, I reduced the number of indicators for this construct
by aggregating Self-Confidence for Learning 1 and Self-Confidence for Learning 3 since it
graphically provided the highest level of internal consistency. Affective Commitment 1 was
positively and significantly correlated with Affective Commitment 2 (r = .36, p < .01) and
Affective Commitment 3 (r = .27, p < .01). Thus, Affective 1 and Affective 2 were
aggregated to a super level. Although all indicators for trust in management were positively
and significantly correlated with each other, I reduced the number of indictors for this
construct by aggregating Trust in Management 1 and Trust in Management 3 because this
combination provided, in graphs, a relatively higher level of internal consistency.
Concerning a perception of colleagues’ resistance to change, a negative and significant
correlation existed between Colleagues’ Resistance 1 and Colleagues’ Resistance 2 (r = -
.21, p < .01). As can be seen in the Appendix C, there was a common pattern of directions
between the two indicators, suggesting that both indicators could be aggregated to a super
level.
113
Table 7: Study 2 – Correlations for All Final Variables
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
1.
AR
.41
2.
PR
.32†
.58
3.
AS
-.54†
-.47†
.59
4.
PS
.49†
.33†
-.43†
.68
5.
POS
.47†
.59†
-.59†
.45†
.69
6.
Justice
-.14*
.12
.11
-.33†
.07
.19
7.
Participation
.47†
.46†
-.45†
.44†
.47†
.00
.56
8.
Need
.35†
.32†
-.39†
.42†
.40†
-.08
.27†
.51
9.
Attitude
.00
.35†
-.25†
.09
.17*
.25†
.26†
.34†
.33
10. Fear Known
.46†
.44†
-.52†
.43†
.53†
-.08
.45†
.31†
.08
.23
11. Fear Un
.20†
.13
-.20†
.20†
.35†
-.02
.09
.35†
.05
.14
.36
12. Power
.51†
.47†
-.47†
.55†
.52†
-.15*
.45†
.45†
.22†
.43†
.23†
.65
13. Status
.16*
.38†
-.22†
.25†
.36†
.15*
.27†
.26†
.29†
.12
.22†
.40†
.41
14. Pride
-.47†
-.44†
.44†
-.44†
-.44†
.10
-.41†
-.29†
-.08
-.46†
-.15*
-.56†
-.21†
-.02
15. Job Sat
.36†
.02
-.18*
.21†
.23†
-.26†
.03
.07
-.36†
.15*
.19†
.06
.09
-.18*
.27
16. Job Security
-.23†
.29†
.00
-.27†
.06
.40†
.11
.02
.53†
-.08
-.05
.06
.29†
.08
-.52†
.85
17. Job M
ot
-.16*
.29†
-.01
-.12
.14*
.46†
.17*
.09
.52†
-.09
.03
.15*
.31†
.06
-.47†
.70†
.63
18. Employ
.27†
.35†
-.24†
.30†
.34†
.02
.26†
.33†
.28†
.14
.08
.43†
.40†
-.27†
.07
.21†
.30†
.30
19. Learning
-.51†
-.09
.33†
-.26†
-.22†
.26†
-.04
-.07
.26†
-.26†
-.04
-.22†
-.05
.27†
-.46†
.36†
.40†
-.01
.63
20. Commitment
-.19†
.17*
.04
-.07
.05
.22†
.09
.09
.32†
-.15*
.02
.04
.11
-.02
-.26†
.37†
.43†
.18†
.44†
.49
21. Trust
-.23†
.07
.10
-.01
-.08
.17*
-.03
-.01
.33†
-.21†
-.04
.01
-.03
.17*
-.32†
.34†
.43†
.10
.30†
.38†
.36
22. Col Resist
-.27†
-.10
.18*
-.01
-.14*
.02
-.07
-.08
.19†
-.21†
-.08
.04
-.04
.07
-.18*
.12
.24†
.12
.32†
.32†
.41†
-.63
23. Col Support
.29†
.28†
-.23†
.44†
.27†
-.05
.28†
.45†
.24†
.18*
.23†
.46†
.30†
-.25†
.02
.04
.19†
.48†
-.07
.14
.23†
.40†
-
24. Age
-.20†
.05
.12
-.06
-.09
.12
-.05
.16*
.26†
-.23†
.04
.05
.26†
.03
-.23†
.29†
.43†
.24†
.31†
.26†
.24†
.18*
.14*
-
25. Education
.29†
.26†
-.29†
.09
.30†
.14
.13
.24†
.26†
.15*
.25†
.22†
.19†
-.28†
-.01
.14*
.19†
.19†
-.12
.01
-.05
-.14
.10
-.06
-
26. Gender
.08
.01
.07
-.07
-.05
-.03
.00
-.07
-.11
-.03
-.04
-.01
-.02
-.07
.03
-.02
-.09
-.09
-.18†
-.16*
-.07
-.17*
-.05
-.20†
.14*
Notes:
N = 197. Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed). † p < .01, * p < .05. Scale
reliabilities (Cronbach’s alpha) are shown along the diagonal.
114
5.2.3. Results for Hypotheses – The Multinomial Ordered Probit Models
As with Study 1, after the number of indicators has been reduced, a correlation analysis for
the final variables was conducted. Table 7 reports the Spearman correlations among all the
variables for Study 2. As with Study 1, for ease of interpretation of all the data, results
relevant to correlations analyses and regression analyses will be interpreted together rather
than in sequentially separate results sections. It should be noted that in comparison to Study
1, a relatively larger sample size in Study 2 suggested that the results of Study 2 should be
treated with higher value than those of in Study 1: that is, the results of Study 1 should be
treated as exploratory due to a small sample size (n = 86).
Tables 8, 9, 10 and 11 present the results of the ordered probit models. As with Study
1, I used the ordered probit models to test Hypotheses 1a-18b. Before the ordered probit
regressions were computed, measurement scales for both dependent variables and
independent variables were recoded (i.e., 1 and 2 = 1; 3 = 2; and 4 and 5 = 3).70 Restricted
models that included only one of the independent variables and only one of the dependent
variables were computed. Then, full models that included all independent variables, one of
the dependent variables, and three control variables were computed. However, the size of
sample in Study 2 (n = 197) did not allow for conducting models that had more than one
independent variable. That is, multiple-variables models with the sample size of 197 cases
inevitably produced a large number of empty cells. Thus, I decided to conduct only two-
variable models to test Hypotheses 1a-18b for Study 2. As with Study 1, the results of the
ordered probit models were considered to be (1) fully supportive of any hypotheses when all
parameters of the independent variable location and all parameter of dependent variable
threshold were significant and (2) partially supportive of any hypotheses only when both
(two) parameters of independent variable location and one parameter of dependent variable
threshold are significant.
Hypothesis 1a predicted that perceived organizational support would be negatively
related to resistance to change. As shown in Table 7, perceived organizational support was
not significantly correlated with active resistance to change but was positively correlated
with passive resistance to change (r = .23, p < .05). The regression results shown in Tables 8
and 9 indicate that the levels of perceived organizational support were not significantly
predictive of the levels of active resistance to change but were negatively and significantly
predictive of the levels of passive resistance to change (b1 = -1.088, p < .01; b2 = -.629, p <
.01). Thus, Hypothesis 1a was supported for only one of the two alternative indicators for
resistance to change: passive resistance to change.
70 See Sections 4.3 and 4.4 for more information.
115
Table 8: Study 2 – Regression Results of Active Resistance to Change
Dependent Variable Threshold Independent Variable Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-.646† .179 .945
† .186 -1.088
† .218 -.405 .223 27.948
†
Perceived Procedural Justice -.048 .119 1.405† .153 -.045 .247 -.065 .183 .132
Perceived Participation in
Decision-Making
-.909† .198 .733
† .193 -1.277
† .227 -.783
† .240 33.298
†
Perceived Need for Change -.625† .165 .933
† .173 -.897
† .224 -.788
† .204 20.657
†
Attitude towards Organizational
Change
-.158 .123 1.369† .157 .413** .250 -.507
† .186 14.179
†
Fear of Known Consequences
of a Change
-.924† .217 .705
† .212 -1.466
† .255 -.694
† .240 37.974
†
Fear of Unknown
Consequences of a Change
-.474* .209 1.013† .219 -.624* .244 -.457** .238 6.541*
Perceived Change in Power -.849† .174 .849
† .174 -1.613
† .234 -.683
† .211 52.483
†
Perceived Change in Status -.346* .155 1.144† .173 -.443* .214 -.475* .199 6.623*
Perceived Change in Pride .453† .126 2.123
† .192 1.501
† .271 .826
† .189 39.513
†
Job Satisfaction -.418 .257 1.091† .268 -.704* .281 -.094 .284 14.210
†
Job Security .105 .108 1.588† .153 .745* .300 .240 .189 6.863*
Job Motivation .058 .109 1.578† .156 .893
† .265 -.066 .198 12.863
†
Perceived Employability -.373† .140 1.140
† .160 -.645* .259 -.540
† .182 11.060
†
Self-Confidence for Learning
and Development
.350† .114 1.950
† .176 1.258
† .310 .867
† .188 31.506
†
Affective Commitment .060 .110 1.533† .152 .534* .249 .048 .196 4.671**
Trust in Management .186** .113 1.664† .158 .434** .257 .531
† .190 8.984*
Colleagues’ Resistance to
Change
.417† .144 1.957
† .191 .547* .242 .785
† .191 17.540
†
Colleagues’ Support for Change -.609† .170 .942
† .178 -.803
† .216 -.766
† .212 17.340
†
Notes: N = 197. Variables have 3 Levels: 1=Low; 2=Medium; 3=High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
116
Table 9: Study 2 – Regression Results of Passive Resistance to Change
Dependent Variable Threshold Independent Variable Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-1.505† .203 -.393* .182 -1.590
† .226 -.629
† .233 58.590
†
Perceived Procedural Justice -.706† .124 .241* .118 -.855* .249 -.297** .177 12.717
†
Perceived Participation in
Decision-Making
-1.572† .218 -.521
† .201 -1.471
† .235 -.918
† .250 43.247
†
Perceived Need for Change -1.404† .184 -.364* .166 -1.033
† .223 -1.284
† .210 40.664
†
Attitude towards Organizational
Change
-.943† .134 .060 .122 -.442** .248 -.972
† .180 29.758
†
Fear of Known Consequences
of a Change
-1.150† .220 -.158 .209 -1.112
† .245 -.411** .242 26.812
†
Fear of Unknown
Consequences of a Change
-1.030† .219 -.086 .211 -.469** .244 -.801
† .242 11.833
†
Perceived Change in Power -1.280† .180 -.271 .165 -1.197
† .214 -.856
† .212 32.821
†
Perceived Change in Status -1.185† .170 -.191 .156 -.936
† .215 -.955
† .201 27.389
†
Perceived Change in Pride -.187 .119 .815† .128 1.528
† .292 .434* .175 31.411
†
Job Satisfaction -1.050† .269 -.119 .262 -.529** .283 -.769
† .292 7.377*
Job Security -.668† .114 .270* .108 -.540** .301 -.519* .185 9.674
†
Job Motivation -.732* .116 .227* .109 -.372 .259 -.777* .193 16.740†
Perceived Employability -1.130† .153 -.121 .138 -1.009
† .249 -.952
† .182 32.123
†
Self-Confidence for Learning
and Development
-.503† .113 .409
† .112 .116 .299 -.138 .176 .938
Affective Commitment -.627† .115 .297
† .110 -.372 .247 -.384* .189 5.382**
Trust in Management -.552† .114 .360
† .112 -.205 .251 -.197 .184 1.506
Colleagues’ Resistance to
Change
-.438† .136 .475
† .136 -.131 .229 .133 .176 1.535
Colleagues’ Support for Change -1.306† .185 -.306** .170 -.905
† .216 -1.168
† .217 30.840
†
Notes: N = 197. Variables have 3 Levels: 1=Low; 2=Medium; 3=High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
117
Table 10: Study 2 – Regression Results of Active Support for Change
Dependent Variable Threshold Independent Variable Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
.073 .175 .962† .185 1.522
† .222 .940
† .228 48.070
†
Perceived Procedural Justice -.843† .129 -.101 .119 -.284 .244 -.008 .184 1.475
Perceived Participation in
Decision-Making
-.296 .184 .502† .186 .939
† .219 .293 .233 22.158
†
Perceived Need for Change -.119 .159 .717† .165 1.183
† .227 .982
† .203 33.961
†
Attitude towards Organizational
Change
-.548† .127 .241* .123 .060 .250 .790
† .188 19.198
†
Fear of Known Consequences
of a Change
-.027 .206 .821† .213 1.497
† .253 .628
† .239 40.854
†
Fear of Unknown Consequences
of a Change
-.253 .208 .524* .210 .913† .247 .480* .238 14.394
†
Perceived Change in Power -.089 .160 .767† .168 1.332
† .219 .894
† .210 39.249
†
Perceived Change in Status -.344* .154 .436† .155 .630
† .214 .753
† .200 15.524
†
Perceived Change in Pride -1.309† .146 -.470
† .126 -1.531
† .271 -.638
† .184 36.248
†
Job Satisfaction -.445** .258 .309 .257 .555* .279 .205 .286 6.108*
Job Security -.861† .119 -.120 .108 -.161 .305 -.183 .188 1.073
Job Motivation -.805† .119 -.046 .109 -.546* .263 .281 .200 7.999*
Perceived Employability -.477† .140 .292* .138 .678
† .259 .515
† .180 10.911
†
Self-Confidence for Learning
and Development
-1.051† .128 -.286* .113 -.584** .304 -.561
† .182 11.236
†
Affective Commitment -.834† .120 -.093 .111 -.252 .251 -.011 .195 1.059
Trust in Management -.813† .121 -.074 .112 .088 .262 -.096 .189 .475
Colleagues’ Resistance to
Change
-1.000† .150 -.252** .139 -.387 .236 -.292 .184 3.651
Colleagues’ Support for Change -.214 .164 .593† .168 .689
† .211 1.036
† .215 23.862
†
Notes: N = 197. Variables have 3 Levels: 1=Low; 2=Medium; 3=High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
118
Table 11: Study 2 – Regression Results of Passive Support for Change
Variable Threshold Location
Level 1 Level 2 Level 1 Level 2
Independent Variables Estimate S.E. Estimate S.E. Estimate S.E. Estimate S.E. χ2
Perceived Organizational
Support
-1.220† .192 .063 .173 -1.567
† .222 -1.046
† .229 51.033
†
Perceived Procedural Justice .050 .119 1.113† .136 .387 .240 .295 .179 4.128
Perceived Participation in
Decision-Making
-1.104† .198 .097 .184 -1.306
† .222 -1.016
† .239 36.011
†
Perceived Need for Change -.878† .168 .319* .159 -1.371
† .230 -.804
† .199 37.580
†
Attitude towards Organizational
Change
-.257* .122 .809* .130 -.376 .256 -.252 .176 3.247
Fear of Known Consequences
of a Change
-1.178† .220 .002 .207 -1.356
† .247 -1.108
† .243 31.688
†
Fear of Unknown
Consequences of a Change
-.594† .208 .497* .207 -.744
† .241 -.403** .234 9.940
†
Perceived Change in Power -1.088† .176 .198 .160 -1.577
† .223 -.963
† .210 52.671
†
Perceived Change in Status -.594† .208 .497* .207 -.744
† .241 -.403** .234 27.029
†
Perceived Change in Pride .085 .120 1.311† .147 1.736
† .282 .116 .179 42.054
†
Job Satisfaction -.232 .255 .826† .259 -.233 .276 -.010 .283 1.929
Job Security .055 .107 1.127† .127 .413 .298 .461* .185 7.233*
Job Motivation -.027 .108 1.027† .124 .177 .261 .225 .189 1.635
Perceived Employability -.714† .144 .470
† .140 -1.237
† .268 -.834
† .180 31.686
†
Self-Confidence for Learning
and Development
-.005 .110 1.060† .127 -.016 .306 .339** .178 3.852
Affective Commitment -.190** .110 .870† .121 -.126 .250 -.249 .193 1.738
Trust in Management -.224* .112 .848† .122 -.606* .271 -.142 .186 5.279**
Colleagues’ Resistance to
Change
-.113 .135 .944† .146 -.182 .235 .066 .178 1.165
Colleagues’ Support for Change -.828† .171 .349* .164 -1.252
† .220 -.658
† .206 33.149
†
Notes: N = 197. Variables have 3 Levels: 1=Low; 2=Medium; 3=High. Parameter for
Independent Variable’s level 3 is set to zero because it is redundant. † p < .01, * p
< .05, ** p < .10
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Hypothesis 1b predicted that perceived organizational support would be positively related to
support for change. As shown in Table 7, perceived organizational support was not
significantly correlated with active support for change but was positively correlated with
passive support for change (r = .34, p < .01). As shown in Tables 10 and, the levels of
perceived organizational support were positively and partially predictive of the levels of
active support for change (b1 = 1.522, p < .01; b2 = .940, p < .01; note that one parameter of
dependent variable threshold was not significant) but was negatively and partially predictive
of the levels of passive support for change (b1 = -1.567, p < .01; b2 = -1.046, p < .01; note
that one parameter of dependent variable threshold was not significant). The negative
coefficients of –1.567 and –1.046 for perceived organizational support imply that the lower
the level of perceived organizational support, the greater the likelihood of having higher
levels of active support for change and passive support for change respectively. Thus,
Hypothesis 1b was supported for only one of the two indicators for support for change:
active support for change.
Hypothesis 2a predicted that perceived procedural justice would be negatively related
to resistance to change. As shown in Table 7, the correlations between perceived procedural
justice on the one hand and active resistance to change and passive resistance to change on
the other hand were not statistically significant. The regression results shown in Tables 8
and 9 indicate that the levels of perceived procedural justice were not significantly
predictive of the levels of active resistance to change but were negatively and significantly
predictive of the levels of passive resistance to change (b1 = -.855, p < .05; b2 = -.297, p <
.10). Thus, Hypothesis 2a was supported for only one of the two indicators for resistance to
change: passive resistance to change.
Hypothesis 2b, which predicted that perceived procedural justice would be positively
related to support for change, was not supported. As shown Table 7, perceived procedural
justice was positively correlated with active support for change (r = .67, p < .01) and
passive support for change (r = .39, p < .01). However, as shown in Tables 10 and 11, the
levels of perceived procedural justice were not significantly predictive of the levels of active
support for change or passive support for change.
Hypothesis 3a predicting that perceived participation in decision-making regarding
organizational change would be negatively related to resistance to change was supported. As
shown in Table 7, neither active resistance to change nor passive resistance to change was
significantly correlated with perceived participation in decision-making regarding the
privatization. However, the results shown in Tables 8 and 9 indicate that the levels of
perceived participation in decision-making regarding the privatization were negatively and
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significantly predictive of the levels of active resistance to change (b1 = -1.277, p < .01; b2 =
-.783, p < .01) and passive resistance to change (b1 = -1.471, p < .01; b2 = -.918, p < .01).
Hypothesis 3b predicting that perceived participation in decision-making regarding
organizational change would be positively related to support for change was not supported.
As shown in Table 7, perceived participation in decision-making regarding the privatization
was not significantly correlated with active support for change but was positively correlated
with passive support for change (r = .26, p < .05). The regression results also indicate that
the levels of perceived participation in decision-making regarding the privatization were not
significantly predictive of the levels of active support for change (see Table 10) or passive
support for change (see Table 11).
Hypothesis 4a predicted that perceived need for change would be negatively related to
resistance to change. As shown in Table 7, perceived need for change was not significantly
correlated with active resistance to change or passive resistance to change. However, as
shown in Tables 8 and 9, the levels of perceived need for change were negatively and
significantly predictive of the levels of active resistance to change (b1 = -.897, p < .01; b2 = -
.788, p < .01) and passive resistance to change (b1 = -1.033, p < .01; b2 = -1.284, p < .01).
Thus, Hypothesis 4a was supported.
Hypothesis 4b predicted that perceived need for change would be positively related to
support for change. As can be seen in Table 7, perceived need for change was not
significantly predictive of active support for change but was positively and significantly
predictive of passive support for change (r = .28, p < .01). Further, as shown in Table 10,
the levels of perceived need for change were positively and partially predictive of the levels
of active support for change (b1 = 1.183, p < .01; b2 = .982, p < .01; note that one parameter
of dependent variable threshold was not significant). However, the negative coefficients for
perceived need for change (see Table 11) mean that the likelihood of having higher levels of
passive support for change did decrease with higher levels of perceived need for change (b1
= -.590, p < .10; b2 = -.519, p < .10). Thus, Hypothesis 4b was partially supported for only
one of the two alternative indicators for support for change: active support for change.
Hypothesis 5a predicted that attitude towards organizational change would be
negatively related to resistance to change. As shown in Table 7, attitude towards
organizational was negatively and significantly correlated with active resistance to change (r
= -.22, p < .05) but was not significantly correlated with passive resistance to change. The
results shown in Tables 8 and 9 indicate that the degrees of attitude towards organizational
change were not significantly predictive of the levels of active resistance to change but were
negatively and partially predictive of the levels of passive resistance to change (b1 = -.442, p
< .10; b2 = -.972, p < .01; note that one parameter of dependent variable threshold was not
121
significant). Thus, Hypothesis 5a was partially supported for only one of the two alternative
indicators for resistance to change: passive resistance to change.
Hypothesis 5b predicted that attitude towards organizational change would be
positively related to support for change. As can be seen in Table 7, attitude towards
organizational change was not significantly correlated with active support for change but
was positively correlated with passive support for change (r = .39, p < .01). In addition, as
shown in Tables 10 and 11, the levels of attitude towards organizational change were not
significantly predictive of the levels of active support for change or passive support for
change. Thus, that Hypothesis 5b was not supported.
Hypothesis 6a predicted that fear of known consequences of a change would be
positively related to resistance to change. As shown in Table 7, fear of known consequences
of the privatization was positively correlated with active support for change (r = .54, p <
.01) and passive support for change (r = .45, p < .01). However, as can be seen in Tables 8
and 9, the levels of fear of known consequences of the privatization were negatively and
significantly predictive of the levels of active resistance change (b1 = -1.466, p < .01; b2 = -
.694, p < .01) and was negatively and partially predictive of the levels of passive resistance
to change (b1 = -1.112, p < .01; b2 = -.411, p < .10; note that one parameter of dependent
variable threshold was not significant). Thus, Hypothesis 6a was not supported.
Hypothesis 6b predicted that fear of known consequences of a change would be
negatively related to support for change. As shown in Table 7 show, fear of known
consequences of the privatization was not significantly correlated with active support for
change or passive support for change. Furthermore, as can be seen in Tables 10 and 11, the
levels of fear of known consequences of the privatization were positively and partially
predictive of the levels of active support for change (b1 = 1.497, p < .01; b2 = .628, p < .10;
note that one parameter of dependent variable threshold was not significant) but was
negatively and significantly predictive of the levels of passive support for change (b1 = -
1.356, p < .01; b2 = -1.108, p < .10; note that one parameter of dependent variable threshold
was not significant). Thus, Hypothesis 6b was partially supported for only one of the two
indicators for support for change: passive support for change.
Hypothesis 7a predicted that fear of unknown consequences of a change would be
positively related to resistance to change. As illustrated in Table 7, fear of unknown
consequences of the privatization was positively correlated with active resistance to change
(r = .24, p < .05) and passive resistance to change (r = .44, p < .01). However, the results
shown in Tables 8 and 9 indicate that the levels of fear of unknown consequences of the
privatization were negatively and significantly predictive of active resistance to change (b1
= -.624, p < .05; b2 = -.457, p < .10) and passive resistance to change (b1 = -.469, p < .10; b2
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= -.801, p < .01; note that one parameter of dependent variable threshold was not
significant). Thus, Hypothesis 7a was not supported.
Hypothesis 7b addressed the negative effect of fear of unknown consequences of a
change on support for change. As shown in Table 7, fear of unknown consequences of the
privatization was negatively correlated with active support for change (r = -.20, p < .05) but
was positively correlated with passive support for change (r = .20, p < .01). The results
shown in Tables 10 and 11 indicate that the levels of fear of unknown consequences of the
privatization were not significantly predictive of the levels of active support for change but
was negatively and significantly predictive of the levels of passive support for change (b1 =
-.744, p < .01; b2 = -.403, p < .10). Thus, Hypothesis 7b was supported for only one of the
two indicators for support for change: passive support for change.
Hypothesis 8a predicted that perceived change in power resulting from a change would
be negatively related to resistance to change. As shown in Table 7, perceived change in
power resulting from the privatization was not significantly correlated with active support
for change or passive support for change. However, as shown in Tables 8 and 9, the levels
of perceived change in power resulting from the privatization were negatively and
significantly predictive of the levels of active resistance to change (b1 = -1.613, p < .01; b2 =
-.683, p < .01) and passive resistance to change (b1 = -1.197, p < .01; b2 = -.856, p < .01;
note that one parameter of dependent variable threshold was not significant). Thus,
Hypothesis 8a was supported.
Hypothesis 8b suggested that perceived change in power resulting from a change
would be positively related to support for change. As shown in Table 7, perceived change in
power resulting from the privatization was positively correlated with passive resistance to
change (r = .29, p < .01). The regression results shown in Tables 10 and 11 indicate that the
levels of perceived change in power resulting from the privatization did increase the
likelihood of having higher levels of active support for change (b1 = 1.332, p < .01; b2 =
.894, p < .01; note that one parameter of dependent variable threshold was not significant)
but did decrease the likelihood of having higher levels of passive support for change (b1 = -
1.577, p < .01; b2 = -.963, p < .01; note that one parameter of dependent variable threshold
was not significant). Thus, Hypothesis 8b was partially supported for only of the two
indicators for support for change: active support for change.
Hypothesis 9a predicted that perceived change in status resulting from a change would
be negatively related to resistance to change. As can be seen in Table 7, perceived change in
status resulting from the privatization was not significantly correlated with active resistance
to change or passive resistance to change. However, as shown in Tables 8 and 9, the degrees
of perceived change in status resulting from the privatization did decrease the likelihood of
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having higher levels of active resistance to change (b1 = -.443, p < .05; b2 = -.475, p < .05)
and passive resistance to change (b1 = -.936, p < .01; b2 = -.955, p < .01; note that one
parameter of dependent variable threshold was not significant). Thus, Hypothesis 9a was
supported.
Hypothesis 9b was that perceived change in status resulting from a change would be
positively related to support for change. As shown in Table 7, perceived change in status
resulting from the privatization was positively correlated with active support for change (r =
.45, p < .01) and passive support for change (r = .49, p < .01). Further, as shown in Table
10, the likelihood of having higher levels of active support for change did increase with
higher levels of perceived change in status resulting from the privatization (b1 = .630, p <
.01; b2 = .753, p < .01). However, as illustrated in Table 11, the likelihood of having higher
levels of passive support for change did decrease with higher levels of perceived change in
status resulting from the privatization (b1 = -.744, p < .01; b2 = -.403, p < .10). Thus,
Hypothesis 9b was supported for only one of the two indicators for support for change:
active support for change.
Hypothesis 10a predicted that perceived change in pride resulting from a change
would be negatively related to resistance to change. As can be seen in Table 7, perceived
change in pride resulting from the privatization was not significantly correlated with active
resistance to change or passive resistance to change. Further, as shown in Tables 8 and 9,
the levels of perceived change in pride resulting from the privatization increased the
likelihood of having higher levels of active resistance to change (b1 = 1.501, p < .01; b2 =
.826, p < .01) and passive resistance to change (b1 = 1.528, p < .01; b2 = .434, p < .05; note
that one parameter of dependent variable threshold was not significant). Thus, Hypothesis
10a was not supported.
Hypothesis 10b predicted that perceived change in pride resulting from a change
would be positively related to support for change. As shown in Table 7, perceived change in
pride was positively correlated with passive support for change (r = .41, p < .01) but was not
significantly correlated with active support for change. The results shown in Tables 10 and
11 indicate that perceived change in pride decreased the likelihood of having active support
for change (b1 = -1.531, p < .10; b2 = -.638, p < .10) but was not significantly predictive of
passive support for change. Thus, Hypothesis 10b was not supported.
Hypothesis 11a predicted that job satisfaction would be negatively related to resistance
to change. As can be seen in Table 7, job satisfaction was positively correlated with active
resistance to change (r = .26, p < .01) but was not significantly correlated with passive
resistance to change. As shown in Tables 8 and 9, the levels of job satisfaction were not
significantly predictive of the levels of active resistance to change, but higher levels of job
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satisfaction decreased the likelihood of having higher levels of passive resistance to change
(b1 = -.528, p < .10; b2 = -.769, p < .01; note that one parameter of dependent variable
threshold was not significant). Thus, Hypothesis 11a was partially supported for only one of
the two indicators for resistance to change: passive resistance to change.
Hypothesis 11b predicted that job satisfaction would be positively related to support
for change. As can be seen in Table 7, job satisfaction was not significantly correlated with
active support for change but was positively correlated with passive support for change (r =
.26, p < .05). Furthermore, the levels of job satisfaction were not significantly predictive of
the levels of active support for change (see Table 10) or passive support for change (see
Table 11). Thus, Hypothesis 11b was not supported.
Hypothesis 12a predicted that job security would be negatively related to resistance to
change. As shown in Table 7, job security was not significantly correlated with active
resistance to change but was positively correlated with passive resistance to change (r = .24,
p < .05). The regression results shown in Tables 8 and 9 indicate that the levels of job
security were not significantly predictive of the levels of active resistance to change but
significantly predictive of the levels of passive resistance to change (b1 = -.540, p < .10; b2 =
-.519, p < .05). Thus, Hypothesis 12a was supported for only one of the two indicators for
resistance to change: passive resistance to change.
Hypothesis 12b, which predicted that job security would be positively related to
support for change, was not supported. As can be seen in Table 7, job security was not
significantly correlated with active support for change but was positively correlated with
passive support for change (r = .34, p < .01). The regression results shown in Tables 10 and
11 indicate that the levels of job security were not significantly predictive of the levels of
active support for change or passive support for change.
Hypothesis 13a predicting that job motivation would be negatively related to
resistance to change was not supported. As can be seen in Table 7, job motivation was not
significantly correlated with active resistance to change or passive resistance to change.
Furthermore, as shown in Tables 8 and 9, the levels of job motivation were not significantly
predictive of the levels of active resistance to change or passive resistance to change.
Hypothesis 13b predicted that job motivation would be positively related to support for
change. As illustrated in Table 7, job motivation was not statistically correlated with active
support for change but was positively correlated with passive support for change (r = .22, p
< .05). Furthermore, as shown in Tables 10 and 11, the levels of job motivation were not
significantly predictive of the levels of active support for change or passive support for
change. Thus, Hypothesis 13b was not supported.
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Hypothesis 14a predicting that perceived employability would be positively related to
resistance to change was not supported. As Table 7 illustrates, perceived employability was
not significantly correlated with active resistance to change or passive resistance to change.
Furthermore, as shown in Tables 8 and 9, higher degrees of perceived employability
decreased the likelihood of having higher levels of active resistance to change (b1 = -.645, p
< .05; b2 = -.540, p < .01) and passive resistance to change (b1 = -1.009, p < .01; b2 = -.952,
p < .01; note that one parameter of dependent variable threshold was not significant).
Hypothesis 14b predicted that perceived employability would be negatively related to
support for change. As shown in Table 7, perceived employability was not significantly
correlated with active support for change or passive support for change. As shown in Table
10, higher degrees of perceived employability increased the likelihood of having higher
levels of active support for change (b1 = .678, p < .01; b2 = -.515, p < .01) However, as
shown in Table 11, higher degrees of perceived employability did decrease the likelihood of
having higher levels of passive support for change (b1 = -1.237, p < .01; b2 = -.834, p < .01).
Thus, Hypothesis 14b was supported for only one of the two indicators for support for
change: passive support for change.
Hypothesis 15a suggested that self-confidence for career-relevant learning and
competence development would be negatively related to resistance to change. As can be
seen in Table 7, self-confidence for career-relevant learning and competence development
was not significantly correlated with active resistance to change or passive resistance to
change. The results shown in Tables 8 an 9 indicate that higher levels of self-confidence for
career-relevant learning and competence development increased the likelihood of having
higher levels of active resistance to change (b1 = 1.258, p < .01; b2 = .867, p < .01), but they
were not significantly predictive of levels of passive resistance to change. Thus, Hypothesis
15a was not supported.
Hypothesis 15b was that self-confidence for career-relevant learning and competence
development would be positively related to support for change. As can be seen in Table 7,
self-confidence for career-relevant learning and competence development was not
significantly correlated with active support for change but was positively correlated with
passive support for change (r = .28, p < .01). Furthermore, as shown Tables 10 and 11,
higher degrees of self-confidence for career-relevant learning and competence development
decreased the likelihood of having higher levels of active support for change (b1 = -.584, p <
.10; b2 = -.561, p < .01), but they were not significantly predictive of the levels of passive
support for change. Thus, Hypothesis 15b was not supported.
Hypothesis 16a predicting that affective commitment would be negatively related to
resistance to change was not supported. As shown in Table 7, affective commitment was
126
positively correlated with active resistance to change (r = .26, p < .01) but was not
significantly correlated with passive resistance to change. Furthermore, the levels of
affective commitment were not significantly predictive of the levels of active resistance to
change (see Table 8) or passive resistance to change (see Table 9).
Hypothesis 16b predicted that affective commitment would be positively related to
support for change. This hypothesis was not supported. As shown in Table 7, affective
commitment was not statistically correlated with active support for change but was
positively correlated with passive support for change (r = .23, p < .05). The results also
indicate that the levels of affective commitment were not significantly predictive of the
levels of active support for change (see Table 10) or passive support for change (see Table
11).
Hypothesis 17a, which predicted that trust in management would be negatively related
to resistance to change, was not supported. As can be seen in Table 7, trust in management
was not significantly correlated with active resistance to change or passive resistance to
change. Furthermore, as shown in Tables 8 and 9, higher levels of trust in management
increased the likelihood of having higher levels of active resistance to change (b1 = .434, p <
.10; b2 = .531, p < .01) but were not significantly predictive of the levels of passive
resistance to change.
Hypothesis 17b predicting that trust in management would be positively related to
support for change was not supported. As shown in Table 7, trust in management was
positively correlated with active support for change (r = .27, p < .05) and passive support
for change (r = .41, p < .01). However, the levels of trust in management were not
significantly predictive of the levels of active support for change (see Table 10) or passive
support for change (see Table 11).
Hypothesis 18a predicted that perceptions of colleagues’ resistance to change would
be positively related to resistance to change, and be negatively related to support for change.
As illustrated in Table 7, a perception of colleagues’ resistance to change was positively
correlated with active resistance to change (r = .28, p < .01) and passive resistance to
change (r = .31, p < .05). However, it was not significantly correlated with active support
for change or passive support for change. As shown in Tables 8 and 9, higher degrees of
perceptions of colleagues’ resistance to change increased the likelihood of having higher
levels of active resistance to change (b1 = .547, p < .05; b2 = .785, p < .01), but they were
not significantly predictive of the levels of passive resistance to change. Further, the degrees
of perceptions of colleagues’ resistance to change were not significantly predictive of the
levels of active support for change (see Table 10) or passive support for change (see Table
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11). Thus, Hypothesis 18a was supported for only one of the four indicators for reactions to
change: active resistance to change.
Finally, Hypothesis 18b predicted that perceptions of colleagues’ support for change
would be negatively related to resistance to change, and be positively related to support for
change. As shown in Table 7, a perception of colleagues’ support for change was not
significantly correlated with active resistance to change or passive resistance to change.
However, it was positively correlated with active support for change (r = .43, p < .01) and
passive support for change (r = .40, p < .05). The regression results shown in Tables 8 and 9
suggest that higher levels of perceptions of colleagues’ support for change decreased the
likelihood of having higher levels of active resistance to change (b1 = -.803, p < .01; b2 = -
.766, p < .01) and passive resistance to change (b1 = -.905, p < .01; b2 = -1.168, p < .01). On
the contrary, the results shown in Tables 10 and 11 indicate that higher levels of perceptions
of colleagues’ support for change increased the likelihood of having higher levels of active
support for change (b1 = .689, p < .01; b2 = 1.036, p < .01; note that one parameter of
dependent variable threshold was not significant), but they decreased the likelihood of
having higher levels of support for change (b1 = -1.252, p < .01; b2 = -.658, p < .01). Thus,
Hypothesis 18b was supported for three of the four indicators for reactions to change: active
resistance to change, passive resistance to change, and active support for change.
5.2.4. Discussion of Study 2
As with Study 1, the purpose of Study 2 was to extend our understanding of the
relationships between perceptions and/or attitudes and reactions to change in an
environmental context of privatization, where many, if not most, of the employees are likely
to be under pressure to radically transform themselves should the stated-owned enterprise
go IPO. Toward this end, I examined perceptions and/or attitudes and reactions of
employees in one state-owned enterprise in Thailand to a pending decision of becoming a
publicly listed company in the Stock Exchange of Thailand that will fundamentally and
significantly alter several aspects of the organization.
Important aspects of Study 2 are that (1) it examined a relatively large set of predictors
and outcomes variables, (2) it received a relatively high response rate (44.8%) to the survey,
and (3) it offered insights about employees’ reactions to change in the context of a
privatization at a large state-owned enterprise in Thailand where research on organizational
change remains extremely sparse. Before going further with this discussion, two important
cautions to the interpretation of the findings must be made. First, it must be noted that, as
with Study 1, it was not possible to control for the effects of age, education, gender and
other control variables for the multinomial ordered probit models due predominantly to a
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relatively small sample size (n = 197). Second, it is also important to note that for the
purpose of conducting the multinomial ordered probit regressions, measurement scales of
both dependent and independent variables were recoded.
In contrast to the results of Study 1, the findings in Study 2 indicate that some
perceptions and/or attitudes were significantly predictive of reactions to change. The pattern
of results lends some empirical support for the core arguments of the conceptual
framework—the perception-based view (PBV) of the employee that deals with the effects
and implications of psychological factors on individuals’ decision-making. Support for the
PBV logic and the research model comes from 17 (fully/partially) supported hypotheses (of
36 hypotheses) I found in Study 2.
The regression results concerning the prediction of employees’ resistance to change
are relatively clear-cut. Consistent with expectations, the findings suggest that higher levels
of perceived participation in decision-making (H3a), perceived need for change (H4a),
perceived change in power (H8a), perceived change in status (H9a), perceptions of
colleagues’ resistance to change (H18a), and perceptions of colleagues’ support for change
(H18b) decreased the likelihood of having higher levels of active resistance to change.
Hypotheses related to the relationships between perceptions about change processes
and passive resistance to change were also supported by the data. Specifically, the findings
suggest that higher levels of perceived organizational support (H1a), perceived procedural
justice (H2a), perceived participation in decision-making (H3a), perceived need for change
(H4a), attitudes towards organizational change decreased the likelihood of having higher
levels of passive resistance to change. Moreover, some hypotheses concerning the
relationships between perceptions about actual and expected consequences of privatization
and passive resistance to change were supported. The results also indicate that perceptions
of higher degrees of pride resulting from the privatization (H8a), perceptions of higher
degrees of status resulting from the privatization (H9a), job satisfaction (H11a), and job
security (H12a) decreased the likelihood of having higher levels of passive resistance to
change. However, hypotheses related to perceptions about employees’ ability were not
supported. Nevertheless, a perception about colleagues’ support for change did in fact
decrease the likelihood of having higher levels of passive resistance to change.
The results concerning the prediction of employees’ support for change are not clear-
cut. That is, concerning the prediction of employees’ active support for change, only five
hypotheses were supported. The results indicate that higher levels perceived organizational
support (H1b), perceived need for change (H4b), perceived change in power (H8b),
perceived change in status (H9b), and perceptions of colleagues’ support for change
increased the likelihood of having higher levels of active support for change.
129
The results also indicate that only three hypothesized relationships between
perceptions and passive support for change were supported. That is, higher levels of fear of
known consequences of a change (H6b), fear of unknown consequences of a change (H7b)
decreased the likelihood of having higher levels of passive support for change.
Like Study 1, the results in Study 2, though not supportive of some hypotheses, reveal
some interesting relationships. First, there is an observable inverse relationship between the
levels of perceived organizational support and the levels of passive support for change
because the results indicate that higher levels of perceived organizational support decreased
the likelihood of having higher levels of passive support for change. In the same vein,
higher levels of perceived participation in decision-making regarding privatization
decreased the likelihood of having higher levels of passive support for change. Similarly,
greater degrees of perceived need for change decreased the likelihood of having higher
levels of passive support for change.
The results also indicate that higher degrees of fear of known consequences of
privatization did in fact decrease the likelihood of having higher levels of active resistance
to change, passive resistance to change, and active support for change. In the same vein,
higher degrees of fear of unknown consequences of privatization decreased the likelihood of
having higher levels of active resistance to change, passive resistance to change, and active
support for change. Consistent with the results of Study 1, this is certainly a surprise as it
demonstrates that the commonsense belief that fear of known and/or unknown consequences
of a change will promote employees’ resistance to change is now known to be (e.g., Morris
and Raben, 1995; Mabin et al., 2001), is not correct.
The findings indicate that higher levels of power resulting from the privatization
decreased the likelihood of having higher levels of passive support for change. Evidence
also shows that higher levels of status resulting from the privatization decreased the
likelihood of having higher levels of passive support for change. The findings also show that
the likelihood of having higher levels of active resistance to change and passive resistance
to change increased with higher levels of pride resulting from the privatization. In contrast,
the likelihood of having higher levels of active support for change decreased with higher
levels of pride resulting from the privatization. Taken collectively, one plausible explanation
to these surprising results is that employees may not have viewed the indicators for passive
support for change as support for change. As can be seen in Table 2, there is an observable
indication that active support for change was negatively and significantly correlated with
passive support to change.
The results also indicate that higher degrees of perceived employability decreased the
likelihood of having higher levels of active resistance to change and passive resistance to
130
change. Moreover, higher degrees of perceived employability increased the likelihood of
having higher levels of active support for change. One plausible explanation to this pattern
of results is that employees may not want to search for a new job even if they believed they
would be able to obtain a job elsewhere; thus, they provided low levels of resistance to
change and higher levels of active support for change.
The results also indicate that higher levels of self-confidence in learning and
development increased the likelihood of having higher levels of active resistance to change
and decreased the likelihood of having higher levels of active support for change. One
plausible interpretation on this pattern of findings is that employees may not be willing to
learn new things even if they believed that they were capable to do so. Thus, they did not
support the privatization. These results may also suggest that inertia exists within
individuals. Further, the finding that higher degrees of trust in management increased the
likelihood of having higher levels of active resistance to change is a surprise. My
interpretation on this finding is that though employees may trust top management, they did
not relate their trust in management to the privatization and, thus, resisted the change.
The finding that greater degrees of perceptions of colleagues’ support for change did
decrease the likelihood of having higher levels of passive support for change is inconstant
with expectations. Given the fact that greater degrees of perceptions that colleagues’ support
for change increased the likelihood of having higher levels of active support to change and
the negative and significant correlation existed between active support for change and
passive support for change, this finding is not a real surprise.
Finally, aside from its empirical contribution, Study 2 also extends our understanding
of the effects of perceptions and/or attitudes on employees’ reactions to change in the
context of privatization by identifying its underpinnings in perception-based view
perspective. While the notion that humans’ perceptions have the effects on their decisions
and behaviors is not a new perspective in the human resource management literature, it has
not been widely applied to the study of employees’ reactions to organizational change, at
least not in the context of Thailand. Study 2 proposed and tested the concept of perceptions-
based prediction of humans’ decisions and behaviors, in line with Simon’s (1978, 1979) call
to incorporate a ‘differentiated approach to understanding humans’ rationality’.
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5.3. General Discussion
5.3.1. Key Contributions of the Dissertation
In this research, the new perspective on employees’ reactions to change was introduced.
Indeed, this dissertation was conducted in an attempt to improve the understanding of how
perceptions and/or attitudes relate to employees’ reactions to change. In Study 1, it was
found that perceptions and attitudes were not significantly predictive of reactions to change.
However, the results of Study 2 indicate that the relationships existed between perceptions
and/or attitudes and reactions to change. Table 12 provides a summary of regressions results
for hypotheses in Study 1 and Study 2. Taken collectively, this dissertation reinforces the
view that perceptions and/or attitudes explain and predict reactions to change. It contributes
five important findings to the theory and research on organizational change.
First, perceptions concerning organizational change processes are significantly
predictive of employees’ reactions to change. In support of Hypothesis 1a in Study 2,
employees who perceived greater organizational support had lower levels of passive
resistance to change and higher degrees of active support for change. These findings support
prior research suggesting that perceptions of organizational support are related to work-
related attitudes and outcomes (Eisenberger, et al., 1986; Eisenberger et al., 1990).
With regard to perceptions of procedural justice, I found that perceived procedural
justice of privatization explains and predicts only passive resistance to change: that is,
employees who perceived greater degrees of procedural justice regarding privatization had
lower degrees of passive resistance to change. The fact that perceived procedural justice was
not significantly predictive of active resistance to change, active support for change, and
passive support for change is contradictory to the justice literature (e.g., Kim and
Mauborgne, 1993; Brockner et al., 1994; Korsgaard et al., 2002).
Further, in support of Hypothesis 3a, perceived participation in decision-making
concerning the privatization decreased the likelihood of having higher levels of active
resistance to change. This finding is valuable as it demonstrates that employees may relate
the extent to which they could influence outcomes of a change to their active resistance to
change. Thus, these findings are in harmony with the literature on participation in decision-
making (e.g., Ruh et al, 1975; Erez et al., 1985; Allen et al., 2003).
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Table 12: Summary of Results for Hypotheses in Study 1 and Study 2
Hypotheses Expected
Sign
Study 1 Study 2
H1a: Perceived Organizational Support - Not supported Partially supported
H1b: Perceived Organizational Support + Not supported Partially supported
H2a: Perceived Procedural Justice - Not supported Partially supported
H2b: Perceived Procedural Justice + Not supported Not supported
H 3a: Perceived Participation in Decision-Making - Not supported Supported
H 3b: Perceived Participation in Decision-Making + Not supported Not supported
H4a: Perceived Need for Change - Not supported Supported
H4b: Perceived Need for Change + Not supported Partially supported
H5a: Attitude towards Organizational Change - Not supported Partially supported
H5b: Attitude towards Organizational Change + Not supported Not supported
H6a: Fear of Known Consequences of a Change + Not supported Not supported
H6b: Fear of Known Consequences of a Change - Not supported Partially supported
H7a: Fear of Unknown Consequences of a Change + Not supported Not supported
H7b: Fear of Unknown Consequences of a Change - Not supported Partially supported
H8a: Perceived Change in Power - Not supported Not supported
H8b: Perceived Change in Power + Not supported Partially supported
H9a: Perceived Change in Status - Not supported Partially supported
H9b: Perceived Change in Status + Not supported Partially supported
H10a: Perceived Change in Pride - Not supported Not supported
H10b: Perceived Change in Pride + Not supported Not supported
H11a: Job Satisfaction - Not supported Partially supported
H11b: Job Satisfaction + Not supported Not supported
H12a: Job Security - Not supported Partially supported
H12b: Job Security + Not supported Not supported
H13a: Job Motivation - Not supported Not supported
H13b: Job Motivation + Not supported Not supported
H14a: Perceived Employability + Partially supported Not Supported
H14b: Perceived Employability - Not supported Partially supported
H15a: Self-Confidence for Learning & Development - Not supported Not supported
H15b: Self-Confidence for Learning & Development + Not supported Not supported
H16a: Affective Commitment - Not supported Not supported
H16b: Affective Commitment + Not supported Not supported
H17a: Trust in Management - Not supported Not supported
H17b: Trust in Management + Not supported Not supported
H18a: Colleagues’ Resistance to Change + / - Not supported Partially supported
H18b: Colleagues’ Support for Change - / + Not supported Partially supported
Notes: For H18a: a “+” sign for resistance to change; a “-” sign for support for change.
For H18b: a “-” sign for resistance to change; a “+” sign for support for change.
133
The extent to which organizational change (e.g., the privatization in Study 2) was seen as
needed was predictive of the levels of active resistance to change, passive resistance to
change and active support for change. However, it is noteworthy that higher levels of
perceived need for change decreased the likelihood of having higher levels of passive
support for change in both studies 1 and 2. Nevertheless, the findings reported here offer
support for the argument that perceived need for change is associated with employees’
reactions to change. The finding that positive attitudes towards organizational change
decreased the likelihood of having higher levels of passive resistance to change offers new
empirical insights into how attitudes towards organizational change play a role in
employees’ reactions to change and is promising for practitioners. Clearly, management can
moderate the negative consequences of organizational change by promoting employees’
positive attitudes towards organizational change prior to initiating a change. While the
results show that several perceptions concerning change processes were significantly
predictive of reactions to change, one caution to these findings is that the data were gathered
at the same point in time. Therefore, it was not possible to determine causality.
Nevertheless, these findings lend strong support for the notion that how employees are
treated during organizational changes has implications for employees’ reactions to change.
Second, perceptions concerning actual and expected consequences of a change explain
and predict employees’ reactions to change. As expected, fear of known consequences of a
change decreased the likelihood of having higher levels of passive support for change.
However, this finding must be tempered by the fact that evidence also shows that employees
who had higher levels of fear of known consequences of a change had lower degrees of
active resistance to change, lower degrees of passive resistance to change, and higher
degrees of active support for change. In addition to these unexpected effects of fear of
known consequences of a change, fear of unknown consequences of a change also had the
unexpected effects. That is, inconsistent with Hypotheses 7a and 7b, employees who had
higher levels of fear of unknown consequences of a change had lower degrees of active and
passive resistance to change and higher degrees of active support for change. It is
noteworthy that higher levels of fear of unknown consequences of a change decreased the
likelihood of having levels of passive support for change. Clearly, these findings do not
support, or indeed weaken the argument made in prior studies (e.g., Judson, 1991; Dubrin
and Ireland, 1993; Kotter, 1995; Galpin, 1996; Kotter and Cohen, 2002) that fear causes
resistance to change.
Moreover, as mentioned in the discussion leading up to Hypotheses 8a and 8b,
perceptions of greater power resulting from the change decreased the likelihood of having
higher levels of active resistance to change, passive resistance to change, and active support
134
for change. This was not true, however, with regard to passive support for change, as higher
levels of power resulted in lower levels of passive support for change. Nevertheless, it is
still possible to draw relatively firm conclusions about perceived change in power as the
findings in this dissertation begin to address the relationship between perceived changes in
power and reactions to change.
Further, the extent to which changes in status resulting from a change was perceived
by employees as positive or negative was significantly predictive of the levels of active
resistance to change, passive resistance to change, and active support for change. These
findings lend strong support for prior studies that negative changes in status will contribute
to resistance to change (e.g., Smith, 1982; Spreitzer and Quinn, 1996). Interestingly, as
evidenced by the analyses, employees who perceived greater levels of pride resulting from a
change had higher levels of active resistance to change, higher levels of passive resistance to
change, and a lower degree of active support for change. Clearly, these findings do not
support Hypotheses 10a and 10b. However, the findings may suggest a new perspective
regarding how employees react to changes in their pride.
Moreover, as hypothesized, higher levels of job satisfaction decreased the likelihood
of having higher levels of passive resistance to change, but it was not significantly
predictive of any other reactions to change. Thus, the findings in this dissertation suggest
that job satisfaction is not a strong predictor of reactions to change. Also, as hypothesized,
higher levels of job security decreased the likelihood of having higher levels of passive
resistance to change; however, the findings do not reveal and significant effect of job
security on other reactions to change. In contrast to Davy et al. (1997) who suggested that
any perceived threat to the job security represents a possible violation of the informal or
psychological contract, and that leads to withdrawal cognitions, the findings here suggest
that the effect of job security was not significantly associated with reactions to change.
Interestingly, job motivation was not significantly predictive of any of the reaction
variables. This finding is valuable as it demonstrates that the extent to which employees are
motivated to perform their job is irrelevant to their reactions to change. However, the
conclusions drawn from these analyses must be treated with caution since only extrinsic
facet of job motivation was measured.
Third, perceptions concerning employees’ ability are significantly predictive of
employees’ reactions to change. Though employees who perceived higher levels of their
employability had lower degrees of passive support for change (consistent with Hypothesis
14b), they also had lower degrees of active resistance to change, lower degrees of passive
resistance to change, and higher degree of active support for change. Clearly, these results
are inconsistent with Hypothesis 14a and 14b by having different signs of regression
135
coefficients. Nevertheless, as mentioned in the discussion leading to Hypotheses 14a and
14b that the main focus of these hypotheses was to determine whether perceived
employability has direct relationships with employees’ reactions to change, these findings
provide suggestive evidence that perceived employability is indeed significantly predictive
of employees’ reactions to change.
Fourth, perceptions concerning employees’ relationships with the organization and
colleagues explain and predict employees’ reactions to change. Consistent with Hypothesis
18a, greater degrees of perceptions of colleagues’ resistance to change increased the
likelihood of having higher levels of active resistance to change. Further, in support of
Hypothesis 18b, perceptions of colleagues’ support for change decreased the likelihood of
having higher levels of active resistance to change and passive resistance to change and
increased the likelihood of having higher levels of active support for change. One caveat to
these findings is that perceptions of colleagues’ support for change decreased the likelihood
of having higher levels of passive support for change. In sum, the findings provide some
empirical insight into the effects of social influence on employees’ reactions to change. One
the one hand, perceptions of colleagues’ resistance to change seem to enhance the likelihood
that employees react negatively to the change; on the other hand, perceptions of colleagues’
support for change seem to enhance the likelihood that employee react positively to the
change.
Finally, the overall finding in this dissertation supports the notion that how employees
perceive or feel during organizational change has significant implications for their
decisions. The findings reported here are relatively in harmony with expectations drawn
predominantly from the perception-based view of the employee, on the one hand, and the
social exchange theories and norm of reciprocity71, on the other hand. The perception-based
view explains variations in decision and/or behavior differences among employees in the
same setting. From the perception-based view perspective, employees primarily rely on the
use of perceptions, attitudes, or emotions for a purpose of selecting a choice in pursuit of
their goals. Consistent with the perception-based-view perspective, as evidenced by
analyses in Study 1, employees appeared not to arrive at expected reactions to change: that
is, the results suggest that perceptions and/or attitudes were not significantly predictive of
employees’ reactions to change. This finding is valuable because it demonstrates that
employees are not always rational at making decisions. Recall that I have argued that
71 Note that I mention here only two of several theories that had been used during a discussion leading to hypotheses.
Though several other theories deserve mention, these two have frequently been extended to argue for many
hypotheses in this dissertation.
136
humans need not necessarily make rational decisions. This notion was initially aimed to
counter arguments and assumptions made implicitly or explicitly in other studies that human
always make rational decisions.72 In contrast, the results reported in Study 2 suggest that
certain perceptions and attitudes were significantly predictive of employees’ reactions to
change. Therefore, it is possible to draw relatively firm conclusions about how and, more
importantly, which perceptions and attitudes explain and predict employees’ reactions to
change. From the social exchange theories and norm of reciprocity perspective, the
significant relationships found in Study 2 are attributable to the social influence (e.g., the
beliefs people have about how to interact with others in social groups) on employees. In
sum, as the perception-based view is considerably supported, the logic of the perception-
based view and findings in this dissertation would appear to be fertile for future study.
5.3.2. Limitations to this Dissertation
A number of limitations to this dissertation deserve mention. One limitation is the relatively
small overall sample size (n = 86 for Study 1; n = 197 for Study 2). Due to the relatively
small population size in Study 1 (n = 120), the high response rate (91%) to the survey in
Study 1 could only allow for simple data analysis (e.g., a regression analysis without any
control variables). Though the relatively high response rate (44.8%) to the survey in Study 2
and the relatively low rate of missing value in some returned questionnaires, only 39.4
percent (197/500) of employees provided completed data. I acknowledge that this call into
questions of the limitations to the sequences and methods of analysis (e.g., the sample sizes
were not sufficient for the inclusion of control variables in the ordered probit models) and
the representativeness of the portion of the sample used (in relation to the whole population)
in the analyses. However, as discussed in the research methodology section, the final
samples used in the analyses were very similar to other subsets of employees (respondents
and non-respondents) in both studies. Moreover, the sample used in both studies was
relatively large in relation to population: that is, the sample used in Study 1 accounted for
71.67 percent (86/120) of the total population; and the sample used in Study 2 accounted for
21.89 percent (197/900) of the total population of locations (four offices) where the sample
was drawn. Thus, I am cautiously optimistic that my results are replicable in other similar
settings.
A second limitation is that all data is self-reported. Thus, there was no way to separate
method variance from true score variance. It is possible that method variance bolstered or
weakened the magnitude of relationships between predictors and outcomes. To reduce the
72 For more information on a discussion of rationality, see Section 2.5 and 3.1 in this dissertation.
137
possibility of mono-method bias, future studies should aim to incorporate other methods
(e.g., direct observations) so as not to rely solely on subjects’ reports.
A third limitation is concerned with the internal consistency reliability for the variable
scales. While I attempted to accommodate a large set of variables to be examined, I used at
most three items to measure any of variables. At first glance, all variables studied could then
be measured in one questionnaire. However, the lack of a more comprehensive measure of
variables dealing with perceptions, attitudes and behaviors may explain why levels of
internal consistency (e.g., reliability scales) were low. Moreover, it must be noted that many
variables were measured with newly developed measures since no prior studies have
examined them before. Consequently, it is possible that the aggregate indicators, which
were derived from the newly developed measures, may not be a truly correct measure of
those variables, implying that the conclusions drawn from these regression results must be
treated with caution. However, I argue that although levels of internal consistency among
measures for variables in Study 2 were low, they were not entirely attributable to the use of
new measures due to the fact that there is observable evidence that there were low levels of
the internal consistency for certain variable scales adopted from prior studies.
A four limitation is that because data in this dissertation is cross-sectional. Thus, I am
not able to make causal inferences regarding predictor/outcome relationships. As Greenberg
and Barling (1999) have suggested, future studies should aim for longitudinal designs so as
to enable true causal inferences.
The above limitations being acknowledged, it is relevant to mention the strengths of
the dissertation. The first and foremost obvious strength is that this dissertation examined a
large and more varied set of variable in one study. In comparison with previous studies
where examined a relatively smaller set of variables, the questionnaire surveys in this study
covered the total of 66 measures for 19 variables. This is crucial because the results reveal
that from a broad range of perceptions tested, which perceptions are significantly predictive
of employees’ reactions to change. Another strength deserves mention is the methods of
analyses used in this dissertation. As emphasized in the research methodology section, this
dissertation conducted the relatively most appropriate regression models in view of the data
available in this study: that is, the ordered probit models, rather than the ordinary regression
models, were conducted to analyze the data where both dependent variables and
independent variables are ordinal (discrete and ordered) in nature. From the methodological
(e.g., statistical) point of view, it is important to choose the most appropriate data analysis
procedures for the data so as to be able to draw firm conclusions. Up to this point, I am
cautiously optimistic that this dissertation at least appeared to meet this requirement.
138
5.3.3. Implications and Directions for Future Research
In view of these results, what can we then say about the implications for future research?
There are several directions I would like to see taken by future research. First, my focus in
this current dissertation was on the direct relationships between predictors and outcomes at
one point in time. Therefore, it was not possible to examine causality. Later work should
aim for longitudinal study so as to draw firm conclusions about true causal inferences.
Second, in the same discussion, I would like to recommend that future study be
directed to examine indirect relationships among variables. As the main focus of this study
was on exploring whether direct relationships between predictors and outcomes existed,
which suggesting that they existed, future study should aim to emphasize on examining the
potential moderating effects of certain variables. For example, it would be interesting to see
if trust in management has moderating effects on the predictors of employees’ perceived
need for change and reactions to change.
Third, I would also suggest that future study should focus on not only confirming
whether these results would be replicable in other similar settings but also determining
whether these results would be replicable in the different settings. The reason is that since
the results in Study 1 did not yield significant predictors/outcomes relationships but the
results in Study 2 did, these contradictory findings are relatively susceptible and suggest that
context differences may exert certain effects on the magnitude of relationships. As many of
hypotheses and arguments in this dissertation can be extended to other forms of
organizational change, it is worthy of additional examination to determine whether
hypotheses investigated here would be endorsed in other contexts. Therefore, I recommend
that future work be directed to more important extensions. For example, it would be
interesting to see if fear of known consequences of a change and consequences reactions
differ in level or form across different archetypes of organizational change.
Finally, concerning the method of analyses, as demonstrated in this dissertation, I
would like to call for attention to the nature of data and the appropriate method of analyses.
I recommend that future work that analyses ordinal data be encouraged to adopt regression
models that are capable of properly treating dependent variables that are measured on an
ordinal scale. For example, the ordered probit models and/or multinomial ordered probit
models would be more appropriate as an analytical tool to analyze the ordinal data. From
the methodological point of view, this is very important because other regression models
would not account for the abovementioned characteristics and the use of such regression
models would violate the underlying assumptions of such models.73
73 For a more detailed discussion, see the research methodology section.
139
5.3.4. Implications and Directions for Practice
As discussed earlier, the main focus of this dissertation was on examining what perceptions
and/or attitudes exert an influence on employees’ reactions to change. As some findings in
this dissertation were consistent with the expectations, this lends some useful insights to
practitioners in areas of organizational change, especially to management consultants. In
sum, two important insights for practice deserve mention.
First, this dissertation informs a perspective that advocates perception and/or attitude
identification to predict employees’ reactions to change, such as resistance to change and
support for change. As certain perceptions and attitudes were significantly predictive of
employees’ reactions to change, others were not. The perception-based view suggests that
this occurred because humans do not always make rational choices. For example, the
commonsense belief that fear of known and/or unknown consequences of a change will
promote employees’ resistance to change is now known to be (e.g., Morris and Raben,
1995; Mabin et al., 2001), is incorrect. The finding that employees do not often arrive at
rational decisions is valuable for firms or managers as it demonstrates that the current
logical thinking they may have about their decisions (e.g., from managers’ point of view,
their decision may be considered highly rational; therefore, they believe that employees
should use the same logical thinking and, thus, consider their decision rational and
acceptable) will unlikely be applicable when predicting employees’ reactions to change.
This occurs because employees may use their perceptions, and perhaps, another way of
thinking when reacting to change. However, the potential benefits of identifying employees’
perceptions and attitudes during organizational change and predicting their future reactions
are considerable. Most notably, this tool can be very useful for identifying corrective actions
to minimize resistance to change and promote support for change. This is because firms that
know how their employees perceive organizational change will have an opportunity to
devise some activities to modify or align employees’ perceptions and attitudes to the ones
desired. Greater levels of support for change and/or lower levels of resistance to change will
certainly increase the likelihood of having a successful organizational change.
Similarly, for those providing advice to firms on change management strategies or
organizational change in general, the findings of this dissertation may help in showing that
they should systematically monitor employees’ perceptions and attitudes during
organizational change projects. With a perceptions-detection mechanism in place,
consultants will be able to understand how employees feel, and have an opportunity to
devise change management strategies that will change employees’ perceptions as the ones
desired in a timely manner. This will certainly help increase the likelihood that change
projects will meet their objectives, and deliver the desired outcomes.
140
6. Conclusions
The theoretical arguments and empirical findings in this dissertation appear to offer new
insights into how perceptions and/or attitudes influence employees’ resistance to and
support for change. Overall, this dissertation has built on diverse streams of research from
the fields of organizational change, strategic management, sociology, and psychology. A
basic tenet of the present study on employees’ perceptions and/or attitudes and resistance to
and support for change was that the employees determine their course of action in response
to their perceptions, interpretation and understanding of the event, i.e., organizational
change. Consequently, this dissertation proposed 18 explanatory variables that were
expected to be related to employees’ resistance to and support for change. These factors
were classified into four groups or dimensions: (1) factors concerning change processes; (2)
factors concerning real and expected consequences of change; (3) factors concerning an
employee’s ability; and (4) factors concerning an employee’s relationship with the firm and
colleagues. It must be noted that the number of variables examined in this dissertation is
limited predominantly due to two key reasons: theoretical aspect (the greater the number of
variables in the model, the less the degree of parsimony of the model), and practical aspect
(the greater the number of variables in the model, the lower the response rates to the survey.
To test the hypothesized relationships proposed in this dissertation, two empirical studies
were conducted: one in the context of the downsizing at the private school in Thailand;
another in the context of the privatization at one stated-owned enterprise in Thailand.
This dissertation extends the idea of bounded-rationality (Simon, 1978, 1979) by
suggesting that perceptions and/or attitudes determine the levels and, perhaps, choices of
reactions to organizational change. To minimize resistance to change and promote support
for change, the understanding of employees’ perceptions and attitudes during change
processes is therefore required. In support of this perspective, the findings indicate that
variations in certain perceptions and/or attitudes explain and predict differences in levels of
resistance to and support for change. Indeed, of the 18 predictors tested, all but job
motivation were significantly predictive of at least one of the four categories of reactions to
change.
In conclusion, the findings are of theoretical importance as they increase our
knowledge concerning the predictors of employees’ reactions to organizational change.
Clearly, we now realize which perceptions and/or attitudes exert an effect on employees’
resistance to and support for change. Precisely, the findings imply that levels of certain
perceptions and/or attitudes would be likely to increase or decrease the likelihood of having
141
higher levels of active and/or resistance to change, and active and/or passive support for
change. These findings also provide a useful starting point for considering the prevention of
employees’ resistance to change and the promotion of employees’ support for change.
However, any attempts to use perceptions and attitudes as predictors of reactions to change
must be sensitive to the context in which organizational change occurs, as evidenced by the
findings that in one setting (as in Study 2), perceptions were significantly predictive of
reactions to change, whereas in another setting (As with Study 1), they were not. This
caveat to the findings is important as it demonstrates that we should always take the context
into consideration when using the framework suggested in this dissertation. Nevertheless,
the findings in this dissertation add to the growing belief that certain perceptions and
attitudes may be at work in determining employees’ decisions and behaviors. Given the fact
that most firms both in Thailand and in many other countries initiate certain types of change
from time to time and the frequency of engaging in organizational change continues to
increase, more research in this area is warranted. It is hoped that the findings presented here
will encourage researchers to continue examining the perceptions-decisions/behaviors
relationship and practitioners to apply knowledge created in this dissertation for the
improvement of their change management practice.
142
References
Adams, J. S. 1965. Inequity in social exchange. In L. Berkowitz (Ed.), Advances in
experimental social psychology, Vol. 2: 267–299. New York, NY: Academic Press.
Adler, P. 2001. Market, hierarchy, and trust: The knowledge economy and the future of
capitalism. Organizational Science, 12(2): 214-234.
Agócs, C. 1997. Institutionalized resistance to organizational change: Denial, inaction and
repression. Journal of Business Ethics, 16: 917-931.
Alderfer, C. P. 1986. An intergroup perspective on group dynamics. In J. W. Lorsch (Ed.),
Handbook of organizational behavior: 190-222. Englewood Cliffs, NJ: Prentice-Hall.
Allen, D. G., Shore, L. M., & Griffeth, R. W. 2003. The role of perceived organizational
support and supportive human resource practices in the turnover process. Journal of
Management, 29(1): 99-118.
Allen, N. J., & Meyer, J. P. 1990. The measurement and antecedents of affective,
continuance, and normative commitments to the organization. Journal of Occupational
Psychology, 63: 1-8.
Allport, G. W. 1935. Attitudes. In C. Murchison (Ed.), Handbook of Social Psychology:
798-844. Worcester, MA: Clark University Press.
Allport, G. W. 1954. The nature of prejudice. Reading, MA: Addison-Wesley.
Alvarez, R. M., & Nagler, J. 1998. When politics and models collide: Estimating models of
multiparty elections. American Journal of Political Science, 42(1): 55-96.
Anderson, C. R., & Paine, F. T. 1975. Managerial perceptions and strategic behavior.
Academy of Management Journal, 18: 811–23.
Appelbaum, S. H., Everard, A., & Hung, T. S. L. 1999. Strategic downsizing: Critical
success factors. Management Decision, 37(7): 535-552.
Argyris, C. 1962. Interpersonal competence and organizational effectiveness. Homewood,
IL: Dorsey Press.
Argyris, C. 1990. Overcoming organizational defenses: Facilitating organizational
learning. Boston, MA: Allyn and Bacon.
Argyris, C. 1999. On organizational learning. 2nd ed. Oxford: Blackwell.
Argyris, C., & Schön, D. A. 1978. Organizational learning: A theory of action perspective.
Reading, MA: Addison-Wesley.
Argyris, C., & Schön, D. A. 1996. Organizational learning II: Theory, method, and
practice. Reading, MA: Addison-Wesley.
143
Armenakis, A. A., Harris, S. G., & Mossholder, K. W. 1993. Creating readiness for
organizational change. Human Relations, 46: 681-703.
Ashby, F. G., & Gott, R. 1988. Decision rules in the perception and categorization of
multidimensional stimuli. Journal of Experimental Psychology: Learning, Memory and
Cognition, 14: 33-53.
Ashford, S., Lee, C. & Bobko, P. 1989. Content, causes, and consequences of job insecurity:
A theory-based measure and substantive test. Academy of Management Journal, 32: 803-
829
Ashkanasy, N. M., Härtel, C. E. J., & Daus, C. S. 2002. Diversity and emotion: The new
frontiers in organizational behavior research. Journal of Management, 28(3): 307-338.
Bandura, A. 1977. Social learning theory. Englewood Cliffs, NJ: Prentice-Hall.
Barber, P. J., & Legge D. 1976. Perception and information. London: Methuen.
Barker, V. L., & Duhaime, I. M. 1997. Strategic change in the turnaround process: Theory
and empirical evidence. Strategic Management Journal, 18(1): 13-38.
Barney, J. B. 1991. Firm resources and sustained competitive advantage. Journal of
Management, 17: 99-120.
Barney, J. B., & Hansen, M. H. 1994. Trustworthiness as a source of competitive advantage.
Strategic Management Journal, Winter Special Issue, 15: 175-190.
Barney, J. B., & Zajac, E. J. 1994. Competitive organizational behavior: Toward an
organizationally-based theory of competitive advantage. Strategic Management Journal,
Winter Special Issue, 15: 5-9.
Bartlett, F. C. 1932. Remembering: A study in experimental and social psychology.
Cambridge, UK: Cambridge University Press.
Bartunek, J. M., & Moch, M. K. 1987. First-order, second-order, and third-order change and
organization development interventions: A cognitive approach. Journal of Applied
Behavioral Science, 23: 483-500.
Bartunek, J. M., Lacey, C. A., & Wood, D. R. 1992. Social cognition in organizational
change: An insider-outsider approach. Journal of Applied Behavioral Science, 28: 204-
223.
Bass, B. M. 1990. Bass & Stogdill's handbook of leadership: Theory, research, and
managerial applications. 3rd ed. New York, NY: Free Press.
Beach, L. R. 1990. Image theory: Decision making in personal and organizational contexts.
Chichester, UK: Wiley.
Beach, L. R. 1993. Making the right decision: Organizational culture, vision, and planning.
Englewood Cliffs, NJ: Prentice-Hall.
144
Beer, M. 1980. Organization change and development: A systems view. Santa Monica, CA:
Goodyear.
Beer, M., & Eisenstat, R. A. 1996. Developing and organization capable of implementing
strategy and learning. Human Relations, 18: 523-545.
Beer, M., Eisenstat R. A., & Spector, B. 1990. Why change programs do not produce
change. Harvard Business Review, 68(6): 158-166.
Bennis, W. G. 1966. Changing organizations. New York, NY: McGraw-Hill.
Berelson, B., & Steiner, G. A. 1964. Human behavior: An inventory of scientific findings.
New York, NY: Harcourt, Brace & World.
Bibeault, D. B. 1982. Corporate turnaround: How manager turns lowers into winner. New
York, NY: McGraw-Hill.
Blau, P. M. 1964. Exchange and power in social life. New York, NY: Wiley.
Boeker, W. 1989. Strategic change: The effects of founding and history. Academy of
Management Journal, 32: 489-515.
Bollen, K. 1989. Structural equations with latent variables. New York, NY: Wiley.
Borooah, V. K. 2002. Logit and Probit: Ordered and multinomial models. Thousand Oaks,
CA: Sage.
Bovey, W. H., & Hede, A. 2001. Resistance to organisational change: The role of defence
mechanisms. Journal of Managerial Psychology, 16(7): 534-548.
Brayfield, A., & Rothe, H. 1951. An index of job satisfaction. Journal of Applied
Psychology, 35: 307–311.
Brewer, M. B. 1991. The social self: On being the same and different at the same time.
Personality and Social Psychology Bulletin, 17: 475-482.
Bridges, W. 1980. Transitions: Making sense of life’s changes. Reading, MA: Addison-
Wesley.
Brockner, J., Konovsky, M., Cooper-Schneider, R., Folger, R., Martin, C., & Bies, R. J.
1994. Interactive effects of procedural justice and outcome negativity on victims and
survivors of job loss. Academy of Management Journal, 37: 397–409.
Brooke, P., Russell, D., & Price, J. 1988. Discriminant validation of measures of job
satisfaction, job involvement, and organizational commitment. Journal of Occupational
Psychology, 73(2): 139-145.
Brooks, L. R. 1978. Non-analytic concept formation and memory for instance. In. E. Rosch
& B. B. Lloyd (Eds.), Cognition and categorization, 169-211. Hillsdale, NJ: Erlbaum.
Burke, W., & Litwin, G. 1992. A causal model of organizational performance and change.
Journal of Management, 18: 523-545.
145
Caplan, R. D., Cobb, S., French, J. R. P. Jr., Van Harrison, R. V., & Pinneau, S. R. Jr. 1975.
Job demands and worker health: Main effects and occupational differences.
Washington, DC: US Department of Health, Education, and Welfare.
Castrogiovanni, G. J., Baliga, B. R., & Kidwell. Jr., R. E. 1992. Curing sick businesses:
Changing CEOs in turnaround efforts. Academy of Management Executive, 6(3), 26-41.
Chandler, A. D. 1962. Strategy and structure: chapters in the history of American industrial
enterprise. Cambridge, MA: MIT Press.
Clarke, J., Ellett, C., Bateman, J., & Rugutt, J. 1996. Faculty receptivity/resistance to
change, personal and organizational efficacy, decision deprivation and effective in
research I universities. Paper presented at the Twenty-first Annual Meeting of the
Association for the Study of Higher Education, Memphis, TN, October 31-November 3.
Cobb, A., Woolen, K., & Folger, R. 1995. Justice in the making: Toward understanding the
theory and practice of justice in organizational change and development. Research in
Organizational Change and Development, 8: 386-400.
Coch, L., & French, J. R. P. Jr. 1948. Overcoming resistance to change. Human Relations,
1: 512-532.
Coghlan, D. 1993. A person-centred approach to dealing with resistance to change.
Leadership and Organization Development Journal, 14(4): 10-14.
Conlon, D. E., & Fasolo, P. M. 1990. Influence of speed of third-party intervention and
outcome on negotiator and constituent fairness judgments. Academy of Management
Journal, 36: 7-27.
Cornelius, R. R. 1996. The science of emotion: Research and tradition in the psychology of
emotion. Upper Saddle River, NJ: Prentice-Hall.
Crossan, M. M, & Berddrow, I. 2003. Organizational learning and strategic renewal,
Strategic Management Journal, 24: 1087-1105.
Cyert, R. M., & March, J. G. 1963. A behavioral theory of the firm. Englewood Cliffs, NJ:
Prentice-Hall.
Daft, R. L., & Weick, K. E. 1984. Toward a model of organizations as interpretation
systems. Academy of Management Review, 9: 284-295.
Davis, J. H., Schoorman, F. D, Mayer, R. C., & Tan, H. H. 2000. The trusted general
manager and business unit performance: Empirical evidence of a competitive advantage.
Strategic Management Journal, 21 (5): 563-576.
Davy, J. A., Kinicki, A. J., & Scheck, C. L. 1991. Developing and testing a model of
survivor responses to layoffs. Journal of Vocational Behavior, 38: 302–317.
146
Davy, J. A., Kinicki, A. J., & Scheck, C. L. 1997. A test of job security’s direct and
mediated effects on withdrawal cognitions. Journal of Organizational Behavior, 18(4):
323-349.
Dawson, S. 1996. Analysing organizations. 3rd ed. Houndmills, UK: Macmillan.
Dean, J. W., & Sharfman, M. P. 1996. Does decision process matter? A study of strategic
decision-making effectiveness. Academy of Management Journal, 39(2): 368-396.
Dean, J., Brandes, J., & Dharwadkar, R. 1998. Organizational cynicism. Academy of
Management Review, 23: 341-352.
Dent, E. B., & Goldberg, S. G. 1999. Challenging ‘resistance to change’. The Journal of
Applied Behavioral Science, 35(1): 25-41.
Denzin, N. K. 1978. The research act. New York, NY: McGraw-Hill.
DeWitt, R. L., Trevino, L. K., & Mollica, K. A. The influence of eligibility on employees’
reactions to voluntary workforce reductions. Journal of Management, 24(5): 593-613.
Dirks, K. T., & Ferrin, D. L. 2001. The role of trust in organizational settings. Organization
Science, 12: 450-467.
Dirks, K. T., & Ferrin, D. L. 2002. Trust in leadership: Meta-analytic findings and
implications for research and practice. Journal of Applied Psychology, 87: 611-628.
Donaldson, L. 1987. Strategy and structural adjustment to regain fit and performance: In
defense of contingency theory. Journal of Management Studies, 24: 1-24.
Dorman, C., & Zapf, D. 2001. Job satisfaction: a meta-analysis of stabilities. Journal of
Organizational Behavior, 22(5): 483-504.
Dubrin, A. A., & Ireland, R. D. 1993. Management & Organization. 2nd ed. Cincinnati,
OH: Southwestern College Publishing Company.
Dulebohn, J. H., & Martocchio, J. J. 1998. Employee perceptions of the fairness of work
group incentive pay plans. Journal of Management, 24(4): 469-488.
Einhorn, H. J., & Hogarth, R. M. 1981. Behavioral decision theory: Processes of judgment
and choice. Annual Review of Psychology, 32: 53-88.
Eisenberger, R., Fasolo, P., & Davis-LaMastro, V. 1990. Perceived organizational support
and employee diligence, commitment, and innovation. Journal of Applied Psychology,
75: 51-59.
Eisenberger, R., Huntington, R., Hutchison, S., & Sowa, D. 1986. Perceived organizational
support. Journal of Applied Psychology, 71: 500-507.
Eisenhardt, K. M. 1989. Building theories from case study research. Academy of Management
Review, 14: 532-550.
147
Eisenhardt, K. M., & Zbaracki, M. J. 1992. Strategic decision making. Strategic
Management Journal, 13: 17-37.
Elangovan, A. R, & Lin Xie, Jia. 1999. Effects of perceived power of supervisor on
subordinate stress and motivation: The moderating role of subordinate characteristics.
Journal of Organizational Behavior, 20(3): 359-373.
Ellis, A., & Harper, R. A. 1975. A new guide to rational living. North Hollywood, CA:
Wilshire Book Company.
Erez, M., Earley, P. C., & Hulin, C. L. 1985. The impact of participation on goal acceptance
and performance: A two-step model. Academy of Management Journal, 28(1): 50-68.
Erickson, K., & Stull, D. 1998. Doing team ethnography. Thousand Oaks, CA: Sage.
Espejo, R., Schuhmann, W., Schwaninger, M., & Bilello, U. 1996. Organizational
transformation and learning: A cybernetic approach to management. New York, NY:
John Wiley & Sons.
Fama, E. F. 1980. Agency problems and the theory of the firm. The Journal of Political
Economy, 88 (2): 288-307.
Farrell, D. 1983. Exit, voice, loyalty, and neglect as responses to job dissatisfaction: a
multidimensional scaling study. Academy of Management Journal, 26(4): 596-607.
Festinger, L. 1954. A theory of social comparison processes. Human Relations, 7: 117-140.
Fetterman, D. M. 1998. Ethnography step by step. 2nd ed. Thousand Oaks: Sage.
Finstad, N. 1998. The rhetoric of organizational change. Human Relations, 51: 717-740.
Fiol, C. M., & Lyles, M. A. 1985. Organizational learning. Academy of Management
Review, 10: 803-813.
Fishbein, M., & Ajzen, I. 1975. Belief, attitude, intention and behavior: An introduction to
theory and research. Reading, Massachusetts: Addison-Wesley Publishing Company.
Fiske, S. T, & Tayler, S. E. 1984. Social cognition. 1st ed. Reading, MA: Addison-Wesley.
Fiske, S. T. 1992. Thinking is for doing: Portraits of social cognition from daguerreotype to
laserphoto. Journal of Personality and Social Psychology, 63: 877-889.
Fiske, S. T., & Tayler, S. E. 1991. Social cognition. 2nd ed. New York, NY: McGraw-Hill.
Fligstein, N. 1996. Markets as politics: A political-cultural approach to market institutions.
American Sociological Review, 61: 656-673.
Foley, S., Kidder, D. L., & Powell, G. N. 2002. The perceived glass ceiling and justice
perceptions: An investigation of Hispanic law associates. Journal of Management, 28(4):
471-496.
Folger, R., & Cropanzano, R. 1998. Organizational justice and human resource
management. Thousand Oaks, CA: Sage.
148
Folger, R., & Greenberg, J. 1985. Procedural justice: An interpretive analysis of personnel
systems. In K. Rowland & G. Ferris (Eds.), Research in personnel and human resources
management, 3: 141–183. Greenwich, CT: JAI Press.
Folger, R., & Konovsky, M. A. 1989. Effects of procedural and distributive justice on
reactions to pay raise decisions. Academy of Management Journal, 32: 115–130.
Ford, J. D., & Ford, L. W. 1995. The role of conversations in producing intentional change
in organizations. Academy of Management Review, 20: 541-570.
Ford., J. D., Ford, L. W., & McNamara, R. T. 2002. Resistance and the background
conversations of change. Journal of Organizational Change Management, 15(2): 105-
121.
Forgas, J. P. 1989. Mood effects on decision-making strategies. Australian Journal of
Psychology, 41: 197–214.
Forgas, J. P. 1990. Affective influences on individual and group judgments. European
Journal of Social Psychology, 20: 441–453.
Forgas, J. P. 1995. Mood and judgment: The affect infusion model (AIM). Psychological
Bulletin, 117(1): 39–66.
Forgas, J. P., & George, J. M. 2001. Affective influences on judgments and behavior in
organizations: An information processing perspective. Organizational Behavior and
Human Decision Processes, 86(1): 3-34
Fossum, J., Arvey, R., Paradise, C., & Robbins, N. 1986. Modeling the skills obsolescence
process: A psychological/economic integration. Academy of Management Review, 11:
362–374.
Fox-Wolfgramm, S., Boal, K., & Hunt, J. 1998. Organizational adaptation to institutional
change: A comparative study of first-order change in prospector and defender banks.
Administrative Science Quarterly, 43: 87-126.
Frabble, D. E. S. 1997. Gender, racial, ethic, sexual, and class identities. In J. T. Spence, J.
M. Darley, & D. J. Foss (Eds.), Annual review of psychology, 48: 139-162. Palo Alto,
CA: Annual Reviews.
Fredrickson, J. W. 1984. The comprehensiveness of strategic decision processes: Extension,
observations, future directions. Academy of Management Journal, 27: 445-466.
Freeman, S. J., & Cameron, K. S. 1993. Organizational downsizing: A convergence and
reorientation framework. Organization Science, 4(1): 10-29.
French, J. P. R. & Raven, B.H. 1959. The bases of social power. In D. Cartwright (Ed.),
Studies in social power, 150-167. Ann Arbor, MI: Institute of Social Research.
149
Friedlander, F. 1983. Patterns of individual and organizational learning. In S. Srivastra &
Associates (Eds.), The executive mind: New insights on managerial thought and action.
San Francisco, CA: Jossey-Bass.
Galpin, T. 1996. The human side of change: A practical guide to organizational redesign.
San Francisco, CA: Jossey-Bass.
Gannon, M. J., Smith, K. G., & Grimm, C. 1992. An organizational information-processing
profile of first movers. Journal of Business Research, 25(3): 231-241.
Gardner, D. G., Dunham, R. B., Cummings, L. L., & Pierce, J. L. 1987. Employee focus of
attention and reactions to organizational change. Journal of Applied Behavioral Science,
23: 351-370.
George, J. M. 1989. Mood and absence. Journal of Applied Psychology, 74: 317
George, J. M., & Jones, G. R. 1995. Understanding and managing organizational behavior.
Reading, MA: Addison-Wesley.
George, J. M., & Jones, G. R. 1996. The experience of work and turnover intentions:
interactive effects of value attainment, job satisfaction, and positive mood. Journal of
Applied Psychology, 81:318-25.
George, J. M., & Jones, G. R. 2001. Towards a process model of individual change in
organizations. Human Relations, 54: 419–444.
George, J. M, & Zhou, J. 2001. When job dissatisfaction leads to creativity: Encouraging
the expression of voice. Academy of Management Journal, 44: 682-696.
Gersick, C. J. G. 1991. Revolutionary change theories: A multi-level exploration of the
punctuated equilibrium paradigm. Academy of Management Review, 16(1): 10-36.
Gianakos, I. 1999. Patterns of career choice and career decision-making self-efficacy.
Journal of Vocational Behavior, 54: 244–258.
Gilmore, T., Shea, G., & Useem, M. 1997. Side effects of corporate cultural
transformations. Journal of Applied Behavioral Science, 33: 174-189.
Glueck, W. F. 1980. Business policy and strategic management. 3rd ed. New York, NY:
McGraw-Hill
Goldstein, J. 1994. The Unshackled Organization. Portland, OR: Productivity Press.
Goodstein, J. D. 1994. Institutional pressures and strategic responsiveness: Employer
Involvement in Work-Family Issues. Academy of Management Journal, 37(2): 350-382.
Gopinath, C., & Becker, T. E. 2000. Communication, procedural justice, and employee
attitudes: Relationships under conditions of divestiture. Journal of Management, 26(1):
63-83.
Gouldner, A. W. 1960. The norm of reciprocity: A preliminary statement. American
Sociological Review, 25: 161-178.
150
Grazer, B., & Strauss, A. 1967. The discovery of grounded theory. Chicago, IL: Aldine.
Greenberg, J. 1982. Approaching equity and avoiding inequity in groups and organizations.
In J. Greenberg & R. L. Cohen (Eds.), Equity and justice in social behavior, 389–435.
New York, NY: Academic Press.
Greenberg, L., & Barling, J. 1999. Predicting employee aggression against coworkers,
subordinates and supervisors: The roles of person behaviors and perceived workforce
factors. Journal of Organizational Behavior, 20(6): 897-913.
Greenhalgh, L. 1982. Maintaining organizational effectiveness during organizational
retrenchment. Journal of Applied Behavioral Science, 18: 155-170.
Greenwald, A. G., & Banaji, M. R. 1995. Implicit social cognition: Attitudes, self-esteem,
and stereotypes. Psychological Review, 102(1): 4-27.
Greenwood, R., & Hinings, C. R. 1988. Organizational design types, tracks, and the
dynamics of strategic change. Organizational Studies, 8: 293-316.
Greenwood, R., & Hinings, C. R. 1993. Understanding strategic change: The contribution of
archetypes. Academy of Management Journal, 36: 1052-1081.
Greenwood, R., & Hinings, C. R. 1996. Understanding radical organizational change:
Bringing together the old and the new institutionalism. Academy of Management Review,
21: 1022-1054.
Gresov. C., Haveman, H., & Oliva, T. 1993. Organizational change and performance under
conditions of fundamental environmental transformation. Administrative Science
Quarterly, 37: 48-75.
Greve, H. R. 1998. Performance, aspirations, and risky organizational change.
Administrative Science Quarterly, 43(1): 58-86.
Gujarati, D. N. 1995. Basic econometrics. 3rd ed. New York, NY: McGraw-Hill.
Hackman, J. R. 1992. Group influences on individuals in organizations. In M. D. Dunnette
& L. M. Hough (Eds.), Handbook of industrial and organizational psychology. Palo
Alto, CA: Consulting Psychologists Press.
Hackman, J. R., & Oldham, G. R. 1975. Development of the Job Diagnostic Survey.
Journal of Applied Psychology, 60: 159-170.
Hackman, J. R., & Oldham, G. R. 1976. Motivation through the design of work: Test of a
theory. Organizational Behavior and Human Performance, 16: 250-279.
Hage, J. 1980. Theories of organizations: form, process, and transformation. New York,
NY: Wiley.
Hambrick, D. C., & Fredrickson, J. W. 2001. Are you sure you have a strategy? Academy of
Management Executive, 15(4): 48-59.
151
Hambrick, D. C., & Schecter, S. M. 1983. Turnaround strategies for mature industrial-
product business units. Academy of Management Journal, 26: 231-248.
Hambrick, D. C., Geletkanycz, M. A., & Fredrickson, J. W. 1993. Top executive
commitment to the status quo: Some tests of its determinants. Strategic Management
Journal, 14: 401-418.
Hammersley, M. 1990. Reading ethnographic research: A critical guide. London:
Longmans.
Hammersley, M. 1992. What’s wrong with ethnography? Methodological explorations.
London: Routledge.
Hannan, M. T., & Freeman, J. 1977. The population ecology of organizations. American
Journal of Sociology, 82: 929-964.
Hannan, M. T., & Freeman, J. 1984. Structural inertia and organizational change. American
Sociological Review, 49(2): 149-164.
Hannan, M. T., & Freeman, J. 1988. Structural inertia and organizational change. In K.
Cameron, R. Sutton & Whetten, D. (Eds.). Readings in organizational change, 75-94.
Cambridge, MA: Ballinger.
Harrigan, K. R. 1985. Strategic flexibility: A management guide for changing times.
Lexington, MA: Lexington Books.
Haveman, H. A. 1992 Between a rock and a hard place: Organizational change and
performance under conditions of fundamental environmental transformation.
Administrative Science Quarterly, 37(1): 48-75.
Hedberg, B. L. T., Nystrom, P. C., & Starbuck, W. H. 1976. Camping on seesaws:
Prescriptions for a self-designing organization. Administrative Science Quarterly, 21:
41-65.
Hellgren, J., & Sverke, M. 2003. Does job insecurity lead to impaired well-being or vice
versa? Estimation of cross-lagged effects using latent variable modeling. Journal of
Organizational Behavior, 24(2): 215-236.
Herzberg, F. 1968. One more time: How do you motivate employees? Harvard Business
Review, 46: 53-62.
Hofer, C. 1980. Turnaround strategies. Journal of Business Strategy, 1: 19-31.
Hofer, C., & Schendel, D. 1978. Strategy formulation: Analytical Concepts. St. Paul, MN:
West Publishing.
Hofstede, G. 1980. Culture's consequences: International differences in work-related
values. Newbury Park, CA: Sage.
Hom, P. W., & Griffeth, R. W. 1995. Employee turnover. Cincinnati, OH: South-Western
College Publishing
152
Hoopes, D. G., Madsen, T. L., & Walker, G. 2003. Guest editors’ introduction to the special
issue: Why is there a resource-based view? Toward a theory of competitive
heterogeneity. Strategic Management Journal, Special Issue 24(10): 889-902.
Hough, J. R., & White, M. A. 2003. Environmental dynamism and strategic decision-
making rationality: An examination at the decision level. Strategic Management
Journal, 24: 481-489.
Huber, G. P. 1991. Organizational learning: An examination of contributing processes and
the literatures. Organizational Science, 2: 88-115.
Huff, J. O., Huff, A. S., & Thomas, H. 1992. Strategic renewal and the interaction of
cumulative stress and inertia. Strategic Management Journal, 13: 55-75
Hui, C., & Lee, C. 2000. Moderating effects of organization-based self-esteem on
organizational uncertainty: Employee response relationships. Journal of Management,
26(2): 215-232.
Hultman, K. 1998. Managing change irresistible: Overcoming resistance to change in your
organization. Davies-Black Publishing.
Huy, Q. N. 1999. Emotional capability, emotional intelligence, and radical change.
Academy of Management Review, 24(2): 325-345.
Isabella, L. 1990. Evolving interpretations as a change unfolds: How managers construe key
organizational events. Academy of Management Journal, 33: 7-41.
Isen, A. M., Daubman, K., & Nowicki, G. 1987. Positive affect facilitates creative problem
solving. Journal of Personality and Social Psychology, 52: 1122-1131.
Isenberg, D. J. 1986. Thinking and managing: A verbal protocol analysis of managerial
problem solving. Academy of Management Journal. 29: 327-351.
Iverson, R. D. 1996. Employee acceptance of organizational change: The role of
organizational commitment. The International Journal of Human Resource
Management, 7(1): 121-149.
Iverson, R. D., & Roy, P. 1994. A causal model of behavioral commitment: Evidence from
a study of Australian blue-collar employees. Journal of Management, 20(1): 15-41.
Jaffe, D., Scott, C., & Tobe, G. 1994. Rekindling commitment: How to revitalize yourself,
your work, and your organization. San Francisco, CA: Jossey-Bass.
Jenkins, G. D., & Lawler, E. E. 1981. Impact of employee participation in pay-plan
development. Organizational Behavior and Human Performance, 28: 111-128.
Jick, T. D. 1985. As the axe falls: Budget cuts and the experience of stress on organization.
In T. A. Beehr & R. S. Bhagat (Eds.), Human stress and cognition in organizations, 83-
114. New York, NY: Wiley.
153
Johnson, E. J., Hershey, J., Meszaros, J., & Kunreuther, H. 1993. Framing, probability
distortions, and insurance decisions. Journal of Risk and Uncertainty, 7: 35-51.
Johnson-Cramer, M. E., Cross, R. L., & Yan, A. 2003. Sources of fidelity in purposive
organizational change: Lessons from a re-engineering case. Journal of Management
Studies, 40(7): 1837-1869.
Judge, T. A., Thoresen, C. J., Pucik, V., & Welbourne, T. M. 1999. Managerial coping with
organizational change: A dispositional perspective. Journal of Applied Psychology, 84:
107-122.
Judson, A. 1991. Changing behavior in organizations: Minimizing resistance to change.
Cambridge, MA: Basil Blackwell.
Kahneman, D. D., Slovic, P., & Tversky, A. 1982. Judgment under uncertainty: Heuristics
and Biases. New York, NY: Cambridge University Press.
Kahneman, D., & Tversky, A. 1979. Prospect theory: Decision under risk. Econometrica,
47: 263-291.
Kanfer, R. 1990. Motivation theory and industrial and organizational psychology. In
Dunnette, M. D. & Hough, L. M. (Eds). Handbook of industrial and organizational
psychology, 1: 75-170. Palo Alto, CA: Consulting Psychologists Press.
Kanter, R. M. 1977. Men and women of the corporation. New York, NY: Basic.
Kanter, R. M. 1983. The change masters. New York, NY: Simon & Schuster.
Kanter, R. M. 1991. Transcending business boundaries: 12,000 world managers view
change. Harvard Business Review, 69(3): 151-164.
Kanter, R. M. 1995. Managing the human side of change. In D. A. Kolb, J. Osland, & I. M.
Rubin (Eds). The organizational behavior reader, 676-685. Englewood Cliffs, NJ:
Prentice-Hall.
Karambayya, R., & Brett, J. M. 1989. Managers handling disputes: Third-party roles and
perceptions of fairness. Academy of Management Journal, 32: 687-704.
Katz, D. 1960. The functional approach to the study of attitudes. Public Opinion Quarterly,
24, 163-204.
Keck, S. L., & Tushman, M. L. 1993. Environmental and organizational context and
executive team structure. Academy of Management Journal, 36(6). 1314-1344.
Kelly, D., & Amburgey, T. L. 1991. Organizational inertia and momentum: A dynamic
model of strategic change. Academy of Management Journal, 24(3): 591-612.
Kemper, T. D. 1978. A social interactional theory of emotions. New York, NY: Wiley.
Kemper, T. D. 1987. How many emotions are there? Wedding the social and automatic
structure. American Journal of Sociology, 93: 263-289.
154
Kemper, T. D. 1990. Social relations and emotions: A structural approach. In T.D. Kamper,
Research agendas in the sociology of emotions. 207-237. New York, NY: State
University of New York.
Kidwell, R. E. Jr., Mossholder, K. W., & Benett, N. 1997. Cohesiveness and organizational
citizenship behavior: A multilevel analysis using work groups and individuals. Journal
of Management, 23(6): 775-793.
Kim, W. C., & Mauborgne, R. A. 1991. Implementing global strategies: The role of
procedural justice. Strategic Management Journal, Summer Special Issue, 12: 125-143.
Kim, W. C., & Mauborgne, R. A. 1993. Procedural justice, attitudes, and subsidiary top
management compliance with multinationals’ corporate strategic decisions. Academy of
Management Journal, 36: 502–526.
King, J. E. 2000. White-collar reactions to job insecurity and the role of the psychological
contract: Implications for human resource management. Human Resource Management,
39(1): 79-92.
Kirton, M. J., & Mulligan, G. 1973. Correlates of managers’ attitudes toward change.
Journal of Applied Psychology, 58(1): 101-107.
Klein, G. A., & Crandall, B. W. 1995. The role of mental simulation in problem solving and
decision making. In P. Hancock, J. Flach, J. Caird, & K. Vincente (Eds.) Local
applications of the ecological approach to human-machine systems, 325-358. Hillsdale,
NJ: Lawrence Erlbaum Associates.
Klimoski, R. J., B. Karol. 1976. The impact of trust on creative problem solving groups.
Journal of Applied Psychology, 61, 630-633.
Knowles, M. 1973. The adult learner: A neglected species. Houston, TX: Gulf Publishing
Co.
Komaki, J. 1982. Managerial effectiveness: Potential contributions of the behavioral
approach. Journal of Organizational Behavior Management, 3(3): 71-83.
Kotey, B., & Meredith, G. G. 1997. Relationships among owners/mangers personal values,
business strategies, and enterprise performance. Journal of Small Business Management,
35(2): 37-61.
Kotter, J. 1995. Leading change: Why transformation efforts fail. Harvard Business Review,
73(2): 59-67.
Kotter, J. P., & Cohen, D. S. 2002. The heart of change: Real-life stories of how people
change their organizations. Boston, MA: Harvard Business School Press.
Kovach, K. A. 1987. What motivates employees? Workers and supervisors give different
answers. Business Horizons, 30: 58-65.
155
Kramer, R. M. 1999. Trust and distrust in organizations: Emerging perspectives, enduring
questions. Annual Review of Psychology, 50: 569-598.
Kyle, N. 1993. Staying with the flow of change. Journal for Quality and Participation,
16(4): 34-42.
Langley, P. & Simon, H. 1981. The central role of learning in cognition. In J. R. Anderson
(Ed.) Cognitive skills and their acquisition, 361-380. Hillsdale, NJ: Lawrence Erlbaum.
Latack, J. C., & Dozier, J. B. 1986. After the ax falls: Job loss as a career transition.
Academy of Management Review, 11: 375-392.
Leanna, C. R., & Feldman, D. C. 1992. Coping with job loss: How individuals,
organizations, and communities respond to layoffs. New York, NY: Lexington Books.
Ledford, G. Jr., Mohrman, S., Mohrman, A., & Lawler III, E. 1989. The phenomenon of
large-scale organizational change. In A. Mohrman, & Associates (Eds.), Large scale
organizational change, 1-31. San Francisco, CA: Jossey-Bass.
Lent, R. W., Hackett, G., & Brown, S. D. 1999. A social cognitive view of school-to-work
transition. Career Development Quarterly, 47: 297–311.
Lewin, K. 1945. The research center for group dynamics at Massachusetts Institute of
Technology. Sociometry, 8: 126-136.
Lewin, K. 1947. Frontiers in group dynamics. Human Relations, 1: 5-41
Lewin, K. 1951. Field theory in social science. New York, NY: Harper & Row.
Lind, E. A., & Tyler, T. R. 1988. The social psychology of procedural justice. New York,
NY: Plenum.
Lindsay, P. H., & Norman, D. A. 1977. Human information processing. Orlando, FL:
Academic Press.
Lippitt, G. L., Longseth, P., & Mossop, J. 1989. Implementing organizational change. San
Francisco, CA: Jossey-Bass.
Locke, E. A. 1976. The nature and causes of job satisfaction. In M. D. Dunnett (Ed.),
Handbook of industrial and organizational psychology. New York, NY: Wiley.
Locke, E. A., & Latham, G. P. 1990. A theory of goal setting & task performance.
Englewood Cliffs, NJ: Prentice-Hall.
Locke, E. A., Frederick, E., Lee, C., & Bobko, P. 1984. Effect of self-efficacy, goals, and
task strategies on task performance. Journal of Applied Psychology, 69, 241-251.
Lovaglia, M. J., & Houser, J. A. 1996. Emotional reactions and status in groups. American
Sociology Review, 61(5): 867-883.
Mabin, J. V., Forgeson, S., & Green, L. 2001. Harnessing resistance: Using the theory of
constraints to assist change management. Journal of European Industrial Training, 25:
168-191.
156
March, J. G. 1955. An introduction to the theory and measurement of influence. The
American Political Science Review, 49(2): 431-451.
March, J. G., & Olsen, J. P. 1976. Ambiguity and choice in organizations. Bergen, Norway:
Universitetsfortlaget.
March, J. G., & Simon, H. A. 1958. Organizations. New York, NY: Wiley.
Martin, H. H. 1975. How we shall overcome resistance. Training and Development Journal,
29(9): 32-34.
Maslow, A. W. 1954. Motivation and personality. New York; NY: Harper & Row.
Maslow, A. W. 1970. Motivation and personality. 2nd ed. New York, NY: Harper & Row.
Mathieu, J. E., & Farr, J. L. 1991. Further evidence for the discriminant validity of measures
of organizational commitment, job involvement, and job satisfaction. Journal of Applied
Psychology, 76:127-133
Maurer, T. J. 2001. Career-relevant learning and development, worker age, and beliefs
about self-efficacy for development. Journal of Management, 27: 123-140.
Maurer, T. J., Wrenn, K. A., Pierce, H. R., Tross, S. A., & Collins, W. C. 2003. Beliefs
about ‘improvability’ of career-relevant skills: relevance to job/task analysis,
competency modelling, and learning organization. Journal of Organizational Behavior,
24(1): 107-131.
McClelland, D. C., & Boyatzis, R. 1984. Leadership motive pattern and long-term success
in management. In C. D. Spielberger (Ed.), Motives, personality, and society: Selected
papers, 293-308. New York, NY: Praeger.
McFarlin, D. B., & Sweeney, P. D. 1992. Distributive and procedural justice as predictors of
satisfaction with personal and organizational outcomes. Academy of Management
Journal, 35: 626-637.
McGregor, D. 1967. The professional manager. New York, NY: McGraw-Hill.
McHugh, M. 1997. The stress factor: Another item for the change management agenda?
Journal of Organizational Change Management, 10: 345-362.
McKelvey, R. D., & Zavoina, W. 1975. A statistical model for the analysis of ordinal level
of dependent variables. Journal of Mathematical Sociology, 4: 103-120.
Meyer, A. D. 1982. Adapting to environmental jolts. Administrative Science Quarterly, 27:
515-537.
Meyer, A., Brooks, G., & Goes, J. 1990. Environmental jolts and industry revolutions:
Organizational responses to discontinuous change. Strategic Management Journal, 11:
93-110.
Meyer, J. P., & Allen, N. J. 1997. Commitment in the workplace: Theory, research, and
application. Thousand Oaks, CA: Sage Publications.
157
Meyer, J. W., & Rowan, B. 1977. Institutionalized organizations: Formal structure as myth
and ceremony. American Journal of Sociology, 83: 340-363.
Meyer, J., & Allen, N. 1977. Commitment in the workplace: Theory, research, and
application. Thousand Oaks, CA: Sage.
Meyer, K., & Robins, M. 1991. 10 rules for change. Executive Excellence, 8(5): 9-10.
Miles, R., & Snow, C. 1978. Organizational strategy, structure, and process. New York,
NY: McGraw-Hill.
Miller, D., & Chen, M. J. 1994. Sources and consequences of competitive inertia. A study of
the US airline industry. Administrative Science Quarterly, 39(1): 1-23.
Miller, D., & Friesen, P. H. 1980. Momentum and revolution in organizational adaptation.
Academy of Management Journal, 23 (4): 591-614.
Miller, D., & Friesen, P. H. 1984. Organizations: A quantum view. Englewood Cliffs, NJ:
Prentice-Hall.
Milliken, F. J. & Lant T. K. 1991. The impact of an organization’s recent performance
history on strategic persistence and change: The role of managerial interpretations. In J.
Dutton, A., Huff & P. Shrivastava (Eds.), Advances in strategic management, 7: 129-
156. Greenwich, CT: JAI Press.
Mintzberg, H. 1979. The structuring of organizations. Englewood Cliffs, NJ: Prentice-Hall.
Mirer, T. W. 1990. Economic statistics and econometrics. New York, NY: Macmillan
Publishing Company.
Mobley, W. H. 1977. Intermediate linkages in the relationship between job satisfaction and
employee turnover. Journal of Applied Psychology, 62: 237–240.
Mobley, W. H., Horner, S. O., & Hollingsworth, A. T. 1978. An evaluation of precursors of
hospital employee turnover. Journal of Applied Psychology, 63(3): 408-414.
Mooreman, R. H. 1991. Relationship between organizational justice and organizational
citizenship behaviors: Do fairness perceptions influence employee citizenship? Journal
of Applied Psychology, 76: 845-855.
Morris, K., & Raben, C. 1995. The fundamentals of change management. In D. Nadler, R.
Shaw, A. Walton & Associates (Eds.). Discontinuing change: Leading organizational
transformation, 47-65. San Francisco, CA: Jossey-Bass.
Morrison, E. W., & Robinson, S. L. 1997. When employees feel betrayed: A model of how
psychological contract violation develops. Academy of Management Review, 22: 226–
256.
Mowday, R. T., Porter, L. W., & Steers, R. M. 1982. Employee-organizational linkages:
The psychology of commitment, absenteeism, and turnover. In P. Warr (Ed.),
158
Organizational and occupational psychology, 219-229. New York, NY: Academic
Press, Inc.
Mowday, R. T., Steers, R. M., & Porter, L. W. 1979. The measurement of organizational
commitment. Journal of Vocational Behavior, 14: 224-247.
Nadler, D. A. 1998. Champions of change. San Francisco, CA: Jossey-Bass.
Nadler, D. A., & Tushman, M. L. 1989. Organizational frame bending: Principles for
managing reorientation. Academy of Management Executive, 111(3): 194-204.
Nelson, R. R., & Winter, S. G. 1982. An evolutionary theory of economic change.
Cambridge, MA: Belknap Press
Nystrom, P. C., & Starbuck, W. H. 1984. To avoid organizational crises, unlearn.
Organizational Dynamics, 12(4): 53-65.
O’Reilly, C., & Chatman, J. 1986. Organizational and psychological attachment: The effects
of compliance, identification, and internationalization on prosocial behavior. Journal of
Applied Psychology, 71: 492-499.
O’Toole, J. 1995. Leading change: Overcoming the ideology of comfort and the tyranny of
custom. New York; NY: Fireside.
Paese, P. W., Bieser, M., & Tubbs, M. E. 1993. Framing effects and choice shifts in group
decision making. Organizational Behavior and Human Decision Processes, 56: 149-
165.
Parker, P. C., Baltes, B. B., Young, S. A., Huff, J. W., Altmann, R. A., Lacost, H. A., &
Roberts, J. E. 2003. Relationships between psychological climate perceptions and work
outcomes: A meta-analytic review. Journal of Organizational Behavior, 24(4): 389-416.
Parks, K. 1989. Personal control in occupational context. In A. Steptoe & A. Apples. (Eds.).
Stress, personal control and health, 21-47 New York, NY: Wiley.
Parnell, J. A. 1997. New evidence in the generic strategy and business performance debate:
A research note. British Journal of Management, 8: 175-181.
Paterson, J. M., & Cary, J. 2002. Organizational justice, change anxiety, and acceptance of
downsizing: Preliminary tests of an AET-based model. Motivation and Emotion, 26(1):
83-103.
Pearce, J. L. 1993. Toward an organizational behavior of contract laborers: Their
psychological involvement and effects on employee co-workers. Academy of
Management Journal, 36: 1082-1096.
Perrow, C. 1986. Complex organizations: A critical essay. 3rd ed. New York, NY:
McGraw-Hill.
Peteraf, M. A. 1993. The cornerstones of competitive advantage: A resource-based view.
Strategic Management Journal, 14(3): 179-192.
159
Pfeffer, J., & Salancik, G. 1978. The external control of organizations. New York, NY:
Harper and Row.
Pfeffer, J. 1981. Power in organizations. Marshfield, MA: Pitman.
Pierce, J. L., & Newstrom, J. W. 1995. Leaders and the leadership process: Readings,
assessments, and applications. Chicago, IL: Austen Press.
Porter, L. W. & Steers, R. M. 1973. Organizational, work, and personal factors in employee
turnover and absenteeism. Psychological Bulletin, 80(2): 151-176.
Porter, L. W., Steers, R. M., Mowday, R. T., & Boulian, P. V. 1974. Organizational
commitment, job satisfaction, and turnover among psychiatric technicians. Journal of
Applied Psychology, 59: 603-609.
Porter, M. E. 1980. Competitive strategy. New York, NY: Free Press.
Porter, M. E. 1990. The competitive advantage of nations. London: Macmillan.
Raynor, M. E., & Bower, J. L. 2001. Lead from the center: How to manage divisions
dynamically. Harvard Business Review, 79(5): 99-100.
Regar, R. K., Mullane, J. V., Gustafson, L. T., & DeMarie, S. M. 1994. Creating
earthquakes to change organizational mindsets. Academy of Management Executive,
8(4): 31-46.
Reichers, A., Wanous, J., & Austin J. 1997. Understanding and managing cynicism about
organizational change. Academy of Management Executive, 11 (1): 48-59.
Rhine, R. J. 1958. A concept-formation approach to attitude acquisition. Psychological
Review, 65: 362-370.
Ridgeway, C., & Johnson, C. 1990. What is the relationship between socio-emotional
behavior and status in task groups? American Journal of Sociology, 95: 1189-1212.
Robbins, K. D., & Pearce, J. A. 1992. Turnaround: Retrenchment and recovery. Strategic
Management Journal, 13(4): 287-309.
Roberts, K. H., & O’Reilly, C. A. 1974. Measuring organizational communication. Journal
of Applied Psychology, 59: 321-326.
Robey, D. 1979. User attitudes and management information use. Academy of Management
Journal, 22(3): 527-538.
Robinson, S. L. 1996. Trust and breach of the psychological contract. Administrative
Science Quarterly, 41: 574–599.
Robinson, S. L., & Morrison, E. W. 1995. Psychological contracts and OCB: The effect of
unfulfilled obligations on civic virtue behavior. Journal of Organizational Behavior, 16:
289–298.
Robinson, S. L., & Rousseau, D. M. 1994. Violating the psychological contract: Not the
exception but the norm. Journal of Organizational Behavior, 15: 245–259.
160
Robinson, S. L., Kraatz, M. S., & Rousseau, D. M. 1994. Changing obligations and the
psychological contract: A longitudinal study. Academy of Management Journal, 37:
137–152.
Rohner, R. P. 1977. Advantages of the comparative method of anthropology. Behavior
Science Research, 12(1): 117-144.
Romanelli, E., & Tushman, M. L. 1994. Organizational transformation as punctuated
equilibrium: An empirical test. Academy of Management Journal, 37(5): 1141-1166.
Rotter, J. B. 1966. Generalized expectancies for internal versus external control of
reinforcement. Psychological Monographs, 80(609).
Rousseau, D. M., & Tijorilawa, S. 1999. What’s a good reason to change? Motivated
reasoning and social accounts in promoting organizational change. Journal of Applied
Psychology, 84: 514-528.
Rousseau, D. M., Sitkin, S. B., Burt, R. S., & Camerer, C. 1998. Not so different after all: A
cross-discipline view of trust. Academy of Management Review, 23: 393-404.
Ruh, R. A., White, J. K, & Wood, R. R. 1975. Job involvement, values, personal
background, participation in decision making, and job attitudes. Academy of
Management Journal, 18(2): 300-312.
Rumelt, R. P., Schendel, D., & Teece, D. J. 1991. Strategic management and economics.
Strategic Management Journal, Winter Special Issue, 12: 5-29.
Russo, M. V. 2003. The emergence of sustainable industries: Building on natural capital.
Strategic Management Journal, 24(4): 317-331.
Sagie, A., & Koslowsky, M. 2000. Participation and empowerment in organizations:
Modeling, effectiveness, and applications. Thousand Oaks, CA: Sage.
Salancik, G. R., & Pfeffer, J. 1977. An examination of needs-satisfaction models of job
attitudes. Administrative Science Quarterly, 22, 427-456.
Salancik, G. R., & Pfeffer, J. 1978. A social information processing approach to job
attitudes and task design. Administrative Science Quarterly, 23: 224-253.
Sanchez R., 1995. Strategic flexibility in product competition. Strategic Management
Journal, Summer Special Issue, 16: 135-159.
Sansone, C., & Harackiewicz, J. M. 2000. Intrinsic and extrinsic motivation: The search for
optimal motivation and performance. San Diego, CA: Academic Press.
Sarnoff, I. 1960. Psychoanalytic theory and social attitudes. Public Opinion Quarterly,
24(2): 251-279.
Scandura, T. A., & Williams, E. A. Research methodology in management: Current
practices, trends, and implications for future research. Academy of Management Journal,
43(6): 1248-1264.
161
Schein, E. 1985. Organizational culture and leadership. San Francisco, CA: Jossey-Bass.
Schendel, D., & Patton, G. 1976. Corporate stagnation and turnaround. Journal of
Economics and Business, 28: 236-241.
Schendel, D., Patton, G., & Riggs, J. 1976. Corporate turnaround strategies: A study of
profit decline and recovery. Journal of General Management, 3: 3-11.
Schneider, B. 1975. Organizational climates: An essay. Personnel Psychology, 40: 437-454.
Schriesheim, C., Castro, S., & Cogliser, C. 1999. Leader-member exchange (LMX)
research: A comprehensive review of theory, measurement, and data-analytic
procedures. Leadership Quarterly, 10: 63-113.
Schwaninger, M. 2004. Methodologies in conflict: Achieving synergies between system
dynamics and organizational cybernetics. Systems Research and Behavioral Science, 21:
411-431.
Scott, C. D., & Jaffe, D. T. 1988. Survive and thrive in times of change. Training and
Development Journal, April: 25-27.
Selznick, P. 1965. TVA and the grass roots. New York, NY: Harper and Row.
Senge, P. 1993. The fifth discipline: The art and practice of the learning organization. New
York, NY: Doubleday.
Shore, L. M., & Tetrick, L. E. 1991. A construct validity study of the survey of perceived
organizational support. Journal of Applied Psychology, 76: 637-643.
Silverman, D. 2000. Doing qualitative research: A practical handbook. London: Sage.
Simon, H. A. 1957. Administrative behavior. New York, NY: MacMillan.
Simon, H. A. 1978. Rationality as process and as product of thought. American Economic
Review: Proceedings, 68(2): 1-16.
Simon, H. A. 1979. Rational decision making in business organizations. American
Economic Review, 69(4): 493-513.
Simon, H. A. 1985. Human nature in politics: The dialogue of psychology with political
science. American Political Science Review, 79(2): 293-304.
Simon, H. A. 1986. Rationality in psychology and economics. Journal of Business, 59(4, 2):
S209-S224.
Simon, H. A. 1991. Organizations and markets. Journal of Economics Perspectives, 5(2):
25-44.
Slatter, S. S. P. 1984. Corporate recovery. Harmondsworth, UK: Penguin.
Smart, B. (Ed.) 1992. Beyond compliance: A new industry view of the environment.
Washington, DC: The World Resource Institute.
162
Smith, E. R. 1998. Mental representation and memory. In D. Gilbert, S. Fisker, & G.
Lindzey (Eds.), Handbook of social psychology, 4th ed., 1: 391-445. New York, NY:
McGraw-Hill.
Smith, K. K. 1982. Groups in Conflict: Prisons in Disguise. Dubuque, IA: Kendall/Hunt.
Smith, P. C., Kendall, L. M., & Hulin, C. L. 1969. The Measurement of Satisfaction in Work
and Retirement. Chicago, IL: Rand McNally.
Spector, B. 1989. From bogged down to fired up: Inspiring organizational change. Sloan
Management Review, 30(2): 32-46.
Spector, P. E. 1986. Perceived control by employee: A meta analysis of studies concerning
autonomy and participation at work. Human Relations, 39: 1005-1016.
Spiker, B. K., & Lesser, E. 1995. We have met the enemy. Journal of Business Strategy,
16(2), 17-21.
Spreitzer, G. M., & Mishra, A. K. 2002. To stay or to go: voluntary survivor turnover
following an organizational downsizing. Journal of Organizational Behavior, 23: 707-
729.
Spreitzer, G. M., & Quinn, R. E. 1996. Empowering middle managers to be
transformational leaders. Journal of Applied Behavioral Science, 32(3): 237-261.
Starbuck, W. H., Greve, A., & Hedburg, B. L. T. 1978. Responding to crisis. Journal of
Business Administration, 9(2): 111-137.
Steinburg, C. 1992. Taking charge of change. Training and Development, 46(3): 26-32.
Strauss, A., & Corbin, J. 1990. Basics of qualitative research: Grounded theory procedures
and techniques. Newbury Park: Sage.
Stumpf, S. A., & Hartman, K. 1984. Individual exploration to organizational commitment or
withdrawal. Academy of Management Journal, 27(2): 308-329.
Susanne, C., & Harackiewicz, J. M. 2000. Intrinsic and extrinsic motivation: The search for
optimal motivation and performance. San Diego, CA: Academic Press.
Taber, T. D., & Alliger, G. M. 1995. A task-level assessment of job satisfaction. Journal of
Organizational Behavior, 16(2): 101-121.
Terry, D. J., & Hogg, M. A. (Eds.) 2000. Attitudes, behaviors, and social context: The role
of norms and group membership. Mahwah, NJ: Lawrence Erlbaum.
Thibaut, J., & Walker, L. 1975. Procedural justice: A psychological analysis. Hillsdale, NJ:
Erlbaum.
Thibaut, J., & Walker, L. 1978. A theory of procedure. California Law Review, 66: 541–
566.
Thurstone, L. L. 1931. The measurement of social attitudes. Journal of Abnormal and
Social Psychology, 26(3): 249-269.
163
Trader-Leigh, K. E. 2002. Case study: Identifying resistance in managing change. Journal
of Organizational Change Management, 15(2): 138-155.
Turnley, W. H., Bolino, M. C., Lester, S. W., & Bloodgood, J. M. 2003. The impact of
psychological contract fulfillment on the performance of in-role and organizational
citizenship behaviors. Journal of Management, 29(2): 187-206.
Tushman, M. L., & Anderson, A. 1986. Technological discontinuities and organizational
environments. Administrative Science Quarterly, 31: 439-465.
Tushman, M. L., & Romanelli, E. 1985. Organizational evolution: A metamorphosis model
of convergence and reorientation. In B. Staw & L. Cummins (Eds.). Research in
organizational behavior, 7: 171-222. Greenwich, CT: JAI Press.
Tversky, A., & Kahneman, D. 1981. The framing of decisions and the rationality of choice.
Science, 221: 453-458.
Vollman, T. 1996. The transformation imperative. Boston, MA: Harvard Business School
Press.
Von Neumann, J., & Morgenstern, O. 1944 Theory of games and economic behavior.
Princeton University Press.
Von Neumann, J., & Morgenstern, O. 1980 Theory of games and economic behavior.
Princeton University Press.
Vroom, V. H. 1964. Work and motivation. New York, NY: Wiley
Wacker, J. G. 1998. A definition of theory: Research guidelines for different theory-
building research methods in operations management. Journal of Operations
Management, 16: 361-385.
Waldron, D. A. 1998. Status in organizations: Where evolutionary theory ranks. Managerial
and Decision Economics, 19(7): 505-520.
Wanberg, C. R., & Banas, J. T. 2000. Predictors and outcomes of openness to changes in a
reorganizing workplace. Journal of Applied Psychology, 85: 132-142.
Watson, D., Clark, L. A., & Tellegen, A. 1988. Development and validation of brief
measures of positive and negative affect: The PANAS scales. Journal of Personality and
Social Psychology, 54: 1063-1070.
Wayne, S. J., Shores, L. M., & Liden, R. C. 1997. Perceived organizational support and
leader-member exchange: A social exchange perspective. Academy of Management
Journal, 40: 82-111.
Webb, E. 1996. Trust and crisis. In R. Kramer & T. Tyler (Eds.), Trust in organizations:
frontiers of theory and research, 288-302. Thousand Oaks, CA: Sage.
Webb, J., & Dawson, P. 1991. Measure for measure: Strategic change in an electronic
instruments corporation. Journal of Management Studies, 28: 191-206.
164
Weick, K. E. 1976. Educational organizations as loosely coupled systems. Administrative
Science Quarterly, 21: 1-19.
Weick, K. E., & Quinn, R. E. 1999 Organizational change and development. Annual Review
of Psychology, 50: 361-386.
Weiner, Y. 1982. Commitment in organizations: A normative view. Academy of
Management Review, 7: 418-428.
Weiss, H., & Cropanzano, R. 1996. Affective Events Theory: A theoretical discussion of the
structure, causes and consequences of affective experiences at work. Research in
Organizational Behavior, 18: 1-74. Greenwich, CT: JAI Press.
Weiss, R., Dawis, G., England, G., & Lofquist, L. 1967. Minnesota studies in vocational
rehabilitation: Manual for the Minnesota satisfaction questionnaire. University of
Minnesota, MN.
Weitzel, W., & Jonsson, E. 1989. Decline in organizations: A literature integration and
extension. Administrative Science Quarterly, 34(1): 91-109.
Wernerfelt, B., & Karnani, A. 1987. Competitive strategy under uncertainty. Strategic
Management Journal, 8: 187-194.
Westman, M., & Etzion, D. 1995. Crossover of stress, strain and resources from one spouse
to another. Journal of Organizational Behavior, 16: 169-181.
Westman, M., Etzion, D., & Danon, E. 2001. Job insecurity and crossover of burnout in
married couples. Journal of Organizational Behavior, 22(5): 467-481.
Whitener, E. M. 2001. Do ‘high commitment’ human resource practices affect employee
commitment? A cross level analysis using hierarchical liner modeling. Journal of
Management, 27: 515-536.
Yin, R. K. 1994. Case study research: Design and methods. 2nd ed. Thousand Oaks, CA:
Sage.
Zander, A. F. 1950. Resistance to change – Its analysis and prevention. Advanced
Management, 4(5): 9-11.
Zentall, T. R., Galizio, M., & Critchfield, T. S. 2002. Categorization, concept learning, and
behavior analysis: An introduction. Journal of the experimental analysis of behavior,
78(3): 237-248.
Zucker, L. G. 1987. Institutional theories of organizations. Annual Review of Sociology, 13:
443-464.
165
Appendices
Appendix A: Questionnaire Survey Items for Studies 1 and 2
Active resistance
1. I am opposing or will oppose this change.
2. I am currently arguing for not making this change.
3. I will let this change happen without any objection. (R)
Passive resistance
1. I certainly withdraw my support for this change.
2. I pay no attention to this change. 3. I ignore this change.
Active support
1. I am embracing this change warmly.
2. I fully cooperate with the organization on this change. 3. This change gets my full support.
Passive support
1. I agree with the organization’s decision to make this change.
2. This change is acceptable to me.
3. I certainly comply with this change.
Perceived organizational support
1. The organization values my contribution to its well-being.
2. The organization really cares about my well-being.
3. The organization would ignore any complaint from me. (R)
Perceived procedural justice
1. Decision-making procedures related to this change have been applied consistently.
2. Overall, the procedures used for making change decisions were fair.
3. There has been two-way communication in decision-making process.
Perceived participation in a decision-making process
1. I am allowed to participate in decisions regarding this change.
2. I am satisfied with ways in which I can express my views on this change.
3. I really have no chance of giving my opinions on this change to decision-makers.
Perceived need for change
1. Reasons provided by top management for making this change are not convincing. (R)
2. I really understand the need for undertaking this change. 3. I agree with top management that we need to make a change.
166
Attitude towards organizational change
1. It is important to make some change within any organization from time to time.
2. I feel positive toward organizational change in general. 3. In general, I am sceptical about benefits of organizational change. (R)
Fear of known consequences of change
1. I am afraid of some aspects of this change.
2. The consequences of this change frighten me.
3. I am not afraid of the known consequences of this change (R)
Fear of unknown consequence of change
1. I am not afraid of the unknown consequences of this change. (R)
2. I am disturbed by not knowing what is going to happen with this change.
3. Unknown consequences of this change frighten me.
Perceived change in power
1. I feel this change grants me more power in this organization.
2. This change gives me more power to do my job.
3. I feel this change gives me a greater sense of control in doing my job.
Perceived change in status
1. In general, this change enhances my position in the organization.
2. After this change, my standing in this organization seems stronger.
3. I feel this change takes me backwards in the rank here. (R)
Perceived change in pride
1. I have lost a bit of respect from my colleagues as the change unfolds. (R)
2. As the change takes place, I feel a sense of greater respect by my colleagues.
3. In general, my colleagues seem to have a better opinion of me than before the
change.
Extrinsic Job satisfaction
1. I am satisfied with pay and amount of work.
2. I am not satisfied with the opportunities for advancement in this company. (R)
3. I am satisfied with current working conditions.
Job security
1. I am certain about what my future career picture looks like in this company.
2. I am certain about what my responsibilities will be six months from now.
3. I am certain about my job security in this company.
Intrinsic Job motivation
1. I take pride in doing my job as well as I can.
2. I try to think of ways of doing my job effectively.
3. I feel a sense of personal satisfaction when I do my job well.
167
Perceived employability
1. I will not have a problem to have a new job at the same level with another
organization.
2. I trust my ability to find a better job when I need one.
3. In case I would lose my job, it would not be easy to find another job at the same
level. (R)
Self-confidence for learning and development
1. I am very confident at learning and developing new skills relevant for my job.
2. I know I am very capable of keeping up with new techniques and knowledge
required for my job.
3. I can develop my career-relevant skills.
Affective commitment
1. When someone praises this organization, I feel like a personal compliment.
2. The reason I prefer this organization to others is because of what it stands for, that is, its values.
3. I feel a sense of ownership for this organization.
Trust in management
1. I feel very favorable toward top management.
2. I trust top management.
3. In general, I believe top management’s motives and intentions are good.
Colleagues’ reactions to change
1. I feel a sense of resistance to this change among my colleagues.
2. My colleagues seem to support this change
3. I know my colleagues oppose to this change.
Note: (R) indicates items that were reverse-ordered
168
Dear Participant, Thank you for taking the time to answer my questions about a recent change << insert here a description of the change>> in << insert here the company name>>. Listed below and on the next pages are statements that represent possible opinions about YOU may have about working at << insert here the company name>> during this change process. Please indicate the degree of your agreement or disagreement with each statement by marking on the box on the right hand side that best represents your point of view about the recent organization change and a situation with which it is related. Please choose from the following answers:
1 2 3 4 5
Strongly Disagree Moderately
Disagree
Neither Agree nor Disagree
Moderately
Agree
Strongly Agree
1 2 3 4 5
I fully cooperate with the organization on this change.
This change is acceptable to me.
Overall, the procedures used for making change decisions were fair.
In general, I am sceptical about benefits of organizational change.
I am opposing or will oppose this change.
The organization really cares about my well-being.
In general, this change enhances my position in the organization.
I trust top management.
Reasons provided by top management for making this change are not convincing.
It is important to make some change within any organization from time to time.
I am not afraid of the known consequences of this change
I am currently arguing for not making this change.
I agree with top management that we need to make a change.
I try to think of ways of doing my job effectively.
I feel positive toward organizational change in general.
I am embracing this change warmly.
There has been two-way communication in decision-making process.
Unknown consequences of this change frighten me.
The organization would ignore any complaint from me.
I will let this change happen without any objection.
This change gets my full support.
I am not afraid of the unknown consequences of this change.
The reason I prefer this organization to others is because of what it stands for, that is, its values.
I know I am very capable of keeping up with new techniques and knowledge required for my job.
I really understand the need for undertaking this change.
I certainly withdraw my support for this change.
I certainly comply with this change.
169
1 2 3 4 5
I am satisfied with current working conditions.
I agree with the organization’s decision to make this change.
I can develop my career-relevant skills.
Decision-making procedures related to this change have been applied consistently.
As the change takes place, I feel a sense of greater respect by my colleagues.
I pay no attention to this change.
I am allowed to participate in decisions regarding this change.
I am not satisfied with the opportunities for advancement in this company.
I feel this change grants me more power in this organization.
I am disturbed by not knowing what is going to happen with this change.
In general, I believe my employer’s motives and intentions are good.
I feel a sense of ownership for this organization.
I am certain about my job security in this company.
I feel a sense of personal satisfaction when I do my job well.
I am afraid of some aspects of this change.
When someone praises this organization, I feel like a personal compliment.
I feel a sense of resistance to this change among my colleagues.
I am satisfied with ways in which I can express my views on this change.
The known consequences of this change frighten me.
The organization values my contribution to its well-being.
In case I would lose my job, it would not be easy to find another job at the same level.
I am satisfied with pay and amount of work.
I ignore this change.
I feel this change takes me backwards in the rank here.
I feel very favorable toward top management.
I have lost a bit of respect from my colleagues as the change unfolds.
I am certain about what my responsibilities will be six months from now.
My colleagues seem to support this change
In general, my colleagues seem to have a better opinion of me than before the change.
I will not have a problem to have a new job at the same level with another organization.
I really have no chance of giving my opinions on this change to decision-makers.
After this change, my standing in this organization seems stronger.
This change gives me more power to do my job.
I trust my ability to find a better job when I need one.
I know my colleagues oppose to this change.
I take pride in doing my job as well as I can.
170
1 2 3 4 5
I am certain about what my future career picture looks like in this company.
I am very confident at learning and developing new skills relevant for my job.
I feel this change gives me a greater sense of control in doing my job.
I fully cooperate with the organization on this change.
This change is acceptable to me.
Please be so kind to provide general information about yourself.
1. How old are you? _______ years
2. What is your highest level of education? A degree below a bachelor level
A degree equivalent to a bachelor level
A degree equivalent to a master level
A degree higher than a master level
3. What is your gender? Male
Female
4. How long have you worked in this position? _______ year(s)
5. How long have you worked for this company? _______ year(s)
6. What is your family status? Single
Married / co-habiting
Divorced
7. If you have a child, how many children do you have? _______ child(children)
Thank you very much for participating in this survey. You have provided a significant amount of valuable information for my doctoral dissertation.
171
Appendix B: Study 1 – Diagrams and Correlations
For Figures 8 – 29, the horizontal axis denotes the number of respondents, whereas the
vertical axis denotes the corresponding scale for the questionnaire item (on a 5-point scale).
Figure 8: Study 1 - Indicators for Active Resistance to Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Active Resistance 1 Active Resistance 2 The Aggregate Indicator
Figure 9: Study 1 - Indicators for Passive Resistance to Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Passive Resistance 1 Passive Resistance 2 The Aggregate Indicator
172
Figure 10: Study 1 - Indicators for Active Support for Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Active Support 1 Active Support 2 Active Support 3 The Aggregate Indicator
Figure 11: Study 1 - Indicators for Passive Support for Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Passive Support 1 Passive Support 2 Passive Support 3 The Aggregate Indicator
173
Figure 12: Study 1 - Indicators for Perceived Organizational Support
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Perceived Organizational Support 1 Perceived Organizational Support 2 The Aggregate Indicator
Figure 13: Study 1 - Indicators for Perceived Procedural Justice
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Procedural Justice 1 Procedural Justice 2 Procedural Justice 3 The Aggregate Indicator
174
Figure 14: Study 1 - Indicators for Perceived Participation in Decision-Making
-
1.00
2.00
3.00
4.00
5.00
6.00
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Participation in Decision-Making 2 Participation in Decision-Making 3 The Aggregate Indicator
Figure 15: Study 1 - Indicators for Perceived Need for Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Need for Change 2 Need for Change 3 The Aggregate Indicator
175
Figure 16: Study 1 - Indicators for Attitude towards Organizational Change
-
1.00
2.00
3.00
4.00
5.00
6.00
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Attitude toward Change 1 Attitude toward Change 2 The Aggregate Indicator
Figure 17: Study 1 - Indicators for Fear of Known Consequences of a Change
0
1
2
3
4
5
6
1 4 7
10
13
16
19
22
25
28
31
34
37
40
43
46
49
52
55
58
61
64
67
70
73
76
79
82
85
88
Fear of known Consequences 1 Fear of known Consequences 2 The Aggregate Indicator
176
Figure 18: Study 1 - Indicators for Fear of Unknown Consequences of a Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Fear of unknown Consequences 2 Fear of unknown Consequences 3 The Aggregate Indicator
Figure 19: Study 1 - Indicators for Perceived Change in Power
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Change in Power 1 Change in Power 2 Change in Power 3 The Aggregate Indicator
177
Figure 20: Study 1 - Indicators for Perceived Change in Status
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Change in Status 1 Change in Status 2 The Aggregate Indicator
Figure 21: Study 1 - Indicators for Perceived Change in Pride
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Change in Pride 2 Change in Pride 3 The Aggregate Indicator
178
Figure 22: Study 1 - Indicators for Job Satisfaction
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Job Satisfaction 1 Job Satisfaction 3 The Aggregate Indicator
Figure 23: Study 1 - Indicators for Job Security
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Job Security 2 Job Security 3 The Aggregate Indicator
179
Figure 24: Study 1 - Indicators for Job Motivation
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Job Motivation 1 Job Motivation 2 Job Motivation 3 The Aggregate Indicator
Figure 25: Study 1 - Indicators for Perceived Employability
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Perceived Employability 2 Perceived Employability 3 The Aggregate Indicator
180
Figure 26: Study 1 - Indicators for Self-Confidence for Learning
-
1.00
2.00
3.00
4.00
5.00
6.00
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Self-Confidence for Learning 1 Self-Confidence for Learning 2 Self-Confidence for Learning 3 The Aggregate Indicator
Figure 27: Study 1 - Indicators for Affective Commitment
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Affective Commitment 1 Affective Commitment 2 The Aggregate Indicator
181
Figure 28: Study 1 - Indicators for Trust in Management
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Trust in Management 1 Trust in Management 2 The Aggregate Indicator
Figure 29: Study 1 - Indicators for Perceptions of Colleagues’ Resistance to Change
0
1
2
3
4
5
6
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31 33 35 37 39 41 43 45 47 49 51 53 55 57 59 61 63 65 67 69 71 73 75 77 79 81 83 85 87
Colleagues' Resistance 1 Colleagues' Resistance 2 The Aggregate Indicator
182
Table 13: Study 1 – Correlations for All Depen
dent Variables
n
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
1.
Active Resistance 1
88
1.00
2.
Active Resistance 2
88
.34†
1.00
3.
Active Resistance 3
88
.12
.12
1.00
4.
Passive Resistance 1
88
.25*
.15
.20
1.00
5.
Passive Resistance 2
88
.26*
.27*
-.15
.23*
1.00
6.
Passive Resistance 3
88
-.04
-.07
.10
.08
.07
1.00
7.
Active Support 1
88
.00
-.15
-.33†
-.02
.16
.05
1.00
8.
Active Support 2
88
-.06
-.09
-.44†
.01
.07
.08
.52†
1.00
9.
Active Support 3
88
.02
-.14
-.38†
.11
.20
-.04
.24*
.48†
1.00
10. Passive Support 1
88
.05
-.06
-.34†
.08
.16
.12
.37†
.58†
.34†
1.00
11. Passive Support 2
88
-.16
-.13
-.20
-.04
.06
.26*
.25*
.32†
.21
.43†
1.00
12. Passive Support 3
88
-.16
-.14
-.17
-.05
.04
.26*
.24*
.30†
.17
.38†
.55†
1.00
13. Age
86
.14
.01
.20
-.02
.01
-.06
-.15
-.15
-.12
-.19
-.09
-.02
1.00
14. Education
88
.02
-.04
.12
-.01
-.02
.08
-.06
-.10
.06
.02
.11
.12
-.03
1.00
15. Gender
88
-.11
-.05
.12
.08
-.04
-.02
.00
.00
.04
.13
.14
.06
-.11
-.20
1.00
16. Position Tenure
87
.15
-.07
.13
.07
-.03
-.01
-.13
-.11
-.12
-.07
-.18
-.17
.61†
-.17
.05
1.00
17. Organizational Tenure
85
.11
-.05
.22*
-.01
-.07
-.03
-.19
-.03
-.07
.02
-.02
.06
.82†
.03
-.01
.65†
1.00
18. Fam
ily Status
86
.20
.02
.09
.18
-.02
.08
-.06
-.08
.13
-.01
.21
.07
.39†
-.06
.08
.33†
.31†
1.00
19. Number of Children
88
.14
.02
-.07
-.02
.11
.05
-.05
.00
.17
.05
.20
.15
.41†
-.06
-.01
.23*
.27*
.67†
Notes:
Correlation typed in bold is significant at the 0.01 level or the 0.05 level (2-tailed). † p < .01, * p < .05.
183
Table 14: Study 1 – Correlations for Active Resistance
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
AR 1
1.00
2.
AR 2
.34†
1.00
3.
AR 3
.12
.12
1.00
4.
POS 1
.12
-.11
-.22*
1.00
5.
POS 2
-.03
-.01
-.12
.28†
1.00
6.
POS 3
-.13
.04
-.10
.17
.20
1.00
7.
Justice 1
-.04
.03
-.24*
.13
.08
.05
1.00
8.
Justice 2
.15
.08
-.26*
.26*
.00
-.08
.34†
1.00
9.
Justice 3
.08
.03
-.31†
.26*
.09
-.06
.15
.34†
1.00
10. Participation 1
.00
.09
-.16
.15
.31†
.03
.33†
.21
.41†
1.00
11. Participation 2
-.11
-.10
-.12
.04
.05
-.05
.20
.03
.27*
.22*
1.00
12. Participation 3
-.08
.01
.24*
.08
-.23*
-.03
-.05
-.23*
-.11
-.09
.24*
1.00
13. Need 1
.20
-.04
-.13
-.05
.18
.05
-.05
.22*
.08
-.02
-.17
-.52†
1.00
14. Need 2
.08
.03
-.04
.45†
.23*
.16
-.09
.01
.10
.15
.06
.12
-.10
1.00
15. Need 3
.04
-.01
-.15
.41†
.48†
.17
-.03
.10
.35†
.24*
.25*
-.05
.03
.56†
1.00
16. Attitude 1
-.05
-.02
.13
.05
-.02
-.06
-.19
-.03
.12
.02
.45†
.29†
-.11
.25*
.31†
1.00
17. Attitude 2
-.23*
-.28†
-.18
.23*
.02
-.03
-.14
.09
.07
.04
.18
.13
-.04
.28†
.34†
.44†
1.00
18. Attitude 3
-.05
-.21
-.22*
.01
.16
.13
-.05
-.09
-.11
-.07
-.18
-.26*
.31†
.02
.11
-.10
.08
1.00
19. Fear of known 1
.38†
.45†
.12
.07
-.07
-.07
-.05
.15
-.09
-.08
-.13
-.06
.10
.08
-.05
-.13
-.15
.00
1.00
20. Fear of known 2
.35†
.38†
-.01
.06
.03
.05
.17
.24*
.16
.15
-.03
-.15
.09
.10
-.02
-.18
-.32†
.05
.52†
1.00
21. Fear of known 3
.04
.06
.12
-.18
.05
.10
.09
-.35†
-.16
-.08
.01
.06
-.12
-.25*
-.11
-.05
-.19
.04
-.15
-.09
1.00
22. Age
.14
.01
.20
-.05
.10
.07
.01
-.11
-.07
.02
.00
-.06
.05
.00
-.04
-.07
-.17
-.17
-.19
-.11
.06
1.00
23. Education
.02
-.04
.12
.01
-.03
.21
-.11
.04
.03
.14
.09
.07
.04
.00
.08
.11
.16
.07
.12
.02
.01
-.03
1.00
24. Gender
-.11
-.05
.12
.04
-.07
-.05
-.05
.05
-.02
.09
.02
.10
-.01
.06
-.03
.11
.04
.11
-.09
-.04
-.13
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
184
Table 15: Study 1 – Correlations for Active Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
AR 1
1.00
2.
AR 2
.34†
1.00
3.
AR 3
.12
.12
1.00
4.
Fear of Un1
-.09
.00
.09
1.00
5.
Fear of Un 2
.20
.14
.24*
-.08
1.00
6.
Fear of Un 3
.16
.16
.10
.02
.44†
1.00
7.
Power 1
.05
.07
-.19
-.15
-.12
.04
1.00
8.
Power 2
.02
.15
.09
-.11
.09
.29†
.27*
1.00
9.
Power 3
.03
-.18
-.10
-.08
-.17
-.06
.42†
.31†
1.00
10. Status 1
.10
-.17
-.27*
-.08
-.29†
.00
.26*
.10
.25*
1.00
11. Status 2
-.01
-.12
-.28†
-.18
-.04
.04
.56†
.24*
.34†
.41†
1.00
12. Status 3
-.08
-.03
.00
-.14
-.31†
-.53†
-.17
-.46†
-.15
.00
-.24*
1.00
13. Pride 1
-.13
-.13
-.16
.11
-.06
-.10
-.24*
-.25*
-.17
-.10
-.17
.19
1.00
14. Pride 2
.13
.09
-.09
-.09
-.11
-.07
.45†
.25*
.36†
.14
.36†
-.13
-.44†
1.00
15. Pride 3
-.10
-.18
-.14
-.08
-.08
.19
.41†
.45†
.25*
.19
.48†
-.22*
-.05
.25*
1.00
16. Job Sat 1
.20
.13
-.13
-.03
.01
.23*
.37†
.34†
.26*
.12
.41†
-.25*
-.15
.28†
.34†
1.00
17. Job Sat 2
-.26*
-.10
.02
-.02
-.13
-.22*
-.23*
-.14
-.07
-.07
-.24*
.12
.19
-.20
-.22*
-.03
1.00
18. Job Sat 3
.12
.14
-.06
.08
-.09
-.09
.02
-.29†
-.13
-.03
.10
.04
-.05
.18
-.13
.21*
.07
1.00
19. Job Security 1
-.06
-.03
-.04
-.24*
-.13
.03
.27†
-.02
.05
.17
.28†
.20
-.14
.16
.16
.28†
-.13
.14
1.00
20. Job Security 2
.13
-.02
.03
-.13
.03
.08
.10
.10
.15
.12
.15
-.17
-.27*
.27†
.06
.20
.03
.21*
.14
1.00
21. Job Security 3
.22*
.01
-.08
.09
-.10
-.12
.18
-.02
.40†
.17
.19
-.01
-.22*
.22*
.08
.11
-.21
.06
.16
.38†
1.00
22. Age
.14
.01
.20
-.05
.14
.05
.02
.01
.08
-.10
-.10
.01
-.05
.04
.04
.20
.15
-.05
-.19
.09
-.08
1.00
23. Education
.02
-.04
.12
.03
.14
-.02
.13
-.09
-.04
.02
.08
-.04
.07
.09
.02
-.03
.05
-.01
-.04
.02
.02
-.03
1.00
24. Gender
-.11
-.05
.12
.09
.07
.13
.11
.07
-.04
.14
.11
-.01
-.22*
.09
.03
-.03
-.13
.16
.22*
-.07
-.04
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
185
Table 16: Study 1 – Correlations for Active Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
AR 1
1.00
2.
AR 2
.34†
1.00
3.
AR 3
.12
.12
1.00
4.
Job M
otivation 1
.30†
.07
.03
1.00
5.
Job M
otivation 2
.12
.08
.05
.59†
1.00
6.
Job M
otivation 3
.10
.17
.05
.54†
.57†
1.00
7.
Employability 1
.05
.08
.20
.20
.31†
.30†
1.00
8.
Employability 2
.07
.13
.04
.21*
.25*
.18
.19
1.00
9.
Employability 3
-.20
.02
-.17
-.25*
-.12
-.16
-.05
.25*
1.00
10. Learning 1
.09
.10
.03
.53†
.65†
.59†
.38†
.21*
-.04
1.00
11. Learning 2
.17
.08
.09
.51†
.57†
.51†
.60†
.10
-.09
.70†
1.00
12. Learning 3
.13
.05
.05
.45†
.46†
.40†
.40†
.26*
.10
.68†
.60†
1.00
13. Commitment 1
.17
.17
.07
.31†
.52†
.57†
.23*
.09
-.25*
.54†
.50†
.32†
1.00
14. Commitment 2
.26*
.13
.06
.41†
.39†
.36†
.25*
.06
-.20
.52†
.35†
.34†
.41†
1.00
15. Commitment 3
.16
-.02
-.15
.26*
.30†
.27*
.22*
.04
-.09
.44†
.42†
.35†
.28†
.48†
1.00
16. Trust 1
.16
.05
-.10
.14
.22*
.20
.16
-.04
-.11
.40†
.28†
.30†
.39†
.41†
.33†
1.00
17. Trust 2
.08
.01
-.14
.17
.25*
.19
.19
-.06
-.04
.42†
.35†
.32†
.33†
.34†
.41†
.90†
1.00
18. Trust 3
.08
-.02
-.09
.30†
.40†
.23*
.28†
.19
.12
.45†
.48†
.50†
.31†
.35†
.57†
.37†
.45†
1.00
19. Col_Resist 1
.18
.18
.31†
.30†
.38†
.43†
.32†
.04
-.32†
.32†
.36†
.21*
.49†
.42†
.17
.16
.06
.08
1.00
20. Col_Support
.10
-.10
-.31†
.04
-.16
-.18
-.04
.11
.03
-.01
-.08
.03
-.12
.05
.25*
.29†
.22*
.24*
-.14
1.00
21. Col_Resist 2
.12
.38†
.22*
.21*
.19
.45†
.27*
-.01
-.41†
.26*
.21*
.01
.43†
.35†
.11
.13
.06
-.03
.60†
-.14
1.00
22. Age
.14
.01
.20
-.03
-.01
-.07
.14
.00
-.10
.01
.09
.04
.08
.19
.09
.09
.00
.02
.20
.01
.20
1.00
23. Education
.02
-.04
.12
.02
.03
-.03
-.01
-.09
-.04
.08
.11
.11
.01
.04
.09
-.04
.02
.06
-.07
-.02
.01
-.03
1.00
24. Gender
-.11
-.05
.12
-.04
.16
.13
.01
.15
-.06
.10
-.03
.05
.13
-.03
-.07
-.06
-.06
-.09
.19
-.08
.08
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
186
Table 17: Study 1 – Correlations for Passive Resistance
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
.23*
1.00
3.
PR 3
.08
.07
1.00
4.
POS 1
.22*
.25*
-.05
1.00
5.
POS 2
.19
.08
-.03
.28†
1.00
6.
POS 3
-.13
.01
-.38†
.17
.20
1.00
7.
Justice 1
.07
.16
.02
.13
.08
.05
1.00
8.
Justice 2
.02
.13
.06
.26*
.00
-.08
.34†
1.00
9.
Justice 3
.12
.25*
-.04
.26*
.09
-.06
.15
.34†
1.00
10. Participation 1
.08
.30†
-.15
.15
.31†
.03
.33†
.21
.41†
1.00
11. Participation 2
.04
-.09
.12
.04
.05
-.05
.20
.03
.27*
.22*
1.00
12. Participation 3
.04
-.20
.08
.08
-.23*
-.03
-.05
-.23*
-.11
-.09
.24*
1.00
13. Need 1
.02
.06
.08
-.05
.18
.05
-.05
.22*
.08
-.02
-.17
-.52†
1.00
14. Need 2
.19
.13
-.14
.45†
.23*
.16
-.09
.01
.10
.15
.06
.12
-.10
1.00
15. Need 3
.12
.02
-.13
.41†
.48†
.17
-.03
.10
.35†
.24*
.25*
-.05
.03
.56†
1.00
16. Attitude 1
.19
-.12
.18
.05
-.02
-.06
-.19
-.03
.12
.02
.45†
.29†
-.11
.25*
.31†
1.00
17. Attitude 2
-.01
-.01
.00
.23*
.02
-.03
-.14
.09
.07
.04
.18
.13
-.04
.28†
.34†
.44†
1.00
18. Attitude 3
-.04
.00
-.01
.01
.16
.13
-.05
-.09
-.11
-.07
-.18
-.26*
.31†
.02
.11
-.10
.08
1.00
19. Fear of Known 1
.28†
.25*
.17
.07
-.07
-.07
-.05
.15
-.09
-.08
-.13
-.06
.10
.08
-.05
-.13
-.15
.00
1.00
20. Fear of Known 2
.37†
.37†
-.06
.06
.03
.05
.17
.24*
.16
.15
-.03
-.15
.09
.10
-.02
-.18
-.32†
.05
.52†
1.00
21. Fear of Known 3
-.08
-.24*
-.27
-.18
.05
.10
.09
-.35†
-.16
-.08
.01
.06
-.12
-.25*
-.11
-.05
-.19
.04
-.15
-.09
1.00
22. Age
-.02
.01
-.06
-.05
.10
.07
.01
-.11
-.07
.02
.00
-.06
.05
.00
-.04
-.07
-.17
-.17
-.19
-.11
.06
1.00
-.03
23. Education
-.01
-.02
.08
.01
-.03
.21
-.11
.04
.03
.14
.09
.07
.04
.00
.08
.11
.16
.07
.12
.02
.01
-.03
1.00
24. Gender
.08
-.04
-.02
.04
-.07
-.05
-.05
.05
-.02
.09
.02
.10
-.01
.06
-.03
.11
.04
.11
-.09
-.04
-.13
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
187
Table 18: Study 1 – Correlations for Passive Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
.23*
1.00
3.
PR 3
.08
.07
1.00
4.
Fear of Un 1
-.24*
-.09
.12
1.00
5.
Fear of Un 2
.29†
.17
-.11
-.08
1.00
6.
Fear of Un 3
.23*
.40†
-.12
.02
.44†
1.00
7.
Power 1
.09
.28†
-.19
-.15
-.12
.04
1.00
8.
Power 2
.13
.38†
-.08
-.11
.09
.29†
.27*
1.00
9.
Power 3
.11
.18
-.07
-.08
-.17
-.06
.42†
.31†
1.00
10. Status 1
-.03
.21*
.22*
-.08
-.29†
.00
.26*
.10
.25*
1.00
11. Status 2
.04
.22*
.08
-.18
-.04
.04
.56†
.24*
.34†
.41†
1.00
12. Status 3
-.32†
-.28†
.12
-.14
-.31†
-.53†
-.17
-.46†
-.15
.00
-.24*
1.00
13. Pride 1
-.31†
-.11
-.04
.11
-.06
-.10
-.24*
-.25*
-.17
-.10
-.17
.19
1.00
14. Pride 2
.08
.09
-.05
-.09
-.11
-.07
.45†
.25*
.36†
.14
.36†
-.13
-.44†
1.00
15. Pride 3
.01
.28†
.00
-.08
-.08
.19
.41†
.45†
.25*
.19
.48†
-.22*
-.05
.25*
1.00
16. Job Sat 1
.17
.35†
.03
-.03
.01
.23*
.37†
.34†
.26*
.12
.41†
-.25*
-.15
.28†
.34†
1.00
17. Job Sat 2
-.01
-.17
.06
-.02
-.13
-.22*
-.23*
-.14
-.07
-.07
-.24*
.12
.19
-.20
-.22*
-.03
1.00
18. Job Sat 3
.10
-.14
.20
.08
-.09
-.09
.02
-.29†
-.13
-.03
.10
.04
-.05
.18
-.13
.21*
.07
1.00
19. Job Security 1
.24*
.26*
.16
-.24*
-.13
.03
.27†
-.02
.05
.17
.28†
.20
-.14
.16
.16
.28†
-.13
.14
1.00
20. Job Security 2
.23*
.13
.00
-.13
.03
.08
.10
.10
.15
.12
.15
-.17
-.27*
.27†
.06
.20
.03
.21*
.14
1.00
21. Job Security 3
.09
.24*
.18
.09
-.10
-.12
.18
-.02
.40†
.17
.19
-.01
-.22*
.22*
.08
.11
-.21
.06
.16
.38†
1.00
22. Age
-.02
.01
-.06
-.05
.14
.05
.02
.01
.08
-.10
-.10
.01
-.05
.04
.04
.20
.15
-.05
-.19
.09
-.08
1.00
23. Education
-.01
-.02
.08
.03
.14
-.02
.13
-.09
-.04
.02
.08
-.04
.07
.09
.02
-.03
.05
-.01
-.04
.02
.02
-.03
1.00
24. Gender
.08
-.04
-.02
.09
.07
.13
.11
.07
-.04
.14
.11
-.01
-.22*
.09
.03
-.03
-.13
.16
.22*
-.07
-.04
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
188
Table 19: Study 1 – Correlations for Passive Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
.23*
1.00
3.
PR 3
.08
.07
1.00
4.
Job M
otivation 1
.10
.01
.07
1.00
5.
Job M
otivation 2
.08
.07
.00
.59†
1.00
6.
Job M
otivation 3
.21
.05
.27*
.54†
.57†
1.00
7.
Employability 1
.26*
.04
.00
.20
.31†
.30†
1.00
8.
Employability 2
-.03
.24*
.09
.21*
.25*
.18
.19
1.00
9.
Employability 3
-.21*
.04
.01
-.25*
-.12
-.16
-.05
.25*
1.00
10. Learning 1
.06
.04
.01
.53†
.65†
.59†
.38†
.21*
-.04
1.00
11. Learning 2
.16
.09
.06
.51†
.57†
.51†
.60†
.10
-.09
.70†
1.00
12. Learning 3
-.10
.04
-.02
.45†
.46†
.40†
.40†
.26*
.10
.68†
.60†
1.00
13. Commitment 1
.11
.10
.17
.31†
.52†
.57†
.23*
.09
-.25*
.54†
.50†
.32†
1.00
14. Commitment 2
.14
-.09
-.05
.41†
.39†
.36†
.25*
.06
-.20
.52†
.35†
.34†
.41†
1.00
15. Commitment 3
.09
.24*
-.08
.26*
.30†
.27*
.22*
.04
-.09
.44†
.42†
.35†
.28†
.48†
1.00
16. Trust 1
.11
-.04
-.03
.14
.22*
.20
.16
-.04
-.11
.40†
.28†
.30†
.39†
.41†
.33†
1.00
17. Trust 2
.06
.01
-.10
.17
.25*
.19
.19
-.06
-.04
.42†
.35†
.32†
.33†
.34†
.41†
.90†
1.00
18. Trust 3
.04
.31†
.06
.30†
.40†
.23*
.28†
.19
.12
.45†
.48†
.50†
.31†
.35†
.57†
.37†
.45†
1.00
19. Col_Resist 1
.33†
.00
.16
.30†
.38†
.43†
.32†
.04
-.32†
.32†
.36†
.21*
.49†
.42†
.17
.16
.06
.08
1.00
20. Col_Support
-.13
.06
-.15
.04
-.16
-.18
-.04
.11
.03
-.01
-.08
.03
-.12
.05
.25*
.29†
.22*
.24*
-.14
1.00
21. Col_Resist 2
.23*
.11
.07
.21*
.19
.45†
.27*
-.01
-.41†
.26*
.21*
.01
.43†
.35†
.11
.13
.06
-.03
.60†
-.14
1.00
22. Age
-.02
.01
-.06
-.03
-.01
-.07
.14
.00
-.10
.01
.09
.04
.08
.19
.09
.09
.00
.02
.20
.01
.20
1.00
23. Education
-.01
-.02
.08
.02
.03
-.03
-.01
-.09
-.04
.08
.11
.11
.01
.04
.09
-.04
.02
.06
-.07
-.02
.01
-.03
1.00
24. Gender
.08
-.04
-.02
-.04
.16
.13
.01
.15
-.06
.10
-.03
.05
.13
-.03
-.07
-.06
-.06
-.09
.19
-.08
.08
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
189
Table 20: Study 1 – Correlations for Active Support
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
Active Support 1
1.00
2.
Active Support 2
.52†
1.00
3.
Active Support 3
.24*
.48†
1.00
4.
POS 1
.19
.16
.22*
1.00
5.
POS 2
.00
.01
-.08
.28†
1.00
6.
POS 3
.08
-.06
-.07
.17
.20
1.00
7.
Justice 1
.46†
.54†
.32†
.13
.08
.05
1.00
8.
Justice 2
.23*
.36†
.31†
.26*
.00
-.08
.34†
1.00
9.
Justice 3
.13
.36†
.64†
.26*
.09
-.06
.15
.34†
1.00
10. Participation 1
.10
.34†
.40†
.15
.31†
.03
.33†
.21
.41†
1.00
11. Participation 2
.33†
.31†
.22*
.04
.05
-.05
.20
.03
.27*
.22*
1.00
12. Participation 3
.04
.02
-.08
.08
-.23*
-.03
-.05
-.23*
-.11
-.09
.24*
1.00
13. Need 1
.01
-.01
-.03
-.05
.18
.05
-.05
.22*
.08
-.02
-.17
-.52†
1.00
14. Need 2
.06
.04
.10
.45†
.23*
.16
-.09
.01
.10
.15
.06
.12
-.10
1.00
15. Need 3
.08
.14
.22*
.41†
.48†
.17
-.03
.10
.35†
.24*
.25*
-.05
.03
.56†
1.00
16. Attitude 1
.02
.04
.09
.05
-.02
-.06
-.19
-.03
.12
.02
.45†
.29†
-.11
.25*
.31†
1.00
17. Attitude 2
.10
.11
.05
.23*
.02
-.03
-.14
.09
.07
.04
.18
.13
-.04
.28†
.34†
.44†
1.00
18. Attitude 3
.02
-.06
-.11
.01
.16
.13
-.05
-.09
-.11
-.07
-.18
-.26*
.31†
.02
.11
-.10
.08
1.00
19. Fear of Known 1
.16
-.05
-.21
.07
-.07
-.07
-.05
.15
-.09
-.08
-.13
-.06
.10
.08
-.05
-.13
-.15
.00
1.00
20. Fear of Known 2
.04
.02
.06
.06
.03
.05
.17
.24*
.16
.15
-.03
-.15
.09
.10
-.02
-.18
-.32†
.05
.52†
1.00
21. Fear of Known 3
14
-.17
-.14
-.18
.05
.10
.09
-.35†
-.16
-.08
.01
.06
-.12
-.25*
-.11
-.05
-.19
.04
-.15
-.09
1.00
22. Age
-.15
-.15
-.12
-.05
.10
.07
.01
-.11
-.07
.02
.00
-.06
.05
.00
-.04
-.07
-.17
-.17
-.19
-.11
.06
1.00
23. Education
-.06
-.10
.06
.01
-.03
.21
-.11
.04
.03
.14
.09
.07
.04
.00
.08
.11
.16
.07
.12
.02
.01
-.03
1.00
24. Gender
.00
.00
.04
.04
-.07
-.05
-.05
.05
-.02
.09
.02
.10
-.01
.06
-.03
.11
.04
.11
-.09
-.04
-.13
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
190
Table 21: Study 1 – Correlations for Active Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
Active Support 1
1.00
2.
Active Support 2
.52†
1.00
3.
Active Support 3
.24*
.48†
1.00
4.
Fear of Un 1
-.16
-.20
-.03
1.00
5.
Fear of Un 2
-.15
-.13
.02
-.08
1.00
6.
Fear of Un 3
-.07
-.01
.00
.02
.44†
1.00
7.
Power 1
.25*
.17
.29†
-.15
-.12
.04
1.00
8.
Power 2
.14
.02
.11
-.11
.09
.29†
.27*
1.00
9.
Power 3
.05
.11
.25*
-.08
-.17
-.06
.42†
.31†
1.00
10. Status 1
.22*
.33†
.32†
-.08
-.29†
.00
.26*
.10
.25*
1.00
11. Status 2
.21
.37†
.33†
-.18
-.04
.04
.56†
.24*
.34†
.41†
1.00
12. Status 3
-.02
-.07
-.20
-.14
-.31†
-.53†
-.17
-.46†
-.15
.00
-.24*
1.00
13. Pride 1
.00
.00
.01
.11
-.06
-.10
-.24*
-.25*
-.17
-.10
-.17
.19
1.00
14. Pride 2
-.04
-.02
.10
-.09
-.11
-.07
.45†
.25*
.36†
.14
.36†
-.13
-.44†
1.00
15. Pride 3
.24*
.24*
.17
-.08
-.08
.19
.41†
.45†
.25*
.19
.48†
-.22*
-.05
.25*
1.00
16. Job Sat 1
.12
.08
.18
-.03
.01
.23*
.37†
.34†
.26*
.12
.41†
-.25*
-.15
.28†
.34†
1.00
17. Job Sat 2
-.12
-.16
-.12
-.02
-.13
-.22*
-.23*
-.14
-.07
-.07
-.24*
.12
.19
-.20
-.22*
-.03
1.00
18. Job Sat 3
-.03
-.07
-.13
.08
-.09
-.09
.02
-.29†
-.13
-.03
.10
.04
-.05
.18
-.13
.21*
.07
1.00
19. Job Security 1
.23*
.12
-.01
-.24*
-.13
.03
.27†
-.02
.05
.17
.28†
.20
-.14
.16
.16
.28†
-.13
.14
1.00
20. Job Security 2
.12
.01
.00
-.13
.03
.08
.10
.10
.15
.12
.15
-.17
-.27*
.27†
.06
.20
.03
.21*
.14
1.00
21. Job Security 3
.10
.06
.02
.09
-.10
-.12
.18
-.02
.40†
.17
.19
-.01
-.22*
.22*
.08
.11
-.21
.06
.16
.38†
1.00
22. Age
-.15
-.15
-.12
-.05
.14
.05
.02
.01
.08
-.10
-.10
.01
-.05
.04
.04
.20
.15
-.05
-.19
.09
-.08
1.00
23. Education
-.06
-.10
.06
.03
.14
-.02
.13
-.09
-.04
.02
.08
-.04
.07
.09
.02
-.03
.05
-.01
-.04
.02
.02
-.03
1.00
24. Gender
.00
.00
.04
.09
.07
.13
.11
.07
-.04
.14
.11
-.01
-.22*
.09
.03
-.03
-.13
.16
.22*
-.07
-.04
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
191
Table 22: Study 1 – Correlations for Active Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
Active Support 1
1.00
2.
Active Support 2
.52†
1.00
3.
Active Support 3
.24*
.48†
1.00
4.
Job M
otivation 1
.06
-.02
-.01
1.00
5.
Job M
otivation 2
.03
.00
-.04
.59†
1.00
6.
Job M
otivation 3
.08
.05
-.01
.54†
.57†
1.00
7.
Employability 1
.03
.00
.06
.20
.31†
.30†
1.00
8.
Employability 2
.12
.06
.12
.21*
.25*
.18
.19
1.00
9.
Employability 3
.02
-.03
.02
-.25*
-.12
-.16
-.05
.25*
1.00
10. Learning 1
.06
.04
-.06
.53†
.65†
.59†
.38†
.21*
-.04
1.00
11. Learning 2
.10
.02
.04
.51†
.57†
.51†
.60†
.10
-.09
.70†
1.00
12. Learning 3
.06
.00
-.03
.45†
.46†
.40†
.40†
.26*
.10
.68†
.60†
1.00
13. Commitment 1
-.15
.04
-.01
.31†
.52†
.57†
.23*
.09
-.25*
.54†
.50†
.32†
1.00
14. Commitment 2
-.09
-.11
-.11
.41†
.39†
.36†
.25*
.06
-.20
.52†
.35†
.34†
.41†
1.00
15. Commitment 3
.06
-.04
.12
.26*
.30†
.27*
.22*
.04
-.09
.44†
.42†
.35†
.28†
.48†
1.00
16. Trust in M
gmt 1
.21
.32†
.10
.14
.22*
.20
.16
-.04
-.11
.40†
.28†
.30†
.39†
.41†
.33†
1.00
17. Trust in M
gmt 2
.21
.30†
.07
.17
.25*
.19
.19
-.06
-.04
.42†
.35†
.32†
.33†
.34†
.41†
.90†
1.00
18. Trust in M
gmt 3
.17
.09
.17
.30†
.40†
.23*
.28†
.19
.12
.45†
.48†
.50†
.31†
.35†
.57†
.37†
.45†
1.00
19. Col_Resist 1
-.28†
-.20
-.08
.30†
.38†
.43†
.32†
.04
-.32†
.32†
.36†
.21*
.49†
.42†
.17
.16
.06
.08
1.00
20. Col_Support
.22*
.38†
.39†
.04
-.16
-.18
-.04
.11
.03
-.01
-.08
.03
-.12
.05
.25*
.29†
.22*
.24*
-.14
1.00
21. Col_Resist 2
-.24*
-.14
-.01
.21*
.19
.45†
.27*
-.01
-.41†
.26*
.21*
.01
.43†
.35†
.11
.13
.06
-.03
.60†
-.14
1.00
22. Age
-.15
-.15
-.12
-.03
-.01
-.07
.14
.00
-.10
.01
.09
.04
.08
.19
.09
.09
.00
.02
.20
.01
.20
1.00
23. Education
-.06
-.10
.06
.02
.03
-.03
-.01
-.09
-.04
.08
.11
.11
.01
.04
.09
-.04
.02
.06
-.07
-.02
.01
-.03
1.00
24. Gender
.00
.00
.04
-.04
.16
.13
.01
.15
-.06
.10
-.03
.05
.13
-.03
-.07
-.06
-.06
-.09
.19
-.08
.08
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
192
Table 23: Study 1 – Correlations for Passive Support
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PS 1
1.00
2.
PS 2
.43†
1.00
3.
PS 3
.38†
.55†
1.00
4.
POS 1
.29†
.24*
.35†
1.00
5.
POS 2
-.06
.23*
.28†
.28†
1.00
6.
POS 3
-.21*
-.11
.09
.17
.20
1.00
7.
Justice 1
.36†
.16
.12
.13
.08
.05
1.00
8.
Justice 2
.32†
.19
.14
.26*
.00
-.08
.34†
1.00
9.
Justice 3
.36†
.15
.25*
.26*
.09
-.06
.15
.34†
1.00
10. Participation 1
.24*
.26*
.19
.15
.31†
.03
.33†
.21
.41†
1.00
11. Participation 2
.16
.37†
.31†
.04
.05
-.05
.20
.03
.27*
.22*
1.00
12. Participation 3
.07
.02
.12
.08
-.23*
-.03
-.05
-.23*
-.11
-.09
.24*
1.00
13. Need 1
.06
.10
.12
-.05
.18
.05
-.05
.22*
.08
-.02
-.17
-.52†
1.00
14. Need 2
.05
.14
.26*
.45†
.23*
.16
-.09
.01
.10
.15
.06
.12
-.10
1.00
15. Need 3
.12
.27*
.31†
.41†
.48†
.17
-.03
.10
.35†
.24*
.25*
-.05
.03
.56†
1.00
16. Attitude 1
.02
.29†
.19
.05
-.02
-.06
-.19
-.03
.12
.02
.45†
.29†
-.11
.25*
.31†
1.00
17. Attitude 2
.26*
.40†
.20
.23*
.02
-.03
-.14
.09
.07
.04
.18
.13
-.04
.28†
.34†
.44†
1.00
18. Attitude 3
-.07
.05
.00
.01
.16
.13
-.05
-.09
-.11
-.07
-.18
-.26*
.31†
.02
.11
-.10
.08
1.00
19. Fear of Known 1
.14
-.08
-.14
.07
-.07
-.07
-.05
.15
-.09
-.08
-.13
-.06
.10
.08
-.05
-.13
-.15
.00
1.00
20. Fear of Known 2
.09
-.12
-.11
.06
.03
.05
.17
.24*
.16
.15
-.03
-.15
.09
.10
-.02
-.18
-.32†
.05
.52†
1.00
21. Fear of Known 3
37†
-.27*
-.36†
-.18
.05
.10
.09
-.35†
-.16
-.08
.01
.06
-.12
-.25*
-.11
-.05
-.19
.04
-.15
-.09
1.00
22. Age
-.19
-.09
-.02
-.05
.10
.07
.01
-.11
-.07
.02
.00
-.06
.05
.00
-.04
-.07
-.17
-.17
-.19
-.11
.06
1.00
23. Education
.02
.11
.12
.01
-.03
.21
-.11
.04
.03
.14
.09
.07
.04
.00
.08
.11
.16
.07
.12
.02
.01
-.03
1.00
24. Gender
.13
.14
.06
.04
-.07
-.05
-.05
.05
-.02
.09
.02
.10
-.01
.06
-.03
.11
.04
.11
-.09
-.04
-.13
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
193
Table 24: Study 1 – Correlations for Passive Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
.43†
1.00
3.
PR 3
.38†
.55†
1.00
4.
Fear of Un 1
-.16
-.19
-.12
1.00
5.
Fear of Un 2
-.18
-.19
-.07
-.08
1.00
6.
Fear of Un 3
.04
-.04
-.06
.02
.44†
1.00
7.
Power 1
.26*
.10
.23*
-.15
-.12
.04
1.00
8.
Power 2
.14
.05
.06
-.11
.09
.29†
.27*
1.00
9.
Power 3
.25*
.01
.07
-.08
-.17
-.06
.42†
.31†
1.00
10. Status 1
.40†
.27†
.22*
-.08
-.29†
.00
.26*
.10
.25*
1.00
11. Status 2
.39†
.22*
.40†
-.18
-.04
.04
.56†
.24*
.34†
.41†
1.00
12. Status 3
-.10
.18
.15
-.14
-.31†
-.53†
-.17
-.46†
-.15
.00
-.24*
1.00
13. Pride 1
-.20
-.10
-.07
.11
-.06
-.10
-.24*
-.25*
-.17
-.10
-.17
.19
1.00
14. Pride 2
.36†
.24*
.18
-.09
-.11
-.07
.45†
.25*
.36†
.14
.36†
-.13
-.44†
1.00
15. Pride 3
.25*
.27†
.22*
-.08
-.08
.19
.41†
.45†
.25*
.19
.48†
-.22*
-.05
.25*
1.00
16. Job Satis 1
.21*
.04
.15
-.03
.01
.23*
.37†
.34†
.26*
.12
.41†
-.25*
-.15
.28†
.34†
1.00
17. Job Satis 2
-.15
-.13
-.16
-.02
-.13
-.22*
-.23*
-.14
-.07
-.07
-.24*
.12
.19
-.20
-.22*
-.03
1.00
18. Job Sat 3
.16
.14
.15
.08
-.09
-.09
.02
-.29†
-.13
-.03
.10
.04
-.05
.18
-.13
.21*
.07
1.00
19. Job Security 1
.32†
.36†
.36†
-.24*
-.13
.03
.27†
-.02
.05
.17
.28†
.20
-.14
.16
.16
.28†
-.13
.14
1.00
20. Job Security 2
.13
.20
.32†
-.13
.03
.08
.10
.10
.15
.12
.15
-.17
-.27*
.27†
.06
.20
.03
.21*
.14
1.00
21. Job Security 3
.21*
.17
.19
.09
-.10
-.12
.18
-.02
.40†
.17
.19
-.01
-.22*
.22*
.08
.11
-.21
.06
.16
.38†
1.00
22. Age
-.19
-.09
-.02
-.05
.14
.05
.02
.01
.08
-.10
-.10
.01
-.05
.04
.04
.20
.15
-.05
-.19
.09
-.08
1.00
23. Education
.02
.11
.12
.03
.14
-.02
.13
-.09
-.04
.02
.08
-.04
.07
.09
.02
-.03
.05
-.01
-.04
.02
.02
-.03
1.00
24. Gender
.13
.14
.06
.09
.07
.13
.11
.07
-.04
.14
.11
-.01
-.22*
.09
.03
-.03
-.13
.16
.22*
-.07
-.04
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
194
Table 25: Study 1 – Correlations for Passive Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PS 1
1.00
2.
PS 2
.43†
1.00
3.
PS 3
.38†
.55†
1.00
4.
Job M
otivation 1
-.03
.07
.15
1.00
5.
Job M
otivation 2
.12
.22*
.11
.59†
1.00
6.
Job M
otivation 3
.14
.21
.15
.54†
.57†
1.00
7.
Employability 1
-.01
.05
.15
.20
.31†
.30†
1.00
8.
Employability 2
.12
.12
.24*
.21*
.25*
.18
.19
1.00
9.
Employability 3
-.03
-.06
.06
-.25*
-.12
-.16
-.05
.25*
1.00
10. Learning 1
.11
.29†
.30†
.53†
.65†
.59†
.38†
.21*
-.04
1.00
11. Learning 2
.02
.20
.23*
.51†
.57†
.51†
.60†
.10
-.09
.70†
1.00
12. Learning 3
.00
.12
.24*
.45†
.46†
.40†
.40†
.26*
.10
.68†
.60†
1.00
13. Commitment 1
.20
.24*
.07
.31†
.52†
.57†
.23*
.09
-.25*
.54†
.50†
.32†
1.00
14. Commitment 2
.03
.06
.13
.41†
.39†
.36†
.25*
.06
-.20
.52†
.35†
.34†
.41†
1.00
15. Commitment 3
.16
.27*
.27*
.26*
.30†
.27*
.22*
.04
-.09
.44†
.42†
.35†
.28†
.48†
1.00
16. Trust in M
gmt 1
.36†
.33†
.32†
.14
.22*
.20
.16
-.04
-.11
.40†
.28†
.30†
.39†
.41†
.33†
1.00
17. Trust in M
gmt 2
.31†
.27*
.28†
.17
.25*
.19
.19
-.06
-.04
.42†
.35†
.32†
.33†
.34†
.41†
.90†
1.00
18. Trust in M
gmt 3
.22*
.32†
.41†
.30†
.40†
.23*
.28†
.19
.12
.45†
.48†
.50†
.31†
.35†
.57†
.37†
.45†
1.00
19. Col_Resist 1
-.04
.09
-.09
.30†
.38†
.43†
.32†
.04
-.32†
.32†
.36†
.21*
.49†
.42†
.17
.16
.06
.08
1.00
20. Col_Support
.33†
.25*
.34†
.04
-.16
-.18
-.04
.11
.03
-.01
-.08
.03
-.12
.05
.25*
.29†
.22*
.24*
-.14
1.00
21. Col_Resist 2
.02
.02
.00
.21*
.19
.45†
.27*
-.01
-.41†
.26*
.21*
.01
.43†
.35†
.11
.13
.06
-.03
.60†
-.14
1.00
22. Age
-.19
-.09
-.02
-.03
-.01
-.07
.14
.00
-.10
.01
.09
.04
.08
.19
.09
.09
.00
.02
.20
.01
.20
1.00
23. Education
.02
.11
.12
.02
.03
-.03
-.01
-.09
-.04
.08
.11
.11
.01
.04
.09
-.04
.02
.06
-.07
-.02
.01
-.03
1.00
24. Gender
.13
.14
.06
-.04
.16
.13
.01
.15
-.06
.10
-.03
.05
.13
-.03
-.07
-.06
-.06
-.09
.19
-.08
.08
-.11
-.20
Notes:
N = 88 (except for age, n = 86). Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed).
† p < .01, * p < .05.
195
Appendix C: Study 2 – Diagrams and Correlations
For Figures 30 – 51, the horizontal axis denotes the number of respondents, whereas the
vertical axis denotes the corresponding scale for the questionnaire item (on a 5-point scale).
Figure 30: Study 2 - Indicators for Active Resistance to Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Active Resistance 1 Active Resistance 3 The Aggregate Indicator
Figure 31: Study 2 - Indicators for Passive Resistance to Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Passive Resistance 2 Passive Resistance 3 The Aggregate Indicator
196
Figure 32: Study 2 - Active Support for Change Indicators
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Active Support 1 Active Support 2 The Aggregate Indicator
Figure 33: Study 2 - Indicators for Passive Support for Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Passive Support 1 Passive Support 2 The Aggregate Indicator
197
Figure 34: Study 2 - Indicators for Perceived Organizational Support
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Perceived Organizational Support 1 Perceived Organizational Support 2 The Aggregate Indicator
Figure 35: Study 2 - Indicators for Perceived Procedural Justice
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Procedural Justice 1 Procedural Justice 3 The Aggregate Indicator
198
Figure 36: Study 2 - Indicators for Perceived Participation in Decision-Making
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Participation 1 Participation 2 The Aggregate Indicator
Figure 37: Study 2 - Indicators for Perceived Need for Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Need for Change 2 Need for Change 3 The Aggregate Indicator
199
Figure 38: Study 2 - Indicators for Attitude towards Organizational Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Attitude towards Change 1 Attitude towards Change 2 The Aggregate Indicator
Figure 39: Study 2 - Indicator for Fear of Known Consequences of a Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Fear of known Consequences 2 Fear of known Consequences 3 The Aggregate Indicator
200
Figure 40: Study 2 - Indicators for Fear of Unknown Consequences of a Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Fear of unknown Consequences 2 Fear of unknown Consequences 3 The Aggregate Indicator
Figure 41: Study 2 - Indicator for Perceived Change in Power
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Change in Power 2 Change in Power 3 The Aggregate Indicator
201
Figure 42: Study 2 - Indicators for Perceived Change in Status
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Change in Status 1 Change in Status 2 The Aggregate Indicator
Figure 43: Study 2 - Indicators for Perceived Change in Pride
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Change in Pride 1 Change in Pride 2 The Aggregate Indicator
202
Figure 44: Study 2 - Indicators for Job Satisfaction
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Job Satisfaction 2 Job Satisfaction 3 The Aggregate Indicator
Figure 45: Study 2 - Indicators for Job Security
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Job Security 1 Job Security 2 The Aggregate Indicator
203
Figure 46: Study 2 - Indicators for Job Motivation
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Job Motivation 2 Job Motivation 3 The Aggregate Indicator
Figure 47: Study 2 - Indicators for Perceived Employability
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Perceived Employability 1 Perceived Employability 2 The Aggregate Indicator
204
Figure 48: Study 2 - Indicators for Self-Confidence for Learning
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Self-Confidence for Learning 1 Self-Confidence for Learning 3 The Aggregate Indicator
Figure 49: Study 2 - Indicators for Affective Commitment
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Affective Commitment 1 Affective Commitment 2 The Aggregate Indicator
205
Figure 50: Study 2 - Indicators for Trust in Management
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Trust in Management 1 Trust in Management 3 The Aggregate Indicator
Figure 51: Study 2 - Indicators for Perceptions of Colleagues’ Resistance to Change
0
1
2
3
4
5
6
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205
Colleagues' Resistance 1 Colleagues' Resistance 2 The Aggregate Indicator
206
Table 26: Study 2 – Correlations for Dep
endent Variables
n
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
1.
Active Resistance 1
207
1.00
2.
Active Resistance 2
207
.28†
1.00
3.
Active Resistance 3
207
.36†
.00
1.00
4.
Passive Resistance 1
207
-.17*
.00
-.37†
1.00
5.
Passive Resistance 2
207
.33†
.10
.29†
-.50†
1.00
6.
Passive Resistance 3
207
.18†
.29†
.18*
-.12
.38†
1.00
7.
Active Support 1
207
-.43†
-.03
-.54†
.35†
-.45†
-.23†
1.00
8.
Active Support 2
207
-.20†
-.18*
-.33†
.57†
-.53†
-.19†
.43†
1.00
9.
Active Support 3
207
.32†
.06
.43†
-.48†
.70†
.33†
-.42†
-.46†
1.00
10. Passive Support 1
207
.21†
-.17*
.24†
-.08
.35†
.03
-.37†
-.16*
.29†
1.00
11. Passive Support 2
207
.56†
.17*
.59†
-.30†
.54†
.38†
-.64†
-.41†
.56†
.45†
1.00
12. Passive Support 3
207
-.17*
-.20†
-.11
-.11
.10
-.17*
.11
-.12
.07
.28†
-.05
1.00
13. Age
205
-.28†
-.05
-.10
.19†
-.10
.19†
.02
.14*
-.05
.04
-.11
.00
1.00
14. Education
200
.15*
.18†
.30†
-.20†
.22†
.23†
-.21†
-.21†
.21†
.00
.24†
-.23†
-.08
1.00
15. Gender
204
.05
.11
.07
.05
-.07
.11
.04
.12
-.05
-.17*
.07
-.13
-.19†
.15*
1.00
16. Position Tenure
202
-.08
.14
-.04
.03
.06
.18†
.01
.00
.00
.13
-.04
-.09
.51†
.18*
-.16*
1.00
17. Organizational Tenure 199
-.34†
-.08
-.16*
.21†
-.18†
.10
.11
.17*
-.10
.06
-.24†
.10
.90†
-.05
-.10
.52†
1.00
18. Fam
ily Status
202
-.17*
-.03
-.16*
.15*
-.23†
-.03
.10
.23†
-.15*
-.06
-.20†
.04
.54†
-.16*
-.02
.23†
.52†
1.00
19. Number of Children
200
-.21†
-.12
-.15*
.09
-.18†
-.06
.11
.14*
-.09
.04
-.18*
.19†
.60†
-.29†
-.22†
.25†
.58†
.69†
Notes:
Correlations typed in bold are significant at the 0.01 level or the 0.05 level (2-tailed). † p < .01, * p < .05.
207
Table 27: Study 2 – Correlations for Active Resistance
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
AR 1
1.00
2.
AR 2
.28†
1.00
3.
AR 3
.36†
.00
1.00
4.
POS 1
.21†
.15*
.18†
1.00
5.
POS 2
.49†
.00
.52†
.50†
1.00
6.
POS 3
-.03
.15*
-.14*
-.06
-.25†
1.00
7.
Justice 1
-.07
.19†
-.14
.16*
-.24†
.32†
1.00
8.
Justice 2
.04
-.05
.04
-.09
.02
-.09
.05
1.00
9.
Justice 3
-.08
.11
-.13
.19†
-.04
-.20†
.15*
-.02
1.00
10. Participation 1
.60†
.04
.57†
.27†
.68†
-.24†
-.28†
.00
-.14*
1.00
11. Participation 2
.17*
.06
.17*
.25†
.26†
-.20†
.08
-.22†
.15*
.37†
1.00
12. Participation 3
.30†
.06
.18†
.09
.26†
-.05
-.05
.25†
-.12
.28†
.09
1.00
13. Need 1
.29†
.08
.27†
.32†
.28†
-.02
-.02
-.14*
-.02
.38†
.26†
-.06
1.00
14. Need 2
.32†
.12
.25†
.46†
.48†
-.18*
-.07
.00
-.01
.49†
.17*
.16*
.18*
1.00
15. Need 3
.15*
-.08
.26†
.09
.31†
-.31†
-.26†
.16*
.02
.36†
-.06
.02
.08
.33†
1.00
16. Attitude 1
-.21†
.08
-.10
.08
-.06
-.35†
.06
-.13
.29†
-.06
.23†
-.14*
-.02
.02
.21†
1.00
17. Attitude 2
-.05
.24†
.17*
.33†
.13
-.12
.14*
.02
.16*
.15*
.19†
-.03
.20†
.41†
.22†
.24†
1.00
18. Attitude 3
.09
.11
.00
.18†
.05
.14*
.15*
-.10
.04
.08
.09
-.18†
.35†
.15*
-.11
-.05
-.03
1.00
19. Fear of known 1
.16*
.00
.14
-.07
.08
-.03
-.01
.10
-.08
.04
.05
.29†
-.25†
.06
.10
-.08
-.16*
-.37†
1.00
20. Fear of known 2
.37†
-.05
.43†
.29†
.59†
-.18*
-.26†
.17*
-.07
.67†
.17*
.28†
.34†
.51†
.38†
-.08
.21†
.15*
.06
1.00
21. Fear of known 3
.28†
-.01
.18*
.30†
.27†
.04
-.01
-.22†
-.04
.24†
.24†
-.12
.48†
.14*
-.04
-.06
.02
.39†
-.19†
.17*
1.00
22. Age
-.28†
-.05
-.10
.01
-.13
-.27†
-.12
.06
.40†
-.12
-.01
-.09
-.20†
.14*
.12
.27†
.21†
-.19†
.03
-.05
-.26†
1.00
23. Education
.15*
.18†
.30†
.20†
.27†
.06
.14
-.07
.06
.21†
.06
-.06
.08
.23†
.16*
.13
.24†
.04
.00
.16*
.03
-.08
1.00
24. Gender
.05
.11
.07
-.13
.03
.17*
.05
-.04
-.13
.05
-.04
.09
-.02
.05
-.12
-.14*
-.01
-.01
.09
.01
-.07
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
208
Table 28: Study 2 – Correlations for Active Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
AR 1
1.00
2.
AR 2
.28†
1.00
3.
AR 3
.36†
.00
1.00
4.
Fear of Un1
.27†
-.06
.20†
1.00
5.
Fear of Un 2
.22†
-.10
.17*
-.05
1.00
6.
Fear of Un 3
.12
.15*
.09
-.04
.22†
1.00
7.
Power 1
.09
.04
.07
-.18†
.26†
.29†
1.00
8.
Power 2
.33†
.15*
.35†
.17*
.27†
.21†
.37†
1.00
9.
Power 3
.39†
.05
.44†
.14*
.17*
.06
.28†
.46†
1.00
10. Status 1
.06
.01
.15*
.01
.17*
.02
.07
.17*
.20†
1.00
11. Status 2
.08
.25†
.15*
-.01
-.01
.29†
.33†
.39†
.36†
.31†
1.00
12. Status 3
-.12
-.15*
-.19†
-.22†
-.02
-.24†
-.18†
-.37†
-.26†
-.16*
-.49†
1.00
13. Pride 1
-.37†
-.01
-.48†
-.25†
-.17*
-.18*
-.14*
-.54†
-.53†
-.18*
-.42†
.50†
1.00
14. Pride 2
-.18†
.04
-.14*
-.23†
-.16*
.20†
.09
-.16*
-.18†
.07
.12
.09
.00
1.00
15. Pride 3
.24†
.11
.21†
.39†
.23†
.11
.13
.33†
.25†
.18†
.20†
-.43†
-.34†
-.12
1.00
16. Job Sat 1
.24†
.19†
.37†
.12
.21†
.39†
.38†
.43†
.41†
.07
.53†
-.43†
-.45†
.05
.49†
1.00
17. Job Sat 2
.35†
.00
.23†
.21†
.19†
.04
-.25†
.04
.08
.00
-.15*
.08
-.17*
-.19†
.12
-.06
1.00
18. Job Sat 3
.10
-.08
.23†
-.08
.27†
.04
-.12
.05
-.03
.34†
.01
.11
-.07
.04
.03
.13
.20†
1.00
19. Job Security 1
-.25†
.18†
-.21†
-.12
-.27†
.01
.24†
-.02
.00
-.01
.32†
-.17*
.07
.20†
.00
.08
-.60†
-.29†
1.00
20. Job Security 2
-.20†
.18†
-.11
.05
-.23†
.13
.15*
.11
.06
.09
.43†
-.37†
-.13
.22†
.20†
.23†
-.45†
-.20†
.76†
1.00
21. Job Security 3
-.19†
-.02
-.12
-.05
-.15*
.01
.15*
.06
-.01
.11
.20†
-.26†
-.07
.12
.01
.11
-.54†
-.09
.58†
.63†
1.00
22. Age
-.28†
-.05
-.10
-.25†
-.07
.07
.12
.04
.05
.24†
.22†
-.08
-.05
.14
-.11
.05
-.41†
.02
.28†
.32†
.35†
1.00
23. Education
.15*
.18†
.30†
.10
.11
.21†
.12
.16*
.22†
.03
.24†
-.23†
-.31†
-.05
.27†
.26†
.04
-.04
.05
.21†
.05
-.08
1.00
24. Gender
.05
.11
.07
.09
-.07
.03
.08
.01
-.03
-.06
.01
.17*
-.07
.02
.05
.04
.05
-.04
-.02
-.01
-.12
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
209
Table 29: Study 2 – Correlations for Active Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
AR 1
1.00
2.
AR 2
.28†
1.00
3.
AR 3
.36†
.00
1.00
4.
Job M
otivation 1
.15*
.07
.07
1.00
5.
Job M
otivation 2
-.13
.23†
-.03
.11
1.00
6.
Job M
otivation 3
-.26†
-.07
-.19†
.20†
.53†
1.00
7.
Employability 1
.22†
.08
.35†
.15*
.33†
.17*
1.00
8.
Employability 2
-.04
-.19†
-.08
.31†
-.07
.27†
.16*
1.00
9.
Employability 3
.11
-.03
.14*
-.08
-.18*
-.25†
-.14*
-.23†
1.00
10. Learning 1
-.35†
.03
-.34†
.00
.32†
.40†
-.10
.16*
-.43†
1.00
11. Learning 2
-.43†
.03
-.50†
-.10
.18†
.27†
-.35†
.13
-.11
.43†
1.00
12. Learning 3
-.33†
-.15*
-.46†
.02
.25†
.50†
-.06
.21†
-.28†
.51†
.48†
1.00
13. Commitment 1
.05
.08
-.04
.20†
.14*
.23†
.10
.27†
-.30†
.22†
.14*
.20†
1.00
14. Commitment 2
-.39†
-.01
-.24†
.09
.46†
.60†
.08
.16*
-.30†
.59†
.43†
.50†
.36†
1.00
15. Commitment 3
.40†
.08
.26†
.37†
.15*
.00
.30†
.02
-.10
-.11
-.43†
-.10
.27†
-.06
1.00
16. Trust 1
-.05
.12
.03
.26†
.15*
.19†
.01
.10
-.09
.01
.15*
.07
.10
.19†
.17*
1.00
17. Trust 2
-.25†
.13
.00
-.27†
.30†
.16*
.21†
-.08
.02
.13
.20†
.10
-.15*
.25†
-.21†
.20†
1.00
18. Trust 3
-.33†
-.09
-.27†
.14*
.32†
.58†
.05
.10
-.21†
.34†
.37†
.46†
.10
.51†
-.13
.22†
.21†
1.00
19. Col_Resist 1
-.37†
.01
-.39†
-.10
.02
.17*
-.33†
.15*
-.05
.27†
.63†
.23†
.16*
.28†
-.36†
.21†
.22†
.27†
1.00
20. Col_Support
.27†
.01
.23†
.25†
.12
.21†
.52†
.12
-.05
-.08
-.28†
.00
.18†
.07
.29†
.06
.06
.19†
-.17*
1.00
21. Col_Resist 2
.20†
-.01
.16*
.31†
.14*
.23†
.46†
.06
-.09
.04
-.22†
.07
.17*
.05
.35†
.03
.04
.21†
-.21†
.76†
1.00
22. Age
-.28†
-.05
-.10
-.02
.34†
.44†
.24†
.11
-.08
.22†
.16*
.38†
.06
.41†
-.06
.06
.33†
.35†
.07
.15*
.18*
1.00
23. Education
.15*
.18†
.30†
.03
.25†
.02
.27†
-.11
.00
-.07
-.14
-.13
.00
-.02
.21†
-.02
-.01
-.09
-.27†
.09
.12
-.08
1.00
24. Gender
.05
.11
.07
-.17*
-.03
-.15*
-.03
-.18*
.19†
-.19†
-.08
-.12
-.15*
-.10
-.08
-.01
.04
-.10
-.08
-.05
-.08
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
210
Table 30: Study 2 – Correlations for Passive Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
-.50†
1.00
3.
PR 3
-.12
.38†
1.00
4.
POS 1
-.42†
.56†
.35†
1.00
5.
POS 2
-.32†
.55†
.34†
.50†
1.00
6.
POS 3
.09
-.18*
-.19†
-.06
-.25†
1.00
7.
Justice 1
-.03
-.02
.01
.16*
-.24†
.32†
1.00
8.
Justice 2
.05
-.11
.10
-.09
.02
-.09
.05
1.00
9.
Justice 3
.05
.08
.15*
.19†
-.04
-.20†
.15*
-.02
1.00
10. Participation 1
-.30†
.52†
.27†
.27†
.68†
-.24†
-.28†
.00
-.14*
1.00
11. Participation 2
-.25†
.38†
.13
.25†
.26†
-.20†
.08
-.22†
.15*
.37†
1.00
12. Participation 3
.04
.16*
.14*
.09
.26†
-.05
-.05
.25†
-.12
.28†
.09
1.00
13. Need 1
-.49†
.48†
.02
.32†
.28†
-.02
-.02
-.14*
-.02
.38†
.26†
-.06
1.00
14. Need 2
-.19†
.34†
.42†
.46†
.48†
-.18*
-.07
.00
-.01
.49†
.17*
.16*
.18*
1.00
15. Need 3
-.03
.12
.11
.09
.31†
-.31†
-.26†
.16*
.02
.36†
-.06
.02
.08
.33†
1.00
16. Attitude 1
-.04
.12
.04
.08
-.06
-.35†
.06
-.13
.29†
-.06
.23†
-.14*
-.02
.02
.21†
1.00
17. Attitude 2
-.22†
.30†
.35†
.33†
.13
-.12
.14*
.02
.16*
.15*
.19†
-.03
.20†
.41†
.22†
.24†
1.00
18. Attitude 3
-.23†
.21†
-.01
.18†
.05
.14*
.15*
-.10
.04
.08
.09
-.18†
.35†
.15*
-.11
-.05
-.03
1.00
19. Fear of Known 1
.13
-.16*
.01
-.07
.08
-.03
-.01
.10
-.08
.04
.05
.29†
-.25†
.06
.10
-.08
-.16*
-.37†
1.00
20. Fear of Known 2
-.18†
.46†
.27†
.29†
.59†
-.18*
-.26†
.17*
-.07
.67†
.17*
.28†
.34†
.51†
.38†
-.08
.21†
.15*
.06
1.00
21. Fear of Known 3
-.38†
.44†
-.01
.30†
.27†
.04
-.01
-.22†
-.04
.24†
.24†
-.12
.48†
.14*
-.04
-.06
.02
.39†
-.19†
.17*
1.00
22. Age
.19†
-.10
.19†
.01
-.13
-.27†
-.12
.06
.40†
-.12
-.01
-.09
-.20†
.14*
.12
.27†
.21†
-.19†
.03
-.05
-.26†
1.00
23. Education
-.20†
.22†
.23†
.20†
.27†
.06
.14
-.07
.06
.21†
.06
-.06
.08
.23†
.16*
.13
.24†
.04
.00
.16*
.03
-.08
1.00
24. Gender
.05
-.07
.11
-.13
.03
.17*
.05
-.04
-.13
.05
-.04
.09
-.02
.05
-.12
-.14*
-.01
-.01
.09
.01
-.07
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
211
Table 31: Study 2 – Correlations for Passive Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
-.50†
1.00
3.
PR 3
-.12
.38†
1.00
4.
Fear of Un 1
-.44†
.41†
.08
1.00
5.
Fear of Un 2
.01
.13
.01
-.05
1.00
6.
Fear of Un 3
-.04
.12
.21†
-.04
.22†
1.00
7.
Power 1
.09
.00
.23†
-.18†
.26†
.29†
1.00
8.
Power 2
-.31†
.50†
.40†
.17*
.27†
.21†
.37†
1.00
9.
Power 3
-.22†
.32†
.33†
.14*
.17*
.06
.28†
.46†
1.00
10. Status 1
-.06
.15*
.21†
.01
.17*
.02
.07
.17*
.20†
1.00
11. Status 2
-.09
.22†
.48†
-.01
-.01
.29†
.33†
.39†
.36†
.31†
1.00
12. Status 3
.30†
-.50†
-.38†
-.22†
-.02
-.24†
-.18†
-.37†
-.26†
-.16*
-.49†
1.00
13. Pride 1
.35†
-.49†
-.43†
-.25†
-.17*
-.18*
-.14*
-.54†
-.53†
-.18*
-.42†
.50†
1.00
14. Pride 2
.21†
-.20†
.17*
-.23†
-.16*
.20†
.09
-.16*
-.18†
.07
.12
.09
.00
1.00
15. Pride 3
-.36†
.48†
.22†
.39†
.23†
.11
.13
.33†
.25†
.18†
.20†
-.43†
-.34†
-.12
1.00
16. Job Sat 1
-.20†
.27†
.39†
.12
.21†
.39†
.38†
.43†
.41†
.07
.53†
-.43†
-.45†
.05
.49†
1.00
17. Job Sat 2
-.13
.16*
-.08
.21†
.19†
.04
-.25†
.04
.08
.00
-.15*
.08
-.17*
-.19†
.12
-.06
1.00
18. Job Sat 3
.04
-.06
.01
-.08
.27†
.04
-.12
.05
-.03
.34†
.01
.11
-.07
.04
.03
.13
.20†
1.00
19. Job Security 1
-.02
-.02
.23†
-.12
-.27†
.01
.24†
-.02
.00
-.01
.32†
-.17*
.07
.20†
.00
.08
-.60†
-.29†
1.00
20. Job Security 2
-.15*
.15*
.42†
.05
-.23†
.13
.15*
.11
.06
.09
.43†
-.37†
-.13
.22†
.20†
.23†
-.45†
-.20†
.76†
1.00
21. Job Security 3
-.05
.04
.26†
-.05
-.15*
.01
.15*
.06
-.01
.11
.20†
-.26†
-.07
.12
.01
.11
-.54†
-.09
.58†
.63†
1.00
22. Age
.19†
-.10
.19†
-.25†
-.07
.07
.12
.04
.05
.24†
.22†
-.08
-.05
.14
-.11
.05
-.41†
.02
.28†
.32†
.35†
1.00
23. Education
-.20†
.22†
.23†
.10
.11
.21†
.12
.16*
.22†
.03
.24†
-.23†
-.31†
-.05
.27†
.26†
.04
-.04
.05
.21†
.05
-.08
1.00
24. Gender
.05
-.07
.11
.09
-.07
.03
.08
.01
-.03
-.06
.01
.17*
-.07
.02
.05
.04
.05
-.04
-.02
-.01
-.12
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
212
Table 32: Study 2 – Correlations for Passive Resistance (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
-.50†
1.00
3.
PR 3
-.12
.38†
1.00
4.
Job M
otivation 1
-.28†
.36†
.07
1.00
5.
Job M
otivation 2
-.13
.15*
.33†
.11
1.00
6.
Job M
otivation 3
.06
.00
.16*
.20†
.53†
1.00
7.
Employability 1
-.19†
.31†
.46†
.15*
.33†
.17*
1.00
8.
Employability 2
-.03
.06
-.04
.31†
-.07
.27†
.16*
1.00
9.
Employability 3
.00
-.07
-.12
-.08
-.18*
-.25†
-.14*
-.23†
1.00
10. Learning 1
.10
-.11
-.01
.00
.32†
.40†
-.10
.16*
-.43†
1.00
11. Learning 2
.33†
-.44†
-.31†
-.10
.18†
.27†
-.35†
.13
-.11
.43†
1.00
12. Learning 3
.27†
-.19†
-.04
.02
.25†
.50†
-.06
.21†
-.28†
.51†
.48†
1.00
13. Commitment 1
-.14*
.14*
.13
.20†
.14*
.23†
.10
.27†
-.30†
.22†
.14*
.20†
1.00
14. Commitment 2
.14*
-.09
.15*
.09
.46†
.60†
.08
.16*
-.30†
.59†
.43†
.50†
.36†
1.00
15. Commitment 3
-.46†
.64†
.27†
.37†
.15*
.00
.30†
.02
-.10
-.11
-.43†
-.10
.27†
-.06
1.00
16. Trust 1
-.03
.07
.01
.26†
.15*
.19†
.01
.10
-.09
.01
.15*
.07
.10
.19†
.17*
1.00
17. Trust 2
.27†
-.22†
.07
-.27†
.30†
.16*
.21†
-.08
.02
.13
.20†
.10
-.15*
.25†
-.21†
.20†
1.00
18. Trust 3
.15*
-.14*
.09
.14*
.32†
.58†
.05
.10
-.21†
.34†
.37†
.46†
.10
.51†
-.13
.22†
.21†
1.00
19. Col_Resist 1
.22†
-.35†
-.34†
-.10
.02
.17*
-.33†
.15*
-.05
.27†
.63†
.23†
.16*
.28†
-.36†
.21†
.22†
.27†
1.00
20. Col_Support
-.11
.25†
.31†
.25†
.12
.21†
.52†
.12
-.05
-.08
-.28†
.00
.18†
.07
.29†
.06
.06
.19†
-.17*
1.00
21. Col_Resist 2
-.14*
.28†
.26†
.31†
.14*
.23†
.46†
.06
-.09
.04
-.22†
.07
.17*
.05
.35†
.03
.04
.21†
-.21†
.76†
1.00
22. Age
.19†
-.10
.19†
-.02
.34†
.44†
.24†
.11
-.08
.22†
.16*
.38†
.06
.41†
-.06
.06
.33†
.35†
.07
.15*
.18*
1.00
23. Education
-.20†
.22†
.23†
.03
.25†
.02
.27†
-.11
.00
-.07
-.14
-.13
.00
-.02
.21†
-.02
-.01
-.09
-.27†
.09
.12
-.08
1.00
24. Gender
.05
-.07
.11
-.17*
-.03
-.15*
-.03
-.18*
.19†
-.19†
-.08
-.12
-.15*
-.10
-.08
-.01
.04
-.10
-.08
-.05
-.08
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
213
Table 33: Study 2 – Correlations for Active Support
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
Active Support 1
1.00
2.
Active Support 2
.43†
1.00
3.
Active Support 3
-.42†
-.46†
1.00
4.
POS 1
-.43†
-.43†
.60†
1.00
5.
POS 2
-.64†
-.38†
.61†
.50†
1.00
6.
POS 3
.19†
.09
-.19†
-.06
-.25†
1.00
7.
Justice 1
.19†
.00
-.02
.16*
-.24†
.32†
1.00
8.
Justice 2
-.01
.00
-.08
-.09
.02
-.09
.05
1.00
9.
Justice 3
.14
.04
.11
.19†
-.04
-.20†
.15*
-.02
1.00
10. Participation 1
-.58†
-.39†
.51†
.27†
.68†
-.24†
-.28†
.00
-.14*
1.00
11. Participation 2
-.21†
-.20†
.35†
.25†
.26†
-.20†
.08
-.22†
.15*
.37†
1.00
12. Participation 3
-.19†
-.05
.05
.09
.26†
-.05
-.05
.25†
-.12
.28†
.09
1.00
13. Need 1
-.27†
-.50†
.49†
.32†
.28†
-.02
-.02
-.14*
-.02
.38†
.26†
-.06
1.00
14. Need 2
-.40†
-.27†
.41†
.46†
.48†
-.18*
-.07
.00
-.01
.49†
.17*
.16*
.18*
1.00
15. Need 3
-.33†
-.21†
.15*
.09
.31†
-.31†
-.26†
.16*
.02
.36†
-.06
.02
.08
.33†
1.00
16. Attitude 1
.03
-.03
.05
.08
-.06
-.35†
.06
-.13
.29†
-.06
.23†
-.14*
-.02
.02
.21†
1.00
17. Attitude 2
-.17*
-.38†
.32†
.33†
.13
-.12
.14*
.02
.16*
.15*
.19†
-.03
.20†
.41†
.22†
.24†
1.00
18. Attitude 3
-.01
-.31†
.23†
.18†
.05
.14*
.15*
-.10
.04
.08
.09
-.18†
.35†
.15*
-.11
-.05
-.03
1.00
19. Fear of Known 1
-.13
.28†
-.16*
-.07
.08
-.03
-.01
.10
-.08
.04
.05
.29†
-.25†
.06
.10
-.08
-.16*
-.37†
1.00
20. Fear of Known 2
-.50†
-.35†
.43†
.29†
.59†
-.18*
-.26†
.17*
-.07
.67†
.17*
.28†
.34†
.51†
.38†
-.08
.21†
.15*
.06
1.00
21. Fear of Known 3
-.29†
-.32†
.38†
.30†
.27†
.04
-.01
-.22†
-.04
.24†
.24†
-.12
.48†
.14*
-.04
-.06
.02
.39†
-.19†
.17*
1.00
22. Age
.02
.14*
-.05
.01
-.13
-.27†
-.12
.06
.40†
-.12
-.01
-.09
-.20†
.14*
.12
.27†
.21†
-.19†
.03
-.05
-.26†
1.00
23. Education
-.21†
-.21†
.21†
.20†
.27†
.06
.14
-.07
.06
.21†
.06
-.06
.08
.23†
.16*
.13
.24†
.04
.00
.16*
.03
-.08
1.00
24. Gender
.04
.12
-.05
-.13
.03
.17*
.05
-.04
-.13
.05
-.04
.09
-.02
.05
-.12
-.14*
-.01
-.01
.09
.01
-.07
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
214
Table 34: Study 2 – Correlations for Active Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
Active Support 1
1.00
2.
Active Support 2
.43†
1.00
3.
Active Support 3
-.42†
-.46†
1.00
4.
Fear of Un 1
-.22†
-.30†
.36†
1.00
5.
Fear of Un 2
-.33†
-.05
.15*
-.05
1.00
6.
Fear of Un 3
-.19†
-.10
.12
-.04
.22†
1.00
7.
Power 1
-.12
.00
.10
-.18†
.26†
.29†
1.00
8.
Power 2
-.44†
-.43†
.52†
.17*
.27†
.21†
.37†
1.00
9.
Power 3
-.41†
-.24†
.39†
.14*
.17*
.06
.28†
.46†
1.00
10. Status 1
-.21†
.07
.12
.01
.17*
.02
.07
.17*
.20†
1.00
11. Status 2
-.29†
-.18†
.21†
-.01
-.01
.29†
.33†
.39†
.36†
.31†
1.00
12. Status 3
.30†
.34†
-.48†
-.22†
-.02
-.24†
-.18†
-.37†
-.26†
-.16*
-.49†
1.00
13. Pride 1
.49†
.34†
-.50†
-.25†
-.17*
-.18*
-.14*
-.54†
-.53†
-.18*
-.42†
.50†
1.00
14. Pride 2
.13
.09
-.22†
-.23†
-.16*
.20†
.09
-.16*
-.18†
.07
.12
.09
.00
1.00
15. Pride 3
-.26†
-.25†
.47†
.39†
.23†
.11
.13
.33†
.25†
.18†
.20†
-.43†
-.34†
-.12
1.00
16. Job Sat 1
-.32†
-.20†
.35†
.12
.21†
.39†
.38†
.43†
.41†
.07
.53†
-.43†
-.45†
.05
.49†
1.00
17. Job Sat 2
-.32†
-.11
.16*
.21†
.19†
.04
-.25†
.04
.08
.00
-.15*
.08
-.17*
-.19†
.12
-.06
1.00
18. Job Sat 3
-.17*
.17*
-.04
-.08
.27†
.04
-.12
.05
-.03
.34†
.01
.11
-.07
.04
.03
.13
.20†
1.00
19. Job Security 1
.19†
-.01
-.07
-.12
-.27†
.01
.24†
-.02
.00
-.01
.32†
-.17*
.07
.20†
.00
.08
-.60†
-.29†
1.00
20. Job Security 2
.07
-.17*
.16*
.05
-.23†
.13
.15*
.11
.06
.09
.43†
-.37†
-.13
.22†
.20†
.23†
-.45†
-.20†
.76†
1.00
21. Job Security 3
.10
-.04
.01
-.05
-.15*
.01
.15*
.06
-.01
.11
.20†
-.26†
-.07
.12
.01
.11
-.54†
-.09
.58†
.63†
1.00
22. Age
.02
.14*
-.05
-.25†
-.07
.07
.12
.04
.05
.24†
.22†
-.08
-.05
.14
-.11
.05
-.41†
.02
.28†
.32†
.35†
1.00
23. Education
-.21†
-.21†
.21†
.10
.11
.21†
.12
.16*
.22†
.03
.24†
-.23†
-.31†
-.05
.27†
.26†
.04
-.04
.05
.21†
.05
-.08
1.00
24. Gender
.04
.12
-.05
.09
-.07
.03
.08
.01
-.03
-.06
.01
.17*
-.07
.02
.05
.04
.05
-.04
-.02
-.01
-.12
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
215
Table 35: Study 2 – Correlations for Active Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
Active Support 1
1.00
2.
Active Support 2
.43†
1.00
3.
Active Support 3
-.42†
-.46†
1.00
4.
Job M
otivation 1
-.20†
-.30†
.42†
1.00
5.
Job M
otivation 2
.02
-.16*
.21†
.11
1.00
6.
Job M
otivation 3
.21†
.09
.00
.20†
.53†
1.00
7.
Employability 1
-.43†
-.26†
.32†
.15*
.33†
.17*
1.00
8.
Employability 2
.09
.17*
.04
.31†
-.07
.27†
.16*
1.00
9.
Employability 3
-.06
.08
-.04
-.08
-.18*
-.25†
-.14*
-.23†
1.00
10. Learning 1
.30†
.05
-.12
.00
.32†
.40†
-.10
.16*
-.43†
1.00
11. Learning 2
.49†
.34†
-.43†
-.10
.18†
.27†
-.35†
.13
-.11
.43†
1.00
12. Learning 3
.34†
.27†
-.18†
.02
.25†
.50†
-.06
.21†
-.28†
.51†
.48†
1.00
13. Commitment 1
-.01
-.10
.18†
.20†
.14*
.23†
.10
.27†
-.30†
.22†
.14*
.20†
1.00
14. Commitment 2
.21†
.07
-.09
.09
.46†
.60†
.08
.16*
-.30†
.59†
.43†
.50†
.36†
1.00
15. Commitment 3
-.38†
-.44†
.57†
.37†
.15*
.00
.30†
.02
-.10
-.11
-.43†
-.10
.27†
-.06
1.00
16. Trust in M
gmt 1
.06
-.09
.11
.26†
.15*
.19†
.01
.10
-.09
.01
.15*
.07
.10
.19†
.17*
1.00
17. Trust in M
gmt 2
.05
.23†
-.26†
-.27†
.30†
.16*
.21†
-.08
.02
.13
.20†
.10
-.15*
.25†
-.21†
.20†
1.00
18. Trust in M
gmt 3
.19†
.13
-.14*
.14*
.32†
.58†
.05
.10
-.21†
.34†
.37†
.46†
.10
.51†
-.13
.22†
.21†
1.00
19. Col_Resist 1
.51†
.24†
-.39†
-.10
.02
.17*
-.33†
.15*
-.05
.27†
.63†
.23†
.16*
.28†
-.36†
.21†
.22†
.27†
1.00
20. Col_Support
-.28†
-.14*
.17*
.25†
.12
.21†
.52†
.12
-.05
-.08
-.28†
.00
.18†
.07
.29†
.06
.06
.19†
-.17*
1.00
21. Col_Resist 2
-.29†
-.21†
.25†
.31†
.14*
.23†
.46†
.06
-.09
.04
-.22†
.07
.17*
.05
.35†
.03
.04
.21†
-.21†
.76†
1.00
22. Age
.02
.14*
-.05
-.02
.34†
.44†
.24†
.11
-.08
.22†
.16*
.38†
.06
.41†
-.06
.06
.33†
.35†
.07
.15*
.18*
1.00
23. Education
-.21†
-.21†
.21†
.03
.25†
.02
.27†
-.11
.00
-.07
-.14
-.13
.00
-.02
.21†
-.02
-.01
-.09
-.27†
.09
.12
-.08
1.00
24. Gender
.04
.12
-.05
-.17*
-.03
-.15*
-.03
-.18*
.19†
-.19†
-.08
-.12
-.15*
-.10
-.08
-.01
.04
-.10
-.08
-.05
-.08
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
216
Table 36: Study 2 – Correlations for Passive Support
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PS 1
1.00
2.
PS 2
.45†
1.00
3.
PS 3
.28†
-.05
1.00
4.
POS 1
.21†
.44†
.04
1.00
5.
POS 2
.44†
.66†
.02
.50†
1.00
6.
POS 3
-.52†
-.21†
-.16*
-.06
-.25†
1.00
7.
Justice 1
-.44†
-.17*
-.21†
.16*
-.24†
.32†
1.00
8.
Justice 2
-.07
-.04
.09
-.09
.02
-.09
.05
1.00
9.
Justice 3
-.03
-.12
-.07
.19†
-.04
-.20†
.15*
-.02
1.00
10. Participation 1
.42†
.68†
-.04
.27†
.68†
-.24†
-.28†
.00
-.14*
1.00
11. Participation 2
.18*
.27†
-.09
.25†
.26†
-.20†
.08
-.22†
.15*
.37†
1.00
12. Participation 3
.17*
.28†
-.06
.09
.26†
-.05
-.05
.25†
-.12
.28†
.09
1.00
13. Need 1
.17*
.39†
.09
.32†
.28†
-.02
-.02
-.14*
-.02
.38†
.26†
-.06
1.00
14. Need 2
.25†
.48†
-.11
.46†
.48†
-.18*
-.07
.00
-.01
.49†
.17*
.16*
.18*
1.00
15. Need 3
.41†
.29†
.18†
.09
.31†
-.31†
-.26†
.16*
.02
.36†
-.06
.02
.08
.33†
1.00
16. Attitude 1
.17*
-.07
.21†
.08
-.06
-.35†
.06
-.13
.29†
-.06
.23†
-.14*
-.02
.02
.21†
1.00
17. Attitude 2
.03
.22†
.03
.33†
.13
-.12
.14*
.02
.16*
.15*
.19†
-.03
.20†
.41†
.22†
.24†
1.00
18. Attitude 3
-.13
.08
.05
.18†
.05
.14*
.15*
-.10
.04
.08
.09
-.18†
.35†
.15*
-.11
-.05
-.03
1.00
19. Fear of Known 1
.13
.11
-.01
-.07
.08
-.03
-.01
.10
-.08
.04
.05
.29†
-.25†
.06
.10
-.08
-.16*
-.37†
1.00
20. Fear of Known 2
.40†
.60†
.13
.29†
.59†
-.18*
-.26†
.17*
-.07
.67†
.17*
.28†
.34†
.51†
.38†
-.08
.21†
.15*
.06
1.00
21. Fear of Known 3
.12
.26†
.06
.30†
.27†
.04
-.01
-.22†
-.04
.24†
.24†
-.12
.48†
.14*
-.04
-.06
.02
.39†
-.19†
.17*
1.00
22. Age
.04
-.11
.00
.01
-.13
-.27†
-.12
.06
.40†
-.12
-.01
-.09
-.20†
.14*
.12
.27†
.21†
-.19†
.03
-.05
-.26†
1.00
23. Education
.00
.24†
-.23†
.20†
.27†
.06
.14
-.07
.06
.21†
.06
-.06
.08
.23†
.16*
.13
.24†
.04
.00
.16*
.03
-.08
1.00
24. Gender
-.17*
.07
-.13
-.13
.03
.17*
.05
-.04
-.13
.05
-.04
.09
-.02
.05
-.12
-.14*
-.01
-.01
.09
.01
-.07
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
217
Table 37: Study 2 – Correlations for Passive Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PR 1
1.00
2.
PR 2
.45†
1.00
3.
PR 3
.28†
-.05
1.00
4.
Fear of Un 1
.08
.30†
.11
1.00
5.
Fear of Un 2
.35†
.30†
.00
-.05
1.00
6.
Fear of Un 3
-.05
.16*
-.20†
-.04
.22†
1.00
7.
Power 1
.13
.20†
-.18†
-.18†
.26†
.29†
1.00
8.
Power 2
.49†
.54†
.08
.17*
.27†
.21†
.37†
1.00
9.
Power 3
.33†
.54†
-.07
.14*
.17*
.06
.28†
.46†
1.00
10. Status 1
.28†
.19†
.06
.01
.17*
.02
.07
.17*
.20†
1.00
11. Status 2
.14*
.35†
-.17*
-.01
-.01
.29†
.33†
.39†
.36†
.31†
1.00
12. Status 3
-.12
-.33†
.09
-.22†
-.02
-.24†
-.18†
-.37†
-.26†
-.16*
-.49†
1.00
13. Pride 1
-.29†
-.58†
.10
-.25†
-.17*
-.18*
-.14*
-.54†
-.53†
-.18*
-.42†
.50†
1.00
14. Pride 2
-.18†
-.14*
-.01
-.23†
-.16*
.20†
.09
-.16*
-.18†
.07
.12
.09
.00
1.00
15. Pride 3
.16*
.34†
-.06
.39†
.23†
.11
.13
.33†
.25†
.18†
.20†
-.43†
-.34†
-.12
1.00
16. Job Satis 1
.14*
.38†
-.19†
.12
.21†
.39†
.38†
.43†
.41†
.07
.53†
-.43†
-.45†
.05
.49†
1.00
17. Job Satis 2
-.03
.21†
-.13
.21†
.19†
.04
-.25†
.04
.08
.00
-.15*
.08
-.17*
-.19†
.12
-.06
1.00
18. Job Sat 3
.18*
.15*
-.02
-.08
.27†
.04
-.12
.05
-.03
.34†
.01
.11
-.07
.04
.03
.13
.20†
1.00
19. Job Security 1
-.20†
-.16*
.03
-.12
-.27†
.01
.24†
-.02
.00
-.01
.32†
-.17*
.07
.20†
.00
.08
-.60†
-.29†
1.00
20. Job Security 2
-.24†
-.02
-.07
.05
-.23†
.13
.15*
.11
.06
.09
.43†
-.37†
-.13
.22†
.20†
.23†
-.45†
-.20†
.76†
1.00
21. Job Security 3
.05
-.06
.03
-.05
-.15*
.01
.15*
.06
-.01
.11
.20†
-.26†
-.07
.12
.01
.11
-.54†
-.09
.58†
.63†
1.00
22. Age
.04
-.11
.00
-.25†
-.07
.07
.12
.04
.05
.24†
.22†
-.08
-.05
.14
-.11
.05
-.41†
.02
.28†
.32†
.35†
1.00
23. Education
.00
.24†
-.23†
.10
.11
.21†
.12
.16*
.22†
.03
.24†
-.23†
-.31†
-.05
.27†
.26†
.04
-.04
.05
.21†
.05
-.08
1.00
24. Gender
-.17*
.07
-.13
.09
-.07
.03
.08
.01
-.03
-.06
.01
.17*
-.07
.02
.05
.04
.05
-.04
-.02
-.01
-.12
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
218
Table 38: Study 2 – Correlations for Passive Support (cont.)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
1.
PS 1
1.00
2.
PS 2
.45†
1.00
3.
PS 3
.28†
-.05
1.00
4.
Job M
otivation 1
.45†
.23†
.23†
1.00
5.
Job M
otivation 2
-.19†
.05
-.09
.11
1.00
6.
Job M
otivation 3
.15*
-.16*
.15*
.20†
.53†
1.00
7.
Employability 1
.21†
.45†
-.18†
.15*
.33†
.17*
1.00
8.
Employability 2
.23†
-.07
.26†
.31†
-.07
.27†
.16*
1.00
9.
Employability 3
.04
.03
-.05
-.08
-.18*
-.25†
-.14*
-.23†
1.00
10. Learning 1
-.13
-.31†
.20†
.00
.32†
.40†
-.10
.16*
-.43†
1.00
11. Learning 2
-.28†
-.59†
.14*
-.10
.18†
.27†
-.35†
.13
-.11
.43†
1.00
12. Learning 3
-.05
-.36†
.17*
.02
.25†
.50†
-.06
.21†
-.28†
.51†
.48†
1.00
13. Commitment 1
.00
.02
-.01
.20†
.14*
.23†
.10
.27†
-.30†
.22†
.14*
.20†
1.00
14. Commitment 2
-.06
-.23†
.12
.09
.46†
.60†
.08
.16*
-.30†
.59†
.43†
.50†
.36†
1.00
15. Commitment 3
.20†
.44†
-.06
.37†
.15*
.00
.30†
.02
-.10
-.11
-.43†
-.10
.27†
-.06
1.00
16. Trust in M
gmt 1
.04
.03
.13
.26†
.15*
.19†
.01
.10
-.09
.01
.15*
.07
.10
.19†
.17*
1.00
17. Trust in M
gmt 2
-.18†
-.08
-.15*
-.27†
.30†
.16*
.21†
-.08
.02
.13
.20†
.10
-.15*
.25†
-.21†
.20†
1.00
18. Trust in M
gmt 3
.10
-.24†
.11
.14*
.32†
.58†
.05
.10
-.21†
.34†
.37†
.46†
.10
.51†
-.13
.22†
.21†
1.00
19. Col_Resist 1
-.28†
-.51†
.14*
-.10
.02
.17*
-.33†
.15*
-.05
.27†
.63†
.23†
.16*
.28†
-.36†
.21†
.22†
.27†
1.00
20. Col_Support
.43†
.41†
-.08
.25†
.12
.21†
.52†
.12
-.05
-.08
-.28†
.00
.18†
.07
.29†
.06
.06
.19†
-.17*
1.00
21. Col_Resist 2
.47†
.37†
-.04
.31†
.14*
.23†
.46†
.06
-.09
.04
-.22†
.07
.17*
.05
.35†
.03
.04
.21†
-.21†
.76†
1.00
22. Age
.04
-.11
.00
-.02
.34†
.44†
.24†
.11
-.08
.22†
.16*
.38†
.06
.41†
-.06
.06
.33†
.35†
.07
.15*
.18*
1.00
23. Education
.00
.24†
-.23†
.03
.25†
.02
.27†
-.11
.00
-.07
-.14
-.13
.00
-.02
.21†
-.02
-.01
-.09
-.27†
.09
.12
-.08
1.00
24. Gender
-.17*
.07
-.13
-.17*
-.03
-.15*
-.03
-.18*
.19†
-.19†
-.08
-.12
-.15*
-.10
-.08
-.01
.04
-.10
-.08
-.05
-.08
-.19†
.15*
Notes:
N = 207 (except for age, n = 205; education, n = 200; gender, n = 204). C
orrelations typed in bold are significant at the 0.01
level or the 0.05 level (2-tailed). † p < .01, * p < .05.
219
Appendix D: Additional Regression Analyses for Study 2
In addition to the number of regressions conducted in the main study, additional tests for
Study 2 were performed and presented in this appendix due predominantly to the fact that
many hypotheses were not supported by the findings in Study 2. Indeed, there existed some
significant relationships that were not consistent with expectations. Consequently, I re-
examined both the data and the methods used in the main study for purpose of identifying
potential explanations to the overall findings in the main study. Up to this point, the re-
examination of the data and the methods performed focused on the reliability of data by
exploring the relationships between measures of variables: that is, I tested whether it was
possible to observe better results using original indicators rather than aggregate indicators as
predictors and outcomes in the multinomial ordered probit regressions. One plausible reason
for re-examining the data is that there is observable evidence that the strength of
correlations among indicators for the study variables was generally low. Consequently, the
use of the aggregate indicators as the variables in regression analyses in the main study may
be attributable to the relatively surprising findings. It is possible that this occurred because
many, if not most, variables were measured using three items that measured different facets
of a certain construct. For example, to measure active resistance to change, three behaviors,
i.e., arguing, opposing, and objecting, which were theoretically defined as active resistance,
were measured using one question for each behavior. Thus, it is entirely possible that due to
the limitation to the questionnaire design, respondent-bias (e.g., within-person consistency)
may be significantly contributed to the low correlations among three behaviors.
Thus, I used another analytical approach to test whether the data would provide
different results to those of in Study 2. For the purpose of comparability and simplicity, a
multinomial ordered probit regression which was employed in the main study was also used
to test the hypotheses. The key difference between these new tests and those of in the main
study is that in the new tests, original indicators rather than aggregate indicators were used
as a predictor and an outcome in the regressions. That is, I separately regressed each of
measures of reactions to change on each of measures of independent variables. It is
important to note that, as with the main study, I did not include control variables in the
regressions. Also, I retained original scales (e.g., from 1 to 5) of measures of variables in the
regression analysis. In sum, the total number of 658 regression models was conducted. For
ease of presentation of the finding, only significant relationships are reported in Tables 41 -
52. Similarly, for ease of interpretation of the findings, Tables 39 and 40 present a summary
of the overall findings of the additional analyses.
220
Table 39 present an overview of the significant relationships for resistance to change
indicators tested in the models. The details of each significant relationship can be found in
Table 41 - 46. The results reported in Table 39 indicate several important findings. First,
several measures of independent variables were significantly predictive of employees’
opposition to the privatization (AR1). However, those relationships are not consistent with
the expectations. Nonetheless, as expected, the likelihood of having higher levels of
opposition to the privatization decreased with higher levels of perceived need for change 2.
Furthermore, higher levels of fear of known consequence of a change 3 increased the
likelihood of having higher levels of opposition to the privatization. Similarly, higher levels
of perceptions of colleagues’ resistance to change 1 increased the likelihood of having
higher levels of opposition to the privatization.
But, as can be seen in Table 39, only job satisfaction was significantly predictive of
the extent to which employees argue against the change (AR2). Furthermore, several
indicators were significantly predictive of employees’ objection to the change. But the
results indicate that many, if not most, of the relationships were positive, implying that the
findings are not consistent with expectations. Two findings with regard to employees’
objection to the change deserve mention. First, higher levels of perceived organizational
support 2 decreased the likelihood of having higher levels of objection to the privatization.
Second, higher levels of fear of known consequences of change increased the likelihood of
having higher levels of objection to the privatization. It is interesting to note that these
results are contradictory to the findings shown in the main study. Recall that the original
findings suggest that higher levels of fear of known consequences of a change decreased the
likelihood of having higher levels of resistance to change (see Table 8). Given the fact that
no other measures of fear of known consequences of a change was significantly predictive
of any other measures of active resistance to change, I am cautiously optimistic that a
relatively firm conclusion about the relationship between fear of known consequences of a
change and active resistance to change can be made: that is, the negative relationship found
in the main study was attributable to differences in patterns of directions of measures of fear
of known consequences of a change and/or measures of active resistance to change.
It is interesting to note that many, if not most, relationships between measures of
passive resistance to change (i.e., PR1 = a measure of employees’ withdrawal, PR2 = a
measure of employees’ ignorance of a change and PR3 = a measure of employees’
ignorance of a change) on the one hand and measures of independent variables on the other
hand were consistent with expectations. Indeed, the aggregate indicator for passive
resistance to change used in Study 2 was derived from the aggregation between PR 2 and
PR 3, which measures degrees of employees’ ignorance of the privatization. The findings
221
here reaffirm the notion that both PR2 and PR3 can be used to measure employees’
ignorance of a change due to the fact that many, if not most, predictors that were
significantly predictive of PR2 were also significantly predictive of PR3, with same sign of
coefficients. But at the same time the findings suggest that many perceptions may have a
negative effect on employee’s ignorance of the change. In this view, many hypotheses
regarding resistance to change, at least for employee’s ignorance of the change, were
strongly supported by these findings.
Table 40 present an overview of the significant relationships for resistance to change
indicators tested in the models. The details of each significant relationship can be found in
Table 47 - 52. For ease of interpretation, I only mentioned the results that are new in these
analyses or significantly different to those of in the main study.
There is observable evidence that the results of AS1, which measured employees’
embracing of a change, are generally similar to those of AS2, which measured employees’
cooperation with the firm on the change. In contrast, the results of AS3, which measured
employees’ support for change, are generally opposite that those of AS1 and AS2. Up to this
point, the examination of the results reported here suggests that perceived participation in
decision-making 1 had a positive effect on AS1, and perceived participation in decision-
making 2 had a negative effect on AS1. These findings are contradictory to that of in the
main study which suggests that perceived participation in decision-making was not
significantly predictive of active support for change. One plausible explanation to this
difference is that perceived participation in decision-making 2 which was not significantly
predictive of AS1 was used as part of the aggregate indicator for this construct.
Consequently, the aggregate indicator for this construct was not significantly predictive of
active support for change. Further, the levels of job security 2 and job motivation 1
increased the likelihood of having higher levels of AS2. Another new finding is that
affective commitment 2 and 3 were significantly related to AS1 and AS2, respectively. The
results also indicate that perceptions of colleagues’ resistance to change 1 were negatively
related to AS1 and AS2. Similarly, perceptions of colleagues’ resistance to change 2 were
positively related to AS1 and AS2. Clearly, this is attributable to the insignificant
relationship between perceptions of colleagues’ resistance to change and employees’
support for change in the main study. Given that there existed many negative significant
relationships between independent variables and AS3 in these analyses, it is entirely
possible to argue that AS3, which measured the extent to which the organization receives
support from employees, is better representative of levels of resistance to change than levels
of support for change.
222
The findings also indicate that higher levels of perceived procedural justice 1 increased
the likelihood of having higher levels of PS1, which measured the extent to which
employees agree with the organization on the change, and PS2, which measured the extent
to which employees feel that the change was acceptable. Similarly, higher levels of
perceived procedural justice 2 did increase the likelihood of having higher levels of PS1.
Taken together, these findings suggest that perceived procedural justice has a positive
significant effect on employee’s agreement with the organization on the change and
employees’ acceptance of the change.
The findings also indicate that higher levels of Perceived Change in Pride 1 increased
the likelihood of having higher levels of PS1 and PS2, and higher levels of Perceived
Change in Pride 2 increased the likelihood of having higher levels of PS2. Recall that the
findings in Study 2 indicate that perceived change in pride was not significantly predictive
of passive support for change. The new findings demonstrate that the original findings are
incorrect. Furthermore, the new findings indicate that all three measure of self-confidence
for learning and development were positively related to PS2, whereas the original findings
indicate that self-confidence for learning and development was not significantly related to
passive support for change. This finding is valuable as it demonstrates that the original
findings in Study 2 are incorrect. Moreover, the new findings indicate that the levels of trust
in management 2 and 3 were positively related to the levels of PS2. Additionally,
perceptions of colleagues’ resistance to change 1 were positively related to PS 1 and PS 2,
whereas perceptions of colleagues’ resistance to change 2 were negatively related to PS 1
and 2. Consequently, these findings clearly explain the insignificant relationship between
perceptions of colleagues’ resistance to change and employees’ passive support for change
originally found in Study 2.
In sum, these additional analyses provide further evidence that perceptions and/or
attitudes are related to reactions to change. As discussed, the main purpose of these
additional analyses was to find explanations to the unexpected relationships found in Study
2. This objective was partially achieved as a different result was obtained. Using a different
set of procedures, in particular the original measures rather than the aggregate indicators in
the multinomial ordered probit regressions, I found that the new results demonstrate that (1)
the sign of coefficients for some measures which was found to be not consistent with
expectations in the main study was consistent with expectations in these tests, and (2) some
relationships which were not found to be significant in the main study were significant in
these tests. One plausible reason for this difference is that the internal consistency level for
most variables in the main study was low.
223
Table 39: Summary of Regression Results of Indicators for Resistance to Change
AR1 AR2 AR3 PR1 PR2 PR3
Perceived Organizational Support 1 + - -
Perceived Organizational Support 2 - - -
Perceived Organizational Support 3 + -
Perceived Procedural Justice 1 + +
Perceived Participation in Decision-Making 1 - -
Perceived Participation in Decision-Making 2 + -
Perceived Participation in Decision-Making 3 + - -
Perceived Need for Change 1 + -
Perceived Need for Change 2 - - -
Perceived Need for Change 3 -
Attitude toward Organizational Change 2 - -
Attitude toward Organizational Change 3 +
Fear of known Consequences of a Change 2 - - -
Fear of known Consequences of a Change 3 + +
Perceived Change in Power 2 - - -
Perceived Change in Power 3 + - -
Perceived Change in Status 2 - -
Perceived Change in Status 3 - + +
Perceived Change in Pride 1 + + - + +
Perceived Change in Pride 2 + +
Perceived Change in Pride 3 + -
Job Satisfaction 1 - - -
Job Satisfaction 2 -
Job Satisfaction 3 -
Job Security 2 -
Job Security 3 -
Job Motivation 1 + + -
Job Motivation 2 -
Perceived Employability 1 - -
Self-Confidence for Learning 2 + + - + +
Self-Confidence for Learning 3 + - -
Affective Commitment 1 -
Affective Commitment 2 +
Affective Commitment 3 + -
Trust in Management 1 + +
Trust in Management 2 + -
Trust in Management 3 + +
Colleagues’ Resistance to Change 1 + + + +
Colleagues’ Resistance to Change 2 - + - -
Colleagues’ Support for Change + - + - -
Notes: AR1, AR2, and AR3 = Indicators 1, 2 and 3 for Active Resistance to Change, respectively.
PR 1, PR2, and PR 3 = Indicators 1, 2, and 3 for Passive Resistance to Change, respectively.
A “+” sign stands for a positive relationship. A “-” sign stands for a negative relationship.
224
Table 40: Summary of Regression Results of Indicators for Support for Change
AS1 AS2 AS3 PS1 PS2 PS3
Perceived Organizational Support 1 + - - -
Perceived Organizational Support 2 + - - -
Perceived Organizational Support 3 + + +
Perceived Procedural Justice 1 - + + +
Perceived Procedural Justice 2 +
Perceived Participation in Decision-Making 1 + - - -
Perceived Participation in Decision-Making 2 -
Perceived Participation in Decision-Making 3 - + +
Perceived Need for Change 1 + - -
Perceived Need for Change 2 - - -
Perceived Need for Change 3 + - - -
Attitude toward Organizational Change 1 -
Attitude toward Organizational Change 2 + -
Attitude toward Organizational Change 3 -
Fear of known Consequences of a Change 1 +
Fear of known Consequences of a Change 2 + - - - -
Fear of known Consequences of a Change 3 + + -
Perceived Change in Power 1 - +
Perceived Change in Power 2 + + - - -
Perceived Change in Power 3 + + - - -
Perceived Change in Status 2 - - -
Perceived Change in Status 3 - - + + +
Perceived Change in Pride 1 - - + + +
Perceived Change in Pride 2 + +
Job Satisfaction 1 -
Job Security 2 +
Job Motivation 1 + - -
Job Motivation 2
Perceived Employability 1 + - - -
Self-Confidence for Learning & Development 1 +
Self-Confidence for Learning & Development 2 - - + +
Self-Confidence for Learning & Development 3 - +
Affective Commitment 1 +
Affective Commitment 2 +
Affective Commitment 3 + - -
Trust in Management 1 - +
Trust in Management 2 - +
Trust in Management 3 +
Colleagues’ Resistance to Change 1 - - + + +
Colleagues’ Resistance to Change 2 + + - - -
Colleagues’ Support for Change + + - - -
Notes: AS1, AS2, and AS3 = Indicators 1, 2 and 3 for Active Support for Change, respectively.
PS 1, PS2, and PS 3 = Indicators 1, 2, and 3 for Passive Support for Change, respectively.
A “+” sign stands for a positive relationship. A “-” sign stands for a negative relationship
225
Table 41: Regression Results of Active Resistance to Change 1
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables Indicators
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 3
.702”
1.284†
1.916†
2.568†
.850†
.472
.806*
.958†
11.556*
Perceived Procedural Justice 1
.884†
1.538†
2.202†
2.869†
.333
1.309†
1.289†
1.339†
45.071†
Perceived Participation in Decision-M
aking 1
-1.248†
-.482*
.268
1.083†
-2.366†
-.808†
-.647*
-.727*
98.677†
Perceived Need for Change 2
-.726†
-.100
.574†
1.252†
-1.459†
-.422
-.618*
-.629*
33.350†
Fear of Known Consequences of a Change 3
.862†
1.553†
2.225†
2.896†
.131
.962†
1.416†
1.625†
59.082†
Perceived Change in Pride 1
1.047†
1.698†
2.370†
3.071†
1.686†
1.187†
1.419†
1.266†
49.019†
Perceived Change in Pride 2
.638†
1.231†
1.855†
2.498†
.425
.976†
.715†
.750†
16.462†
Self-Confidence for Learning &
Development 2
.793†
1.474†
2.156†
2.860†
1.123†
1.280†
1.529†
.615*
56.759†
Affective Commitment 2
.450†
1.077†
1.754†
2.463†
2.108†
1.220†
.794†
.364**
34.815†
Trust in M
anagem
ent 1
.583*
1.162†
1.789†
2.427†
.508
.748*
.582*
.769*
7.580
Trust in M
anagem
ent 2
.610†
1.256†
1.955†
2.703†
-.153
1.641†
.908†
.843†
47.365†
Trust in M
anagem
ent 3
.442†
1.047†
1.694†
2.349†
1.114†
.819†
.805†
.467*
22.235†
Colleagues’ Resistance to Change 1
.789†
1.432†
2.101†
2.748†
1.077†
1.306†
1.168†
.687†
38.545†
Colleagues’ Support for Change 1
-.667†
-.066
.575*
1.263†
-1.715†
-.608*
-.678†
-.495**
26.501†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
Table 42: Regression Results of Active Resistance to Change 2
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Job Satisfaction 1
-1.391†
-.818†
-.022
.691†
-.767†
-.524*
-.678†
-.600*
11.975*
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
226
Table 43: Regression Results of Active Resistance to Change 3
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 2
-1.509†
-.846†
-.221
.674†
-1.771†
-.555*
-.616*
-.588**
65.739†
Perceived Procedural Justice 1
.453*
1.094†
1.681†
2.530†
.584*
1.452†
1.464†
1.310†
52.500†
Perceived Participation in Decision-M
aking 3
.140
.712*
1.262†
2.089†
.198
.871†
.968†
.925*
22.968†
Attitude towards Organizational Change 3
.303
.867†
1.418†
2.261†
.600*
.934†
.793†
1.263†
23.082†
Fear of Known Consequences of a Change 3
.257
.856†
1.422†
2.270†
.411
.617*
1.214†
1.366†
35.947†
Perceived Change in Power 2
-1.180†
-.626†
-.060
.833†
-1.173†
-1.018†
-.587*
-.448**
26.044†
Perceived Change in Pride 1
.454†
1.102†
1.713†
2.603†
1.722†
1.300†
1.487†
1.027†
60.669†
Perceived Change in Pride 2
-.061
.476†
1.007†
1.841†
.080
.680†
.456*
.536*
10.598*
Perceived Change in Pride 3
.211
.782†
1.355†
2.212†
.240
.673*
.922†
1.303†
27.126†
Job M
otivation 1
.504
1.050†
1.580†
2.435†
.540
1.249†
1.017†
1.316†
18.992†
Self-Confidence for Learning &
Development 2
.289*
.955†
1.577†
2.434†
1.369†
1.363†
1.442†
.915†
59.227†
Self-Confidence for Learning &
Development 3
.171
.781†
1.366†
2.269†
1.795†
1.173†
1.119†
.707†
47.730†
Trust in M
anagem
ent 3
-.111
.448†
.992†
1.834†
.109
.800†
.753†
.473*
19.308†
Colleagues’ Resistance to Change 1
.273**
.873†
1.448†
2.316†
1.159†
1.200†
1.092†
.952†
40.587†
Colleagues’ Resistance to Change 2
-1.172†
-.647†
-.101
.790†
-.683*
-.928†
-.822†
-.729*
14.102†
Colleagues’ Support for Change 1
-1.176†
-.636†
-.082
.790†
-1.298†
-.576*
-.786†
-.629*
18.764†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
227
Table 44: Regression Results of Passive Resistance to Change 1
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-.736†
.145
.767†
1.587†
1.554†
.774†
.848†
.113
46.337†
Perceived Organizational Support 3
-2.090†
-1.330†
-.770†
.006
-.789†
-.653*
-.948†
-.835†
11.829*
Perceived Participation in Decision-M
aking 2
-.862†
-.065
.504†
1.270†
.914†
.527*
.606*
.286
16.336†
Perceived Participation in Decision-M
aking 3
-1.956†
-1.203†
-.659*
.097
-.678*
-.622*
-.716*
-.636**
5.467
Perceived Need for Change 1
-.272
.625
1.248†
2.113†
2.027†
1.613†
1.005†
.814†
60.623†
Fear of Unknown Consequences of a Change 2
-2.720†
-1.948†
-1.376†
-.586
-1.305*
-1.602†
-1.109*
-1.829†
18.423†
Perceived Change in Power 3
-.570†
.234
.822†
1.610†
.960†
1.128†
.759†
1.117†
23.021†
Perceived Change in Status 3
-2.113†
-1.330†
-.750†
.041
-1.178†
-.841†
-.817†
-.468**
21.599†
Perceived Change in Pride 1
-1.791†
-.992†
-.386†
.427††
-1.236
-.473*
-.518*
.014
30.214†
Perceived Change in Pride 3
-.746†
.032
.624*
1.434†
1.211†
.749*
.633*
.178
25.367†
Job M
otivation 1
.294
1.184†
1.798†
2.597†
2.126†
1.749†
2.057†
1.482†
41.903†
Perceived Employability 1
-.985†
-.224
.341*
1.106†
.583*
.618†
.296
.501*
9.416**
Self-Confidence for Learning &
Development 2
-1.796†
-1.049†
-.459†
.354†
-.625*
-.861†
-.739†
-.282
20.841†
Self-Confidence for Learning &
Development 3
-1.652†
-.912†
-.343*
.454†
-.752*
-.474**
-.631†
-.113
14.543†
Affective Commitment 3
-.583†
.294
.943†
1.794†
1.720†
.805†
.927†
.556**
54.461†
Trust in M
anagem
ent 1
-.769†
.041
.593†
1.339†
.395
.625*
.796†
.729†
11.779*
Trust in M
anagem
ent 2
-1.730†
-.921†
-.354*
.415†
-1.236†
-.522*
-.364*
-.267
19.185†
Colleagues’ Resistance to Change 2
-.794†
.039
.640†
1.424†
1.123†
.224
.918†
.738†
27.377†
Colleagues’ Support for Change 1
-.712†
.081
.658†
1.423†
.630*
.603*
.962†
.650*
14.873†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
228
Table 45: Regression Results of Passive Resistance to Change 2
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-1.876†
-1.427†
-.633†
-.040
-2.347†
-1.418†
-1.301†
-.216
89.500†
Perceived Organizational Support 2
-2.395†
-1.928†
-1.140†
-.596*
-2.520†
-1.821†
-1.373†
-1.535†
85.927†
Perceived Participation in Decision-M
aking 1
-2.362†
-1.907†
-1.127†
-.596*
-2.326†
-1.909†
-1.451†
-1.299†
75.805†
Perceived Participation in Decision-M
aking 2
-1.532†
-1.141†
-.452*
.059
-1.531†
-1.171†
-.980†
-.664*
39.915
Perceived Need for Change 1
-1.648†
-1.215†
-.502**
-.005
-1.818†
-1.303†
-1.018†
-.426
55.484†
Perceived Need for Change 2
-1.355†
-.969†
-.289
.174
-1.344†
-.821†
-.840†
-.534**
27.751†
Perceived Need for Change 3
-1.024†
-.648†
-.004
.444*
-.855†
-.348
-.646†
-.657†
12.362*
Attitude towards Organizational Change 2
-1.006†
-.611†
.069
.534†
-1.501†
-.499*
-.674†
-.275
28.811†
Fear of Known Consequences of a Change 2
-2.356†
-1.929†
-1.192†
-.682*
-2.382†
-1.780†
-1.679†
-1.306†
59.447†
Perceived Change in Power 2
-2.084†
-1.665†
-.896†
-.316
-2.331†
-1.662†
-1.644†
-1.078†
72.692†
Perceived Change in Power 3
-1.791†
-1.406†
-.712†
-.197
-1.557†
-1.602†
-1.195†
-1.194†
38.647†
Perceived Change in Status 2
-1.185†
-.812†
-.157
.312**
-1.001†
-.762†
-.794†
-.710†
17.086†
Perceived Change in Status 3
.844†
1.280†
2.039†
2.591†
2.609†
1.715†
1.407†
1.188†
73.764†
Perceived Change in Pride 1
.038
.473†
1.237†
1.784†
2.321†
.865†
.737†
.304
71.783†
Perceived Change in Pride 3
-1.537†
-1.098†
-.358
.156
-1.884†
-1.006†
-.939†
-.023
63.217†
Job Satisfaction 1
-1.126†
-.741†
-.069
.403*
-.955†
-.716†
-.812†
.015
23.871
Job M
otivation 1
-3.165†
-2.769†
-2.049†
-1.481†
-3.067†
-2.740†
-2.824†
-2.038†
59.975†
Perceived Employability 1
-1.28†1
-.901†
-.207
.288
-1.046†
-1.015†
-1.050†
-.479**
28.916†
Self-Confidence for Learning &
Development 2
.075
.533†
1.242†
1.684†
.990†
1.411†
1.076†
.493*
46.111†
Affective Commitment 3
-2.487†
-1.974†
-1.112†
-.496*
-2.956†
-1.782†
-1.652†
-1.219†
120.098†
Colleagues’ Resistance to Change 1
-.029
.381†
1.062†
1.512†
1.025†
1.103†
.564†
.336
28.766†
Colleagues’ Resistance to Change 2
-1.891†
-1.500†
-.783†
-.247
-1.789†
-1.221†
-1.676†
-1.190†
46.204†
Colleagues’ Support for Change 1
-2.870†
-2.468†
-1.716†
-1.108†
-2.263†
-2.418†
-2.689†
-2.227†
71.994†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
229
Table 46: Regression Results of Passive Resistance to Change 3
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-2.375†
-1.763†
-.964†
-.410**
-1.824†
-1.615†
-1.223†
-1.254†
43.211†
Perceived Organizational Support 2
-2.437†
-1.819†
-1.014†
-.464**
-1.702†
-1.601†
-1.185†
-1.377†
43.145†
Perceived Participation in Decision-M
aking 1
-2.058†
-1.462†
-.687†
-.162
-1.232†
-1.271†
-.972†
-.660**
27.213†
Perceived Participation in Decision-M
aking 3
-1.614†
-1.047†
-.301
.194
-.760*
-.651*
-.683*
-.412
7.217
Perceived Need for Change 2
-1.919†
-1.279†
-.435*
.105
-1.464†
-1.067†
-.491**
-.584**
42.151†
Attitude towards Organizational Change 2
-1.927†
-1.311†
-.508†
.032
-1.769†
-.903†
-1.025†
-.851†
39.684†
Fear of Known Consequences of a Change 2
-2.403†
-1.807†
-1.014†
-.483**
-1.596†
-1.453†
-1.487†
-1.050†
30.114†
Perceived Change in Power 2
-2.647†
-2.034†
-1.191†
-.575*
-1.812†
-2.112†
-1.700†
-1.267†
62.825†
Perceived Change in Power 3
-2.041†
-1.445†
-.658†
-.122
-1.310†
-1.332†
-.981†
-.696*
31.815†
Perceived Change in Status 2
-2.093†
-1.447†
-.598†
-.030
-1.881†
-1.292†
-.965†
-.620*
56.185†
Perceived Change in Status 3
-.236
.387**
1.189†
1.726†
1.716†
.933†
.867†
.554*
40.149†
Perceived Change in Pride 1
-.579†
.048
.890†
1.467†
1.938†
.920†
.443*
.315
55.391†
Job Satisfaction 1
-1.989†
-1.380†
-.571†
-.016
-1.476†
-1.077†
-1.066†
-.334
41.311†
Job Satisfaction 2
-2.170†
-1.607†
-.855
-.351
-1.071*
-1.387*
-1.216*
-1.421*
9.064**
Job Satisfaction 3
-1.843†
-1.265†
-.505
.004
-.886*
-.405
-1.035†
-.946*
15.975†
Job Security 2
-1.625†
-1.000†
-.181
.364†
-1.384†
-1.330†
-.715†
-.610†
42.195†
Job Security 3
-1.519†
-.951†
-.183
.353*
-.575
-.677†
-.806†
-.720†
21.998†
Job M
otivation 2
-1.426†
-.810†
-.026
.484†
-1.319†
-.702†
-.512†
-.307
27.475†
Perceived Employability 1
-2.187†
-1.560†
-.709†
-.124
-1.846†
-1.328†
-1.262†
-.835†
56.847†
Self-Confidence for Learning &
Development 2
-.666†
-.062
.702†
1.214†
1.300†
.806†
.523†
.223
24.820†
Affective Commitment 1
-1.863†
-1.293†
-.533*
-.016
-.862†
-.750*
-1.068†
-.823†
16.492†
Colleagues’ Resistance to Change 1
-.670†
-.057
.733†
1.253†
1.412†
.662†
.407*
.135
31.036†
Colleagues’ Resistance to Change 2
-2.568†
-1.962†
-1.114†
-.522*
-1.373†
-1.801†
-1.863†
-1.244†
52.516†
Colleagues’ Support for Change 1
-2.715†
-2.116†
-1.297†
-.714*
-1.806†
-1.861†
-1.941†
-1.324†
48.627†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
230
Table 47: Regression Results of Active Support for Change 1
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-.208
.547*
1.247†
1.704†
2.287†
1.261†
1.114†
1.166†
63.377†
Perceived Organizational Support 2
-.112
.614†
1.379†
1.971†
2.558†
1.190†
1.075†
.801*
108.239†
Perceived Procedural Justice 1
-2.361†
-1.760†
-1.100†
-.599†
-.707†
-1.566†
-1.465†
-1.089†
49.885†
Perceived Participation in Decision-M
aking 1
-.169
.510*
1.232†
1.764†
2.103†
1.153†
.881†
.874
77.089†
Perceived Participation in Decision-M
aking 3
-1.858†
-1.260†
-.648*
-.211
-.172
-.748*
-.953†
-.926*
20.801†
Perceived Need for Change 3
-.588†
.096
.778†
1.288†
2.907†
.456**
.752†
.988†
79.660†
Attitude towards Organizational Change 2
-.729†
-.054
.595†
1.025†
1.491†
.325
.591*
.923†
33.592†
Fear of Known Consequences of a Change 2
-.402
.229
.907†
1.410†
1.833†
.829†
.594*
.549**
59.055†
Perceived Change in Power 2
-.385**
.334
1.002†
1.444†
1.687†
1.403†
1.085†
.609*
48.277†
Perceived Change in Power 3
-.424*
.256
.907†
1.352†
1.620†
1.163†
.681†
.785†
42.262†
Perceived Change in Status 3
-2.495†
-1.793†
-1.124†
-.684†
-1.919†
-.825†
-1.180†
-1.128†
44.124†
Perceived Change in Pride 1
-2.597†
-1.886†
-1.148†
-.630†
-2.353†
-1.016†
-1.446†
-1.276†
80.287†
Perceived Employability 1
-.537†
.200
.873†
1.321†
2.016†
1.064†
.944†
.791†
55.165†
Self-Confidence for Learning &
Development 2
-2.183†
-1.543†
-.843†
-.336
-1.239†
-1.472†
-1.362†
-.565*
58.974†
Self-Confidence for Learning &
Development 3
-1.756†
-1.136†
-.506†
-.073
-1.155†
-.907†
-.728†
-.371**
23.122†
Affective Commitment 2
-.666†
-.020
.583*
.983†
.838†
.426
.628*
.987†
12.524*
Trust in M
anagem
ent 1
-1.956†
-1.354†
-.760†
-.346
-.518
-.707*
-.823†
-.877†
11.025*
Trust in M
anagem
ent 2
-1.523†
-.910†
-.294*
.142
.988†
-.650*
-.440*
-.449**
25.891†
Colleagues’ Resistance to Change 1
-2.339†
-1.663†
-.961†
-.468†
-1.578†
-1.767†
-1.036†
-.809†
63.268†
Colleagues’ Resistance to Change 2
-.240
.489*
1.143†
1.565†
1.681†
1.153†
1.429†
1.000†
40.062†
Colleagues’ Support for Change 1
-.229
.484*
1.135†
1.564†
1.941†
1.013†
1.398†
.960†
41.676†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
231
Table 48: Regression Results of Active Support for Change 2
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 3
-.752†
.214
.788†
1.570†
1.323†
.761†
.602*
-.179
43.623†
Perceived Need for Change 1
.130
1.161†
1.743†
2.571†
2.260†
1.811†
1.565†
1.000†
65.718†
Attitude towards Organizational Change 2
-.923†
.004
.564†
1.383†
1.746†
.529*
.486*
.064
45.990
Fear of Known Consequences of a Change 1
-2.032†
-1.115†
-.593*
.154
-1.277†
-.999†
-.458
-.783*
25.143†
Fear of Known Consequences of a Change 2
-.452**
.460**
.992†
1.765†
1.252†
.883†
.814†
.192
30.323†
Perceived Change in Power 2
-.639†
.297
.856†
1.655†
1.455†
.813†
.723†
.125
42.028†
Perceived Change in Power 3
-.647†
.233
.748†
1.484†
.852†
.766†
.655*
.338
14.744†
Perceived Change in Status 3
-2.440†
-1.540†
-.996†
-.201
-1.568†
-1.368†
-1.249†
-1.133†
36.123†
Perceived Change in Pride 1
-1.722†
-.851†
-.319*
.459†
-1.107†
-.732†
-.621†
-.289
24.286†
Job Security 2
-1.032†
-.161
.355†
1.090†
1.071*
.535*
.011
.417*
12.730*
Job M
otivation 1
-.318
.599**
1.141†
1.894†
1.499†
.835*
1.129†
.518
26.877†
Self-Confidence for Learning &
Development 2
-1.764†
-.909†
-.366†
.442†
-.555**
-1.019†
-.893†
-.470*
28.199†
Affective Commitment 3
-.479*
.448*
1.026†
1.860†
1.574†
.637*
.862†
.495**
48.224†
Trust in M
anagem
ent 1
-.746†
.122
.624†
1.339†
.694*
.369
.554*
.579*
6.997
Colleagues’ Resistance to Change 1
-1.593†
-.707†
-.186
.563†
-.618*
-.839†
-.128
-.590*
19.310†
Colleagues’ Resistance to Change 2
-.498*
.426**
.982†
1.745†
1.291†
.495**
1.101†
.747†
30.277†
Colleagues’ Support for Change 1
-.371
.544*
1.086†
1.839†
1.057†
.733*
1.253†
.853†
25.348†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
232
Table 49: Regression Results of Active Support for Change 3
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-1.987†
-1.379†
-.694†
-.173
-2.617†
-1.603†
-1.378†
-.356
102.307†
Perceived Organizational Support 2
-2.620†
-1.980†
-1.299†
-.812†
-2.826†
-2.103†
-1.689†
-1.405†
103.586†
Perceived Organizational Support 3
.317
.803†
1.364†
1.763†
1.114†
.740*
.989†
.582**
17.138†
Perceived Procedural Justice 1
-.050
.489†
1.058†
1.423†
-.082
.909†
.700†
.662†
26.798†
Perceived Participation in Decision-M
aking 1
-2.190†
-1.612†
-.975†
-.529*
-2.201
-1.734
-1.433
-.910*
70.950†
Perceived Participation in Decision-M
aking 2
-1.218†
-.716†
-.135
.282
-1.289†
-.831†
-.587*
-.373
30.575†
Perceived Participation in Decision-M
aking 3
.450
.957†
1.509†
1.878†
.755*
1.043†
1.149†
1.308†
15.907†
Perceived Need for Change 1
-1.731†
-1.167†
-.555*
-.131
-1.993†
-1.352†
-1.107†
-.599**
58.514†
Perceived Need for Change 2
-1.599†
-1.067†
-.459*
-.041
-1.653†
-1.286†
-1.009†
-.745*
41.445†
Perceived Need for Change 3
-1.086†
-.599†
-.043
.349**
-1.020†
-.452**
-.733†
-.724†
15.839†
Attitude towards Organizational Change 2
-1.007†
-.490†
.098
.505†
-1.702†
-.537*
-.634*
-.286
34.535†
Fear of known Consequences of a Change 2
-1.953†
-1.399†
-.801†
-.391
-2.082†
-1.262†
-1.278†
-1.077†
51.967†
Perceived Change in Power 2
-2.068†
-1.502†
-.856†
-.363
-2.503†
-1.636†
-1.553†
-1.159†
79.454†
Perceived Change in Power 3
-1.614†
-1.089†
-.482*
-.046
-1.479†
-1.636†
-.906†
-.715*
46.032†
Perceived Change in Status 2
-1.065†
-.590†
-.031
.373*
-.810†
-.829†
-.701†
-.487**
14.041†
Perceived Change in Status 3
.790†
1.349†
1.984†
2.444†
2.464†
1.574†
1.357†
1.023†
68.076†
Perceived Change in Pride 1
.184
.745†
1.379†
1.837†
2.270†
1.047†
.833†
.521
68.839†
Perceived Change in Pride 2
-.018
.488†
1.048†
1.425†
.683*
.924†
.343
.590*
17.455†
Job M
otivation 1
-3.166†
-2.642†
-1.998†
-1.486†
-3.194†
-2.865†
-2.82†9
-1.896†
68.696†
Perceived Employability 1
-1.255†
-.757†
-.178
.243
-1.020†
-1.224†
-.885†
-.602*
29.549†
Self-Confidence for Learning &
Development 2
.201
.775†
1.364†
1.745†
1.371†
1.158†
1.214†
.773†
46.812†
Affective Commitment 3
-2.114†
-1.505†
-.833†
-.334
-2.557†
-1.536†
-1.205†
-1.307†
96.624†
Colleagues’ Resistance to Change 1
.190
.732†
1.313†
1.699†
1.301†
1.171†
.874†
.742†
36.982†
Colleagues’ Resistance to Change 2
-1.707†
-1.203†
-.603†
-.159
-1.620†
-1.059†
-1.530†
-1.030†
39.542†
Colleagues’ Support for Change 1
-1.763†
-1.270†
-.678†
-.234
-1.069†
-1.422†
-1.606†
-1.097†
35.052†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
233
Table 50: Regression Results of Passive Support for Change 1
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-1.675†
-1.219†
-.441**
-.092
-1.154†
-1.087†
-1.170†
-.823†
21.376†
Perceived Organizational Support 2
-2.545†
-2.008†
-1.142†
-.764†
-2.335†
-1.611†
-1.582†
-1.874†
68.507†
Perceived Organizational Support 3
.314
.820†
1.738†
2.196†
2.338†
1.071†
.761*
.678*
80.910†
Perceived Procedural Justice 1
.182
.696†
1.566†
1.929†
1.554†
1.447†
.947†
.887†
50.197†
Perceived Procedural Justice 2
.125
.637†
1.458†
1.791†
.218
1.425†
1.092†
.870†
36.411†
Perceived Participation in Decision-M
aking 1
-1.932†
-1.399†
-.556*
-.211
-1.722†
-.844†
-1.141†
-.760*
50.636†
Perceived Need for Change 2
-1.509†
-1.035†
-.240
.096
-1.110†
-.756*
-.937†
-.591*
20.050†
Perceived Need for Change 3
-1.838†
-1.342†
-.491*
-.120
-1.870†
-1.190†
-1.251†
-.880†
46.698†
Fear of Known Consequences of a Change 2
-2.304†
-1.785†
-.940†
-.589*
-2.086†
-1.370†
-1.549†
-1.141†
48.951†
Fear of Known Consequences of a Change 3
-.264
.242
1.035†
1.355†
.011
.920†
.586*
.861†
27.585†
Perceived Change in Power 2
-2.271†
-1.723†
-.836†
-.443*
-2.539†
-1.460†
-1.403†
-1.352†
78.195†
Perceived Change in Power 3
-1.695†
-1.203†
-.390**
-.045
-1.557†
-.834†
-.963†
-.887†
34.816†
Perceived Change in Status 2
-1.267†
-.815†
-.037
.302
-.677†
-.499*
-.843†
-.613*
13.786†
Perceived Change in Pride 1
-.283**
.222
1.062†
1.421†
1.790†
.147
.445*
.657†
46.649†
Perceived Change in Pride 2
.055
.588†
1.420†
1.751†
.203
.956†
1.369†
.798†
44.462†
Perceived Employability 1
-1.273†
-.805†
-.020
.316**
-.876†
-.490*
-.899†
-.455**
19.184†
Affective Commitment 3
-1.261†
-.791†
-.040
.278
-.806†
-.734†
-.563*
-.477
12.340*
Colleagues’ Resistance to Change 1
-.263**
.225
.996†
1.310†
.996†
.696†
.542†
.454**
18.416†
Colleagues’ Resistance to Change 2
-1.957†
-1.424†
-.540*
-.173
-2.162†
-1.517†
-.881†
-1.032†
60.527†
Colleagues’ Support for Change 1
-2.410†
-1.888†
-1.001†
-.618*
-2.508†
-2.008†
-1.435†
-1.682†
62.277†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
234
Table 51: Regression Results of Passive Support for Change 2
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Organizational Support 1
-1.585†
-.973†
-.336
.060
-2.281†
-1.496†
-1.251†
-1.049†
60.297†
Perceived Organizational Support 2
-2.708†
-1.915†
-1.157†
-.603*
-3.523†
-2.316†
-1.757†
-2.212†
145.894†
Perceived Procedural Justice 1
1.036†
1.730†
2.324†
2.634†
.868†
1.883†
1.753†
1.662†
67.733†
Perceived Participation in Decision-M
aking 1
-1.984†
-1.174†
-.496*
-.102
-2.789†
-1.410†
-1.132†
-.885*
121.275†
Perceived Participation in Decision-M
aking 3
.449
1.083†
1.655†
1.961†
.003
.960†
1.203†
1.203†
43.382†
Perceived Need for Change 2
-1.282†
-.633†
-.012
.347
-2.043†
-.930†
-.936†
-.449†
64.453†
Perceived Need for Change 3
-1.035†
-.417*
.161
.501*
-2.296†
-.542*
-.744†
-.920†
54.623†
Fear of Known Consequences of a Change 2
-2.033†
-1.273†
-.617*
-.251
-2.958†
-1.394†
-1.380†
-1.244†
106.490†
Fear of Known Consequences of a Change 3
.439**
1.077†
1.655†
1.968†
.042
.750*
1.096†
1.395†
47.941†
Perceived Change in Power 1
-.791†
-.234
.330**
.657†
-1.199†
-.602*
-.798†
-.276
17.679
Perceived Change in Power 2
-1.742†
-1.079†
-.393**
.041
-2.433†
-2.082†
-1.241†
-1.138†
84.000†
Perceived Change in Power 3
-1.619†
-.944†
-.302
.093
-2.454†
-1.593†
-.951†
-1.063†
83.108†
Perceived Change in Status 2
-.943†
-.353**
.240
.593†
-1.839†
-.712†
-.760†
-.439**
42.910†
Perceived Change in Status 3
.738†
1.330†
1.922†
2.292†
1.943†
.741*
1.073†
.730*
46.318†
Perceived Change in Pride 1
.983†
1.696†
2.352†
2.751†
2.778†
1.578†
1.588†
1.183†
98.277†
Perceived Change in Pride 2
.316**
.886†
1.430†
1.727†
.401
.793†
.502*
.818†
14.302†
Job Satisfaction 1
-.910†
-.314
.281
.634†
-1.634†
-.817†
-.635†
-.033
43.733†
Perceived Employability 1
-1.201†
-.574†
.039
.412*
-2.343†
-1.146†
-.959†
-.817†
63.948†
Self-Confidence for Learning and Development 1
.402*
1.000†
1.540†
1.834†
.138
.982†
1.029†
.514*
27.832†
Self-Confidence for Learning and Development 2
.868†
1.670†
2.325†
2.662†
1.512†
2.007†
2.119†
.971†
105.032†
Self-Confidence for Learning and Development 3
.303*
.904†
1.441†
1.721†
1.044†
.934†
.842†
.430*
24.274†
Trust in M
anagem
ent 2
.104
.693†
1.239†
1.527†
-.579**
.662*
.532†
.582*
20.781†
Trust in M
anagem
ent 3
.156
.749†
1.281†
1.556†
-.125
.581*
.812†
.473*
18.159†
Colleagues’ Resistance to Change 1
.869†
1.549†
2.148†
2.470†
1.867†
1.778†
1.399†
1.143†
69.320†
Colleagues’ Resistance to Change 2
-1.462†
-.873†
-.276
.096
-1.720†
-1.560†
-1.391†
-.866†
44.295†
Colleagues’ Support for Change 1
-2.047†
-1.425†
-.798†
-.385
-2.743†
-1.941†
-1.972†
-1.527†
68.325†
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
235
Table 52: Regression Results of Passive Support for Change 3
Estim
ates for Dependent Variable Threshold
Estim
ates for Independent Variable Location
Independent Variables
1
2
3
4
1
2
3
4
χ2
Perceived Need for Change 1
-1.923†
-1.193†
-.597*
-.166
-1.028†
-.738*
-.994†
-.945†
12.810*
Attitude towards Organizational Change 1
-1.310†
-.582†
.013
.445†
-.929*
-.439*
-.542*
-.104
11.966*
Attitude towards Organizational Change 3
-1.743†
-1.020†
-.416*
.026
-.741†
-.552*
-.827†
-.973†
15.163†
Fear of Known Consequences of a Change 1
-.581*
.162
.758†
1.176†
.688*
.210
.596*
.692*
9.722*
Fear of Known Consequences of a Change 2
-1.598†
-.859†
-.270
.147
-.631*
-.704*
-.604*
-.238
8.148**
Fear of Known Consequences of a Change 3
-1.968†
-1.227†
-.608*
-.155
-1.030†
-.535**
-1.097†
-1.201†
23.855†
Perceived Change in Power 1
-.685†
.050
.637†
1.056†
.853*
.499*
.437*
.172
8.565**
Job M
otivation 1
-3.041†
-2.280†
-1.675†
-1.225†
-2.393†
-2.056†
-1.941†
-1.937†
31.195†
Affective Commitment 1
-.555*
.188
.791†
1.211†
.638*
.362
.498*
.891†
10.400*
Notes:
N = 197. Variables have 5 L
evels: 1 = L
ow; 2 = R
elatively L
ow; 3 = M
edium; 4 = R
elatively H
igh; and 5 = H
igh.
Param
eter for Independent Variable’s level 5 is set to zero because it is redundant; † p < .01, * p < .05, ** p < .10
236
Curriculum Vitae
Chaiporn Vithessonthi
PERSONAL DATA
Date of Birth: 26 September 1975
Nationality: Thai
EDUCATION
University of St. Gallen (HSG), Dr.oec., Concentration in Strategy and Organizational Change, 2003-2005
University of St. Gallen (HSG), Lic.oec. and M.Sc. in International Management, 2001-2003
Erasmus University Rotterdam (RSM), Certificate of International Business, 2002
Western Illinois University, M.A. in Economics, Concentration in Macroeconomic Theory, 1999-2000
Assumption University, B.B.A., Concentration in Finance and Accounting, 1993-1997
PROFESSIONAL EXPERIENCE
Novartis Pharma AG, Basel, Switzerland, 2003-Present
Consultant
� Engaged in a process redesign project at Novartis Pharma A.G. in Basel, which aimed at simplifying
and improving planning processes related to Strategy, Finance, Marketing, and R&D.
� Carried out activities related to the analysis, design, implementation and active support of the
organizational change required for the successful implementation of the new processes.
� Carried out activities related to global financial management reporting, monthly management analysis.
Heineken International, Zoeterwoude, the Netherlands, 2002
Consultant, in conjunction with the Rotterdam School of Management
� Managed a team (of four members) that engaged in a supply sourcing strategy project aimed at
ensuring the sustainability of key strategic packaging materials.
� Carried out activities related to the analysis, design and implementation of a framework for Heineken
to analyze the packaging industry in Europe and North America and its suppliers.
Accenture, Bangkok, Thailand, 2001
Experienced Analyst: Client Financial Management
� Worked with engagement executives to set-up and coordinate the engagement work; financial
management processes, tools and reporting structure; and responsible for deal financial analysis for
business process management (BPM) projects.
� Prepared project pricing models; reviewed proposals; monitored engagement profitability.
� Responsible for financial management reporting and analysis of IT ONE Company (Accenture’s first
joint-venture company in Asia).
Accenture, Chicago, IL, USA, 2000
Financial Analyst
� Responsible for monitoring and analyzing financial results of operating units: Financial Services North
America Client Group
� Recommend ways to maximize profitability and enable predictable financial results.
Western Illinois University, Macomb, IL, USA, 1999-2000
Graduate Assistant
� Tutored undergraduate courses in economics (e.g., microeconomics, macroeconomics, econometrics,
international trade theory).
237
Laufen Asia Ltd. (a member of the Keramic Laufen Group of Switzerland), Hong Kong, 1998-1999
Business Analyst and Special Assistant to Managing Director
� Assisted the work involving financial analysis and planning.
� Assisted managing director focusing on activities related to marketing analysis and planning.
UMI-Laufen (a member of the Keramic Laufen Group of Switzerland), Bangkok, Thailand, 1998
Business Analyst
� Assisted purchasing and planning manager focusing on materials planning.
� Worked with top management team to set up and implement efficiency improvement projects aimed at
redesigning and improving inventory and production planning processes.
Standard Chartered Bank, Bangkok, Thailand, 1997
Staff Accountant
� Responsible for monitoring accounting transactions and performing reconciliation processes.
� Ensured accuracy of accounts for the credit card department.
Jaques (Thailand) Ltd. (a member of Clyde Industry Group of Australia), Bangkok, Thailand, 1995-1996
Project Assistant
� Assisted project managers focusing on project management of two rock-quarrying-plant projects.
� Worked with project managers to prepare project financial reports.
SELECTED GRANTS, AWARDS AND FELLOWSHIPS
International Business Consulting Project, First Prize, Rotterdam School of Management, 2002
ERASMUS Scholarship, 2002
Mercuria San Gallensis 100th Jubilee Scholarship, University of St. Gallen, 2001-2002
Graduate Assistantship, Western Illinois University, 1999-2000