high performance work system at bank
TRANSCRIPT
High Performance Work System at Bank
Branches: Exploring the ‘Black Box’ of Strategic
Human Resource Management through the Lens of
Resource Based View and Organizational Justice
Theory
By
Amir Riaz
CIIT/FA12-PMS-011/LHR
PhD Thesis
In
Management Sciences
COMSATS University Islamabad
Lahore Campus - Pakistan
Fall, 2017
ii
COMSATS University Islamabad, Lahore Campus
High Performance Work System at Bank Branches:
Exploring the ‘Black Box’ of Strategic Human
Resource Management through the Lens of Resource
Based View and Organizational Justice Theory
A Thesis Presented to
COMSATS University Islamabad
In partial fulfillment
of the requirement for the degree of
PhD (Management Sciences)
By
Amir Riaz
CIIT/FA12-PMS-011/LHR
Fall, 2017
viii
DEDICATION
To my parents, family, teachers and friends
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ACKNOWLEDGEMENTS
First of all, from the core of my heart, I am thankful to Almighty ALLAH and Holy
Prophet Muhammad (S.A.W.W.) that I have been succeeded in completing my PhD
thesis.
Moreover, it would not be doing justice in presenting this thesis without mentioning
people around me who have been inextricably related with the completion of my PhD
thesis.
With greatest homage and regards, I am thankful to my supervisor, Dr. Hafiz Zahid
Mahmood, for his dedication and valuable guidance throughout the completion of my
PhD journey. Without his generosity, it would have been impossible for me to
accomplish this task. I also express my sincere thanks to Dr. Muhammad Ibrahim
Abdullah and Dr. Tajammal Hussain, members of my supervisory committee, for their
guidance and support throughout this research project. I would also like to say thanks to
Department of Management Sciences, COMSATS University Islamabad, Lahore Campus
for the support during the journey of my PhD. There are many people around who gave
me support in my research and even more in my daily life during last four years, some of
them are Mr. Kashif Mahmood, Dr. Zafar Uz Zaman and Dr. Basharat Naeem. I also
express thanks to the people who helped and assisted me in data collection for this
research thesis and the managers and employees who participated in this research project.
Finally, I would like to thank my parents, brothers and sisters for their continuous
support, encouragement and unconditional love. Most of all, a big thanks to my beloved
wife, Samina Amir, and my kids, Jannat Fatima and Muhammad Hashir, for using from
their time to complete this study.
Thank you all for your support and trust, without your support and motivation, this study
would just have been a dream.
Amir Riaz
CIIT/FA12-PMS-011/LHR
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ABSTRACT
High Performance Work System at Bank Branches: Exploring the
‗Black Box‘ of Strategic Human Resource Management through
the Lens of Resource Based View and Organizational Justice
Theory
Previous research linking high performance work systems and organizational
performance, mainly done at organizational level of analysis, is declared managerially
biased. Moreover, researchers are exploring the mediating mechanisms linking high
performance work system with performance outcomes and termed this issue as ‗black
box‘ debate in the literature. In addition to this, previous studies have been criticized for
using intended, instead of implemented, high performance work system highlighting that
intended may not be implemented, by the line managers, in same way throughout the
organization.
Keeping in view these gaps in literature, this study attempts to investigate the relationship
of implemented high performance work system with bank branch performance and
employee outcomes, and the mediating processes for explaining these relationships.
Drawing upon mutual gains perspective of HRM, this study, first, hypothesizes that
implemented high performance work system is positively related to both bank branch
performance and employee outcomes (employee engagement, service performance and
service oriented organizational citizenship behavior). Further, based upon resource based
view of the firm, the study hypothesizes that implemented high performance work system
and bank branch performance relationship is mediated by branch level collective human
capital. In the last, using social exchange theory, this study also investigates
organizational justice dimensions (distributive justice, procedural justice and interactional
justice) as mediating mechanisms for explaining the relationship between implemented
high performance work system and employee outcomes.
For this multilevel study, survey technique is used to obtain data from 323 bank branch
managers and 1369 front line employees of 30 commercial banks operating in Punjab,
Pakistan. For data analysis, structural equation modeling is employed to test branch level,
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whereas hierarchal linear modeling is used to test cross-level proposed relationships of
the study. Findings of the study indicate that (i) implemented high performance work
system is positively related with bank branch collective human capital and bank branch
performance; (ii) branch level collective human capital partially mediates the relationship
between implemented high performance work system and branch performance; (iii)
implemented high performance work system is significantly related with three
dimensions of organizational justice and employee outcomes and (iv) distributive justice,
procedural justice and interactional justice perceptions partially mediates the relationship
between implemented high performance work system and employee outcomes.
This study contributes into literature through proposing and empirically examining a
comprehensive integrative framework linking implemented high performance work
system with branch performance and employee outcomes, and the intermediary
mechanisms for explaining these direct relationships. In specific, findings of the study
support the mutual gains perspective of human resource management (i.e. human
resource management is beneficial for organization and employees both) and that human
capital of bank branch emerges as intervening mechanism to explain the relationship
between implemented high performance work system and branch performance. Further,
employees‘ justice perceptions are also emerged as important factor in explaining the
effects of implemented high performance work system on employee outcomes. The
findings of this study also assist organizations and HR practitioners in understanding the
role of line managers in effective implementation of high performance work system and
the focus areas (intermediary mechanisms) for such systems to favorably influence both
bank branches performance and employee outcomes.
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TABLE OF CONTENTS
1. Introduction ...................................................................................................... 2
1.1 Background of the Study ................................................................................ 2
1.2 Statement of the Problem ................................................................................ 8
1.3 Context of the Study ....................................................................................... 9
1.4 Research Questions ....................................................................................... 11
1.5 Research Objectives ...................................................................................... 12
1.6 Significance of the Study .............................................................................. 12
1.7 Thesis Progression ........................................................................................ 14
1.8 Conclusion .................................................................................................... 15
2. Literature Review .......................................................................................... 17
2.1 Introduction ................................................................................................... 17
2.2 Emergence of Human Resource Management and Performance ................. 17
2.2.1 Scientific Management ........................................................................... 18
2.2.2 Human Relations Movement .................................................................. 19
2.2.3 Quality of Working Life ......................................................................... 20
2.2.4 Human Resource Management ............................................................... 21
2.3 High Performance Work Systems (HPWS) .................................................. 26
2.3.1 Debates in HPWS-Performance Research .............................................. 31
2.3.1.1 Debate 01: ―Black Box‖ Issue of SHRM ............................................ 31
2.3.1.2 Debate 02: Inclusion of Employees' perspective in HPWS-
Performance ..................................................................................................... 33
2.3.1.3 Debate 03: Intended Vs Implemented HPWS ..................................... 36
2.3.1.4 Debate 04: Level of Analysis .............................................................. 38
2.3.1.5 Debate 05: Methodological Issues in SHRM Research ...................... 40
2.4 Human Resource Management Research in Pakistan .................................. 42
2.5 Conceptual Framework ................................................................................. 44
2.6 Branch Level Hypotheses ............................................................................. 46
2.6.1 Manager-HPWS and Bank Branch Performance ................................... 46
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2.6.2 Mediating Role of Branch Level Collective Human Capital ................. 49
2.7 Cross-Level Hypotheses ............................................................................... 52
2.7.1 High Performance Work System (HPWS) and Employee Outcomes .... 52
2.7.2 Mediating Role of Organizational Justice .............................................. 59
2.7.2.1 Manager-HPWS, Distributive Justice and Employee Outcomes ........ 62
2.7.2.2 Manager-HPWS, Procedural Justice and Employee Outcomes .......... 64
2.7.2.3 Manager-HPWS, Interactional Justice and Employee Outcomes ....... 69
2.8 Conclusion .................................................................................................... 73
3. Methodology ................................................................................................... 75
3.1 Introduction ................................................................................................... 75
3.2 Research Philosophy ..................................................................................... 75
3.3 Research Design ........................................................................................... 77
3.4 Target Study Area ......................................................................................... 79
3.5 Population and Sample ................................................................................. 79
3.6 Data Collection Technique and Survey Procedure ....................................... 82
3.7 Measures for Common Method Bias ............................................................ 84
3.8 Measurement of Variables ............................................................................ 85
3.8.1 Branch Level Variables .......................................................................... 85
3.8.1.1 Manager HPWS ................................................................................... 85
3.8.1.2 Collective Human Capital ................................................................... 86
3.8.1.3 Bank Branch Performance ................................................................... 86
3.8.2 Employee Level Variables ...................................................................... 87
3.8.2.1 Distributive Justice .............................................................................. 87
3.8.2.2 Procedural Justice ................................................................................ 87
3.8.2.3 Interactional Justice ............................................................................. 88
3.8.2.4 Employee Engagement ........................................................................ 88
3.8.2.5 Employee Service Performance ........................................................... 88
3.8.2.6 Service Oriented OCB ......................................................................... 89
3.8.3 Control Variables .................................................................................... 89
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3.9 Data Analysis Techniques ............................................................................ 90
3.9.1 Descriptive Statistics .............................................................................. 90
3.9.2 Reliability Analysis ................................................................................ 90
3.9.3 Structural Equation Modeling ................................................................ 91
3.9.4 Hierarchical Linear Modeling ................................................................ 92
3.10 Ethical Considerations ................................................................................ 96
3.11 Conclusion .................................................................................................. 97
4. Results of the Study ....................................................................................... 99
4.1 Introduction ................................................................................................... 99
4.2 Characteristics of Participants ...................................................................... 99
4.2.1 Characteristics of Participated Bank Branches ..................................... 100
4.2.2 Characteristics of Participated Employees ........................................... 101
4.3 Data Handling and Preliminary Analysis ................................................... 103
4.3.1 Missing Values and Data Cleaning Up................................................. 103
4.3.2 Normality and Outliers ......................................................................... 104
4.4 Individual Items Descriptive Analysis........................................................ 105
4.4.1 Item Wise Descriptive Analysis: Branch Level ................................... 105
4.4.1.1 Manager-HPWS ................................................................................. 106
4.4.1.2 Collective Human Capital ................................................................. 110
4.4.1.3 Bank Branch Performance ................................................................. 111
4.4.2 Item Wise Descriptive Analysis: Individual Level .............................. 112
4.4.2.1 Distributive Justice ............................................................................ 112
4.4.2.2 Procedural Justice .............................................................................. 113
4.4.2.3 Interactional Justice ........................................................................... 115
4.4.2.4 Employee Engagement ...................................................................... 117
4.4.2.5 Employee Service Performance ......................................................... 118
4.4.2.6 Employee Service Oriented OCB ...................................................... 119
4.5 Confirmatory Factor Analysis (CFA) ......................................................... 121
4.5.1 Branch Level Measurement Model (CFA) ........................................... 123
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4.5.2 Individual Employee Level Measurement Model (CFA) ..................... 125
4.6 Reliability of Variables ............................................................................... 127
4.7 Means, Standard Deviations and Correlation Results ................................ 129
4.8 Hypotheses Testing: Branch Level Relationships ...................................... 133
4.9 Hypotheses Testing: Cross-Level Relationships ........................................ 136
4.9.1 Cross-Level Direct Relationships ......................................................... 138
4.9.2 Cross-Level Mediation Analysis .......................................................... 141
4.9.2.1 Mediation Effects of Distributive Justice .......................................... 142
4.9.2.2 Mediation Effects of Procedural Justice ............................................ 145
4.9.2.3 Mediation Effects of Interactional Justice ......................................... 147
4.10 Summary of Hypotheses Testing Results ................................................. 149
4.11 Conclusion ................................................................................................ 150
5. Discussion of Results, Implications and Conclusion ................................ 152
5.1 Introduction ................................................................................................. 152
5.2 Discussion of Results .................................................................................. 152
5.2.1 Branch Level Relationships .................................................................. 152
5.2.2 Cross-Level Relationships .................................................................... 154
5.3 Implications of the Study ............................................................................ 159
5.3.1 Theoretical Implications ....................................................................... 159
5.3.2 Methodological Implications ................................................................ 161
5.3.3 Practical Implications ........................................................................... 162
5.4 Limitations and Future Research Avenues ................................................. 164
5.5 Conclusions ................................................................................................. 165
6. References ..................................................................................................... 168
Appendices .......................................................................................................... 209
APPENDIX A: Details of Bank Branches........................................................ 209
APPENDIX B: Branch Manager Survey .......................................................... 210
APPENDIX C: Front-Line Employee Survey .................................................. 214
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LIST OF FIGURES
Figure 2.1: Hypothesized Model....................................................................................... 45
Figure 3.1: Model for Structure Equation Modeling (SEM) ............................................ 92
Figure 3.2: Cross-level Proposed Relationships ............................................................... 96
Figure 4.1: Structural Equation Modeling, Direct Effects .............................................. 134
Figure 4.2: Structure Equation Modeling, Indirect Effects............................................. 134
Figure 4.3: Cross-level Relationships ............................................................................. 137
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LIST OF TABLES
Table 4.1: Characteristics of Participated Bank Branches (n = 323) .............................. 100
Table 4.2: Characteristics of Participated Front Line Service Employees (n = 1369) ... 102
Table 4.3: Skewness and Kurtosis Values of Variables ................................................. 105
Table 4.4: Descriptive Statistics for Manager-HPWS Items .......................................... 107
Table 4.5: Descriptive Statistics for Branch Level Collective Human Capital Items .... 110
Table 4.6: Descriptive Statistics for Branch Performance Items .................................... 111
Table 4.7: Descriptive Statistics for Distributive Justice Items ...................................... 113
Table 4.8: Descriptive Statistics for Procedural Justice Items ........................................ 114
Table 4.9: Descriptive Statistics for Interactional Justice Items ..................................... 116
Table 4.10: Descriptive Statistics for Employee Engagement Items .............................. 117
Table 4.11: Descriptive Statistics for Employee Service Performance Items ................ 119
Table 4.12 Descriptive Statistics for Employee Service Related OCB Items ................ 120
Table 4.13: Model Fit Criteria ........................................................................................ 122
Table 4.14: Measurement Models Comparisons (Branch Level) ................................... 124
Table 4.15: Measurement Models Comparisons (Individual Level) .............................. 126
Table 4.16: Reliability Scores of the Variables .............................................................. 128
Table 4.17: Means, Standard Deviations and Correlation Results (Branch Level) ........ 131
Table 4.18: Means, Standard Deviations and Correlation Results (Individual Level) ... 132
Table 4.19: Regression Results for Manager-HPWS, Collective Human Capital and
Branch Performance........................................................................................................ 135
Table 4.20: HLM Results of Manager-HPWS and Employee Outcomes ...................... 140
Table 4.21: HLM Results of Manager-HPWS, Distributive Justice (Mediator) and
Employee Outcomes ....................................................................................................... 144
Table 4.22: HLM Results of Manager-HPWS, Procedural Justice (Mediator) and
Employee Outcomes ....................................................................................................... 146
Table 4.23: HLM Results of Manager-HPWS, Interactional Justice (Mediator) and
Employee Outcomes ....................................................................................................... 148
Table 4.24: Summary of Hypotheses Testing Results .................................................... 149
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LIST OF ABBREVIATIONS
AMO Ability, Motivation and Opportunity to Perform
AMOS Analysis of Moment Structures
CEO Chief Executive Officer
CFA Confirmatory Factor Analysis
CFI Comparative Fit Index
d.f. Degree of Freedom
FDI Foreign Direct Investment
GDP Gross Domestic Product
GLS Generalized Least Square
HCM High Commitment Management
HLM Hierarchical Linear Modeling
HPWS High Performance Work System
HR Human Resource
HRM Human Resource Management
ICC Interclass Correlation
IFI Incremental Fit Index
IRA Industrial Relations Act
KSAs Knowledge, Skills and Abilities
OCB Organizational Citizenship Behavior
OLS Ordinary Least Squares
QWL Quality of Working Life
RBV Resource Based View of the Firm
RMR Root Mean Square Residual
RMSEA Root Mean Square Error of Approximation
ROA Return on Assets
SBP State Bank of Pakistan
SD Standard Deviation
SHRM Strategic Human Resource Management
SEM Structural Equation Modeling
SPSS Statistical Package for the Social Sciences
TLI Tucker-Lewis Index
χ2
Chi Square
Chapter 01:
Introduction
2
1. Introduction
1.1 Background of the Study
Managing human resource is one of the most important concerns for contemporary
organizations because of its potential to generate competitive advantage. Strategic human
resource management (SHRM) is a research area devoted to investigate and understand
the impact of bundle of HR practices (called high performance work system: HPWS) on
organizational performance outcomes (e.g. Combs, Liu, Hall & Ketchen, 2006; Guest,
2011). Theorists and researchers in strategic HRM argued that the influence of HR
practices can be better understood by using the combination of HR practices as system
rather than studying any HR practice individually which they termed as high performance
work system (e.g. Huselid, 1995; Becker & Huselid, 1998; Ostroff & Bowen, 2000;
Wright & Boswell, 2002; Takeuchi, et al., 2007; Liao, Toya, Lepak & Hong, 2009). More
specifically, a set of HR activities which are mutually reinforcing and generate
synergistic impact is called high performance work system (Huselid, 1995). In this
research area, researchers have developed consensus that HPWS is positively related with
various organizational performance outcomes including profitability, productivity,
innovation, customer services and various other organizational performance metrics (e.g.
Arthur, 1994; Huselid, 1995; Delaney & Huselid, 1996; Delery & Doty, 1996; Youndt,
Snell, Dean & Lepak, 1996; Appelbaum, Bailey, Berg & Kalleberg, 2000; Guthrie,
2001; Datta, Guthrie & Wright, 2005; Combs, et al., 2006; Subramony, 2009; Jiang,
Lepak, Hu & Baer, 2012; Katou & Budhwar, 2015; Agarwal & Farndale, 2017).
However, despite the empirical confirmation regarding positive HPWS-performance
relationship, the basic question that ―how (intermediary mechanisms) these systems of
integrative HR practices impact organizational outcomes‖, is still on its way of searching
answers and is one of the most recent debates in the area of SHRM (e.g. Bowen &
Ostroff, 2004; Boselie, Dietz & Boon, 2005; Jiang, Takeuchi & Lepak, 2013; Van De
Voorde & Beijer, 2015). Researchers termed this issue as ―black box‖ of SHRM,
3
highlighting the fact that mediating mechanisms through which HPWS affects
performance outcomes have not been established yet, firmly (e.g. Purcell, 2003; Evan &
Davis, 2005; Danford, Richardson, Stewart, Tailby & Upchurch, 2008). In a systematic
review of 104 studies, Boselie, et al. (2005: 77) put this fact as ―plenty of
acknowledgements of the existence of the ‗black box‘ and some speculation on its
possible contents, however, few studies tried to look inside‖. Similarly, Wright and
Gardner (2003) claimed that the ―black box‖ components remain a mystery as not much
is known regarding what goes on in between HPWS and performance. In addition,
Wright and Nishii (2007) argued that analyzing the ―black box‖ requires the researchers
to examine HR causal chain starting from intended to actually implemented HRM
practices, to employee perceptions of HRM practices which further shape employee
responses, followed by organizational performance outcomes. In particular, Guest (2011,
p. 3) recently concluded that ―even after two decades of extensive research, it is not yet
possible to fully understand this linkage‖. Recently, Boxall, Guthrie and Paauwe (2016)
highlighted that researchers have made considerable efforts to decode ―black box‖,
efforts are still required to explore mediating mechanisms for HPWS relationship with
organizational performance and employee outcomes.
Furthermore, previous studies in SHRM have been criticized because of using
management-centric approach while examining HPWS-performance linkage (Boselie, et
al., 2005; Paauwe, 2009; Kaufman, 2010), thus, declared to be managerially biased
(Boxall & Macky, 2014). Researchers further argued that employees‘ perceptions about
HR practices, not intended HR practices, influence their reactions at work and highlight
the need to incorporate employees‘ perspective in order to have a more deeper insight
into HPWS-performance relationship. Following these lines, researchers have
investigated the mediating role of employees‘ perceptions of HPWS for HPWS and
employee outcomes relationship (e.g. Liao et al., 2009; Huang, Ma & Meng, 2017).
Another reason for involving into employees‘ perspective is that this research regarding
HPWS-performance relationship has been developed upon mutual gains perspective of
employment relations, which claims that HRM interventions have favorable outcomes for
both organizations and employees (e.g. Appelbaum, et al., 2000; Guest, 1999). Whereas,
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the critiques argued that improvements in organizational performance are due to the
factors like work intensification, pressures to perform, more formalized structures rather
than autonomy, higher job satisfaction and greater discretions (Ramsey, Scholarios &
Harley, 2000), therefore, enhance organizational performance without increasing
employees‘ well-being (i.e. conflicting interests perspective). This fact also supports the
thought that HPWS is not different from the previous methods of employees‘ control
(Grant & Shields, 2002). Recently, researchers have started examining HPWS and
employee outcomes relationship, however, reported contradictory results (Van De
Voorde, Paauwe & Van Veldhoven, 2012). Moreover, literature is scarce related to
examining impact of same HPWS on organizational performance and employee
outcomes simultaneously (Boxall, et al., 2016).
Extant HPWS-performance literature has also been criticized for using organization-level
data, assuming that intended HPWS is implemented in the same manner throughout the
organization as intended (Wright & Nishii, 2013). Whereas, in reality, the top
management/ HR departments reported HR practices representing their espoused/
intended HR policies, which may not be implemented in the same way across the
organization (Khilji & Wang, 2006; Nishii & Wright, 2007). Studies have also confirmed
this fact by illustrating that HR managers have reported more practices than number of
practices reported by line managers and workers (e.g. Liao, et al., 2009; Guest, et al.,
2010). Line managers are people responsible for the implementation of organizational
intended HR practices within their respective departments and, therefore, are main source
of determining quality of implementation and effectiveness of HR practices. Therefore,
focusing implemented (called manager-HPWS from now onwards), instead of intended,
HR practices with performance outcomes would have more meaningful insights about
HPWS-performance relationship. Consequently, a new stream of research has recently
emerged within SHRM literature, focusing on implemented, instead of intended, HPWS
(e.g. Aryee, Walumbwa, Seidu & Otaye, 2012; Chuang, Jackson & Jiang, 2013; Pak &
Kim, 2016; Jiang, & Messersmith, 2018) while examining HPWS-performance
relationship.
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Moreover, a significant limitation of SHRM literature is its major focus on manufacturing
sector while examining HPWS-performance relationship with increasing coverage to
service sector in recent years (Combs, et al., 2006; Liao, et al., 2009), whereas, financial
sector is largely unexplored (Mansour, Ouerdian & Gaha, 2014). Financial sector is
considered knowledge intensive where competencies and knowledge of its employees are
considered the main source of competitive advantage. This is, therefore, quite consistent
with the call for research by Lengnick-Hall, Lengnick-Hall, Andrade & Drake (2009) in
order to develop better understanding of strategic contribution of HRM in sector having
knowledge intensive employees. Furthermore, extant literature also showed that most of
the research on HPWS-performance relationship have been conducted in manufacturing
sector (Combs, et al., 2006), with more than 51 % research studies conducted in Anglo-
American countries (Posthuma, Campion, Masimova & Campion, 2013). These
researchers highlighted the need to conduct future studies relating HPWS-performance
relationship in service sector and in countries other Anglo-American region.
Keeping in view above mentioned gaps in literature, the main aim of this study is to
investigate the effects of implemented HPWS, by bank branch managers, on bank branch
performance and employee outcomes along with the mediating mechanisms explaining
these relationships. This type of investigation will help in answering the ―black box‖
debate in the literature relating to HPWS-performance linkage. Researchers have made
several attempts by using different theoretical perspectives to explore and answer the
―black box‖ debate in SHRM literature (Jiang, et al., 2013). Moreover, researchers also
argued that the use of multiple theoretical perspectives simultaneously and multi level of
analysis would contribute to a better understanding of the complex HPWS-performance
relationship, thereby, directly contributing to the wider ―black box‖ debate (e.g. Paauwe,
2009; Chuang & Liao, 2010; Jiang, et al., 2013; Shen, Messersmith, & Jiang, 2018).
Further, Liao, et al. (2009) have used individual employees‘ human capital as mediating
process to explain HPWS and employee performance relationship. However, it is argued
that the use of collective human capital of an organization or group rather than individual
human capital would be more appropriate for the reason that an employee may have
required knowledge, skills and abilities but is not using it based upon the perceptions and
6
behaviors of other employees in his/ her work unit (employees‘ perceptions influence and
are influenced by others: e.g. Youndt & Snell, 2004; Takeuchi, Lepak, Wang &
Takeuchi, 2007). Human capital refers to the skills, abilities and knowledge of
organizational members that are critical and considered source of competitive advantage
(e.g. Subramaniam & Youndt, 2005). Therefore, this study hypothesized bank branch
level collective human capital as mediating mechanism to connect manager-HPWS with
bank branch performance. According to resource based view of the firm (RBV), HPWS
would influence branch performance through branch collective human capital by
developing valuable, rare, non-substitutable and difficult to inimitable human capital
(Barney, 1991; Barney & Wright, 1998). In other words, properly implemented HPWS
enhances competence (skills, knowledge and abilities) and motivation of the employees
to form high quality pool of human capital (Delery & Shaw, 2001; Huselid, 1995) and,
therefore, organizations will extensively use these HR practices to ensure organizational
success through their employees (MacDuffie, 1995; Guthrie, 2001).
Next, Boxall and Macky (2007) argued that considering employees‘ perspective of and
reactions to organizational HRM is a prerequisite for enhancing understanding about the
contribution of HRM for organizational effectiveness. Moreover, according to Homans
(1961), justice evaluation is important to understand what people feel and how they react.
Organizational justice refers to the perceptions of fairness employees have regarding
workplace related outcomes, process and the interpersonal treatment they received from
their employer (Cropanzano & Greenberg, 1997). Extant researches on the association of
HR practices and organizational justice have demonstrated that employees‘ justice
perceptions are significantly associated with various HR practices like compensation
(McFarlin & Sweeney, 1992), staffing (Gilliland, 1993) and performance appraisal
(Greenberg, 1986). However, there is dearth of literature related to the justice perceptions
of HR system as a whole. Further, organizational justice also explains the effects of
employees‘ judgment regarding fairness and unfairness on their feelings, attitudes and
behaviors such as organizational commitment, turnover intentions, job satisfaction,
employee engagement, performance, OCBs and so on, while working in organizations
(e.g. McFarlin & Sweeney, 1992; Masterson, et al., 2000).
9
approach, this study proposed that the ability of HPWS to influence the performance
through enhanced human capital (knowledge skills and abilities) and employee outcomes
through employees‘ fairness perceptions simultaneously will broaden the understanding
related to HPWS impact on performance and employee outcomes through multiple
processes simultaneously.
In addition to this, previous literature has also been criticized for using intended, instead
of implemented, HPWS (Wright & Nishii, 2013; Pak & Kim, 2016). These researchers
have argued that intended HR policies may not be implemented in the same way across
the organization. This study, therefore, considered implemented, instead of intended,
HPWS to contribute into body of knowledge around HPWS-performance relationship.
Moreover, a significant limitation in strategic HRM literature is that its major focus has
been on manufacturing sector with limited coverage of service sector (Liao et al., 2009, p.
371) and financial sector is largely unexplored (Mansour, et al., 2014) with more than 51
% research studies conducted in Anglo-American countries (Posthuma, et al., 2013).
Thus, scientific investigation related to HPWS-performance relationship in banking
sector of developing countries like Pakistan would add significant insights about
aforesaid relationship.
This study, therefore, proposes branch level collective human capital and organizational
justice dimensions (i.e. distributive justice, procedural justice and interactional justice) as
mediating mechanisms to explain the linkage of manager-rated HPWS with bank branch
performance and employee outcomes (employee engagement, service performance and
service-oriented OCB) respectively in banking sector operating in Punjab, Pakistan.
1.3 Context of the Study
From the last two and a half decades, Pakistan has been transformed into a liberal
economy model from a controlled economy with privatization and deregulation of state
corporations along with an increasing number of foreign companies in almost all
important sectors. Pakistan is ranked as 41st largest economy with a total population of
over 200 million people. It is one of the growing developing economies with the label of
semi-industrial economy (Board of Investment, 2016) where the importance of foreign
10
direct investment cannot be ignored. Foreign companies not only brought much needed
financial capital into the country but also introduced the country with latest management
trends and practices. Khilji (2002) argued that multinational corporations in Pakistan act
as change agents and set benchmarking standards in the area of HRM. Her study on
management practices in local organizations reported bureaucratic management style
used in these organizations. However, current study argued that latest HR practices have
been increasingly used by multinational and also local companies in last one decade or
so. Reasons for such adoption included increased foreign direct investment (FDI) and
more multinational organizations in the sector, involvement of private sector and the
introduction of revised labor policy, Industrial Relations Act 2010 (IRA 2010), by
Government of Pakistan. This revision in labor related policies was aimed to encourage
better management labor relations and to improve the productivity of workforce in the
country. The main features of IRA (2010) includes (i) the acknowledgement of workers‘
right to form union and develop a framework within organization to ensure close
management workers relationship, (ii) measures to ensure job security, (iii) involvement
of workers in matters of interest, (iv) designing and implementation of effective
grievance mechanism in the organizations and (v) an increased emphasis on employees‘
training and other management practices with the focus to enhance labor productivity.
Therefore, the companies operating in Pakistan are required to understand and implement
modern and innovative management practices (also known as high performance work
practices) to not only enhance the productivity of the workers but also to gain financial
advantages through the route of workers‘ wellbeing. This study, therefore, aimed at
studying the relationship of implemented HPWS with organizational performance and
also with employee outcomes to understand and comprehend the uses and benefits drawn
as result of these implemented high performance work practices in the banking sector,
one of the most prominent sectors, of Pakistan.
Banking sector operating in Pakistan is one of the most vibrant and fastest growing
sectors of the economy. Numerous local and multinational establishments are operating
in this sector with huge amount of FDI in last two decades. According to the Board of
Investment, (2016), banking sector of Pakistan has been the recipient of US $ 5.9 billion
11
as FDI during the period from 2001 to 2015. Moreover, this sector holds assets of US $
99 billion with a total equity amounts to US $ 8.4 billion (Board of Investment, 2016).
Banking sector of the country remained strong and resilient during the global financial
crisis around 2008 and faced the challenges because of deteriorating macroeconomic
condition. A number of foreign and private local banks have joined this sector after the
deregulation of banking sector in Pakistan in 1990s. The situation now is that around half
of the assets of the banks operating in Pakistan are owned by the foreign banks. Banking
sector in Pakistan consists of above 50 banking organizations out of which 30 are
commercial banks. In 2010, almost 80 % of the banking assets were owned by private
banks compared to 1990s when around 90% assets were kept with state owned banks.
The huge amount of FDI inflows in the sector, intense global competition, presence of
many foreign and private banks and future growth potential make it worthwhile to study
the management and HRM practices used in this sector. Moreover, banking sector in
Pakistan is one of the major source of employment in the country, therefore, gives good
reasons for the choice of this sector of economy as target population for this study.
1.4 Research Questions
Following the previous discussion, current study focuses on answering the following
research questions:
Does manager-HPWS influence bank branch performance and employee
outcomes (employee engagement, service performance and service oriented-
OCB)?
Does branch level human capital mediate the relationship between manager-
HPWS and bank branch performance?
Do organizational justice dimensions (distributive justice, procedural justice and
interactional justice) mediate the relationship of manager-HPWS and employee
outcomes?
12
1.5 Research Objectives
Stated precisely, following research objectives are set for this research:
To study the effects of manager-HPWS on bank branch performance and
employee outcomes (employee engagement, service performance and service-
oriented-OCB).
To examine the mediating role of branch level collective human capital for the
relationship between manager-HPWS and bank branch performance at branch
level of analysis.
To investigate the mediating role of organizational justice dimensions
(distributive justice, procedural justice and interactional justice) for the
relationship between manager-HPWS and employee outcomes, at cross level of
analysis.
1.6 Significance of the Study
Keeping in view the above discussed limitations in literature, this study contributes in the
literature of SHRM in a number of ways. Firstly, this research takes lead by using
predictions of resource based view of the firm (RBV) and organizational justice theory to
investigate the processes which connect manager-HPWS with bank branch performance
and employee outcomes respectively, thus, address the ―black box‖ debate in the
literature (Wright & Gardner, 2003). Second, this study also adds value in the literature
by studying the effects of same HPWS on organizational performance and employees
outcomes simultaneously. Previous studies, based upon mutual gains perspective,
investigated the effects of HPWS on employee outcomes only. However, hardly any
study considered both organizational performance and employee outcomes
simultaneously while studying the impact of HPWS. Therefore, considering both,
organizational performance and employee outcomes, provides clear picture about how
same organizational HPWS is related and beneficial (mutual gains) for both the
organizations and employees. Thirdly, this research incorporates responses of employees
13
regarding implemented HR practices, in terms of their fairness perceptions regarding
implemented HPWS, to have a clearer understanding about the process through which
these implemented organizational practices influence employee outcomes (Boxall &
Macky, 2007). Lastly, the inclusion of line managers‘ implemented HPWS provides more
accurate picture of the relationship of HPWS and performance instead of the relationship
of presence of HR practices (intended HR practices reported by top management/ HR
manager) and performance outcomes in previous research because intended HPWS may
not be implemented in same way throughout the organization (Khilji & Wang, 2006;
Nishii & Wright, 2007).
Along with its contribution for theory, this study also provides meaningful insights for
the organizations and practitioners in banking industry. For instance, findings of the study
highlight the role properly implemented HPWS play for generating favorable market
performance and employee outcomes. In other words, effectively implemented HR
practices by branch managers bring more profitability, sale and improved market
performance of the bank branch along with favorable employee outcomes. Second, this
research highlights the critical role of line managers (branch managers in case of this
study) in effectively implementation of organizational intended HPWS. Acknowledging
line managers as front line agents of HR function, HR department would better
coordinate with them to obtain maximum benefit from organizational intended HPWS
(Purcell & Hutchinson, 2007). Along with highlighting the importance of properly
implemented HPWS for bank branch performance, this research also provides insights
about the intermediary mechanisms through which implemented HPWS influence bank
branch performance and employee outcomes. In the last, proposed mediating mechanisms
provide organization with the information of focal areas with respect to implemented
HPWS to impact bank branch performance and employee outcomes in a favorable way.
14
1.7 Thesis Progression
This thesis is comprised of five chapters. First chapter presents introduction and
background of this study, highlighting research gaps and discusses the context of the
study. The chapter further presents research questions and research objectives followed
by an overview of the significance of the study for literature and practitioners in the end.
Chapter 02 presents a review of literature related to the topic of research. This chapter
provides detail regarding the emergence of human resource management in organizations
(brief history) and prevailing debates in HPWS-performance literature. Next, this chapter
also presents the current status of SHRM research in Pakistan followed by the discussion
of previous research studies for the development of hypotheses for this study.
Chapter 03 describes employed research methodology in order to achieve objectives of
this study. The chapter starts with a discussion on research philosophy adopted by this
study followed by details of the research design used for the research study. Next, the
chapter discusses about the population and sample along with data collection techniques
and procedures to achieve the objectives of the study. However, chapter ends with a
discussion of measurement instruments and techniques used for data analysis in the
study.
Chapter 04 exhibits empirical findings of the study. The chapter starts with a description
of the characteristics of bank branches and employees participated in this study. Next,
descriptive analysis of key constructs of the study is presented followed by confirmatory
factor analysis and reliability analysis. After this, correlation analysis is presented and
chapter ends up with testing of hypotheses.
Chapter 05 presents the discussion of results in the light of extant literature. Next,
theoretical and practical implications of the study are delineated followed by an overview
of the limitations and future research directions. This chapter is ended with the
conclusion of the whole study.
15
1.8 Conclusion
This chapter illustrated introduction of research topic and background to the problem in
order to highlight the rationale and motivation for current study. Based upon the
problems identified in literature, research objectives for this study were articulated
followed by an overview of the significance of this study. Structure and progression of
this thesis document is also presented in the end. Next chapter will provide a review of
literature including brief overview of the emergence of management of human resource
in organizations along with development of hypotheses of this study.
16
Chapter 02:
Literature Review
17
2. Literature Review
2.1 Introduction
Previous chapter presented introduction and background of the topic, articulation of
research problem, objectives set for research study and contribution of the study. Now,
the focus of this chapter is to present a review of literature in order to discuss what has
been done so far with respect to people management and performance linkage, the
debates and issues of the research area and what needs to be done to carry forward this
research area. More specifically, this chapter provides a brief history of the management
of human resources for organizational performance, review of the HPWS construct and
developments in research area of strategic HRM along with emerging issues/ debates of
this area of research. Research efforts regarding HPWS-performance relationship in
Pakistani context are also discussed followed by conceptual framework and development
of the hypotheses for current study in the end.
2.2 Emergence of Human Resource Management and Performance
Research on ―management of human resources and performance‖ relationship under the
umbrella of SHRM gives an impression that this relationship has been established
recently. However, in actual, interest for management of human resources to improve
organizational performance has a long history (Barley & Kunda, 1992; Cappelli &
Neumark, 2001). For the purpose of understanding some of the historical background and
current debates within the area of HRM and performance, it is necessary to have a look
on the ways organizations have adopted to devise organizational structure and work
design for effectiveness, efficiency and performance. Therefore, some of the main
contributors towards human resources management for organizational performance
including Scientific Management, Human Relations Movement, Quality of Working Life
(QWL) and Human Resource Management (HRM) will be discussed in this section.
18
2.2.1 Scientific Management
Efficiency and performance were one of the main focuses of the industrial and social
scientists in early twentieth century. The central feature of management at that time was
greater use of the methods to exercise direct control over labor in response to decline in
workers efforts after increased awareness regarding workers efforts as negotiable feature
of labor force and as skilled labor started organizing (Friedman, 1977). Consequently,
organizations started exploring new incentive programs and ways of organizing work
processes to enhance organizational productivity. The concepts of mass production and
work organization were the fundamental components in the principles of scientific
management presented by F.W. Taylor. In this era of mass production, scientific
management was considered as handmaid of employers (Frenkel, 1999) and work
activities were organized by large bureaucracies featured with clear differentiation
between management and labor on planning and execution of organizational operations.
In this era of scientific management, unskilled or semi-skilled workers got very little
attention in terms of trainings and involvement, and they were seen as just cogs in
production process (Belanger, Giles, & Murray, 2002). Scientific management entirely
neglected the psychological aspects of workers with almost all the emphasis on the
organizational processes and systems. Hence, ―it was to be expected that employers, with
their chief attention absorbed by questions relating to machines and methods, should
neglect the greatest of all their assets …... their employees‖ (Delbridge & Lowe, 1997:
869). Other authors criticized this work organization by stating that it is impossible to
build ―high-trust relationship‖ that is based upon ―low-trust‖ system (Fox, 1974, 1985).
In summary, they view scientific management not as an approach of job design, but as a
tool for controlling alienated labor (Braverman, 1974). Friedman (1977) criticized this
approach by declared Taylorism as a modern approach of directing labor through division
of labor where employee‘s body movements were subdivided and reassigned to many
employees. These employees were seen as machines consisted of numerous motions per
unit of time. With the passage of time, interest in scientific management decreased for the
reasons such as unable to reduce cost, wastage and ―bring about an industrial utopia‖
(Barley & Kunda, 1992) which caused the proponents to re-examine their standpoint.
19
Subsequently, a transformed perspective, known as human relations school, for
―industrial betterment‖ evolved where psychological aspects of workforce, especially
motivation and satisfaction turned out to be the important factors in management theory.
2.2.2 Human Relations Movement
Advocates of ―Human Relations Movement‖ argued that workers' productivity could be
enhanced by concentrating on their needs, especially through meaningful and challenging
work and better working environment. Authors paid attention to macro processes like
technology (e.g. Elton Mayo‘s work in 1930s), bureaucratization in organizations
(Gouldner, 1954) and segmentation of organizational social system (Cass, Warner &
Low, 1947). In other words, central idea of human relation perspective was to treat the
workers well and make efforts for building ―a non-authoritarian environment in an
authoritarian setting‖ (Perrow, 1984: 59). Contrary to rationalism and individualism
principles of scientific management, these micro-level studies emphasized on the effects
of group norms and interpersonal relationship on productivity and the workplace informal
social systems and its association with society (Simpson, 1989). This perspective
transformed the organization and the management into an adhesive unit by utilizing the
efficacy of groups for the interest of management. This group perspective surpassed the
early employee relation work through stressing upon redesigning of the jobs and the
effectiveness of small groups as potential sources of employees' motivation (Appelbaum,
et al., 2000). Collectively, they contributed significantly to the idea of organizational
structures assisted in channelizing the discretionary efforts of workers by providing them
opportunities for self-actualization (Bailey, 1993). This approach, thus, focused upon the
satisfaction and job design (to form more challenging and interesting work) as rewards
that would contribute towards improved efficiency and performance.
However, critiques viewed human relation thought as ―benevolent paternalism‖ that has
much emphasis on workers wellbeing but said very little about power sharing. In a
renowned review of these criticisms, Braverman (1974) declared employee relations
approach as a rhetoric for ―the maintenance crew for the human machinery‖ (p. 87).
Despite the criticism, human relation movement contributed significantly by initiating the
20
application of behavioral sciences to organizations and examining the ways in which
workers behaviors could be adjusted and modified for organizational effectiveness
(Gunnigle, Heraty & Morley, 2002).
2.2.3 Quality of Working Life
Along with human relation movement, this era also witnessed the evaluation of ―Quality
of Working Life‖ perspective to change work organization and relationships at work.
Writers such as Blauner (1964) and Beynon (1984) were the pioneers who argued that
organizational structures as suggested by scientific management were not viewed as
appropriate place of work by employees. The overarching argument of this approach was
intrinsic motivation which was viewed as an important factor for employees‘ satisfaction
and jobs were characterized by more responsibilities along with opportunities for
decision making (Herzberg, 1966). In this regard, the concept of job enrichment emerged
as an alternative work arrangement with the objective of providing employees
challenging and meaningful work along with some autonomy and feedback over
performance (Buchanan, 1979). So, the ―people management - performance‖ relationship
holds a prominent position within Quality of Working Life (QWL) paradigm with the
focus of enriching the jobs and provides workers autonomy as basis for organizational
effectiveness. However, some critiques have highlighted the point that the principles of
Quality of Working Life (QWL) paradigm such as job enrichment, and modification in
work practices ―are clearly Taylorist in their effect, if not their purpose‖ (Braverman,
1974). Other commentators had pointed out possibilities for more managerial control
inbuilt in numerous employee involvement programs (Braverman, 1974; Ramsay, 1980)
in which ―humanization of work‖ intentions masks the actual objectives of
―rationalization of work‖ and ―managerial control‖. According to them, rather than
offering a human alternative to conventional mass production, employees in teams
―participate mainly in the intensification of their own exploitation, mobilizing their
detailed firsthand knowledge of the labor process to help management speed up
production and eliminate wasteful work practices‖ (Milkman, 1997: 16).
21
Numerous Quality of Working Life (QWL) advocates have drawn greatly on the theories
of employee relations discussed already. For instance, socio-technical approach (Trist,
Higgin & Murray, 1963) emphasized on incorporating both social and technical aspects
side by side to optimize the two. Further, arguments by advocates of employee relations
(e.g. Maslow and Herzberg) also highlighted the significance of participation at
workplace and capability of self control would assist in satisfying needs like self-
actualization (Watson, 1995). These scientists argued that, basically, these are the
underlying principles through which managers can improve the performance of
employees at workplace.
2.2.4 Human Resource Management
In general, this term ―human resource management‖ refers to all activities which
organizations use for employment relationship management (Grant & Shields, 2002).
Although, there is no agreed upon definition of human resource management (Boxall &
Purcell, 2003), however, for this research purpose, it is defined as a way of managing
employees at work ―which seeks to achieve competitive advantage through the strategic
deployment of a highly committed and capable workforce, using an integrated array of
cultural, structural and personnel techniques‖ (Storey, 1995: 5). For the purpose of this
research study, it is required to define HRM for the contextual comprehension of the
main variable being studied in current research i.e. high performance work system
(HPWS).
HRM is often described and explained as either Soft HRM or Hard HRM, one of the two
alternative perspectives, emerged as result of studies of US researchers in 1980s (e.g.
Beer, et al., 1984; Walton & Lawrence, 1985). The soft HRM perspective emphasizes on
the ―human resource‖ feature of HRM term (Storey, 1992). This perspective argued and
suggested that strategic orientation of HRM can be understood as some sort of
―developmental humanist‖ program (Grant & Shields, 2002; Legge, 2005). Soft HRM
perspective acknowledges the importance of linking HR function with business
objectives, however, based upon their adaptability, commitment, high quality
competencies and productivity (Guest, 1987), human resource is considered as valuable
22
resource rather that treating them like other resources of the organization (Beer, et al.,
1984; Guest, 1999). This approach reflects human relations movement of employees'
management and is (has) been represented frequently by using tag i.e. ―high commitment
work systems‖ (Walton, 1985).
Contrary to soft HRM, the basic argument of hard HRM perspective is to integrate
human resources into strategic decision making in order to serve organization through its
maximum contribution. This perspective emphasizes on ―management‖ aspect of HRM
concept which represents ―a utilitarian instrumentalism model‖ (Legge, 2005). In case of
hard HRM perspective, the focal point is a tight integration of HRM function with
business strategy to ensure that HRM function of the organizations is being utilized to
―drive the strategic objectives of the organization‖ (Fombrun, et al., 1984: 37). According
to this perspective, organizations treat human resources in the same way as other
resources are being treated and therefore, human resource should be acquired and utilized
in a cost effective way to ensure that the core objectives of organizations are achieved.
This hard HRM model focuses on the ―quantitative, calculative and business strategic
aspects of managing the headcount resource in as rational a way as for any other
economic factor‖ (Storey, 1987: 6). Thus, human resource is considered as an ordinary
resource (Legge, 2005) instead of considering it a ―sources of creative energy in any
direction the organization dictates and fosters as emphasized in the soft model‖ (Tyson &
Fell, 1986: 135). This model of HRM, therefore, reflects ―scientific management‖
approach of managing employees.
Similar to these soft / hard approaches of HRM, Peccei (2004) presented two alternative
perspectives of human resource management named as ―optimistic‖ and ―pessimistic‖
perspectives of HRM. Optimistic perspective argues that HRM is beneficial for
employees and it has positive influence on employees' well-being. In other words,
organization's adoption of more HR practices leads towards higher levels of employees'
empowerment, greater job discretion, satisfaction and development of supportive, more
rewarding and interesting work environment. In turn, this results into better quality of
work life and transformed into favorable employees' reactions at workplace.
Consequently, in line with the norm of reciprocity (Gouldner, 1960), social exchange
23
theory (Blau, 1964), and behavioral theories of HRM (Wright & MacMahan, 1992;
Guest, 1997; Appelbaum, et al., 2000), employees are expected to reciprocate to their
employer by putting extraordinary efforts and by involving in citizenship behaviors. In
short, optimistic view not only declares HRM function beneficial for both employer and
employees but it indicates employees' wellbeing a key for organizational performance.
Contrary to optimistic perspective of HRM, ―pessimistic view of HRM‖ describes HRM
as harmful for employees having negative effect on their well-being (Peccei, 2004).
Basing upon labor process theory (Godard, 2001; Appelbaum, 2002), this approach
argues that organizational adoption of more HR practices leads towards systematic
exploitation of workforce at workplace (Delbridge & Turnbull, 1992; Ramsay, et al.,
2000; Appelbaum, 2002) through work intensification and increased control and
monitoring of employees' working efforts (Sewell & Wilkinson, 1992; Barker, 1993).
Consequently, employees have greater work pressure, less discretion and reduced well-
being at work. This may benefit organization in form of enhanced productivity but at the
cost of sacrificing employees' well-being. In brief, according to pessimistic view, it is
employers only not employees who are likely to benefit from HRM function. Although,
according to some critiques (e.g. Willmott, 1993; Legge, 1995; Keenoy, 1997), at many
circumstances, employees may be fooled by making them think that they too are better
off through the rhetoric of HRM.
More recently, Van de Voorde (2010) extended the work of Peccei‘s (2004) and
presented two approaches of HRM namely ―mutual gains‖ and the ―conflicting
outcomes‖ perspectives of HRM. Similar to Peccei's (2004) optimistic approach, drawing
upon behavioral perspectives of HRM (Wright & MacMahan, 1992; Guest, 1997; Becker
& Huselid, 1998; Appelbaum, et al., 2000) and social exchange theories (Gouldner, 1960;
Blau, 1964), the mutual gains perspective assumes that HRM has favorable impact on
both employees and organizational performance. She emphasized on employees' well-
being as a means through which HRM could generate productivity and performance.
According to mutual gains perspective, HRM is perceived by employees as source of
organizational care and support for them that then reciprocates in terms of satisfaction,
24
commitment and trust (Whitener, 2001) which in turn, contributes towards organizational
performance.
Whereas, drawing upon Paauwe (2009), Peccei (2004) and Boxall and Purcell (2008), as
well as on Quinn and Rohrbaugh‘s (1983) competing values framework, conflicting
returns perspective presented by Van de Voorde (2010) argues that HRM has favorable
impact on organizational performance but at the cost of employees' well-being i.e. HRM
has no or even negative impact on employees‘ well-being. Based upon the arguments of
labor process theory (Ramsay, et al., 2000; Godard, 2001), she argued that HR practices
that enhance employees' well-being may not contribute towards organizational
performance and vice versa. In other words, HRM is transformed into organizational
performance through job intensification, job strain (Ramsay, et al., 2000) and that human
resource management is exploitative in nature (Legge, 1995).
In conclusion, whether, soft HRM, optimistic view of HRM or mutual gains perspective,
the focal point of these perspectives is employees. These approaches point employees'
well-being a way that leads towards organizational performance. In contrast to this, hard
HRM, pessimistic view or conflicting outcomes perspective declares HRM a tool that
employers use to exploit employees to achieve their business objectives.
However, this ―hard/soft‖, ―optimistic/ pessimistic‖ or ―mutual gains/ conflicting returns‖
dichotomy of human resource management is criticized on various levels (Keenoy, 1999;
Legge, 2005). In general, human relations and quality of work life (QWL) approaches of
management of human resources are reflected in soft HRM perspective and hard HRM
echoes scientific management approach of managing employees. Keenoy (1990)
criticized soft HRM variant and argued that even soft HRM can have hard outcomes like
work intensification, strict control and job insecurity. Further, Keenoy and Anthony
(1992) criticized human resource management for being as a ―rhetoric aimed at achieving
employees‘ normative commitment to a politico-economic order, in which the values of
25
variety of management styles that exists in contemporary workplaces‖ (p. 184). However,
a main controversy in modern human resource management literature is that whether the
scenario of labor-management relationship has been transformed due to the adoption of
new management techniques in 1980s (e.g. Millward & Stevens, 1986; Edwards &
Heery, 1989; Richardson & Wood, 1989). Based upon surveys data of UK workforce,
Guest (1999) responded to some of the criticism by presenting whether or not HRM
might be considered as manipulative. His research results showed that employees
consistently preferred organizational environment where few HR practices were present.
These debates and ambiguities regarding HRM and its recognition as a source of
competitive advantage are perhaps the reason for emergence of a variety of labels
including high commitment management; high involvement management; best fit, best
practices and so on. For simplicity, these terms and labels are categorized under the
rubric of high performance work system (HPWS) that need more elaboration and critical
investigation to broaden the understanding of HRM-performance relationship debate.
It was in the 1980s, when human resource management was seen and discussed from
strategic perspective by the theorists and the researchers who used the term ―strategic
human resource management‖ for the first time. Strategic human resource management
(SHRM) refers to ―the pattern of planned human resource deployments and activities
intended to enable an organization to achieve its goals‖ (Wright & McMahan, 1992:
298). Fombrun, et al. (1984) and Miles and Snow (1984) started linking organizational
strategy with HRM function of the business. Further, in 1985, Walton highlighted the
importance and need of shifting to commitment based models of managing human
resources from control based approaches. In addition to this, researchers at Harvard
(Beer, et al., 1984) along with Schuler and Jackson (1987) started studying the concepts
of ―external fit‖ and ―internal fit‖ to develop a conceptual framework (Noon, 1992) that
provides the foundations of current HRM. On the other hand, in UK, researchers and
theorists in SHRM started producing research on lines of normative perspective of HRM
(e.g. Guest, 1987; Storey, 1992). On other side, Foulkes (1980) and Peters and Waterman
(1982) had presented some support for the contribution of ―high commitment‖ HRM
26
model in organizational success. These early research efforts provided a foundation to the
extensive body of research knowledge that linked HRM with performance.
2.3 High Performance Work Systems (HPWS)
Whether labeled as high commitment management, high involvement management or
soft HRM, the discussion of people management approaches revolve around the
argument that some kind of competitive advantage could be achieved by managing the
ways of doing work, employees and the labor processes. This is the premise that lies at
the center of high performance work system (HPWS) construct.
Strategic HRM is area of study that is devoted to investigate and understand the influence
of bundle of HRM practices on organization-wide performance outcomes (Combs, et al.,
2006; Guest, 2011). It focused on a set of HR activities which are mutually reinforcing
and generate synergistic impact (Huselid, 1995). He further elaborated that such bundles
of HR practices that researchers and theorists in the area consider as performance
enhancing are called high performance work systems (HPWS).
However, even after more than two decades of extensive investigation in SHRM, still no
consensus on ―which‖ practices constitute high performance work system and thus, no
one definition of high performance work system exists (e.g. Wall & Wood, 2005). A
systematic review exploring the components of HPWS by Posthuma, et al. (2013)
reported that researchers have developed different combinations of HR practices ranging
from three to thirteen practices to study the bundle effect on various organization wide
performance outcomes. Although, no agreement established on the components and
number of practices, the existing literature do share some commonalities with respect to
the components of HPWS. For instance, sophisticated selection, performance based pay,
extensive trainings, team working, appraisals, communication/ information sharing,
employee empowerment and employment security are the most common and frequently
used components of high performance work system (Wall & Wood, 2005).
Appelbaum and Batt (1994) categorized HPWS into (i) management methods, (ii) HRM
practices, (iii) work organization, and (iv) industrial relations. Where ―management
methods‖ refers to employees' participation in quality enhancement; ―work organization‖
27
refers to organizational structure and autonomy of teams; ―human resource management‖
includes contingent pay, trainings, employment security; and ―industrial relations‖ targets
no conflict of interest between workforce and management i.e. unitary perspective.
Collectively, these work practices mutually reinforce each other and develop synergistic
impact in order to enhance business performance through workers‘ skills, knowledge and
abilities, increasing their motivation level and empowering them (Appelbaum, et al.,
2000).
Other authors have used different terms for these bundles of practices but investigating
the impact of HR practices in the form of bundle have been the focal point of SHRM with
different synonyms like high commitment work systems (Arthur, 1994; Pfeffer, 1998),
high involvement work systems (Batt, 2000; Guthrie, et al., 2002), innovative work
practices (Mkamwa, 2010), high investment HR systems (Lepak, et al., 2007) and people
management (Purcell, 2003). Other researchers conducted studies to investigate the
association of bundles of HR practices with performance without using any specific term
mentioned above (Guest, 1997; Bowen & Ostroff, 2004).
Most recently, ―high commitment management‖ and ―high performance work systems‖
are used as synonyms (Legge, 2005) representing bundle of HR practices having positive
impact on organizational performance. However, some researchers differentiate the
concepts of high commitment management (HCM) and HPWS by using ―soft‖ and
―hard‖ HRM debates discussed earlier. High commitment management (HCM) focuses
on job design, job security, employee development and so on as ways to superior
performance and increased employees' commitment and satisfaction (Legge, 2005).
Sparham and Sung (2006) elaborated HCM as a concept intended to build employee as
resourceful and valued humans to gain superior performance by using ―cultural/
motivational‖ approach. Therefore, employer would be expected to use practices ensuring
high involvement, rewards and staff development (Grant & Shields, 2002). Contrary to
this, they argued that HPWS focuses on superior performance where the workforce is
considered as a costly resource. The practices in this case include result based approaches
for rewards management and performance, instead of autonomy, use of internal labor
markets and job security (Harley, 1999). Moreover, Pil & MacDuffie (1996) also
28
suggested to use ―high involvement‖ or ―high commitment‖ instead of ―high performance
work systems‖ and caution that the use of last-mentioned concept ―can be misleading in
the absence of clear empirical tests of their actual link to economic performance in a
given situation‖ (p. 423). Above mentioned debates could be categorized as ―high road‖
and ―low road‖ organizational work systems where low road systems includes activities
such as lack of job security, short-term employment contracts and less employees'
trainings whereas high road practices focus on getting high level of employees'
commitment (Guest, 1997).
However, recent scholars have started using the term ―high performance work systems‖
for the purpose of broadening the emphasis from just commitment or just involvement to
include aspects like skills development, performance management, work structuring and
pay satisfaction. These researchers argued that employment models and work systems are
viewed as supportive for superior performance considering a combination of key
practices like rigorous selection, better and extensive trainings to enhance competency
levels, more use of comprehensive incentives (like commissions, bonuses and career
development) to amplify motivation level and use of participative work structures that
provide employees more opportunities to participate (Appelbaum, et al., 2000). Pfeffer
(1998) included sophisticated hiring, employment security, extensive training, internal
labor markets, learning and development, high and contingent compensation, team
working and reduced status distinctions to form best practices HRM. HPWS refers to the
―system of HR practices designed to enhance employees‘ skills, commitment, and
productivity in such a way that employees become a source of sustainable competitive
advantage‖ (Datta, Guthrie, & Wright, 2005, p. 136).
29
The bottom line of HPWS is an organization that enhances employees' discretion (Giles
Murray & Belanger, 2002) that is translated into superior organizational performance. As
Appelbaum, et al. (2000) asserted:
―The core of a HPWS…is that work is organized to permit
front-line workers to participate in decisions that alter
organizational routines…..Workers in an HPWS experience
greater autonomy over their tasks and methods of work and
have higher levels of communication about work matters
with other workers, managers, experts…..Work organization
practices in an HPWS require front-line workers to gather
information, process it and act on it‖ (p. 7-8).
Therefore, researchers have argued that it is basically autonomy/ discretion given to the
employee that results into organizational performance (e.g. Bailey, Berg & Sandy, 2001)
in the form of giving employees opportunity to utilize ―their initiative, creativity, and
knowledge in the interests of the organization‖ (Appelbaum, 2002: 123). According to
these scholars, performance is a product of employees' skills, motivation and opportunity
to perform, a well known ―AMO theory‖ of performance in literature of strategic HRM
(Appelbaum, et al., 2000). In Mathematical expression:
Performance = ƒ (A, M, O)
Means, superior employees‘ performance when:
A: they have the abilities to do their jobs (they possess required skills
knowledge and abilities to perform);
M: they have motivation to do their jobs (they get adequate incentives to
remain motivated);
O: they have enough opportunity to perform from their working environment
(e.g. opportunity to participate or express when face problems).
(Boxall & Purcell, 2003: 20)
While, debates exist regarding the particular combination of HRM practices, one of the
basic arguments throughout the literature is that HR practices operate better in the form
of ―bundle‖ or ―system‖ (MacDuffie, 1995; Ichniowski, et al., 1996). The advocates of
HR bundle argue that although a single HR practice might be useful in itself, bundles of
30
work practices, mutually reinforcing each other, will generate greater performance
compared to the summation of the results produced by the HR practices in isolation
(Purcell, 1999). In addition to this, according to Ichniowski, et al. (1997), adding only
one practice may ―have little or no effect on performance‖ (p. 311). In conclusion,
individual HR practices will not help organizations to gain competitive advantage rather
HR practices as component of broader high performance work system (HPWS) to form
system that has positive, synergistic impact on organizational performance.
To date, literature provides substantial evidence for strong relationship between HPWS
and organization wide performance outcomes (e.g. Huselid, 1995; MacDuffie, 1995;
Delery & Doty, 1996; Youndt, et al., 1996; Datta, et al., 2005; Shin & Konrad, 2014;
Katou & Budhwar, 2015). Most of such research studies have conducted in US but
similar results have been found in other parts of the world. For instance, Guest, et al.
(2003) in UK; Guerrero and Baraud-Didier (2004) in France; Den Hartog and Verburg
(2004) in the Netherlands; Boxall, Ang and Bertram (2011) in Australia; Guthrie (2001)
in New Zealand; Bello-Pintado (2015) in Uruguay and Heffernan, et al. (2009) in Ireland.
Recently, a meta-analysis conducted by Subramony (2009) confirmed empirically that
organizational work practices in form of systems are strongly related with organizational
performance compared to individual HR practices. Likewise, another meta-analysis of 92
quantitative studies, investigating HPWS-performance relationship, by Combs, et al.
(2006) established that one standard deviation raise in HPWS caused 4.6 percent
improvement in return on assets (ROA) along with 4.4 percent reduction in employees'
turnover. Therefore, the study concluded that the influence of HPWS ―on organizational
performance is not only statistically significant but managerially relevant‖ (p. 518). On
the other hand, some authors warn that although empirical findings support the
relationship of HPWS and performance, numerous theoretical and methodological issues
still exist while studying this relationship (Wall & Wood, 2005; Paauwe, 2009). A
number of such debates in literature and challenges will be discussed here.
31
2.3.1 Debates in HPWS-Performance Research
Much of the research efforts in SHRM have focused on HPWS and organizational
performance relationship and confirmed positive association between these two
constructs. However, authors have highlighted a number of problems or issues around
the relationship of HPWS and performance which require further research efforts to
broaden the understanding about HPWS-performance relationship. For instance, Delery
(1998) suggested that establishment of HPWS and performance relationship was just first
step, now the further focus should be on understanding the processes and mechanisms
that link HPWS with organizational performance outcomes. Previous section has already
highlighted the arguments and debates regarding the components and subject matter of
HPWS. This section will discuss few of the debates currently prevailing in the research
area of HPWS and performance relationship.
2.3.1.1 Debate 01: “Black Box” Issue of SHRM
Majority of the research studies in SHRM have investigated the linkage of HPWS with
some form of organizational performance (e.g. Arthur, 1994; Huselid, 1995; MacDuffie,
1995; Delery & Doty, 1996; Youndt, et al., 1996; Ichniowski, et al., 1997), or on the
context that enhances their impact (e.g. Osterman, 1994; Pil & MacDuffie, 1996).
However, these studies investigated very little about the mechanisms through which
HPWS creates value for the organization (Wright & Gardner, 2003). This issue is well
known as ―black box‖ issue of strategic HRM, highlighting the fact that mediation
mechanisms through which HPWS is related with various performance dimensions has
not established firmly (e.g. Mueller, 1996; Purcell, 2003; Evan & Davis, 2005; Danford,
et al., 2008;). For instance, based upon a review of 104 studies relating to HPWS-
performance relationship, Boselie, et al. (2005: 77) concluded that ―plenty of
acknowledgements of the existence of the ‗black box‘ and some speculation on its
possible contents, few studies tried to look inside‖. Further, Hesketh and Fleetwood
(2006) highlighted that ―empirical evidence for the existence of an HRM-Performance
link is inconclusive…a statistical association in, and of itself, constitutes neither a theory
nor an explanation‖ (p. 678). In the same way, Wright and Gardner (2003) also
32
highlighted this issue in these words: ―little is known about what happens in between HR
practices and performance, and hence the contents of the ‗black box‘ remain a mystery‖.
In particular, Guest (2011, p. 3) recently concluded that ―even after two decades of
extensive research, it is not yet possible to fully understand this linkage‖.
The critiques argued that the theory is confused in this regard and researchers (especially
involved in quantitative research) are not consistent at level of theorizing while treating
HRM as a variable (Legge, 2005; Hesketh & Fleetwood, 2006). In their review of studies
related to HPWS-performance relationship, Boselie, et al. (2005) pointed out three
theoretical frameworks used most frequently by researchers. These theories included
resource based view of the firm (RBV), contingency framework, and AMO (ability,
motivation and opportunity to perform) model. Where, RBV and contingency theory are
situated at organizational level of analysis with main focus on their performance boosting
effect from business perspective while, AMO model investigated HPWS at individual
employee's level of analysis and rooted in organizational/ industrial psychology (Paauwe,
2009). More recently, based upon a systematic review of research studies in SHRM,
Jiang, et al. (2013) reported that along with these three theoretical perspectives,
researchers have also used some other theoretical approaches to address ―black box‖
debate in SHRM literature. For instance, researchers have used behavioral perspective of
HRM (Jackson, et al., 1989; Schuler & Jackson, 1987) to link HPWS with organizational
performance through employees' outcomes (attitudes and behaviors). Some other
researchers benefited from organizational climate literature to link HR systems with
organizational performance (e.g. Ostroff & Bowen, 2000; Collins & Smith, 2006; Lepak,
et al., 2006; Chuang & Liao, 2010; Cafferkey & Dundon, 2015). Similarly, researcher
also used social exchange perspective and human capital theory to propose and
empirically tested the HPWS and performance linkage (e.g. Takeuchi, et al., 2007).
One the other hand, some scholars have attempted to explain mediating mechanisms by
using some complex theoretical perspectives. For example, Bowen and Ostroff (2004)
emphasized on the role of climate as well as the ―strength of the HR system‖ for
understanding HPWS and performance outcomes relationship. Similarly, Guthrie, Flood,
Liu, MacCurtain and Armstrong (2011) have proposed social capital as intermediary
33
mechanism for HPWS and performance relationship. Furthermore, Gittell, et al. (2009)
proposed relational theory to argue that HPWS foster the relationship of employees
performing different functions and concluded that relationship coordination mediated this
HPWS-performance relationship. Moreover, Nishii, Lepak and Schneider (2008) used
attribution theory to propose ―employees' attributions regarding HR function‖ as
mediator to link HPWS with performance outcomes. In addition to this, using HR causal
chain framework, Liao, et al. (2009) examined perceived HPWS as mediating mechanism
in between organizational intended HPWS and employee outcomes relationship. Boxall,
Hutchison and Wassenaar (2015) concluded that the HPWS and important employee
outcomes relationship is mediated by employees‘ skill utilization and intrinsic
motivation. Further, Fu, et al. (2015) used resource-based and dynamic capability
theories to explain the linkage between HPWS and performance in order to address
―black box‖ debate. Furthermore, Mostafa, et al. 2015 proposed and empirically tested
public service motivation as intermediary mechanism to connect HPWS with employee
outcomes in public sector organizations. Voorde, et al. (2016) proposed and tested job
demands and resources as mediating mechanism to link empowerment-focused HR
practices and productivity and the ―black box‖ debate still continues.
Along with mapping the progress with respect to ―black box‖ debate, researchers have
also recommended ways to further carry forward this research area in this regard. For
instance, researchers suggested that it is required that various theoretical perspectives
simultaneously across multiple levels of analysis should be considered in addition to
organizational level HPWS and top management perspectives significant value addition
to the body of knowledge related to HPWS and performance relationship. (e.g. Paauwe,
2009; Jiang, et al., 2013). Researchers also suggested using multiple pathways to
contribute into the ―black box‖ debate of SHRM literature (Chuang & Liao, 2010).
2.3.1.2 Debate 02: Inclusion of Employees' perspective in HPWS-
Performance
Review of previous research work related to HPWS-performance relationship highlighted
the fact that a major portion of research has been done at organizational level of analysis
34
by considering organizational outcomes while neglected the role of employees in this
relationship. Consequently, previous research regarding HPWS-performance relationship
is flawed because it does not consider the role of employees who actually experience
organizational HR practices (Lepak, et al., 2006). Saying it differently, HPWS-
performance linkage research has been criticized for its ―highly management-centric
standpoint‖ and ignoring both employees‘ perceptions and experiences of HPWS (e.g.
Boselie, et al., 2005, p.73; Paauwe, 2009; Delbridge & Keenoy, 2010; Kaufman, 2010;
Farndale, et al., 2011). This viewpoint is evident of the just economic perspective of
HPWS-performance research, considering just improvement in organizational
performance because of HRM (Godard, 2004; Boxall & Macky, 2009), whereas the
impact of organizational work practices in the form of HPWS on employees is less
explored (Sparham & Sung, 2006; Kalmi & Kauhanen, 2008; Kroon, van de Voorde &
van Veldhoven, 2009; Meijerink, Bondarouk & Lepak, 2016). SHRM research either
ignores employee outcomes (Boselie, et al., 2005; Paauwe, 2009; Farndale, et al., 2011),
or consider employee outcomes as intermediary mechanisms only for the relationship of
HPWS with organizational performance (Boselie, et al., 2005; Sparham & Sung, 2006).
Therefore, it can be asserted that even the researchers that consider workers as important
actors in HPWS-performance causal chain, do so for a particular standpoint (called ―win-
win‖ or ―mutual gains‖), not much different from the unitarist approach i.e. with the
assumption that something good for organization must also be beneficial for workers.
This argument is reflected in HPWS-performance research studies conducted in different
industries (e.g. Arthur, 1994; Kochan & Osterman, 1994; Huselid, 1995; Delaney &
Huselid, 1996; Youndt, et al., 1996). For instance, Appelbaum, et al. (2000) identified
that HPWS influence various employee and organizational outcomes including job
satisfaction, trust, intrinsic motivation, commitment and stress.
Keegan and Boselie (2006), perhaps, cynically suggested that majority of academic
journals encourage research findings that support dominant discourse in HRM
(managerialistic, win-win). Previous research work is evident that this type of research is
largely US-based. For instance, Wright and Boswell (2002) emphasized on the
significance of incorporating employees' perspective on HRM within the organization
35
and do this by asking the managers about ―how strategic employee alignment is
supported‖. In addition to this, they unconvincingly claimed that this assisted in
―considering the degree to which the actual human resources (i.e. employees) are aligned
with and contributing to the organization‘s strategic goals‖ (p. 265). Along with this,
empirical validation of their argument, epistemological and ontological issues are also
there because this approach is based upon the premise that workers are ―objects‖ which
can be transformed to facilitate organizational strategy to be converted into some stated
organizational objectives without knowing what employees really think or recognizing
them as active agents rather than passive objects of organizational HRM function.
Researchers, however, highlighted the importance of employees‘ responses in HPWS-
performance relationship by arguing that these are not the actual practices but the
perceptions employees made about these practices that determine their attitudes and
behaviors at work. Saying it differently, employee may perceive organizational practices
differently from what top management has intended or reported that may not result into
the same relationship of management reported HPWS and employee's response regarding
HPWS with performance outcomes (Liao, 2009). Recently, based upon an empirical
investigation, Choi (2014) concluded that employees‘ perceived HPWS were more
strongly associated with productivity and financial performance of organizations than
manager reported HPWS.
Therefore, without any doubt, it is clear that during 1990's, consideration given to
investigating the relationship between HPWS and organizational performance was far
ahead compared to the consideration given to understand the impact of HPWS on
workers (Bacon, 2003), thus, evident dearth of research focused on understanding
employees' responses towards HPWS. This is mainly because of the research methods
dominated, predominantly in US literature, which focused mainly on large survey
researches that might ensure high level of reliability but with some questionable validity
(Purcell, 1999). This extensive attention of HPWS on organizational performance,
therefore, caused lack of research efforts to investigate its on employees (Godard &
Delaney, 2000). Consequently, disconnection exists between what organizations and
36
managers report about their HPWS and what employees experience actually (Liao, et al.,
2009).
For these reasons, researchers have suggested to conduct more employee-centered studies
to understand the impact of HPWS on employees to have a balanced and meaningful
picture of HPWS-performance linkage (Boselie, et al., 2005; Delbridge & Keenoy, 2010).
Paauwe (2009) asked for ―a more balanced approach that pays equal attention both to the
managerial, functionalist perspective and to the concerns, involvement, and well-being of
employees‖ (p. 130) to avoid just employer perspective on HPWS-performance
relationship that represents just half picture of the whole story. Recently, a systematic
review of literature by Van De Voorde, et al. (2012) identified 36 studies that
incorporated both employee's and employers' outcomes and highlighted the need for more
research on these lines as these studies have reported mixed findings. More recently,
however, Boxall, Guthrie and Paauwe (2016) reported some progress in this regard and
again stressed on the need to investigate business and employee outcomes simultaneously
with same HPWS to have a more comprehensive view of how these work systems effect
the both.
2.3.1.3 Debate 03: Intended Vs Implemented HPWS
Another issue that has been emerged within the HPWS-performance relationship
literature is the importance of understanding and recognizing HR policies and practices
differentiation (Gerhart, et al., 2000) that may be the potential reason for varied findings
in HPWS-performance research. Huselid and Becker (2000) asserted that researchers
should measure HPWS through HRM practices those are actually implemented in the
company instead of intended HRM polices which might not be implemented necessarily.
While differentiating organizational HR policies and practices, HR policies of the firm
represent intention of top management regarding the type of HR interventions which
should be implemented in the company. Besides this, HR practices represent HR
interventions which are actually carried out in the company (Gerhart, et al., 2000; Khilji
& Wang, 2006). Moreover, Guest (1987) had already highlighted this concern and
separated, clearly, espoused HR policy and HR practices by highlighting his concern that
37
the discussion of HR policies would suppress its practice in the organizations. According
to him, ―there is a danger of . . . assuming that because human resource management is
being talked about, it is also being practiced. There is a risk that it will be ‗talked‘ or
‗written‘ into existence, independent of practice‖ (p. 505).
Likewise, Khilji and Wang (2006) also highlighted the fact that intended practices within
an organization are different from implemented practices and thus, further investigation
should be carried out with the focus on implemented practices and its relationship with
performance outcomes as employees experience implemented rather than intended
practices. Wright and Nishii (2007) further elaborated this phenomenon through their
proposed ―HR causal chain‖ framework represented sub-processes that link HRM with
organizational performance. In their proposed model, they distinguish among intended
HR practices, actually implemented HR practices and perceived HR practices. This
model spotlighted the gap and also the linkage between intended and implemented HRM.
Intended HR practices refer to HR policies designed by top management and represent
the outcomes of HR strategy that is developed to produce favorable employee behaviors.
Whereas, actual or implemented HR refers to HR practices those are actually carried out
in the organization by line managers. Next, employee's perceived HR practices refer to
subjectively interpreted and perceived HR practices by the employees. These subjectively
perceived HR practices further influence workers attitudes and behaviors and finally
impact organizational performance outcomes. Various researchers have reported that all
the top management espoused HR practices are not implemented in a way they were
intended and thus HR practices reported by top management or HR department varied
from the response of line managers and the employees (e.g. Liao, et al., 2009; Guest, et
al., 2010).
While examining HPWS-performance relationship, much of the research efforts have
been done on investigating the said relationship at business level (e.g. Huselid, 1995;
MacDuffie, 1995; Delery & Doty, 1996) where senior HR position or top management
were asked to report their organizations' HPWS. However, researchers have argued that
by doing this, one is only studying the relationship of presence of certain HR practices
with the performance outcomes (Combs, et al., 2006) whereas effectiveness of HRM
38
practices required more than just their presence in the company as merely a policy that is
not implemented properly (Wright & Nishii, 2007). Further, line managers implement
HR practices differently based upon their level of motivation and interest for HRM,
competence and opportunity they get (Purcell & Hutchinson, 2007; Wright & Nishii,
2007; Harney & Jordan, 2008). Moreover, employees' perception regarding HR practices
will be dependent upon the level of efforts and effectiveness of line managers in
implementation of organizational intended HR practices within their departments.
Implemented HR practices are therefore more proximal, appropriate and validated
determinant of HR practices experienced by employees and their subsequent reactions,
than intended HR. In other words, effective implementation of HR practices depends
upon the line managers and therefore, studying their responses (in the form of actually
implemented HR) will have more true insights for HPWS-performance relationship (e.g.
Guest & Bos-Nehles, 2013; Piening, et al., 2014; Kim et al., 2018). Consequently, a
separate stream of research emerged recently within SHRM literature where researchers
are focusing on the effects of implemented/ line manager-rated HPWS, instead of
intended HPWS, on performance outcomes (Aryee et al., 2012; Choi, 2014; Kuvaas, et
al., 2014; Pak & Kim, 2016) to have a more meaningful view of HPWS-performance
relationship.
2.3.1.4 Debate 04: Level of Analysis
Another issue emerged within HPWS-performance research area is the level of analysis
while examining the effects of HPWS on performance outcomes. Researchers have
identified that HPWS-performance relationship is too distant and complex where HR
policy is intended at organizational level and then implemented at departmental, group or
team level by line managers, then how employees perceive and experience organizational
HRM further influences their attitudes, behaviors and performance outcomes (Bowen &
Ostroff, 2004; Takeuchi, et al., 2009). Based upon this differentiation among levels of
analysis, Wright and Boswell (2002) recommended breaking down the barriers between
macro HRM (focusing on organizational/ management perspective of HRM) and micro
HRM (emphasizing on studying the effects of HR practices on individual employees).
39
Therefore, the researchers are required to use multilevel approach to bridge the gap of
management and employees‘ perspective of HRM (Klein & Kozlowski, 2000; Wright &
Boswell, 2002; Shen, 2015; Renkema, et al., 2017) to have more comprehensive picture
of HPWS-performance relationship. However, despite this recognition for the need of
multilevel approach, majority of research studies, examined HPWS-performance
relationship, have used a single level of analysis. Among these studies used single level
of analysis, main emphasis was on organizational level of analysis (Combs, et al., 2006)
with an increasing number of recent research studies conducted, recently, at individual
level of analysis (e.g. Kuvaas, 2008; Boon, et al., 2011; Alfes, et at., 2013; Lee, et al.,
2015; Baluch, 2016). Although few researches have used multilevel approach to advance
theory on HPWS-performance relationship (e.g. Ostroff & Bowen, 2000; Bowen &
Ostroff, 2004; Arthur & Boyles, 2007; Wright & Nishii, 2007), less empirical research is
done by using multilevel approach in this regard. Wright and Boswell (2002) further
highlighted that practical difficulties of getting data from various respondents across
multiple levels of an organization may restrict researchers from adoption of multilevel
approach.
Based upon multilevel approach, Guest (1999) reported that organizational HPWS
improved employee motivation, job satisfaction and job security and reduced work
pressure of individual employee. Following same reasoning, Wright and Nishii (2007)
proposed framework, called HR causal chain, with clear distinction among organizational
intended HRM (designed at organizational level), implemented HR practices
(implemented by line managers) and perceived HR practices (employees‘ experiences of
HR practices) which influence employee reactions and further performance outcomes.
Extending on their work, Jiang, et al. (2013) drew a framework clearly mentioning
organizational, group and individual perspective of HR practices and their relationship
with each other and with subsequent performance outcomes. Paauwe (2009) suggested
that considering employees into the relationship between organizational HR practices and
various individual and organizational outcomes is a ―conditio sine qua non‖ for carrying
forward this field of research. He further argued that this is also important to effectively
respond to the criticism by Legge (1995), Keenoy (1997) and others for main focus on
40
management perspective by majority of HPWS-performance research work. Furthermore,
he suggested that much research efforts are still required for both theorizing and testing
this complex and distant HPWS-performance relationship through more appropriate
multilevel methodologies.
In the last, the studies to-date which used multilevel approach while examining HPWS-
performance relationship have connected intended HPWS (organizational level) with
employees‘ perceptions of HPWS and their subsequent outcomes (e.g. Sun, et al., 2007;
Takeuchi, et al., 2009; Ogbonnaya & Valizade, 2016; Shin, et al., 2016; Shen et al.,
2018). Following HR causal chain framework, literature is scarce in terms of connecting
and testing effects of implemented HPWS by line managers on employees‘ experiences
of HPWS and subsequent outcomes. Furthermore, using multilevel approach to explore
HPWS-performance relationship is entirely missing in the case of Pakistan.
2.3.1.5 Debate 05: Methodological Issues in SHRM Research
Review of the literature on HPWS-performance relationship highlighted numerous
methodological shortcomings faced in this research area. One such issue in SHRM
research area is debate regarding the measurement of organizational HR practices. In this
regard, Legge (2001) reported that researchers have measured organizational HR
practices in different ways including (i) their presence (dichotomous scale: yes/ no or
presence/ absence); (ii) their coverage (a continuous percentage based scale requires the
portion of employees covered by certain practice) and (iii) their magnitude (a continuous
scale to capture the extent of exposure to certain HR practice/ policy by an employee).
Further, majority of research in SHRM relied upon single respondent to achieve large
data set requirements of statistical analysis that leads towards data reliability issues
(Guest, 2001). In this case, according to Huselid and Becker (2000), in most cases, senior
position of organizations HR department were the best respondents for information
regarding HR practices across numerous jobs. However, Purcell (1999) argued that
whether one single manager can know about all the practices used in organizations with
diversified structure. Gerhart, et al. (2000) provided empirical evidence representing
reliability of HR measure may be close to zero when used single respondent and another
41
study conducted by Wright, et al. (2001) supported their concern. Several other
researchers have criticized extant studies for their reliance on the responses from HR
senior position or CEO or top management regarding HR practices while neglecting the
significance of implemented HR practices, by line managers, or employees' perceptions
of HR practices (e.g. Lepak, et al., 2006; Liao, et al., 2009).
In addition to this, researchers have identified several other reasons that cause variation in
findings such as sample size and characteristics, low response rate, variation in research
design, composition of HPWS as bundle of HR practices and variation in performance
measures used (Becker & Gerhart, 1996; Wood, 1999). Furthermore, Paauwe (2004)
stressed on the ―context‖ to understand the composition of HPWS and its relationship and
interaction with performance. For these reasons, Hesketh and Fleetwood (2006) argued
that there is a need to go beyond the most prevalent scientific approach being used by
researchers in SHRM research to advance the theory around HPWS-performance
relationship.
Moreover, most of the studies examined HPWS-performance relationship were
conducted in developed countries including U.S., UK, Canada, Netherland, Australia
(Boselie, et al., 2001; Guerrero & Barraud-Didier, 2004) and some other western
countries (Lobel, 1999). However, there are limited research investigations on HPWS-
performance relationship in developing countries like Pakistan. HR practices used in one
country may not result into same results in another country because of the influence of
national culture, industrial and organizational context and characteristics (Paauwe, 2004;
Poelmans & Sahibzada, 2004). Therefore, the appropriateness of such HPWS-
performance models in countries other than U.S and UK are a major concern in SHRM
research area.
Another methodological aspect in HPWS-performance research is to identify
organizational contexts that cause variation in the impact of HPWS on performance
(Delery, 1998; Batt, 2002; Datta, et al., 2005). Majority of research studies in SHRM
have been conducted in manufacturing sector for many reasons such as the use of
complex and potentially dangerous machinery, more need of inculcating competencies
and motivation, heavy reliance on people, processes and technology and better alignment
42
of HR systems with manufacturing work (Combs, et al., 2006). They also concluded that
organizational HPWS is more strongly associated with performance in manufacturing
sector than in service organizations. They further suggested that set of HRM practices for
an organization is very much dependent upon the type of operations carried out in that
particular firm and therefore future scientific investigation should be conducted with
HPWS specific to service sector because of the unique characteristics of operations and
the nature of work in service organizations. However, despite the rapid worldwide growth
of service sector in recent years and its contribution to economies, this sector has got less
research attention in terms of studying HPWS-performance relationship. It is hard to
ignore the contribution of service sector for its occupation of workforce i.e. 42%
worldwide as compared to 22.7% in manufacturing and 35.3% in agriculture sector (The
World Factbook, 2008). In addition to this, the behaviors of employees in service sector
are more critical in determining the quality of service for the reason that service sector
involves direct interaction of employees who produce service and the customers (Liao &
Chung, 2004). Although, an increasing number of research studies are focusing service
industry from last four to five years, researches recommended exerting future research
efforts in service sector while investigating HPWS-performance relationship to have
insights from this critical industrial context which is emerging rapidly and also much
different from manufacturing environment (Combs, et al., 2006).
2.4 Human Resource Management Research in Pakistan
Contrary to research efforts made in the area of SHRM by researchers around the world,
not many efforts have been made so far to understand the nature of HPWS-performance
relationship in context of organizational settings operating in Pakistan. Few simple
studies at individual employee level of analysis were conducted to study the effects of
employees‘ perceptions of organizational HPWS on their attitudes and behaviors. For
instance, Bashir, et al. (2011) studied the association between perceived HPWS and
employee commitment along with the moderating role of demographic characteristics
among academic staff of 22 higher education institutes of Pakistan. Moreover, Hassan, et
al. (2013) concluded that the relationship of perceived HPWS with organizational
43
performance and employee loyalty is mediated by job satisfaction. Recently, Gulzar et al.
(2014) used labor process theory to study the adverse effects of HPWS on employees.
They examined the mediating role of anxiety, job burnout and role overload in between
employees‘ perceived HPWS and employees‘ counter productive work behavior in 287
different organizations based in Islamabad. All these studies were conducted at employee
level of analysis and therefore, did not capture much of the insights regarding complex
HPWS-performance relationship.
Recently, however, using multi-level modeling approach, Riaz and Mahmood (2017)
investigated the impact of implemented HPWS by managers on employees‘ service
related behaviors (service performance and service oriented-OCB) through the mediating
role of affective commitment in banking sector operating in Punjab, Pakistan. The said
research used the data set of this thesis and is one of the pioneer studies in Pakistan using
multi-level approach to connect bank branch level variable with individual employee
level variables. Next, Riaz (2016) studied mediating role of social exchange, relational
coordination and employee reactions (job satisfaction, commitment and OCB) for the
linkage between employees‘ perceived HPWS and perceived organizational performance,
at employee level of analysis, among 17 service and manufacturing organizations
operating in Pakistan. Along with this, she also investigated the mediating role of human
capital between manager rated HPWS and organizational performance at organizational
level of analysis. Interestingly, she tested both organizational and individual level models
separately as two distinct models and did not connect them. Ahmad and Allen (2015)
conducted a study to gauge diffusion of HR practices in the form of HPWS in Pakistani
industry and found limited empirical support for the applicability and effectiveness of HR
practices in the form of HPWS in organizations operating in Pakistan.
On the other hand, some researchers have studied the impact of individual HR practices,
rather than HR practices in the form of bundle or system (one of the basic assumption of
SHRM research), on various employee related outcomes including employee
performance (Shahzad, et al., 2008; Shaukat, et al, 2015), employee motivation (Naqvi &
Nadeem, 2011) and organizational commitment (Imran & Ahmed, 2012; Ahmad, et al.,
2015). Furthermore, Dar, et al. (2014) investigated the mediating role of employees‘
44
commitment for the association of individual HR practices with employee performance
among the employees working in Islamic banks operating in Pakistan. All these
investigations have also been carried out at employee‘s level of analysis with a focus on
employee perceived HPWS and its impact on various subsequent employee outcomes. It
is evident from the above that not much research studies have been conducted to explore
the processes or intermediary variables which explain, this is not so simple, HPWS-
performance relationship. In addition to this, unlike done by researchers in other
countries, no study has used multilevel approach to investigate the complex and distal
HPWS-performance relationship. Therefore, limited insights are available regarding how
and why HPWS is connected with various performance outcomes in the context of
Pakistan.
2.5 Conceptual Framework
Figure 2.1 illustrates a multi-level conceptual framework depicting direct relationship
along with the processes linking implemented HPWS to bank branch performance and
employee outcomes (employee engagement, service performance and service oriented
OCB). First, based upon resource based view of the firm (RBV) and at branch level of
analysis, this study proposed that implemented HPWS by bank branch managers enhance
branch performance through branch level collective human capital. Next, underpinned by
social exchange theory and behavioral perspective of HRM and at cross-level of analysis,
current study also proposed that manager-HPWS has an impact on employee outcomes
including employee engagement, service performance and service oriented OCB. Finally,
based upon social exchange theory and at cross-level of analysis, this study examined
organizational justice dimensions (i.e. distributive fairness, procedural fairness and
interactional fairness) as mediating mechanisms through which manager-HPWS is related
with employee outcomes. The proposed relationships of this study are tested by using
multisource data (i.e. branch managers and front line employees) collected from 323 bank
branch managers and 1369 front line employees of 30 commercial banks operating in
Punjab province of Pakistan.
45
H1
H3(a-c) Branch Level
Individual Level
Manager- HPWS
Bank Branch
Performance
Procedural
Justice
H5(a-c)
Distributive
Justice
H4(a-c)
Interactional
Justice
H6(a-c)
Employee Outcomes
Employee Engagement
Service Performance
Service Oriented OCB
Collective
Human Capital
H2
Figure 2.1: Hypothesized Model
46
2.6 Branch Level Hypotheses
Previous part of this chapter demonstrated the emergence of people management in
organizational settings with emphasis on the contemporary HRM and its relationship with
organizational performance. The chapter also illustrated the developments in the research
area of SHRM in the context of Pakistan, criticism and the key prevailing debates
regarding HPWS-performance relationship. This section will now present the review of
literature in order to develop the proposed relationships of the study. Review of literature
and hypotheses development for branch level relationships and cross-level relationships
are presented in section 2.6 and 2.7 respectively.
2.6.1 Manager-HPWS and Bank Branch Performance
Theorists and researchers in SHRM have concluded that sets of HR practices in form of
HR bundles or systems have stronger impact than any HR practice individually (e.g.
Huselid, 1995; MacDuffie, 1995; Delery & Doty, 1996; Ichniowski, et al., 1996; Youndt,
et al., 1996; Combs, et al., 2006). Huselid‘s (1995) study of more than 800 US firms
served as a seminal work that investigated the association of HPWS with firm
performance. He used a set of 13 HR practices and proved significant relationship
empirically between these practices with both operational performance (productivity and
turnover) and short as well as long term financial performance of selected corporations.
This study acted as spring board for a significant body of research that empirically
confirmed the relationship of HPWS with firm performance (e.g. MacDuffie, 1995;
Delery & Doty, 1996; Appelbaum, et al., 2000; Guthrie, 2001; Batt, 2002).
Combs, et al. (2006) conducted a meta-analytic study which confirmed positive
association between HPWS and firm performance. They used 92 studies (published
during 1990 and 2005) in their meta-analysis and concluded that (i) HPWS has
significant impact on firm performance, (ii) set of HR practices in form of system has
greater effect on firm performance than individual HR practices and (iii) HPWS has
greater performance enhancing impact in manufacturing firms than service sector. They
further suggested that set of HR practices for an organization is very much depends upon
47
the type of operations carried out in that particular organization. Therefore, future
scientific investigations should be conducted with HPWS specific to service sector due to
unique characteristics of operations and nature of work to have meaningful insights
regarding HPWS-performance relationship from this rapidly growing sector.
Based upon, Bowen & Ostroff (2004) argument and suggestion that components of
organizational work systems ―should be largely driven by the strategic goals and values
of the organization‖ and that ―the foci of human resource management practices must be
designed around a particular strategic focus, such as service or innovation‖ (p. 206), this
study used HPWS developed by Liao, et al. (2009) which they proposed for service
organizations in order to improve service quality by increasing employees' competencies,
motivation and performance. They developed HPWS construct consisted of extensive
service training, information sharing, interdepartmental services, compensation based
upon service quality, self managed teams and employee participation, service discretion,
employees‘ performance evaluation based upon service delivery and job design. This
conception of HPWS related to service quality was built by Schneider, et al. (1998) on
the general HRM concerns considered vital for service delivery and included HRM
dimensions studied in previous SHRM researches in service context (Delery & Doty,
1996; Batt, 2002). Due to the characteristics of services such as intangibility,
simultaneous production and utilization, and involvement of client in production process
(Bowen & Schneider, 1988), it is not possible to have controls and checks after it is
produced in order to assure quality as it is common practice in manufacturing context
(Schneider, et al., 1998; Liao, et al., 2009). For this reason, performance of employees
involved in serving customers (front-line employees), in form of behaviors towards
clients, to satisfy their needs (Liao & Chuang, 2004) and in a straight way effects
customer satisfaction through service quality. Therefore, service firms are required to
devise a work system that equips the employees with required competencies, keeps them
motivated and provides them frequent opportunities to contribute in order to meet
customer expectations. For example, extensive training enables employees to provide
high quality services, performance appraisals considers service provision as evaluation
criteria and the use of incentives to links pay with quality of service. These practices
48
together in form of HPWS develop in employees the competencies (knowledge, skills
and abilities), information, resources, discretion along with the motivation to deliver high
quality services to fulfill customer demands (Liao, et al., 2009).
In the light of above discussion of literature and the recommendations, this study used
HPWS established by Liao, et al. (2009) because the ―best‖ combination of HRM
practices for a specific organization is very much dependent upon the nature of work
activities and operations of that organization. For instance, in this regard, Bakker,
Demerouti and Euwema (2005) also suggested that organizations need to make efforts for
utilizing their employees‘ abilities for enhanced customer satisfaction in order to have
effective and sustainable customer relations. Thus, it is required to inquire HPWS
specifically designed for service organization to identify its potential impact on
performance outcomes because of the unique nature of work in service settings (Combs,
et al., 2006).
Further, Ostroff and Bowen (2000) pointed that performance in organizational studies is a
multi-dimensional construct. In SHRM research area, Dyer and Reeves (1995) segregated
organizational performance into three categories including (i) financial/ accounting
outcomes (e.g. sales, profit, Tobin's Q, stock price, return on investment, shareholder
return) (ii) organizational/ operational outcomes (e.g. productivity, efficiency) and (iii)
HR outcomes (employee reactions like commitment, job satisfaction, absenteeism and
turnover intentions). This study used subjective measure of market performance adopted
from the study of Delaney and Huselid (1996) to measure bank branch performance. This
measure includes marketing performance, profitability, sales and market share as
dimensions of organizational performance and used by Aryee, et al. (2012) to measure
performance of bank branches in their study. Although subjective measures of
performance are criticized for reasons including chances of common method biases and
increased measurement error, researchers have used subjective measures and provided
convincing reasons (e.g. Delaney & Huselid, 1996; Takeuchi, et al., 2007; Chuang &
Liao, 2010; Aryee, et al., 2012). First, Gupta (1987) and Gupta and Govindarajan (1984;
1986) pointed out that it is not easy, even almost impossible to get objective data of
financial performance of individual units where there are chances of disclosure of their
49
organizational identifications. Second, Wall, et al. (2004) suggested that self-reported
responses on performance measures could be the replacement of objective performance
measures where objective measures are not accessible and/ or available. They also
reported an average correlation of 0.52 between actual objective and manager's perceived
performance of the firms. They also compared construct, discriminant and convergent
validities of subjective measures of performance against objective measures in an
investigation related to HPWS-performance relationship. Third, Tomaskovis-Devey,
Leiter and Thompson (1994) suggested that comparative approach is more effective than
directly requiring the respondent to give exact financial figures. Moreover, manager
reported measures of performance have been extensively used in many renowned studies
of the area even (e.g., Delaney & Huselid, 1996; Youndt, et al., 1996; Takeuchi, et al.,
2007; Chuang & Liao, 2010; Aryee, et al., 2012; Darwish, et al., 2016) perhaps because
of difficult or no access to actual performance data.
Therefore, this study has used subjective measure of bank branch performance including
profitability, sales and the marketing performance as branch/ group level dependent
variable because no meaningful slippage across performance outcomes is there in HPWS-
performance research area. Therefore, studies can choose from various valid performance
measures by assuring that the size of the effects should not be affected negatively
(Combs, et al., 2006). In case of this study, the main reason for selecting the subjective
measure of branch performance is non availability and non accessibility of bank branch
objective performance data. On the basis of above discussion, it is hypothesized that:
H1: Manager-HPWS has positive relationship with bank branch performance.
2.6.2 Mediating Role of Branch Level Collective Human Capital
Previous research studies in SHRM have suggested that organizational HR systems may
be considered as sources of establishing employees‘ competency and attitudes
(motivation) in a way that amplifies performance (e.g. Wright & Snell, 1991; Huselid,
1995; Delery & Shaw, 2001). Further, studies have used aggregated/ collective employee
related variables including aggregated employee performance (Aryee, et al., 2012) and
50
customer satisfaction (Nishii, et al., 2008) with firm level outcomes. On the basis of these
arguments, it can be inferred that the HPWS and branch performance relationship is
mediated by branch level collective human capital that will impact branch performance
through developing required knowledge, skills and abilities (KSAs) in employees.
Human capital is defined as the skills, knowledge and abilities of the workers that are
critical and considered the main source of competitive advantage for companies (e.g.
Subramaniam & Youndt, 2005). Human capital uplifts productivity through enhanced
knowledge, skills and abilities of the employees (Snell & Dean, 1992). According to
resource based view of the firm (RBV), HPWS would be associated with collective
human capital based upon the competitive advantage organizations gain through HPWS
by developing valuable, rare, non-substitutable and difficult to inimitable human capital
(Barney, 1991; Barney & Wright, 1998). In other words, HR system enhances
knowledge, skills and abilities and motivation of the employees to build pool of high
quality human capital (Delery & Shaw, 2001; Huselid, 1995) and therefore, organizations
will extensively use these HR practices to ensure organizational success through their
employees (MacDuffie, 1995; Guthrie, 2001). Organizations where HPWS are effectively
implemented, there are several practices such as the use of well designed and rigorous
staffing practices and extensive trainings that leads to high quality of organizational
human capital (e.g., Zacharatos, et al., 2005; Takeuchi, et al., 2007). Furthermore,
Delanery and Huselid (1996) emphasized on the importance of HR practices that ensure
high quality workforce hiring, and developing and raising the knowledge, skills and
abilities level of the existing workforce. Additionally, competitive compensation and
employee benefits are some other tools to attract, hire and retain high quality human
resource (e.g. Arthur, 1994; Guthrie, 2001). Finally, job design with flexible job
assignments also provide employees learning opportunities and develop their skills and
abilities (Liao et al., 2009). Moreover, Takeuchi, et al. (2007) concluded that
establishment level human capital was positively affected by HPWS as well as it
mediated the relationship of HPWS with establishment performance.
Moreover, the potential of human capital to impact organizational performance is widely
studied and well recognized in the literature of HRM and strategy (e.g. Barney, 1991;
51
Pennings, Lee & van Witteloostuijn, 1998; Coff, 1999; Hatch & Dyer, 2004; Nyberg,
Reilly, Essman & Rodrigues, 2018). Stating simply, an organizational pool of human
capital reflects employees‘ potential role in organizational success (e.g. Wright & Snell,
1991). In this regard, resource-based view of the firm (RBV) argued that competitive
advantage is the result of a firm‘s rare, valuable and difficult to reproduce resources
(Barney, 1991). An organizational resource is rare if it is costly or even impossible for
competitors to replicate or even non-substitutable with any other resource. Furthermore, a
resource is said valuable if it assists firm to take advantage of the opportunities or to
diffuse and neutralize threats arise in the external environment. In this way, these
valuable, rare and difficult to duplicate resource contribute towards achieving sustainable
competitive advantage through superior performance (Amit & Schoemaker, 1993).
Resource based view of the firm (RBV) suggests that HPWSs have the capability to
achieve sustainable competitive advantage by developing firm specific human capital and
complex social relationships among its members that would generate tacit knowledge
(Takeuchi, et al., 2007). Putting it together, branch level collective human capital should
mediate manager-HPWS and branch performance relationship. This argument is in line
with the work of Delery and Shaw, (2001) that identified employees‘ knowledge, skills,
abilities (KSAs) and motivation level as mediating mechanisms for the relationship
between HR system and labor productivity.
In addition to this, although much emphasis has been made on theoretical underpinning
of the concept of human capital (Jackson & Schuler, 1995), few studies have examined
this concept as a mediator linking HPWS with performance outcomes. For instance, Liao,
et al. (2009) concluded that the relationship between perceived HPWS and employee
service performance is mediated by individual employee's human capital. Yet, barely any
study has conceptualized bank branch level collective human capital as an intermediary
mechanism between manager-HPWS and bank branch performance. Therefore,
arguments based upon resource based view of the firm (RBV) suggest that branch level
collective human capital acts as mediator between implemented HPWS and branch
performance. Thus, on the basis of the above discussion, following relationship among
manager-HPWS, collective human capital and bank branch performance is hypothesized:
52
H2: Branch level collective human capital mediates the relationship between manager-
HPWS and bank branch performance.
2.7 Cross-Level Hypotheses
2.7.1 High Performance Work System (HPWS) and Employee Outcomes
Researchers have identified that HPWS impacts firm performance through employees‘
attitudes and behaviors (Boselie, et al., 2005). Theorists and researchers in HRM also
argued that attitudes and behaviors of employees are shaped, controlled and directed by
―the communicative nature of everyday HR practices‖ (Guzzo, et al., 1994: 453). Review
of extant literature highlighted lack of research on employees‘ response to HRM practices
with both positive and negative relationship of HPWS with individual outcomes (Van De
Voorde, et al., 2012). Moreover, these research studies demonstrated HPWS from mutual
gains perspective i.e. HRM is beneficial for both employer and employees through norm
of reciprocity and social exchange (Tsui, et al., 1997). Social exchange theory (Blau,
1964) and literature on psychological contract (Guest, 2004) argued that it‘s not just
monetary rewards but also non monetary aspects like future advancement opportunities,
recognition and participation which have significant impact on employees at workplace.
For instance, HPWS encourages employees through opportunities for participation,
enhance their competencies and recognitions (Lepak, et al., 2006) and in return
employees respond in more favorable ways such as work harder, demonstrate more
loyalty, job performance, commitment and even discretionary efforts towards their
employers (e.g. Appelbaum, et al., 2000; Sun, et al., 2007; Snape & Redman, 2010; ).
In SHRM research, researchers have mainly focused on management perspective while
examining HPWS-performance relationship and employee related factors were less in
consideration in this regard. Recently, however, researchers have started taking into
account employees outcomes into HPWS-performance debate. For instance, Kehoe and
Wright, (2013) reported that affective commitment fully mediated perceived HPWS and
turnover intentions relationship, whereas in case of perceived HPWS and OCB
relationship, affective commitment partially mediated the relationship. Zhang and Morris,
(2014) also tested relationship of HPWS with employee outcomes and firm performance
53
and concluded that employee outcomes mediated HPWS and organizational performance
relationship. Similarly, Ko and Smith-Walter (2013) reported that employees‘ work
related outcomes (i.e. organizational commitment, organizational citizenship behavior,
and job involvement) mediated the linkage between HPWS and organizational
performance in public sector organizations. On similar lines, Boxall and Macky (2014)
also found that HPWS was significantly related with employee well being. For the
purpose of this research, based upon the review and suggestions from extant literature,
three employee outcomes including employee engagement, employee service
performance and service-oriented OCB have been identified to investigate their
relationship with manager-HPWS.
Employee engagement construct was established and introduced by Kahn, (1990) to
represent one‘s self in-role expression, and involve cognitive, emotional and physical
dimensions (e.g. Schaufeli, et al., 2002; Schaufeli & Bakker, 2004; Salanova &
Schaufeli, 2008; Rich, et al., 2010). Employee engagement refers to a positive, affective
and psychological state of mind that compels an employee to express actively and invest
himself/ herself cognitively, emotionally and physically in their job performance (Catlette
& Hadden, 2001; Schaufeli, et al., 2002; Rurkkhum, 2010). Although researchers have
adopted a bit different views to define the concept of employee engagement (e.g., Kahn,
1990; Maslach, et al., 2001; Harter, et al., 2002; Schaufeli, et al., 2002; May, et al., 2004;
Sirota, et al., 2005), but in literature of human resource management, researchers agreed
that employee engagement is a psychological attribute that include high level of energy,
enthusiasm and efforts (Macey & Schneider, 2008; Gruman & Saks, 2011). In general,
engaged employees are described as individuals who have high level of energy and
resilience in performing their job, involve in their work by heart with persistence and
always willing to make efforts, demonstrate deep involvement in their work along with a
strong sense of meaningfulness, significance, passion, enthusiasm, inspiration,
excitement, pride, take their work as challenge, concentrate and involve themselves in
their work without having any sense of passing time (Schaufeli & Bakker, 2004; Bakker
& Demerouti, 2008).
54
Employee engagement research is drawn on social exchange theory which advocates that
employees will be more engaged with their job by feeling more positive emotions at
workplace, through intellectual efforts, and experiencing meaningful relations at work
(Alfes, Truss, Soane, Rees & Gatenby, 2010). The antecedents of employee engagement
are once in place, pass signals that employees are valued and trusted (Rich, et al., 2010).
Organizational work practices in the form of HPWS are one such antecedent that
broadcast signals for employees regarding their employer‘s willingness to support and
invest in them and, therefore, these systems of HR practices may have positive
association with employee engagement.
Despite the fact that understanding employee engagement is one of the major areas of
interest for organizational scientists, it is less studied in the context of HPWS as
compared to other employee attitudinal outcomes like commitment and satisfaction
(Alfes, et al., 2013). Recently, however, theorists of HRM argued and suggested that it is
required to study cognitive and activated impact of HR system for the reason that HR
systems are developed to enhance employees‘ empowerment at their workplaces
(Vandenberg, Richardson & Eastman, 1999; Boxall & Macky, 2009). Thus, this study
argued that HRM and employees‘ outcomes relationship could be better understood and
explained by using an attitudinal outcome that has a more comprehensive view of
employee‘s individual self and also contains activated components. A concept that
includes emotional, cognitive and physical activation all together, ―employee
engagement‖ and, hence, covers a more comprehensive view of an individual‘s self
(Rich, et al., 2010). Therefore, this study considered this comprehensive employee
outcome as one of its dependent employee level variable to have a much wider view of
this HPWS-employee outcome relationship.
Job demands-resource model provides another platform to link HR practices with
employee engagement. For example, job demands-resources model argues that job
demands like emotional strain and extensive workload (work overload) are linked with
exhaustion and lack of job resources like job control or social support predicts employee
disengagement (Demerouti, Nachreiner, Bakker & Schaufeli, 2001). Scientific evidences
generated from job demands-resources model have showed that HR practices in the form
55
of job related resources such as training opportunities (Salanova, Agut & Peiro, 2005),
performance or interpersonal feedback from immediate supervisors (Schaufeli & Bakker,
2004) or task variety (Salanova & Schaufeli, 2008) had significant positive association
with employee engagement. Recently, Alfes, et al. (2013) studied mediating role of
employee engagement for the relationship of employees perceived HPWS with OCB and
turnover intentions. Therefore, on the basis of this discussion, this research proposed a
positive linkage between manager-HPWS and employee engagement and established
following relationship for empirical testing.
H3(a): Manager-HPWS is positively related with employee engagement.
Further, in general, employee performance refers to physical reactions of employees that
are essential and relevant for achievement of organizational goals and those behaviors are
under employees' control (Campbell, McCloy, Oppler & Sager, 1993). In service
context, clients are one of the most important factors considered when defining employee
performance (Bowen & Waldman, 1999). Employee service performance refers to their
behaviors related to serving and helping customers (Liao & Chuang, 2004). Further, the
concept of employee service performance is different from that of service effectiveness,
which includes the consequences of employee service performance like customer
satisfaction, commitment, loyalty and retention. Factors that (which) are not in control of
employees may cause variance in service effectiveness and, therefore, behavioral factor
in control of employees has been used in this study that is less contaminated (Campbell,
et al., 1993).
The environment and nature of service industry is quite different from production setup
and, therefore, requires different types of employees as compared to manufacturing
industry. Service industry is characterized by factors like service intangibility, production
and consumption of services at the same time, and involvement of customer in service
process (Bowen & Schneider, 1988) which makes it almost impossible to have quality
control checks to ensure quality like in manufacturing context (Schneider, et al., 1998).
Due to these reasons, front-line employees‘ performance and their behaviors (helping,
assisting or serving) towards clients are of paramount importance to address the needs of
56
customers (Liao & Chuang, 2004) which directly affect customers‘ outcomes, such as
customer satisfaction, customer loyalty, with service quality. For these reasons,
organizations design work systems that include practices to ensure required level of
employee KSAs and motivation to match customer needs through superior service
performance.
Adding to this, Bowen and Ostroff (2004) suggested that organizational work practices
―should be largely driven by the strategic goals and values of the organization‖ and that
―the foci of the human resource management practices must be designed around a
particular strategic focus, such as service or innovation‖ (p. 206). To be an effective work
system, it should echo that how the employees can contribute towards organizational
success. To achieve this, work practices within the system must be aligned with some
strategic objective, without which, work system lacks its capability of showing
employees the clear direction.
Review of extant literature revealed that majority of the studies have used general
measures of individual performance like in-role performance behaviors (e.g. Uen, Chien
& Yen, 2009; Snape & Redman, 2010), and job performance (e.g. Kim & Wright, 2011).
However, researchers have argued and suggested to use organization-specific
performance measures while investigating HPWS and employee performance
relationship because of the reasons discussed in last paragraph. For example, some
researchers have recently used organization specific employee performance measures
such as service performance (Liao, et al., 2009), quality and efficiency of patient care in
health-care sector (Gittell, et al., 2010), teacher‘s performance (Shen, et al., 2014) and
volunteers‘ performance in hospital settings (Rogers, et al., 2016).
This study, therefore, hypothesized a positive relationship between manager-HPWS and
employee service performance, as service sector specific individual performance
measure, and established following hypothesis for empirical testing.
H3(b): Manager-HPWS is positively related with employee service performance.
Further, Katz and Kahn (1966) highlighted that employees‘ discretionary (also called
spontaneous) behaviors are vital for organizational effectiveness. Researchers suggested
57
that these are employees‘ discretionary efforts that differentiate average and outstanding
firms through influencing service quality perceptions of the customers (e.g. Morrison,
1997; Berry, 1999; Bowen, et al., 2000).
Organ (1997) demarcates employees‘ organization citizenship behaviors as employees‘
discretionary efforts that contribute ―to the maintenance and enhancement of the social
and psychological context that supports task performance‖ (p. 91). The concept of
organizational citizenship behavior has been conceptualized in different ways by various
researchers during last three decades (e.g. Bateman & Organ, 1983; Organ, 1988;
Williams & Anderson, 1991). Among these, Organ (1988) developed one of the most
known conceptualization where he initially conceptualized a five-dimensional OCB
framework including altruism (i.e. helping and assisting other employees in their job
tasks and problems); courtesy (i.e. discussion and consultation with others before an
action); civic virtue (i.e. showing interest in the matters and affairs that influence the
organization); conscientiousness (i.e. employees‘ behavior showing that they accept and
follow organizational rules, procedures and regulations); and sportsmanship (i.e.
employees‘ willingness to bear and tolerate less ideal circumstances and giving greater
consideration to even smaller organizational problems). He further extended this model
by including peacekeeping and cheerleading as two other OCB dimensions (Organ,
1990). However, empirical researches indicated that managers often feel it difficult to
differentiate these two dimensions from others (Bachrach, Bendoly & Podsakoff, 2001;
Podsakoff & Mackenzie, 1994) and thus, they viewed peacekeeping, cheerleading,
altruism and courtesy as component of overall helping aspect of OCB (Podsakoff,
Whiting, Podsakoff & Blume, 2009).
Adding to workers‘ discretionary behaviors debates, Borman and Motowidlo (1993)
added by arguing that ―some types of OCB are probably more appropriate for certain
types of organizations than others. Service companies have special requirements on
dimensions related to dealing with customers and representing the organization to
outsiders‖ (p. 90). Consequently, Bettencourt and Brown (1997: 41) presented the
concept of ―service oriented OCB‖ to represent ―discretionary behaviors of customer
contact employees in servicing customers that extend beyond formal role requirements‖.
58
Bettencourt, Gwinner and Meuter (2001) further identified dimensions of service oriented
OCB including participation, loyalty and service delivery. Where loyalty focuses on
employees‘ actions that not only promote and advocate the products and services to
outsiders but also image of the company. Through participative service oriented OCB,
employees take initiatives, particularly in information sharing (communication) in order
to improve not only their own service behavior but that of their coworkers as well. This
concept is the basis for organizations‘ ability to respond to their customers‘ changing
needs in more effective and efficient way. Finally, service delivery service-oriented OCB
focuses on employees‘ conscientious behavior during service delivery activities.
Organizational efforts through HR practices are argued to be very useful in producing
and encouraging more OCB among employees (Morrison, 1996) and therefore,
combination of HR practices in form of HPWS has been identified as a source to produce
workplace environment that encourages employees‘ discretionary behaviors (Sun, et al.,
2007). Employees‘ OCBs have also been recognized as the behavioral outcomes of the
psychological climate (Wayne, Shore & Liden, 1997; Rhoades & Eisenberger, 2002;
Spreitzer, 2008; Seibert, et al., 2011).
Researchers claimed that an organization's way of managing its human resource is
instrumental in determining the level of citizenship behaviors of its employees (e.g.
Rousseau, & Greller, 1994; Morrison, 1996). Sun, et al. (2007) reported that HPWS
develops and promotes employees' perceptions of organizational support that encourages
employees to exhibit discretionary behaviors essential for organizational success. In this
regard, practices like extensive training and development and promotions from within
organization establish employees‘ perceptions of supportive workplace atmosphere that
reciprocate in form of more frequent discretionary behaviors. Numerous researchers have
conceptualized and tested the relationship between HPWS and general form of OCB (e.g.
GONG & CHANG, 2008; Snape & Redman, 2010; Messersmith, Patel, Lepak & Gould-
Williams, 2011; Zhang & Morris, 2014). Further, Sun, et al. (2007) identified positive
relationship between intended HPWS and OCB in service sector employees. However,
service oriented OCB, rather than general OCBs, while investigating its relationship with
HPWS is rarely been considered. Therefore, in this study, service context specific OCB
59
has been considered to investigate the relationship of HPWS with discretionary or extra-
role behaviors that assist in serving organizational customers and established following
hypothesis for empirical testing.
H3(c): Manager-HPWS is positively related with employee service-oriented OCB.
2.7.2 Mediating Role of Organizational Justice
Along with direct relationship between manager-HPWS and employee outcomes, this
study also hypothesized that this relationship is mediated by employees‘ perceptions of
organizational fairness (i.e. distributive fairness, procedural fairness, interactional
fairness). The concept of justice has been found in numerous philosophical works
focused on the characteristics of model social setup and serves as ―the origin from which
the whole of Western political theory begins‖ (Runciman, 1966: 254). ―Justice‖ has a
long and rich history as a philosophical concern and as a social construct and the work of
Aristotle and Plato had significant historical value in philosophy. In comparison to this,
the study of justice or fairness in social sciences is a recent phenomenon and Greenberg,
(1987) was the one who coined the term ―organizational justice‖. According to
Greenberg (1987), ―organizational justice‖ refers to the application of interpersonal and
social fairness theories in organizations to understand the behaviors of employees in the
workplace. First form of justices that captured the attention of researchers in
organizational studies was the concern regarding fairness of outcomes (Greenberg, 1987).
People's perception regarding fairness of outcomes is known as distributive fairness
(Leventhal, 1976). Individuals' opinion about procedures used for the allocation of
resources is known as procedural fairness (Thibaut & Walker, 1975). Further, last
dimension of organizational justice refers to the evaluation of interpersonal treatment
individuals receive from the decision makers (usually their supervisors or employers) is
called interactional fairness (Bies & Moag, 1986). Initially, the research on justice was
mainly concerned with the fairness of outcomes (i.e. distributive justice) only. In this
regard, Adams‘ Equity Theory is considered as a breakthrough work in justice research.
According to Adam (1965), people fairness evaluations of the outcomes were a relative
term where they calculate a ratio of inputs (competence, education and experience) and
60
outputs (rewards) and then make a comparison of their own ration with that of others.
This theory suggested by Adam was based on the rule of equity and subjective in nature,
later on, however, some other researchers have used other allocation principles such as
need and equality (e.g. Leventhal, 1976) which are being discussed in greater detail
following section.
Organizational justice perceptions of employees and its dimensions attempt to investigate
and explain the effects of people's judgment regarding fairness and unfairness on their
feelings, attitudes and behaviors while working in organizations. In other words, these
dimensions focus on the extent to which employees' attitudes and feelings are influenced
and shaped by their fairness perceptions. Tyler, et al. (1997) also explained the concept of
organizational justice through identifying criteria that individuals use while evaluating
fairness of procedures and outcomes. According to them, evaluation of organizational
justice phenomena can be seen in four waves. They further described that the first wave
was the rise of research related to distributive justice (1940s to 1970s), the second wave
was dominated by the rise of procedural justice (1970s to late 1990s) and the third wave
emphasized on interactional justice (1980s to 2010). Moreover, Colquitt, et al. (2005)
added another wave named as ―integrative wave‖ where researchers attempt to study
different combinations of these three dimensions of organizational justice. This research
has used Tyler's metaphor of organizational justice to link HPWS with employee
outcomes. Each of these dimensions is discussed in greater detail in their respective
sections below.
Based upon organizational justice theory, this study addresses the ―black box‖ debate of
strategic HRM by explaining three dimensions of organizational fairness (distributive,
procedural and interactional) as mediating mechanisms that link manager-HPWS with
employee outcomes. Previous research studies have shown that HPWS has positive
association with various employees‘ attitudinal and behavioral outcomes as it develops
employees‘ competencies and provide them the incentives and participation opportunities
(Appelbaum, et al., 2000). Further, the organizational justice perceptions are widely
studied with individual HR practices in the extant literature (e.g. Greenberg, 1986;
McFarlin & Sweeney, 1992; Gilliland, 1994; Greenberg, 2003). Moreover, organizational
61
justice acts as one of the most important antecedents of various employee attitudes and
behaviors (Dailey & Kirk, 1992; McFarlin & Sweeney, 1992; Masterson, et al., 2000).
Despite its importance in HRM, organizational justice construct has got less attention in
SHRM research to incorporate the psychological processes that explain the effects of a
system of organizational work practices on worker‘ reactions. Although studies have
investigated the relationship of fairness perceptions with HR practices individually, like
with compensation (McFarlin & Sweeney, 1992) or performance appraisals (Cheng,
2014), fairness of the HR ―system‖ has been rarely studied (Farndale, et al., 2011).
Therefore, this study proposed organizational justice a process to explain the linkage
between manager-HPWS and employee outcomes. According to Bowen, Gilliland and
Folger (1999):
―Although HRM practices are often guided by technical,
financial, legal and strategic concerns, most employees do
not have the information or expertise to evaluate practices
from these perspectives. Employees evaluate HRM
practices from the users‘ perspective that is largely driven
by desires for fair and equitable treatment‖ (pp. 3).
HR systems in the form of bundle of practices have many components and features that
are expected to affect fairness perceptions of employees. As discussed earlier, in general,
HPWS includes several components such as selective hiring and rigorous selection,
active employees' participation in work processes, extensive trainings, information
sharing, learning and development, validated performance appraisals and performance
based equitable compensations (Arthur, 1994; Huselid, 1995). These elements not only
impact employees‘ skills and motivation but can also influence employees' justice
perceptions which further impact their attitudes and behaviors.
This relationship of HPWS, organizational justice and various employee outcomes could
be explained through social exchange theory where employees reciprocate the actions of
employer with their own actions accordingly (Blau, 1964). In other words, employees
more willingly accept decisions, cooperate and even ready for assistance when they get a
fair treatment from their employers (Tyler & Smith, 1998). Opposite to this, if employees
62
have a feeling that their employer is not treating them fairly, they are more likely to show
counterproductive behaviors and emotional exhaustion (Cole, et al., 2010), seek revenge
(Bies & Tripp, 2005), stealing (Greenberg, 1993) and take legal actions (Lind, et al.,
2000). Three meta-analytic studies summarized much of this research and reported high
level of correlation between organizational justice and employees reactions (e.g. Cohen-
Charash & Spector, 2001; Colquitt, et al., 2001; Viswesvaran & Ones, 2002) including
confidence on management, job performance, OCBs and counterproductive behaviors.
Next sections will discuss each dimension of organizational fairness (distributive
fairness, procedural fairness and interactional fairness) separately as psychological
mechanisms through which manager-HPWS is related with employee outcomes
(employee engagement, service performance and service oriented OCB).
2.7.2.1 Manager-HPWS, Distributive Justice and Employee Outcomes
Distributive justice is referred to as employees‘ perceptions of fairness concerning the
outcomes received in response of organizational allocation decisions. Employees usually
establish their evaluation opinion by comparing it with some referent standard
(Greenberg, 1990). Three rules are particularly important to establish and understand the
association of HPWS and distributive justice are (i) equality; (ii) equity and (iii) need.
Extant literature showed that individual HR practices like selection, compensation,
promotions and downsizing have been studied with employees‘ distributive justice
perceptions.
For instance, in the context of selection decision, distributive fairness refers to the
perceptions of evaluation accuracy and appropriateness of final selection decision.
Gilliland (1993) concluded that in selection decisions, equity-based selection rules were
crucial because candidates give more value to fairness of outcomes by comparing them
with some referent standard and were not concerned much regarding absolute level of
outcome (Colquitt, et al., 2001). Whereas hiring situation with these equality-based rules
argues that through unbiased evaluation, all the job applicants should treat equally and
have equal chances of being hired on job (Anderson, et al., 2001). On similar lines of
scientific investigation, Singer (1990) reported that equality of opportunities and avoiding
63
nepotism were rated as the most important determinants of fairness perceptions of
distributive justice.
In performance appraisal settings, distributive fairness could be understood as
employees‘ responses to their performance evaluation based upon principles including:
(i) evaluation scores should meet worker‘s expectations; (ii) post-evaluation decisions
should be determined on the basis of evaluation scores and (iii) these decisions should
meet workers‘ expectations (Bowen, Gilliland & Folger, 1999). In simple words,
employees evaluate the outcomes they receive as a result of their performance evaluation
ratings. Further, Gabris and Ihrke (2001) found that employees became more doubtful
about the fairness of organizational compensation system when they did not get the
rewards on the basis of their performance evaluation scores (i.e. distributional equity).
Negative distributive justice perceptions regarding the performance appraisal system of
an organization can enhance the burnout level of the employees (Gabris & Ihrke, 2001).
They further reported that in response to such poorly perceived distributive justice
context, some employees decrease their efforts level while others start working harder
that cause increased exhaustion and burnout.
According to Miceli and Lane (1991), the concept of distributive justice applies to
employee compensation and benefits as ―employees‘ evaluation of the perceived inputs
and outcomes of referent others and through this process identify benefit types and levels
they consider appropriate or desirable‖ (p. 20). Sweeney (1990) studied employees‘
perceptions of distributive justice regarding their pay on the basis of equity rule and
reported that fairness perceptions regarding performance rating and pay satisfaction had a
curvilinear relationship. He also reported that fairness perceptions of compensation were
highly associated with their pay satisfaction. In other words, employees who perceived
their compensation as more fair were more satisfied with their pay compared to those
who perceive their pay level lesser than what they actually deserve who were dissatisfied
with their pays. Finally, employees with the perceptions of getting more than what they
deserve were also less satisfied with their pay but this relationship was not statistically
significant. Furthermore, employees establish distributive fairness evaluations on the
basis of internally and externally equitable remuneration and incentives (Applebaum, et
64
al., 2000). Similarly, extensive and formal trainings enhance employees‘ perceptions of
distributive justice as these trainings help employees in improving their knowledge, skills
and abilities and assist them in superior performance execution (Applebaum, et al., 2000).
On the other hand, extant research highlights that employees‘ perceptions of distributive
justice have significant association with their attitudes and behaviors at work (e.g.
McFarlin & Sweeney, 1992; Blancero, et al., 1996; Masterson, et al., 2000) Therefore,
these positive perceptions should assist organizations in developing favorable attitude of
employees like enhancing their engagement, commitment and job related satisfaction
along with their performance and discretionary behaviors. In addition to this, previous
researches showed that pay equity perceptions are related to some of the most desired
HPWS consequences in form of employees‘ attitudinal and behavioral outcomes such as
job satisfaction, (e.g. Agho, et al., 1993; Tekleab, et al., 2005), employee engagement
(e.g. Saks, 2006) organizational commitment (Alexander & Ruderman, 1987; Chang,
2002) and increased workload (e.g. Brockner, et al., 1994). Thus, on the basis of the
above discussion, this study has proposed that distributive justice dimension of
organizational justice acts as mediating mechanism that links manager-HPWS with
employee outcomes and established following hypotheses for empirical testing:
H4(a): Distributive justice mediates the relationship of manager-HPWS with employee
engagement.
H4(b): Distributive justice mediates the relationship of manager-HPWS with employee
service performance.
H4(c): Distributive justice mediates the relationship of manager-HPWS with employee
service oriented OCB.
2.7.2.2 Manager-HPWS, Procedural Justice and Employee Outcomes
Greenberg and Tyler (1987) defined procedural fairness as ―the perceived fairness of the
means used to make decisions‖ (p. 129). Procedural justice indicates a decision making
process that is incorporating opinions and suggestions of individuals and felt more
transparent and fair by employees. Leventhal (1980) described six factors for fair
procedure including consistent, correct, unbiased, representative, accurate and ethical.
65
Previous empirical evidences showed that there are many components of organizational
HRM function that are significantly associated with the perceptions of procedural justice
including (i) selection decisions (Gilliland, 1993, 1994); (ii) employee evaluation
(Greenberg, 1986); (iii) promotion decisions (Bagdadli, et al., 2006); (iv) employee
compensation (McFarlin & Sweeney, 1992); (v) career related decisions (Crawshaw,
2006); and (vi) layoffs (Brockner, et al., 1994).
In case of using job-based selection techniques on job applicants, the participating
employees consider the fact that firm has used consistent and valid measure(s) for hiring
(Gilliand, 1993). In the same manner, Korsgaard and Roberson (1995) have noted that
providing employees a ―voice in decision procedures provides an indirect way to control
or ensure a fair decision‖ (p. 660). In the presence of HR practices, employees are more
engaged in decision making processes and have more trust on other parties, therefore,
they have higher level of procedural fairness perceptions (Konovsky & Pugh, 1994).
Further to a certain degree, ―procedural justice can be enhanced by giving employees a
voice in determining the methods by which outcome decisions are made—for example,
involving employees in designing behavior or outcome-based performance appraisals‖
(Bowen & Ostroff, 2004: 213). Researchers have also argued that employees are more
motivated in sharing information when their point of view got consideration by the
decision makers (Miller & Lee, 2001). When workers are more comfortable in expressing
their views by using communication channels inbuilt in organizational HPWS, they feel
higher level of procedural justice in such situation. As a result of these feelings of
procedural justice due to HPWS context, employees will reciprocate with higher
engagement, commitment, job satisfaction and job related and discretionary performance
behaviors.
In the context of employee appraisal, for example, many procedural justice rules are
having stronger impact on outcomes of HPWS. Employee voice was reported as the most
significant procedural fairness rule. Providing employees with the opportunity for voice
in performance appraisal refers to asking the subordinate to comment on his/ her
performance during evaluation period and vice versa (Holbrook, 2002). A meta-analysis
concluded that employees were more motivated, satisfied and considered the decision
66
making process more fairly conducted when they had more opportunities for voice
(Cawley, Keeping & Levy, 1998). This was the case even when employee participation
did not affect the results of their performance ratings. Moreover, extant research studies
have concluded that employee voice can result into positive procedural justice
perceptions regardless of the final outcomes (Folger & Greenberg, 1985; Korsgaard &
Roberson, 1995). Similar results had also found where employee voice procedures were
considered more fair in employee evaluation and pay packages (Folger & Greenberg,
1985), participatory decision-making (Greenberg & Folger, 1983), and conflict
management (Sheppard, 1985). Studies also concluded that involving employees in
decision making (participative decision making) caused enhancing their beliefs regarding
the procedural justices from their employers (e.g. Bies & Shapiro, 1988; Greenberg,
1990; Avery & Quiñones, 2002).
In context of employee compensation, the role of procedural justice is another important
perspective in understanding HPWS and justice relationship. Cloutier and Vilhuber
(2008) categorized the effect of pay determinants on procedural justice into four
dimensions. These dimensions includes: (i) perceptions of allocation procedures
characteristics (including accurate information of the contents of job, relevant employee
appraisal criterion and persistence of application); (ii) perception of decision makers‘
characteristics (perceived competence and impartiality); (iii) perceptions regarding
system transparency (procedures and outcomes information access) and (iv) procedure
for appeal (information availability about the procedure of filing a complaint and security
from fear of adverse action on it and correctability). Previous studies have reported that
procedural fairness perceptions explain huge variation in pay satisfaction in the area of
compensation (e.g. Dyer & Theriault, 1976; Tremblay, et al., 2000). Research studies
supported the idea of minimizing dissatisfaction with compensation outcomes if
employees perceived the decision making procedure fair and just (Greenberg & Folger,
1983; McFarlin & Sweeney, 1992). Additionally, Welbourne (1998) reported that
perceptions of procedural fairness and gainsharing satisfaction had positive relationship.
In the context of team working, Naumann and Bennett (2000) reported that supervisor‘s
visibility and perceived cohesiveness were positively related with perceptions of
67
procedural fairness in teams. In addition to this, Price, et al. (2006) also stated that
employees‘ perceptions of fairness were more stronger when they were given opportunity
of voice in team and further team was allowed voice at organizational level by
management. Colquitt and Jackson (2006) recommended that team environment might
impact its members‘ choices of justice norms that they apply to evaluate further for
procedural justice and identified consistency, equality and decision making control as the
most important rules. Research studies have reported that organizational practices with
perceptions of procedurally unfair are related with poorer employees‘ attitudes at work
explaining that the association of justice and HR practices is not always positively biased
(McEnrue, 1989; Ambrose & Cropanzano, 2003). This perspective supports the
pessimistic view of human resource management (e.g. Ramsey, et al., 2000) that
considers it beneficial for the organization only and reducing employees‘ wellbeing at
workplace through work intensification, lowering job security and work pressures.
Similarly, Bagdadli, et al. (2006) studied procedural justices perceptions in employee
promotion process and identified inverse impact on commitment for reason that how
employee perceive personal advancement opportunities and perceptions of the criteria
being used in the promotion process. This showed that workers were concerned about the
fairness of both the procedure and results in a promotion system. Similar relationship has
been identified between perceptions of procedural fairness and employee outcomes for
individual high performance work practices including career management (Crawshaw,
2006); grievance procedures (Shapiro & Brett, 1993); teamworking (Shapiro & Kirkman,
1999); and layoffs (Brockner, et al., 1994).
On the other hand, extant literature has also demonstrated that employees‘ perceptions of
procedural justice have positive association with their attitudes and behaviors at work
(Folger & Konovsky, 1989; Mossholder, et al., 1998; Colquitt, et al., 2001). As
Konovsky and Cropanzano (1991) reported that ―procedural justice is associated with
employee loyalty because the use of fair procedures generates expectations of fair
treatment in the long run‖ (p. 699). Moreover, employees‘ perceptions of procedural
justice regarding HRM practices are strongly related to the job satisfaction, employee‘s
organizational commitment and trust in management (Folger & Konovsky, 1989;
68
McFarlin & Sweeney, 1992). Moorman, Niehoff and Organ (1993) concluded that
procedural justice perceptions of employees were positively related with their
organizational citizenship behavior. In their study of 475 hospital employees, Konovsky
and Pugh (1994) empirically tested the association of procedural justice perception and
OCB and found that the perceptions of procedural justice are strong predictor of
employees OCB. Recently, Chen and Jin (2014) also reported that employees‘
perceptions of distributive and procedural fairness were more positively related with their
OCB than interactional justice perceptions. They conducted this study in Chinese context
for the first time to study justice and OCB relationship in Eastern culture where most of
the previous research work has been done in Western context. In return, organizational
citizenship behavior (OCB) has been identified as potential antecedent of numerous
individual and group outcomes (Podsakoff, et al., 2009).
Furthermore, Wu and Chaturvedi (2009) studied the mediating role of procedural fairness
perceptions for the relationship of intended HPWS with affective commitment and job
satisfaction. Therefore, it can be argued that these positive perceptions caused by
implemented HPWS should assist organizations in developing favorable attitude of
employees like enhancing their engagement, commitment and job related satisfaction
along with their performance and discretionary behaviors. Therefore, on the basis of the
above discussion, this study proposed that procedural justice dimension of organizational
justice acts as mediating mechanism that links manager-HPWS with employee outcomes
and established following hypotheses for empirical testing:
H5(a): Procedural justice mediates the relationship of manager-HPWS with employee
engagement.
H5(b): Procedural justice mediates the relationship of manager-HPWS with employee
service performance.
H5(c): Procedural justice mediates the relationship of manager-HPWS with employee
service oriented OCB.
69
2.7.2.3 Manager-HPWS, Interactional Justice and Employee Outcomes
Third type of organizational justice used in this study is interactional justice also ensured
through the components of implemented HR system of an organization. Interactional
fairness refers to employees‘ perceptions of fairness regarding the interpersonal treatment
they receive from their supervisors (Chang, 2005). Employees usually seek this fair
treatment from their supervisors on the behalf of their employer. Bies and Moag (1986)
argued that the literature around procedural fairness had not covered the breadth of
employees‘ perceptions of fairness of processes and procedures. Although procedural
fairness has critical role as how employees perceive fairness of formal processes or
procedures used in making decisions, social aspect is also important and missing as how
these procedures work in practice. Bies and Moag (1986) listed: (i) interpersonal fairness
and (ii) informational fairness as two such social dimensions of fairness. These two
dimensions collectively form interactional justice which is used in this study.
Interpersonal justice refers to the interpersonal treatment that employees receive while
enacting organizational procedures. In the context of employee selection, interpersonal
effectiveness during, recruitment, screening and selection decisions are important
determinants of employees‘ perceptions of procedural and outcome fairness. Numerous
research studies have found that organizational recruiters with better interpersonal skills
and warmth behavior are one of the main reasons of accepting job offers by the job
successful applicants (Barber, 1998; Taylor & Collins, 2000).
In contexts related to performance management, the ways in which organizational
procedures are enacted have more influence on fairness perceptions than the procedures
themselves (Cobb, Vest & Hills, 1997). Erdogan, et al. (2001) identified that punctuality,
voice tone of the rater and attentiveness, kindness and respectful attitude for the ratee are
the important factors they consider for making their judgments of fairness. Moreover,
Aryee, et al. (2007) reported that employees‘ perceptions of justice or injustice are
strongly based upon the interpersonal treatments they receive from their supervisors.
They further found that supervisor‘s perceptions of interactional justice i.e. how well he/
she was treated by the supervisor was linked with the interactional justice perceptions of
their own staff and declared it trickledown effect. In other words, according to Aryee, et
70
al. (2007), ―supervisors who experience interactional injustice at the hands of their
immediate bosses may take out their frustration on subordinates‖ (p. 192).
In the context of compensation decision processes, interactional justice refers to
communication between supervisors and their subordinates for deciding about
compensation. Andersson-Straberg, et al. (2007) found that greater respect shown by the
manager during performance reviews and day to day performance feedback was strongly
related to interactional justice perceptions of employees. With respect to the scenarios
relating to organizational change process, taking care of the employees who are
influenced by the reorganization by providing them support through activities like career
counseling and outplacements enhance their interactional justice perceptions as they see
this treatment as respect and sensitivity shown by their employer towards the employees
(Kernan & Hanges, 2002). They found employers‘ input, communication and support for
employees as the strongest predictors of employees‘ interactional justice perceptions in
their study conducted on one major pharmaceutical company that had gone through
organizational change process. As a result, trust in management improved through these
interactional justice perceptions. Research studies reported similar findings for the
association of interactional justice perceptions and variable pay (Cox, 2003), work team
settings (Byrne, 2001), employee grievance mechanisms (Nabatchi, Blomgren, Bingham
& Good, 2007), employee dismissals (Darcy, 2005) and layoffs (Brockner, et al., 1994).
Further, informational justice is a concept related to truthfulness and provision of
adequate information and justification for the decisions taken by managers (Cropanzano,
et al., 2007). In the context of employee selection, timeliness and honestly providing the
selection information are important determinants of informational justice perceptions of
employees (Gilliland, 1993, 1994). Likewise, researchers have identified that not
knowing the procedures increase the uncertainty level for the candidates during
recruitment phase and they attribute themselves as poor performers rather than not
knowing the expectations and the situation (Arvey & Sackett, 1993; Bauer, et al., 1998).
During the selection phase, dishonesty in providing the information to the job applicants
reduces trust level and perceptions of fairness (Gilliland & Hale, 2005; Lind & Tyler,
1988). Bauer, et al. (1998) and Gilliland, et al. (2001) argued that providing job
71
applicants with the information about the use of particular selection method and
evaluation criteria along with the justification for some specific selection decision
positively influence fairness perceptions of the applicants. Cropanzano and Wright
(2001) further argued that job applicants‘ perceptions regarding lack of necessary
information regarding selection decision enhance their perceptions of injustice.
In the settings of performance appraisal, studies have shown the importance of
informational justice (e.g. Bies & Shapiro, 1988) and highlighted the importance of
information sharing in shape of performance feedback and justifications to the
subordinates along with their appraisal ratings (Bies & Shapiro, 1988; Holbrook, 1999).
Bies and Shapiro (1988) further identified that unfavorable incidences were perceived
fair by employees if they had acceptable justifications and explanations along with their
performance ratings. However, Holbrook (1999) proposed that not all information
sharing and explanations are effective and may cause adverse impact and further
distinguished between external and internal explanation. Internal explanation focus on
personal traits or characteristics of the employee, where the decision recipient (the
subordinate) believes that he/ she can potentially influence the rater‘s scores through their
performance and actions. Whereas, external explanation or justification (or excuses)
refers to other factors than employee‘s personal characteristics and employee believes
that the decision maker (rater) has not enough control over the rating decision (e.g.
organizational directive, historical precedent). Furthermore, favorable outcomes in term
of rating decisions are linked with internal explanations of the decisions. However, the
second preposition of his study i.e. the explanation whether external or internal would
result into positive employees‘ reactions was not substantiated.
Kernan and Hanges (2002) conducted a research study on the surviving employees‘
reaction towards reorganization indicated that informational justice has significant
predictive potential for trust in management. Their study concluded that employees‘
perceptions of informational fairness were positively associated with information quality
(employee voice opportunities and communication) and implementation (management
actions consistency) during reorganization phase. Lind, et al. (1998) highlighted that
employees did not blame their employers who understand and accepted the economic
72
rational as reason for their job loss and even after they lose their job, they perceived this
treatment as fair and in respectable and dignified way. Factors included timely layoff
notices, assisting them in search of new jobs and dealing them with ultimate respect and
dignity. Folger and Skarlicki (1998) identified that when managers have bad news
regarding their subordinates, they often distance themselves from the victims of layoff
decision through decreasing their interpersonal contact instead of providing them
adequate information and explanation in a more sensitive manner.
In terms of employee compensation, employers who regularly explain the criteria for
compensation decision were perceived as more fair by their employees (Holbrook, 1999).
Schaubroeck, et al. (1994) identified that in case of continuous pay freeze, presence of
adequate justifications significantly reduce employee‘s turnover intentions, maintain their
procedural justice perceptions and enhance their satisfaction with their job and
commitment with their employers. Moreover, previous research studies showed that
employees perceive negative pay outcomes like merit pay freeze, pay cuts as fair,
appropriate and just when they have been provided adequate justifications and
explanations (Greenberg, 1990; Schaubroeck, et al., 1994).
On the other hand, numerous research studies have been conducted in laboratories and
fields that demonstrate the association of interactional justice perceptions with expected
employee outcomes of HPWS like affective commitment, job satisfaction and employee
performance (e.g. Cropanzano, et al., 2001). For instance, Pate, Martin and McGoldrick
(2003) studied the association of employees‘ perception of interactional justice with
employee attitudes including job satisfaction and organizational commitment. In addition
to this, Blancero, et al. (1996) investigated the relationship of interactional justice and
employees‘ discretionary behavior in services industry. Results of various research
studies have also demonstrated that employees' perceptions of interactional fairness were
positively linked with trust (e.g. Barling & Phillips, 1993; Ambrose & Schminke, 2003;
Saunders & Thornhill, 2003). Therefore, on the basis of the above discussion, this study
proposed that interactional justice dimension of organizational justice acts as mediating
mechanism that links manager-HPWS with employee outcomes and established
following hypotheses for empirical testing:
73
H6(a): Interactional justice mediates the relationship of HPWS with employee
engagement.
H6(b): Interactional justice mediates the relationship of HPWS with employee service
performance.
H6(c): Interactional justice mediates the relationship of HPWS with employee service
oriented OCB.
2.8 Conclusion
This chapter is written with the aim of providing review of literature on HPWS-
performance relationship. The chapter started with the discussion of history and
emergence of people management in organizations. This chapter then discussed in detail
the concept of high performance work system, its relationship with performance
outcomes along with current debates prevailing in this research area. Further, based upon
review of literature, this study indentified and proposed mediating mechanisms
connecting HPWS with bank branch performance and employee outcomes (employee
engagement, service performance and service related OCB). First, based upon resource
based view of firm (RBV), this study proposed bank branch level collective human
capital as mediating variable between manager-HPWS and bank branch performance.
Further, based upon social exchange theory, organizational fairness dimensions
(distributive fairness, procedural fairness and interactional fairness) are proposed as
intermediary mechanisms for the relationship between manager-HPWS and employee
outcomes. In total, six main hypotheses along with a number of sub-hypotheses were
developed for empirical testing. Next chapter will present research methodology
employed to test proposed relationships of this study.
74
Chapter 03:
Methodology
75
3. Methodology
3.1 Introduction
This chapter discusses in detail the methodological considerations employed while
carrying out this research. Chapter starts with the discussion of research paradigm
adopted in this study followed by the description of research design. Further, details on
sampling design including target population, sampling technique, sample size, and data
collection tools and procedure are also presented in this chapter. Finally, discussion of
measurement instruments used for the variables of the study is presented and the chapter
ends with the discussion of data analysis techniques used in this study followed by ethical
considerations while conducting this study.
3.2 Research Philosophy
―All research is based on assumptions about how the world is perceived and how we can
best come to understand it‖ (Uddin & Hamiduzzaman, 2009: 658). Thus, understanding
of research philosophy is critical for at least two reasons (Hughes & Sharrock, 1997).
One, research paradigm directs ―in-depth thinking, and generates further questions in
relation to the topic under consideration‖ (Crossan, 2003: 47). Next, research philosophy
considerations enable scholars to select, improve and assess research methods to be
employed (Easterby-Smith, et al., 2002).
In organizational research, four research paradigms are used including positivism,
constructivism, realism and critical theory (Sobh & Perry, 2006). In positivist paradigm,
knowledge is generalized for a larger population based upon the empirical analysis of
data. In constructivism, findings of research are related to researcher‘s perspectives about
the reality and their manifold constructed realities. In case of realism, knowledge is
generated through analytically demonstrating empirical findings enclosed within theories.
In case of critical theory, the generalization of knowledge is done through its
appropriateness to the judgments in the society.
Of these four research approaches, positivism is a main research philosophy used in
organizational research. Aguinis, et al. (2009) presented a review of research methods in
organizational studies indicating that majority of the empirical studies in organizational
76
sciences adopted positivist paradigm. This concept of ―positivism‖ was first introduced
by August Comte (1798-1857), a French philosopher, in nineteenth century. According to
him, ―society could be analyzed empirically just like other subjects of scientific enquiry
and social laws and theories could be on the basis of psychology and biology‖
(Walliman, 2005: 203). Stating simply, knowledge could be gathered through how people
see reality (Comte, 1853). Thus, research studies based upon positivism generally adopts
quantitative approach to examine the reality which has several advantages. First,
quantitative approach enables researchers to make comparisons between locations,
groups and time which can be gauged for difference. Second, positivism paradigm
enables researchers to predict phenomena by attempting to examine the causal
relationships. Therefore, scientific investigation through a small group (sample) can
provide reliable reflection of a larger population. Third main advantage is the control of
researcher over research process (e.g. controlling factors such as variables and survey
instrument standardization). There are numerous other advantages of this research
approach such as clear theoretical focus, economical data collection from large number of
respondents and easy data comparisons (Saunders, et al., 2007). Despite several
advantages, positivist approach has also been criticized for not ―providing the means to
examine human beings and their behaviors in an in-depth way‖ (Crossan, 2003: 51).
Consequently, post-positivism emerged as an amendment to positivist approach and
accounts for the criticism on positivism (Popper, 1959) which believe that ―reality is
multiple, subjective and mentally constructed by individuals‖ (Crossan, 2003: 54). Thus,
positivism approach is refined and not rejected by post-positivism.
Positivist approach has been widely used in social sciences and also in organizational
research because of several advantages, discussed above, over other research paradigms.
Like other organizational researches, survey is the approach mostly used while
investigating HPWS-performance relationship (e.g. Arthur, 1994; Huselid, 1995; Becker
& Gerhart, 1996; Delery & Doty, 1996; Guthrie, 2001; Datta, et al., 2005; Takeuchi, et
al., 2007; Guthrie, et al., 2009; Liao, et al., 2009; Aryee, et al., 2012). This study also
used positivist approach like all main stream empirical studies in the area of SHRM. The
main goal of current research was to investigate the influence of implemented HPWS on
77
bank branch performance and employee outcomes and the intermediary mechanisms
explaining these relationships. Therefore, positivist approach is best suitable as it uses
surveys for gathering observations and employs statistical analysis for testing proposed
relationships among variables to explain their relationships in order to reach a conclusion
generalizable to entire population (Malhotra, et al., 2000). In addition to this, as
positivism paradigm uses a structured research process, the findings from such process
can provide suggestion for future strategies which are reliable empirically because of
objective procedures and criteria (Wright & Crimp, 2000). Reliability of findings is also
ensured through a large sample size used representing the population under study.
Positivist approach also allows comparing the findings of current study with that of
previous ones. Finally, this approach also allows testing the intermediary variables which
explain the HPWS-performance relationship.
3.3 Research Design
In any scientific study, decision regarding research design is based upon the purpose and
type of research study. According to the purpose of the study, there are three types of
research design including descriptive, exploratory and causal research (Zikmund, Babin,
Carr & Griffin, 2010). A descriptive research design is employed to illustrate the
characteristics of objects under study such as percentage, mean and so on. The main
purpose of descriptive research is to provide accurate and reliable data (Neuman, 2007).
Next, exploratory research is required to define and clarify a problem (Malhotra, et al.,
2006). Contrary to this, causal research is employed to test cause-and-effect relationship
between variables based upon clearly defined research problem (Sarantakos, 2005;
Zikmund, et al., 2010). Causal design is suitable where the purpose of the study is to
establish the nature of relationship among variables.
Based upon the objectives set for this study i.e. to examine direct and mediation effects of
implemented HPWS with bank branch performance and employee outcomes, this study
has mainly employed causal research design (also called hypotheses testing) along with
the descriptive one. Descriptive research was first used to illustrate the profiles of the
participants and characteristics of all the variables used in this study. Causal research
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design was then employed to test the proposed relationships among the constructs of the
study. For this multilevel quantitative study, survey method was used to collect cross-
sectional data from two sources. First, bank branch managers were requested to give
responses on bank branch level constructs including implemented HPWS (manager-
HPWS), branch collective human capital and bank branch performance. Second, front
line employees were asked to give information regarding the individual level variables
including distributive fairness perceptions, procedural fairness perceptions, interactional
fairness perceptions, employee engagement, service performance and service oriented
OCB. Details on how the survey was administered for this research study are given in
section 3.6 of this chapter.
This study considered the commercial banks operating in Pakistan because of their huge
size and operations across Pakistan. According to State Bank of Pakistan, (2015), 30
commercial banks with over 11,000 branches are operating in the country. Of 30
commercial banks, five are public banks, 16 are privately owned banks, five are Islamic
banks and remaining four are specialized banks. In terms of number of branches, state
owned banks had a total of 2,100 branches, private banks had 8,119 branches, Islamic
banks had 1,021 branches and specialized banks had a total of 603 branches across
Pakistan. The website of each of these banking organizations was consulted to estimate
number of branches across country in October 2014. For the purpose of this study, bank
branches of all the commercial banks operating in Punjab were targeted because of many
reasons. First, Punjab represents the largest proportion of population i.e. over 100 million
(55.6%) with the largest share in the GDP of the country. Second, approximately 56%
(over 6500 branches) of the bank branches are operating in Punjab which constitutes the
largest proportion of banking industry operating in any area of Pakistan. Further, all 30
commercial banks operating in the country also have their branches operational in
Punjab. Appendix A presents details on the breakdown of the branches of commercial
banks operating in Pakistan and Punjab. Sufficient number of bank branches provided the
opportunity to cast a broad net for this research.
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3.4 Target Study Area
This study has targeted the Punjab province of Pakistan for being the largest province
of the country in terms of population and share towards national GDP. Moreover, it has
the largest and fastest growing economy as compared to other provinces and
administrative units (ESP, 2014). The population of Punjab is more than 100 million that
is approximately 55.6 % of total population of the country occupying just 26 % land area
of the country with largest number of developed civic centers as compared to any other
province of Pakistan. Further, approximately 55.6% of the banking sector is located in the
Punjab province of Pakistan that is reasonably higher ratio than any other province and
administrative units of Pakistan including Sindh, Balochistan, Khyber Pakhtunkhwa,
Gilgit Bultistan and Azad Jamu & Kashmir.
3.5 Population and Sample
This section illustrates the detail of the population targeted for this study along with the
issues related to sampling including sampling technique used and sample size selected for
this study. Defining the target population for research study is the first step of sampling
design. Targeted population, for the purpose of current study, consisted of all the bank
branches of commercial banks operating in the Punjab province of Pakistan and front line
employees working in these bank branches.
Currently, according to State Bank of Pakistan (2015), 30 commercial banks are
operating in Pakistan with a total of 11,843 branches all over the country. Further, all 30
commercial banks operating in Pakistan are also present and doing their business
activities in Punjab. It was estimated that 6,581 bank branches of these banks (consist of
about 55.6 % of the total banking industry of the Pakistan) are operating in Punjab. SBP
has categorized these commercial banks into four categories: (i) public sector banks, (ii)
private banks, (iii) Islamic banks and (iv) specialized banks. Appendix A presents detail
of this categorization of banks by SBP in terms of number of branches operating in
Pakistan and in Punjab.
In any survey or experiment, it is not possible to include each and every unit of
population and therefore, researchers draw samples from a large population (Strati, 2000;
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Babbie, 2011). Mainly two methods are available for drawing samples from a large
population for any research study i.e. probability and non-probability sampling. In the
case of probability sampling design, simple random sampling, stratified sampling,
systematic sampling and cluster sampling are the approaches used by the researchers. On
the other hand, convenience sampling, quota sampling, snow ball sampling and purposive
sampling are the options available with non-probability sampling design (Zikmund, et al.,
2010; Saunders, 2011). Probability sampling design is considered more reliable than that
of non-probability methods of drawing sample from the population (Babbie, 2011). This
study used probability sampling technique to select a sample from targeted population
which means that every element of the targeted population has equal and known chances
to be selected as sample (Zikmund, et al., 2010; Saunders, 2011).
Moreover, multistage area sampling technique was used to identify the sample for the
purpose of the current study. In this regard, Punjab was selected first as target province
due to its largest proportion (i.e. more than 55%) of banking industry and was further
divided into 36 districts. Following the division of Punjab province into districts,
systematic random sampling was employed to select the target bank branches operating
in each district located in Punjab. Because all the districts and also all the banking
organizations had not equal number of bank branches, therefore, a list of all bank
branches was first developed carefully with its district wise categorization (first level
categorization) in alphabetic order. Next, the sub categorization within each district was
also done on the basis of bank names following once again in alphabetic order. Purpose
of this two level categorization was to maintain the proportion of bank branches from
each district and from each banking organization. After successful compilation of the said
list of bank branches, desired numbers of bank branches were selected through systematic
random sampling. Systematic random sampling was used to ensure the right proportions
of bank branches from each district and from each banking organization to keep the
sample representative of the targeted population as suggested by Saunders, (2011).
For this study purpose, 450 bank branches were selected as a sample for collection of
data. Sample size requirements for a research study are determined by many factors
including the proportion of the population size, data requirements of data analysis
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techniques employed along with access, time and financial resources available for that
particular research project (Sekaran, 2006; Zikmund, et al., 2010; Saunders, 2011).
According to the estimation given by Saunders (2011) and Sekaran (2006), in fact, a
sample size of 370 is required from a population with 10,000 units and 357 for a
population size of 5,000 units. Therefore, approximately, a size of 360-365 bank branches
was appropriate for current study having around 6,500 elements in the population.
Further, according to Tabachnick and Fidell (2007) and Hair, et al. (2010), data size of
250 observations is appropriate for testing hypotheses by using structural equation
modeling. Because there is often a low response rate from a survey (Zikmund, et al.,
2010), therefore, it was decided to select 450 bank branches as a sample for this study to
had a reasonable response rate which fulfill the requirements of similar to population
characteristics as well as observations required for data analysis.
Secondly, being the key employees, the front-line employees of 450 selected bank
branches who were directly involved in customer services and had atleast one year of
experience were considered for individual level data in this research. The reason for
including ―one year experience‖ as criteria was that new employees require some time to
understand organizational personnel policies and to make judgments about organizational
policies and procedures. Therefore, it was deemed reasonable to collect data from only
those employees who had spent some good amount of time with the bank to experience
and then express their feelings about organizational policies. A total of 2,500 front-line of
450 selected branches were contacted for responses on individual level variables for this
research study purpose.
Researchers identified and agreed that HR practices are not applied in the same manner
across all employee groups within same organization (Lepak, et al., 2007; Wright &
Boswell, 2002). Moreover, Boxall, et al. (2011) highlighted that in an organization, not
all the employees are managed in the same way with the main focus on key employees of
the organization. Researches also showed that an organization is a common place for
different employee groups including managers, production workers, professionals,
supporting staff, clerical employees and technical specialists that have different levels of
importance for employer and therefore are managed in different ways in terms of level of
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compensation, retention efforts, security of job, work pressure, autonomy and the
development and growth opportunities they have (e.g. Herzenberg, et al., 1998; Lorenz &
Valeyre, 2005; Kalleberg, et al., 2006; Gallie, 2007). Therefore, it is necessary to begin
with identification of the employee category in question when conducting any research
study on organizational systems (Lepak, et al., 2006). Extant studies also suggested that
organizations are always more concerned about their key workers (Lepak & Snell, 2002;
Lepak, et al., 2007) and organizational HR activities for these employee groups are more
sophisticated than other employee groups (Melian-Gonzalez & Verano-Tacoronte, 2006).
Therefore, for this study, front-line employees from selected branches were considered
for being the key contributors towards strategic objectives of service organizations. They
were requested to provide data related to employee level variables.
Bank branch managers provided data for variables conceptualized at branch level of
analysis including ―high performance work system‖, ―branch level collective human
capital‖ and ―bank branch performance‖. Whereas, front-line employees working in these
bank branches were requested to give their responses regarding variables conceptualized
at individual level of analysis including ―distributive justice‖, ―procedural justice‖,
―interactional justice‖ and ―employee outcomes (employee engagement, employee
service performance and service oriented OCB)‖.
3.6 Data Collection Technique and Survey Procedure
This cross-sectional quantitative study used self-administered survey questionnaires for
obtaining data from the respondents. Due to multilevel nature of the study, this study
required data for two different levels of analysis i.e. branch level and employee level.
Therefore, two separate self-administered questionnaires were developed to collect data
for this study. The respondents of branch level data were branch managers and they
provided their responses related to the variables including implemented HPWS, branch
level collective human capital and bank branch performance. In addition to this, front-line
service employees gave their responses for individual level variables including
distributive fairness, procedural fairness and interactional fairness, employee
engagement, employee service performance and service-oriented OCB. These
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questionnaires contained Likert scale statements, respondents profile information and a
cover letter. Cover letter presented information on the objectives of this research,
instructions to fill questionnaires along with the assurance of data privacy and anonymity.
Both the questionnaires were structured clearly and they were designed professionally to
ensure all participants would clearly understand and fill them. Most importantly,
instruments were pilot studied (tested) with the aim to eliminate the issues of misreading
and misinterpretation of survey statements and to improve the validity of the
measurement scales used for data collection. For the purpose of pilot testing, 10 bank
branch managers and 30 front line employees were contacted for responses relating
branch level and individual employee level constructs, respectively. Responses from six
branch managers and 18 front line employees were received and majority of the
participants have not reported any difficulty in understanding and filling the survey.
Further, only minor changes (replacement of original words with easy synonyms at four
places) were made in final questionnaire to increase its usefulness and understanding in
actual survey process. Both branch manager‘s and front line employee‘s surveys are
given in Appendix B and Appendix C respectively.
Self-administered surveys were either distributed in person or mailed to the branch
managers of 450 selected bank branches. Prior to the distribution of survey
questionnaires, branch managers were contacted to brief them about the purpose of
research project, procedure of the survey and requested their support in data collection
process. Each packet sent to branch manager contained one branch manager related
survey questionnaire and many front-line employee related survey questionnaires (7-25,
depending upon the size of the bank branch) with necessary information to carry out the
survey. Each questionnaire consisted of a cover letter stating the information regarding
the objective of this research, assurance of the privacy of data and the instructions for
―how to fill‖ the questionnaire. Researcher‘s contact number and email was also given on
the cover letter so that the participants could contact him in case of any query.
A total of 450 branch manager and 2500 front-line employee survey questionnaires were
distributed for data collection purpose. A total of eight months had spent for data
collection which included the pilot testing of the measurement instruments and the actual
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survey for the study. The survey started in October, 2015, after piloting the measurement
instruments, and took five to six months to complete the whole data collection activity
which was ended in March, 2016. Continuous reminders and follow-ups started after 10
days of distribution of surveys and continued for a period of almost five months to ensure
maximum response rate. These efforts yielded 347 branch manager and 1763 front line
employee surveys received back to the researcher. Data of 323 bank branches along with
their 1369 front line employees were finally used for data analysis after dropping some
with missing information and inappropriately filled questionnaires.
3.7 Measures for Common Method Bias
Researchers have showed concerns about the cross-sectional research design by raising
questions about common method bias and stressed upon taking appropriate measures to
control and minimize its effects (Ostroff et al. 2002; Podsakoff, et al., 2003;). This issue
arises when data on all the constructs of the study are collected from one source
(Podsakoff et al. 2012). First of all, this study collected data from multiple sources (i.e.
bank branch managers and front line employees) which, at first hand, reduced the
chances of the adverse effects of common method bias issue. Further, this study has also
taken several measures as suggested by Podsakoff et al. (2003) to control the possible
common method bias effects. First, to ensure respondents motivation and active
participation in the study, a detailed cover letter was attached with survey to explain the
objectives of the study along with the use of information collected for this study. Second,
the survey was designed in such a way so that the task difficulty should be minimized and
used concise and clear language to ensure that the responses from the participants are
more accurate. Next, to avoid social desirability bias, it was assured to the participants
that their responses would be kept confidential and anonymous. Further, they were
encouraged to give their honest opinion in terms of what exactly they feel about each of
the survey statement instead of considering some right or wrong answers. In the last,
possibility of common method bias issue was further reduced by ensuring good
psychometric properties of the scales used for the measurement of the constructs in this
study through confirmatory factor analysis (in Section 4.5). Even though, several
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measures have been taken to address the issue of common method bias, interpretation of
results of this study should be done by keeping in mind this caveat.
3.8 Measurement of Variables
This section illustrates the instruments used to gauge the constructs used in this research
study. As this study adopted a multilevel approach, therefore, data were collected from
two different sources (i.e. branch manager and front-line employees). Section 3.5.1 and
section 3.5.2 demonstrate the measures used for bank branch level and individual
employee level variables respectively. To ensure validity of survey, all the instruments
employed in current study were either adopted or adapted from previous researches.
Moreover, multiple-item scales were used in this study for all variables.
3.8.1 Branch Level Variables
This section presents details on the measures used to gauge branch level variables of this
study. Manager-HPWS, branch level collective human capital and bank branch
performance were the variables conceptualized at branch level analysis. Branch
manager‘s survey questionnaire is given in Appendix B.
3.8.1.1 Manager HPWS
Manager-HPWS was assessed through a 37-item measurement adopted from Liao, et al.
(2009) which they established to ensure service quality in banking organizations. They
established this scale based upon the HPWS measures developed by Zacharatos, et al.
(2005) with the focus of service quality outcomes. Manager-HPWS measure has eight
dimensions or eight high performance work practices which were measured through 37
items. These eight dimensions included extensive service training (06 items), information
sharing (08 items), inter-departmental services (02 items), team working and employee
participation (05 items), service discretion (05 items), performance appraisal (04 items),
performance based pay (03 items) and job design for quality work (04 items). Sample
items include ―The formal orientation programs to new employees are helpful for them to
perform their jobs‖ for extensive service training and ―Departments of this branch
cooperate well with each other‖ for interdepartmental services.
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Further, this study considered manager-HPWS as unitary index which has been widely
recommended and used in the research area of SHRM (e.g. Huselid, 1995; Becker &
Huselid, 1998; Liao, et al., 2009). This approach is in line with one of the basic
supposition of Strategic HRM suggests that the influence of HR practices can be better
understood by using the combination of HR practices as system rather than studying any
HR practice individually (e.g. Huselid, 1995; Becker & Huselid, 1998; Ostroff & Bowen,
2000; Wright & Boswell, 2002; Takeuchi, et al., 2007; Liao, et al., 2009). Responses on
all the items of manager-HPWS were recorded on five-point Likert scale ranging from ―1
= strongly disagree‖ to ―5 = strongly agree‖. Bank branch managers were requested to
indicate the extent to which each of the high performance practice was implemented in
their respective bank branch.
3.8.1.2 Collective Human Capital
Branch level collective human capital was measured through 5-item scale designed by
Subramaniam and Youndt (2005). These items focused service-related knowledge, skills
and abilities as the main focus of this study was front-line employees directly involved in
serving customers. Sample items include ―Our employees working in the branch are
highly skilled in serving customers‖ and ―Our employees working in the branch are
widely considered to be the best in our industry‖. Responses on all the items of branch
collective human capital were recorded on five-point Likert scale ranging from ―1 =
strongly disagree‖ to ―5 = strongly agree‖. Bank branch managers were requested to
report their agreement or disagreement with each statement related to human capital of
their respective bank branch.
3.8.1.3 Bank Branch Performance
Bank branch performance was measured by using 4-item scale from the study of Aryee,
et al. (2012), originally developed by Delaney & Huselid (1996) to measure the
establishment‘s market performance relative to its competitors operating in nearby area.
This 4-item branch performance scale covered the profitability, marketing, market share
and sales growth aspects of the bank branch performance. Although, the subjective
measure of branch performance may raise concerns like common method biases and
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some measurement error. It was not possible to get the objective data for branch
performance and there are also evidences regarding the use of subjective measures of
performance in literature (e.g. Delaney & Huselid, 1996; Sun, et al., 2007; Takeuchi, et
al., 2007; Chuang & Liao, 2010; Aryee, et al., 2012). Moreover, Wall, et al., (2004)
provided empirical evidences for discriminant, convergent and construct validity of both
the objective as well as the subjective measures of organizational performance. Bank
branch managers were asked to indicate last three years performance of their bank branch
in comparison to the nearby competitor bank branches on five-point Likert scale ranging
from ―1 = much worst‖ to ―5 = much better‖.
3.8.2 Employee Level Variables
This section presents details on the measurement instruments used to gauge individual
employee level variables used in this study. Distributive justice perceptions, procedural
justice perceptions, interactional justice perceptions, employee engagement, employee
service performance and service oriented OCB were the variables conceptualized at
individual employee level of analysis. Front-line employee survey questionnaire used in
this study is given in Appendix C.
3.8.2.1 Distributive Justice
Distributive justice perceptions of front-line employees were measured using 5-item scale
developed by Nieoff & Moorman (1993). Sample items include ―My work schedule is
fair‖ and ―I think that my level of pay is fair‖. Responses on all the items of distributive
justice perceptions were recorded on five-point Likert scale ranging from ―1 = strongly
disagree‖ to ―5 = strongly agree‖. Front-line employees were required to give their
opinion against each statement of distributive fairness.
3.8.2.2 Procedural Justice
Procedural justice perceptions of front-line employees were measured using 6-item scale
from the study of Nieoff & Moorman (1993). Sample items include ―Job decisions are
made by the branch manager in an unbiased manner‖ and ―My branch manager makes
sure that all employee concerns are heard before job decisions are made‖. Responses on
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all the items of procedural justice were recorded on five-point Likert scale ranging from
―1 = strongly disagree‖ to ―5 = strongly agree‖. Front-line employees were asked to give
their opinion against each statement relating to procedural justice.
3.8.2.3 Interactional Justice
Interactional justice perceptions of front-line employees were gauged using 9-item scale
developed by Nieoff & Moorman (1993). Sample items include ―When decisions are
made about my job, the branch manager treats me with kindness and consideration‖ and
―When decisions are made about my job, the branch manager is sensitive to my personal
needs‖. Responses on all the items of interactional justice were recorded on five-point
Likert scale ranging from ―1 = strongly disagree‖ to ―5 = strongly agree‖.
3.8.2.4 Employee Engagement
Front-line employees‘ level of engagement was assessed through 17-item measurement
scale adopted from Schaufeli, et al. (2002). Sample items include ―At my work, I feel that
I am full of energy‖ and ―I find the work that I do full of meaning and purpose‖.
Responses on all the items of employee engagement were recorded on five-point Likert
scale ranging from ―1 = strongly disagree‖ to ―5 = strongly agree‖. Front-line employees
were required to report their level of agreement or disagreement with each statement
relating to employee engagement.
3.8.2.5 Employee Service Performance
Service performance of front-line employee was measured through 7-item scale adopted
from Liao & Chuang (2004). Sample items include ―I am friendly and helpful to
customers‖ and ―I always try to approach customers quickly‖. Responses on all the items
of employee service performance were recorded on five-point Likert scale ranging from
―1 = strongly disagree‖ to ―5 = strongly agree‖. Front-line employees were required to
report their level of agreement or disagreement with each statement of service
performance.
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3.8.2.6 Service Oriented OCB
Service oriented OCB was assessed through 16-item scale developed by Bettencourt, et
al. (2001) to gauge discretionary behavior of front-line employees when serving
customers. Sample items include ―I often tell outsiders this is a good place to work‖ and
―I encourage my co-workers to contribute ideas and suggestions for service
improvement‖. Responses on all the items of employee‘s service oriented OCB were
recorded on five-point Likert scale ranging from ―1 = strongly disagree‖ to ―5 = strongly
agree‖. Front-line employees were required to report their level of agreement or
disagreement with each statement.
3.8.3 Control Variables
Due to multilevel nature of this research, control variables at both branch and individual
level of analysis are used. The study used branch size, branch age and type of ownership
as control variables at branch level of analysis. Branch size represented total employees
working in bank branch and was controlled because it might be related with the
sophistication of HPWS (e.g. Sun, et al., 2007; Aryee, et al., 2012) and also with
performance (Datta, et al., 2005; Shepherd, 1975). Further, branch age in terms of
number of years since its establishment was controlled to capture ―advantages associated
with increased time for the evolution or adoption of HPWS or differences in our outcome
measures‖ (Guthrie, et al., 2009: 118). Furthermore, effect of ownership type (public or
private bank) was also controlled as it has been reported as a factor with significant
influence on both organizational HPWS and performance (Wei & Lau, 2008; Su, Wright
& Ulrich, 2015).
In addition, this study used employee‘s gender, age and employment tenure with current
banking organization as control variables at individual level of analysis. Previous
research studies have shown that demographic variables of employees were found to be
associated with employees‘ workplace related attitudes and behaviors (e.g. Mathieu &
Zajac, 1990). Additionally, Boselie, et al. (2005) also reported that HPWS research
studies used employees‘ personal characteristics as control variables at individual level of
analysis. Therefore, in this study, demographic characteristics including age, gender and
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length of service at current organization, were taken as control variables at individual
level of analysis.
3.9 Data Analysis Techniques
This section presents details on techniques used to analyze data in this study. Based upon
the objectives set for this study, various data analysis techniques including descriptive
statistics, reliability and validity analysis of the measures, structural equation modeling
(SEM) and hierarchical linear modeling (HLM) were employed. Following section gives
details on each of the data analytical technique used in this research.
3.9.1 Descriptive Statistics
First and foremost statistical analysis conducted in this research study was descriptive
analysis. Descriptive statistics was used to describe and summarize the characteristics of
participants and variables of the study. This analysis includes averages, percentages,
frequencies and the spread of data (Zikmund, et al., 2010). In specific, the demographic
characteristics of bank branches and front line employees were described first by using
descriptive statistics. Next, the descriptions of study variables were made and presented
in terms of their mean scores, standard deviation; moreover, item wise descriptive
analysis of the study variables was also conducted and presented in next chapter.
3.9.2 Reliability Analysis
Reliability of a construct reflects the extent to which a measurement instrument generates
steady results when used repeatedly (Hair, et al., 1995; Zikmund, 2000). This analysis is
essential before going for hypothesis testing in order to ensure reasonable level of
reliability of measurement instruments used in any research study. Cronbach alpha test is
the most popular test used for reliability analysis and, therefore, was used for measuring
the reliability of the measurement instruments used in this study. According to Spector
(1992), the Cronbach‘s alpha score should be above 0.70 for a measurement scale to be
reliable. However, according to Moss, et al. (1998), the value of 0.60 for reliability alpha
(Cronbach‘s alpha) is generally acceptable. This criterion was used in this study to test
and ensure the reliability of the measures.
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3.9.3 Structural Equation Modeling
Structural equation modeling (SEM) was used to examine branch level proposed
relationships of this study. SEM is a statistical technique for hypothesis testing to
investigate the association among observed and latent variables (Hoyle, 1995). SEM
starts with model specification (i.e. statistical statement about the association of
variables) to be tested. According to Kaplan (2000), structural equation modeling is
defined as a class of analytical methodologies which represents hypotheses regarding the
means, variances and covariance of observations in the form of fewer structural
parameters suggested by a proposed model.
Structural equation modeling starts with a model (i.e. statistical statement regarding
relationships among variables) to be specified by researcher. Model specification refers to
the process of stating the relationships among variables which is fundamental to SEM
technique. In fact, no statistical analysis can be conducted in SEM until a model has been
specified by the researcher (Hoyle, 1995). Model specification refers to the formulation
of an equation regarding a set of either fixed or free parameters. Values are normally
fixed at zero for fixed parameters and these parameters have not measured from
observations collected. On the other hand, free parameters are estimated from data as
their values are believed to be non-zero by the researcher (Hoyle, 1995).
General structure equation model has two components: (i) measurement model i.e. that
section of model where latent constructs are defined and (ii) structural model i.e. the
other component of general model that stipulates the relationships among latent and
observed variables that are not latent variable indicators (Hoyle, 1995; Kaplan, 2000).
Although SEM has some commonalities with other approaches including correlation,
regression, however, it is different from aforesaid conventional methods and has a
number of advantages over these traditional approaches. For example, SEM provides
more flexibility and is more comprehensive data analytical technique than any other
traditional statistical model used in quantitative organizational and social sciences
research studies. Although, the standard approaches have the capacity of testing
hypotheses, SEM is capable of testing more complex and specified hypotheses than these
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traditional approaches (Hoyle, 1995; Kaplan, 2000). Therefore, this study used SEM for
analysis of branch-level proposed relationships.
In addition, SEM was also employed to run a number of confirmatory factor analysis
(CFA) for branch and individual level observations to estimate the validity (convergent
and discriminant) of the constructs used in this research. At branch level analysis, this
study tested three-factor hypothesized model including manager-HPWS, branch level
collective human capital and bank branch performance. Whereas, at individual-level of
analysis, a six-factor model was tested including distributive fairness, procedural fairness,
interactional fairness, employee engagement, employee service performance and service-
oriented OCB. Secondly, this study also required testing direct and indirect (mediation)
proposed relationships at branch level. SEM not only gives opportunity of controlling
confounding or extraneous variables but also for measurement error (Hoyle, 1995).
Therefore, in this study, first two hypotheses (H1 and H2) related to branch level
variables relationships were tested by using SEM. In specific, the following structural
model was investigated empirically by using SEM (in AMOS 20).
Figure 3.1: Model for Structure Equation Modeling (SEM)
3.9.4 Hierarchical Linear Modeling
Hierarchical linear modeling (HLM) was employed to investigate cross-level proposed
relationships of this study as this technique is increasingly used by researchers for
analysis of multilevel data (Raudenbush & Bryk, 2000). HLM has also application in
SHRM research area (Ostroff & Bowen, 2000) where individual-level data nested within
organizations, units or groups are frequently used. In such cases, the individual data are
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nested within groups or organizations and therefore are not independent and also contrary
to the assumptions of traditional regression or OLS model. In order to study individuals
nested in organizations, it is required not only to investigate the characteristics of
individuals but also needed to assess characteristics of the group or organizational context
within which individuals are working. As a result of such investigations, the data results
into variables at different levels of analysis including individual, group/ team and/ or
organizational (Hofmann, 1997). In such cases, three options are available for data
analysis (Hofmann, 1997).
First approach to test multilevel relationships could be to aggregate lower-level
observations to higher-level group/ team or organizational variables. For instance, the
relationship between organizational factors and individual outcomes could be
investigated through aggregating individual outcomes to organizational level (Hofmann,
1997). However, the meaningful variance at lower-level could not be accounted for in
both dependent variable and predictors while using aggregation of data approach
(Hofmann, et al., 2000; Klein, et al., 1994).
Second option available to test cross-level relationships is disaggregation of data i.e. all
the individual level units are given values according to their value on group or
organizational level variable. According to Bryk & Raudenbush (1992), in such cases,
data will be totally based upon the number of lower level units i.e. OLS regression. For
example, all individual within same group might give same value representing their
group characteristics when investigating a relationship between group characteristics and
some individual level outcome(s). Issue with this method is that several lower-level units
are working in same organization or group and experiencing similar stimuli. Therefore, it
is impossible to satisfy the assumption of independence of observations while using
traditional approaches of data analysis (Bryk & Raudenbush, 1992; Hofmann, 1997).
Along with this, while using disaggregation approach, the scores assigned to higher level
variable are based on units at lower level that can impact the measures of standard errors
and related empirical interpretations (Bryk & Raudenbush, 1992). Consequently, neither
of these two approaches is appropriate for satisfactorily testing of study‘s cross-level
hypotheses (from H3 to H6) as ignoring potentially meaningful variance at individual
94
level which might result in questionable construct validity in case of branch level
variables.
Hierarchical linear modeling (HLM) is the third approach for analyzing multilevel data
with notable advantages over aggregation and disaggregation approaches of multilevel
data analysis. First, HLM clearly recognizes that individuals within one group are more
similar than the individuals of other group and hence may not give independent
observations (Hofmann, 1997; Hofmann, et al., 2000). Saying it differently, HLM
explicitly model random error components at lower and higher level, thus, recognizes that
individuals within same group are interdependent. Whereas in OLS models as compared
to HLM, lower and upper level random errors are not estimated independently. Contrary
to previously discussed approaches (data aggregation and data disaggregation), HLM
allows for investigating the variance in the dependent variable at both individual and
group level while retaining suitable levels of analysis for predictors (Hofmann, et al.,
2000).
HLM approach estimates variance at both levels of analysis. Conceptually, HLM works
at two stages which analyze variables conceptualized at different levels of analysis.
Level-1 estimates regression separately for each group considering lower level predictors
and outcome. Further, level-2 estimates the variance in the intercept and slope of level-1
using organizational or group (upper level) level variables (Hofmann, 1997; Hofmann, et
al., 2000). Moreover, both lower and upper level models are investigated concurrently.
In case of estimation of multilevel models, three key terms are important to understand.
First, fixed effects that are parameters which remains same across upper level (i.e.
groups, teams or organizations) in multilevel models. In HLM, generalized least square
(GLS) regression is used to calculate fixed effects (Hofmann, et al., 2000). Even though
these can also be estimated through OLS regression, but this may affect the precision in
lower level (i.e. level-1) parameters across groups and this precision in variation is
eventually estimated in analysis of Level-2 (Hofmann, et al., 2000). Generalized least
square (GLS) measure provides a weighted regression due to which groups with more
precise estimates are given more weightage, thus, have more influence in level-2
95
regression. In case of fixed parameters, t-test statistics are provided in HLM (Hofmann,
1997; Hofmann, et al, 2000).
Second, random coefficients, refer to the coefficients with not fixed values across groups.
For example, intercepts and slopes at lower level (level 1) are random coefficients (i.e.
these change across groups). Although HLM does not explicitly measure random
coefficient parameters, it can be assessed by viewing mean and variance of random
coefficients which should be significantly departed from zero (Hofmann, et al., 2000).
Further, variance components refer to the variance and variance-covariance of residuals.
Expectation–maximization (EM) algorithm is used in HLM to measure maximum-
likelihood estimates for these variance components. HLM reports the results of chi-
square test for residual variances at upper level (level-2) to assess variance component‘s
significant departure from zero (Griffin, 1997; Hofmann, 1997).
Furthermore, talking about sample requirements, Kreft (1996) suggested that large
numbers of groups are required for multilevel data analysis. Hofmann, et al. (2000)
indicated that a sample size of 30 upper level units with each of these containing 30 lower
level units is appropriate to test cross-level relationships with sufficient power of 0.90.
They further indicated that there are trade-offs between number of upper level units and
lower level units within each group i.e. either more number of level-2 units with fewer
level-1 units in each group or few groups but having large number of individuals in each
group.
HLM has edge of incorporating interclass correlation (ICC) and measuring standard
errors that are corrected for observations dependence nested within group or organization.
Prior to HLM, researchers have the choice to investigate cross-level data through
disaggregation approach resulting into downward biased standard errors or through data
aggregation causing smaller sample size and larger standard errors. HLM eliminates this
trade-off and it forces the researcher to explicitly tackle the issue of level of analysis.
In sum, HLM has many advantages over other approaches of cross-level data analysis.
First, HLM specifically estimates both group/ organizational and individual level
residuals. In this way, HLM recognizes the partial interdependence of individual
members in same group or organization. Next, HLM approach provides researcher the
96
opportunity to identify and differentiate between different sources of variation in
dependent variable. Based upon these advantages, HLM was employed to analyze cross-
level proposed relationships of this study i.e. hypothesis 3 to hypothesis 6 were examined
by using HLM. Saying specifically, the following model showing cross-level
relationships, direct and indirect (mediating), were tested by using hierarchical linear
modeling (HLM).
Branch Level
H3(a-c)
Individual Level
3.10 Ethical Considerations
A number of ethical considerations are applied when conducting scientific investigations
in social sciences (McDaniel & Gates, 2002; Neuman, 2007). According to them, such
ethical issues include (i) ensure the respect and privacy right of individuals participated in
research (ii) voluntary participation and no forceful data collection, (iv) no deception is to
be used while collected data, (v) the right of respondents to know the objectives of the
research and (vi) report data in an unbiased and objective manner.
The researcher, by all means, ensured the above mentioned ethical considerations while
conducting this research study. The participants have briefed regarding the aim of the
Manager
HPWS
Distributive
Justice
H4 (a-c)
Interactional
Justice
H6 (a-c)
Procedural
Justice
H5(a-c)
Employee Engagement
Service Performance
Service Oriented OCB
Figure 3.2: Cross-level Proposed Relationships
97
study and the privacy of their data was promised along with the assurance of not using
this data other than academic purpose or to share it with any other. Other ethical issues
which had also been given careful consideration included sharing of summary of the
findings with the participants upon the completion of research project, if anyone want to,
no forceful participation and report the results in an unbiased manner.
3.11 Conclusion
This chapter first presented the importance of research philosophy and illustrated the
discussion of positivism paradigm used in this study. This quantitative multilevel study
adopted survey method to collect cross-sectional data from two sources (i.e. bank branch
managers and front-line employees) to test the proposed relationships of this research.
Further, this chapter also illustrated the targeted area, population sample design, sample
size and data collection tools and procedures employed in this study. The chapter ended
with a discussion of measures used for study variables and the techniques used for data
analysis. Next chapter will present details regarding analysis of data and the results will
be reported accordingly.
98
Chapter 04:
Results of the Study
99
4. Results of the Study
4.1 Introduction
This study aimed at investigating the direct relationship of manager-HPWS with bank
branch performance and individual employee outcomes, simultaneously. Further, based
upon resource based view of the firms (RBV), this study proposed branch level collective
human capital as intermediary mechanism between manager-HPWS and bank branch
performance relationship at branch level of analysis. In addition, based upon social
exchange theory, the study also proposed that employees' justice perceptions
(distributive, procedural and interactional) mediates the cross-level relationship between
manager-HPWS and employee outcomes. In light of these objectives, current chapter
starts with presenting the characteristics of participated bank branches and front line
employees followed by item wise descriptive statistics of all the measures used in this
study. Further, preliminary analyses including missing values, data cleaning issues,
normality and outlier issues are illustrated. After this, reliability of the measures,
confirmatory factor analysis (CFA), and correlation analysis results are also presented.
Finally, the results of hypotheses testing are delineated for which structural equation
modeling (SEM) is used to test branch level relationships and hierarchical linear
modeling (HLM) is used to examine cross-level relationships proposed in the study.
4.2 Characteristics of Participants
This section portrays an overview of the participants (i.e. bank branches and the front-
line service employees) across a number of demographic variables. Overall, 323 bank
branches of commercial banks operating in Punjab and their 1369 front line employees
participated in this research. Table 4.1 demonstrates the profile of participated bank
branches across a number of demographic variables. Whereas, Table 4.2 illustrates the
demographic characteristics of front-line employees participated in this study.
100
4.2.1 Characteristics of Participated Bank Branches
Organizational size is considered critical aspect while understanding the human resource
and employee relations management related activities (e.g. Sun, et al., 2007). In this
research, organizational size refers to total employees working in the bank branch. Table
4.1 indicates that, of 323 bank branches, 133 (41.2 %) bank branches employed 10 or less
employees. Moreover, bank branches with 11-19 employees represented the largest
category with a total number of 151 (46.7 %) bank branches. Remaining 39 (12.1 %)
branches were those which had a total of 20 or more employee. As far as age of bank
branches is concerned, 124 (28.4 %) branches were seven or less years old. While, 99
(30.7 %) bank branches belonged to an age category of 08-15 years. Next, 38 (11.8 %)
bank branches had been established within a time duration of 16-24 years and rest 62
(19.2 %) were an age of 25 years or more.
Table 4.1: Characteristics of Participated Bank Branches (n = 323)
Characteristics Frequency Percentage
Branch Size (No of Employees)
Upto 10
11-19
20 and Above
133
151
39
41.2 %
46.7 %
12.1 %
Branch Age (In Years)
Upto 07
08-15
16-24
25 and Above
124
99
38
62
28.4 %
30.7 %
11.8 %
19.2 %
Ownership Type
Public
Private
54
269
16.7 %
86.3 %
Bank Category (as per SBP)
Private Bank
Public Bank
Islamic Bank
Specialized Bank
236
49
31
07
73.1 %
15.2 %
9.6 %
2.2 %
Notes. SBP = State Bank of Pakistan
101
Table 4.1 highlights that majority of the bank branches, 269 (86.3 %), belonged to
privately owned banks and the remaining 54 (16.7 %) were of state owned banks.
Moreover, as mentioned in the Table 4.1, State Bank of Pakistan (SBP) categorized all
the commercial banks operating in Pakistan into four categories including private banks,
public banks, Islamic banks and specialized banks. As per the categorization of banks by
SBP, mentioned in Table 4.1, 236 (73.1 %) bank branches were of private banks.
Moreover, 49 (15.2 %) bank branches belonged to state owned banks followed by 31 (9.6
%) bank branches of Islamic banks and the remaining seven (2.2 %) bank branches were
of specialized banks.
4.2.2 Characteristics of Participated Employees
This research obtained data from two sources (i.e. bank branch managers and individual
employees) because of the multilevel nature of the study. Table 4.1 showed demographic
overview of the bank branches participated in this research. Next, Table 4.2 demonstrates
an overview of the characteristics of individual employees participated in this study. As
mentioned in Table 4.2, of 1369 front line employees participated in this study, 1067
(77.9 %) were male and remaining 302 (22.1 %) were female. In terms of the age of
individual employees, 159 (11.6 %) employees had an age of 24 years or less. While, 986
(72 %), the most, employees belonged to the age category of 25-34 years. Next, 170 (12.4
%) employees belonged to the age group of 35-44 years followed by remaining 54 (3.9
%) employees with an age of 45 years or above.
Moreover, Table 4.2 also reports the academic qualification of individual employees
participated in this study. Of 1369 front-line employees, only three (0.2 %) employees
had an academic qualification of intermediate or below. While 484 (35.4 %) respondents
were bachelor degree holders (14 years of education). Further, 799 (58.4 %) of them had
a master degree (16 years education) followed by 81 (5.9 %) employees with 18 years of
education. However, only two (0.1 %) employees held a doctoral degree.
102
Table 4.2: Characteristics of Participated Front Line Service Employees (n = 1369)
Characteristics Frequency Percentage
Gender
Male
Female
1067
302
77.9 %
22.1 %
Employee Age (In Years)
Upto 24 Years
25 - 34 Years
35 - 44
45 Years and Above
159
986
170
54
11.6 %
72.0 %
12.4 %
3.9 %
Highest Qualification
Intermediate and Below
Bachelors Degree (14 Years Education)
Masters Degree (16 Years Education)
M.S/ M.Phil Degree (18 Years Education)
Doctoral Degree
03
484
799
81
02
0.2 %
35.4 %
58.4 %
5.9 %
0.1 %
Salary
Below 20,000 Rupees
20,001 - 40,000 Rupees
40,001 - 60,000 Rupees
60,001 - 80,000 Rupees
80,001 - 100,000 Rupees
Above 100,000 Rupees
177
778
292
84
32
06
12.9 %
56.8 %
21.3 %
6.1 %
2.3 %
0.4 %
Employment Status
Permanent
Contractual
1120
249
81.8 %
18.2 %
Employment Tenure (Current Bank)
Upto 02 Years
03 - 07 Years
08 - 15 Years
16 Years and Above
899
427
38
05
65.7 %
31.2 %
2.8 %
0.4 %
Total Professional Experience
Upto 02 Years
03 - 07 Years
08 - 15 Years
16 Years and Above
347
685
276
61
25.3 %
50.0 %
20.2 %
4.5 %
103
In terms of the salary of individual employees, 177 (12.9 %) employees had a salary of
PKR 20,000 or below. Next, 788 (56.8%) employees belonged to the salary group of
PKR 20,001 – 40,000 and 292 (21.3 %) were those who had a salary range of PKR
40,001 – 60,000. Further, 84 (6.1 %) employees belonged to a salary range of PKR
60,001 – 80,000, followed by 32 (2.3 %) employees with a salary range from PKR
80,001 – 100,000 and the rest six (0.4 %) had a salary of PKR 100,001 or above.
In addition to this, as can be seen in Table 4.2, of 1369 front-line employees, 1120 (81.8
%) were permanent employees and rest 249 (18.2 %) had contractual employment.
Furthermore, talking about the tenure of employees with their current employer, 899
(65.7 %) employees had employed with their current bank from last two years or less.
Next, 427 (31.2 %) employees were those who had a tenure of 3–7 years followed by 38
(2.8 %) employees with a tenure of 08–15 years and remaining five (0.4 %) employees
had a tenure of 16 years or above with their current employer bank.
4.3 Data Handling and Preliminary Analysis
This section presents the details on the statistical analyses and treatments to be done
before actual data analysis. These preliminary analyses included treatment of missing
data and data cleanup, testing normality of the data collected for this research and any
issues of outliers in the data. Section 4.3.1 discusses various steps taken to deal with the
issue of missing data and cleaning up. Further, section 4.3.2 presents the details on the
normality and the issues of outliers in the data.
4.3.1 Missing Values and Data Cleaning Up
Missing data is the most widespread and frequent problem faced by researchers in data
analysis (Tabachnick & Fidell, 2007). According to Hair, et al., (2010), if upto 10 % of
missing data is there in case of an individual item or observation, it can be ignored. In
current research, no variables had more than 2 % missing values highlighting that missing
values was not an issue in this study. Moreover, Tabachnick and Fidell, (2007) suggested
that mean scores could be used to substitute the missing values in the data if the
proportion of these values is very small. Therefore, mean scores were put in only for
missing information. This mean imputation for missing value was done in SPSS by using
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―Replace with mean‖ option which filled the missing value cell with the average score of
the variable (Hair, et al., 2010; Pallant, 2011).
On next stage, data were also examined for having any odd pattern of responses. There
are chances of response set bias if participants do not read the statements properly and
therefore, answer every question on a same pattern. Nunnally and Bernstein, (1994)
suggested including few reverse coded or negatively worded questions in the survey to
ensure that the respondents have filled the survey by reading the items in order to
eliminate response set bias. While entering data for analysis, two such branch managers‘
and 23 front line employee filled questionnaires were eliminated where they responded
on the same score for almost all the responses including the reverse coded items. Further,
two more cases were deleted from data because both the surveys were filled by
respondents who were internee and have not spent even two months in the branches.
However, 323 branch level and 1369 employee level responses were taken up for data
analysis finally.
4.3.2 Normality and Outliers
Normality of continuous variables is another critical issue in multivariate data analysis.
Statistical inferences turn out to be less robust if the distributions are away from normal
(Mellahi & Budhwar, 2010). Skewness and kurtosis of each variable were assessed to
check the normality of the variables of this study. The scores on skewness and kurtosis
for all the variables are given in Table 4.3. According to Kline (2005), a value outside the
range of -2.0 and +2.0 for skewness and a value greater than 10.0 for kurtosis reflect a
violation of normal distribution. As can be seen in Table 4.3, no value for skewness is
greater than the cutoff value of 3.0 and no kurtosis value is greater than the benchmark
value of 10.0. Further, histograms were also observed for assessing normal distribution
and no non-normal distribution was found. These findings showed that normality of data
was not an issue in this study. Moreover, data was also examined for the possibilities of
outliers and no outliers were found.
105
Table 4.3: Skewness and Kurtosis Values of Variables
Variables Skewness Kurtosis
Statistics Std Error Statistics Std Error
Manager-HPWS -.75 .14 .49 .27
Collective Human Capital -.93 .14 1.95 .27
Branch Performance -.75 .14 1.57 .27
Distributive Justice -.63 .07 .14 .13
Procedural Justice -.70 .07 .89 .13
Interactional Justice -.77 .07 .79 .13
Employee Engagement -.62 .07 .93 .13
Service Performance -.71 .07 .97 .13
Service Oriented OCB -.65 .07 .76 .13
4.4 Individual Items Descriptive Analysis
This section presents a description of the responses on various items of the variables used
in this study. In case of branch level variables including manager-HPWS, collective
human capital and branch performance, a summary of 323 responses given by branch
managers is presented in section 4.4.1. Further, in case of individual employee level
variables (distributive justice, procedural justice, interactional justice, employee
engagement, service performance and service oriented OCB), a description of 1369
responses by front line employees is also presented in section 4.4.2.
4.4.1 Item Wise Descriptive Analysis: Branch Level
This section presents a descriptive analysis of branch level variables and their individual
measurement items. Branch level variables include manager-HPWS, collective human
capital and branch performance. A summary of 323 responses by branch managers on
branch level variables is presented in this section.
106
4.4.1.1 Manager-HPWS
Table 4.4 illustrates the breakdown of responses by branch managers on each item for all
eight dimensions of HPWS implemented in their respective bank branch. These
dimensions of manager-HPWS included extensive service training, information sharing,
interdepartmental services, teamworking and participation, service discretion, pay
contingent with service quality, job design and service quality based performance
appraisals respectively. Branch managers were requested to report the extent to which
each of the high performance practice was implemented in their respective bank branches
on a five-point Likert scale ranging from ―1 = strongly disagree‖ to ―5 = strongly agree‖.
The descriptive statistics for manager-HPWS variable items provided evidence for the
implementation of HPWS in the bank branches under study. Branch managers tended to
report a score above the mid-point on a five-point scale for the indicators of HPWS. On
average, the overall score for HPWS reported by branch manager was 3.92. Further,
average scores for the eight dimensions of manager-HPWS were: 4.16 for extensive
service training, 3.99 for information sharing, 4.10 for interdepartmental services, 4.00
for teamworking and participation, 3.74 for service discretion, 3.49 for pay contingent
with service quality, 3.73 for job design and 3.92 for service quality based performance
appraisals. A higher mean score for an item indicated strong agreement of the branch
managers with the statement and vice versa.
As given in Table 4.4, most of the manager-HPWS statements averaged above 3.5 on a
scale ranging from 1 to 5 indicating a high level of HPWS implementation in bank
branches. For example, ―The formal orientation programs to new employees are helpful
for them to perform their jobs‖ (EST_1) showed the highest mean score (4.43) of all the
items used to measure HPWS implemented in the bank branches. The second highest
mean score (4.20) was found for ―Employees have the manuals and individual computers
they need for the network systems they work with‖ (IS_7), an indicator of information
sharing dimension of HPWS. The lowest mean score were found for two items including
―This branch pays above market wages to employees‖ (PSP_1) and ―Employees‘ pay is
tied to the quality of service they provide‖ (PSP_3). The scores for these two indicators
were 3.38 and 3.46, respectively. Both of these were the indicators of pay based upon
107
service quality. These findings indicated that employees‘ compensation relative to other
banks and its link with employee‘s service performance were less evident than other 35
HPWS measurement items. In addition, only these two indicators had a mean score
below 3.5. All other indicators of manager-HPWS except these two had a mean score
above 3.5.
Table 4.4: Descriptive Statistics for Manager-HPWS Items
Sr. No. HPWS Measurement Mean Standard
Deviation
Manager-HPWS 3.92 .50
Extensive Service Training 4.16 .55
EST_1 ―The formal orientation programs to new employees are
helpful for them to perform their jobs‖ 4.43 .67
EST_2
―Training programs other than corporate-wide orientation
program are effective in teaching employees the skills
they need in serving customers‖
4.18 .81
EST_3 ―Our training programs effectively prepare employees to
provide high quality customer service‖ 4.17 .80
EST_4 ―Employees will normally go through training programs
to improve their customer service skills every few years‖ 4.10 .76
EST_5 ―Employees are adequately trained to handle the
introduction of new products and services‖ 3.99 .87
EST_6 ―This branch assists employees to join the customer
service training program provided by the headquarters‖ 4.09 .83
Information Sharing 3.99 .60
IS_1 ―The findings from employee surveys are communicated
to employees of this branch‖ 3.67 1.03
IS_2 ―The findings from customer surveys are communicated
to employees of this branch‖ 3.80 1.03
IS_3 ―All business memos of this branch are shared with
employees‖ 3.78 .98
IS_4 ―Customers‘ suggestions for how to improve service
quality are shared with employees‖ 4.09 .87
IS_5 ―Information about how well the branch is performing
financially is shared with employees‖ 4.07 .91
IS_6
―Complaints or negative comments about this branch‘s
service from external customers are shared with
employees‖
4.18 .85
IS_7 ―Employees have the manuals and individual computers
they need for the network systems they work with‖ 4.20 .89
108
Sr. No. HPWS Measurement Mean Standard
Deviation
IS_8 ―Employees have, or have access to, the product and
policy information they need to do their work‖ 4.15 .91
Interdepartmental Services 4.10 .70
IDS_1 ―Departments of this branch cooperate well with each
other‖ 4.17 .79
IDS_2
―In this branch, employees in one department get the
needed materials from other departments in a timely
fashion‖
4.02 .82
Service Teams and Participation 4.00 .59
STP_1 ―The development of work teams among employees is an
important element of this branch‘s strategy‖ 4.18 .75
STP_2 ―This branch supports team development and training for
employees‖ 4.11 .82
STP_3 ―This branch asks employees for their suggestions on
how to improve customer service‖ 4.08 .82
STP_4 ―Employees‘ suggestions on customer service are
implemented in full or in part within this branch‖ 3.83 .81
STP_5 ―Decision-making by employees is encouraged in this
branch‖ 3.81 .92
Service Discretion 3.74 .67
SD_1 ―Employees have the authority to resolve customer
complaints on their own‖ 3.68 .99
SD_2 ―Employees have the discretion to customize the service
offering to meet customer needs‖ 3.64 .96
SD_3 ―Employees may decide how to personalize the service
for the customer‖ 3.61 .96
SD_4 ―Employees may use a wide variety of strategies to
satisfy the customer‖ 3.78 .91
SD_5 ―Employees are encouraged to adapt their behaviors to
the needs of the customer‖ 4.00 .85
Compensation Contingent to Service Performance 3.49 .86
PSP_1 ―This branch pays above market wages to employees‖ 3.38 1.11
PSP_2
―The way in which employees in this branch are
compensated encourages them to adopt a long-term
focus‖
3.62 .96
PSP_3 ―Employees‘ pay is tied to the quality of service they
provide‖ 3.46 1.10
Job Design for Quality Work 3.73 .74
109
Sr. No. HPWS Measurement Mean Standard
Deviation
JDQ_1 ―Fostering involvement in decision-making of employees
is an important element of the corporate strategy‖ 3.70 .95
JDQ_2 ―Many employees in this branch perform simple and
repetitive tasks as part of their work‖ 3.74 .94
JDQ_3
―Providing employees with high quality jobs (i.e., jobs
that are challenging, fulfilling, etc.) is a priority in this
branch‖
3.78 .92
JDQ_4 ―Employees of this branch are given lots of opportunity
to decide how to do their work‖ 3.69 1.01
Service Performance Based Performance Appraisals 3.92 .70
SPA_1
―Employees‘ courteous (well-mannered) service to
customers is considered for employee‘s performance
appraisal in this branch‖
3.98 .91
SPA_2
―The ability of the employees to resolve customer
complaints or service problems in an efficient manner is
considered for their performance appraisal in this
branch‖
3.94 .87
SPA_3
―The ability of the employees to innovatively deal with
unique situations and/or meet customer needs is
considered for their performance appraisal in this
branch‖
3.84 .85
SPA_4 ―Employees‘ commitment to customers is considered for
their performance appraisal in this branch‖ 3.92 .81
Further, the dispersions of branch managers‘ ratings from the average scores for
manager-HPWS were quite similar. For instance, the lowest standard deviation was
found in EST_1 i.e. ―formal orientation programs to new employees are helpful for them
to perform their jobs‖ of extensive trainings dimension. Therefore, branch managers were
mostly in agreement about the usefulness of orientation programs for new comers in the
bank branches to start their work. Contrary to this, the highest score of dispersion were
found in PSP_1 i.e. ―branch pays above market rate to employees‖ and PSP_3
―employees‘ pay is tied to service quality‖ (SD = 1.10). These finding indicated a higher
level of disagreement amongst branch manager‘s responses on these items compared to
the other indicators of manager-HPWS.
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4.4.1.2 Collective Human Capital
The descriptive statistics results for individual items of branch level collective human
capital can be seen in Table 4.5. Branch managers were asked to report overall human
capital level of their respective bank branches on a five-point Likert scale ranging from
―1 = strongly disagree‖ to ―5 = strongly agree‖. On average, the overall score of branch
level collective human capital reported by the branch managers was 3.89. Further, the
average score of all the indicators of collective human capital was above 3.75 indicating
agreement amongst branch managers regarding collective human capital indicators. A
higher mean score for an item of collective human capital indicated strong agreement of
the branch manager with the statement and vice versa.
As shown in Table 4.5, ―Our employees working in this branch are experts in their
particular jobs and functions‖ (HC_4) showed the highest mean score (4.00) of all the
items used to measure collective human capital of bank branches. The lowest mean score
(3.79) was found for ―Our employees working in this branch develop new ideas and
knowledge‖ (HC_5). These findings indicated that employees‘ contribution through new
ideas and knowledge was less evident than other indicators of collective human capital.
Moreover, all indicators of branch level collective human capital had a mean score above
3.75.
Table 4.5: Descriptive Statistics for Branch Level Collective Human Capital Items
Sr. No. Variables and Items Mean Standard
Deviation
Branch Level Collective Human Capital 3.89 .67
HC_1 ―Our employees working in this branch are highly
skilled in serving customers‖ 3.94 .85
HC_2 ―Our employees working in this branch are widely
considered to be the best in our industry‖ 3.83 .86
HC_3 ―Our employees working in this branch are creative
and bright‖ 3.89 .86
HC_4 ―Our employees working in this branch are experts in
their particular jobs and functions‖ 4.00 .84
HC_5 ―Our employees working in this branch develop new
ideas and knowledge‖ 3.79 .90
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Branch managers‘ ratings dispersions from the average scores for branch level collective
human capital were quite similar too. For instance, the lowest standard deviation was
found for indicator HC_4 i.e. ―employees working in this branch are experts in their
particular jobs and functions‖. Thus, branch managers were mostly in agreement about
the ―expertise of employees in their jobs and functions/ area‖. Contrary to this, the
highest score of dispersion was found in HC_5: ―employees working in this branch
develop new ideas and knowledge‖ revealing a higher level of disagreement amongst
branch managers‘ responses compared to the other indicators of collective human capital.
4.4.1.3 Bank Branch Performance
The descriptive statistics for individual items of branch performance is presented in Table
4.6. Branch managers were requested to report relative performance of their bank
branches in comparison with the nearby bank branches on a relative five-point Likert
scale ranging from ―1 = much worst‖ to ―5 = much better‖. This comparison was based
upon four performance dimensions including ―marketing performance‖, ―growth in
sales‖, ―profitability‖ and ―market share‖. On average, the overall score of branch
performance reported by the branch managers was 4.06. Further, the average score of all
the indicators of branch performance was above 3.90 indicating better performance rated
by branch managers while comparing their branch performance with other competing
bank branches in the area.
Table 4.6: Descriptive Statistics for Branch Performance Items
Sr. No. Variables and Items Mean Standard
Deviation
Branch Performance 4.06 .59
BP_1 ―Marketing performance‖ 4.16 .73
BP_2 ―Growth in sales‖ 4.04 .77
BP_3 ―Profitability‖ 4.10 .78
BP_4 ―Market share‖ 3.94 .76
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As can be seen in Table 4.6, ―Marketing performance‖ (BP_1) showed the highest mean
score (4.16) of all the items used to measure bank branch performance. The lowest mean
score (3.94) was found for ―Market share‖ (BP_4). Moreover, all indicators of branch
performance had a mean score above 3.90. Branch manager‘s ratings dispersions from
the average scores for bank branch performance were quite similar. For instance, the
lowest standard deviation was in indicator BP_1 i.e. ―Market performance‖. On the other
hand, the highest score of dispersion were in BP_3 i.e. ―profitability‖ of bank branch.
4.4.2 Item Wise Descriptive Analysis: Individual Level
This section presents a descriptive analysis of employee level variables and their
individual measurement items. Employee level variables include distributive justice,
procedural justice, interactional justice and employee outcomes (i.e. employee
engagement, employee service performance and service oriented OCB). A summary of
these employee level variables based upon the responses by 1369 front-line employees is
presented in this section.
4.4.2.1 Distributive Justice
Table 4.7 illustrates the breakdown of responses by front-line employees on each item of
distributive justice. These perceptions of front-line employees were measured by using
items given in Table 4.7. They were required to give their response for each indicator on
a five-point Likert scale ranging from ―1 = strongly disagree‖ to ―5 = strongly agree‖.
The descriptive statistics for distributive justice perceptions indicated a higher agreement
regarding the existence of distributive justice perceptions among the front-line employees
participated in this study. Front-line employees tended to report a score above the mid-
point on a five-point scale for the indicators of distributive justice. On average, the
overall score of distributive justice reported by front-line employees was 3.65. Further,
the average of all the items of distributive justice perceptions was above 3.45 indicating
agreement amongst front line employees regarding distributive justice indicators. A
higher mean score for an item of distributive justice indicated strong agreement of front-
line employee with the statement and vice versa.
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As shown in Table 4.7, ―My work schedule is fair‖ (DJ_1) showed the highest mean
score (3.87) of all the items used to measure distributive justice perceptions of front line
employees. Two indicators of distributive justice have a mean score slightly less than 3.5.
The mean score for both indicators of distributive justice i.e. ―I think that my level of pay
is fair‖ (DJ_2) and ―Overall, the rewards I receive here are quite fair‖ (DJ_4) were 3.49.
These findings indicated that employees‘ agreement on these indicators of distributive
justices was low compared to other indicators of this construct.
Table 4.7: Descriptive Statistics for Distributive Justice Items
Sr. No. Variables and Items Mean Standard
Deviation
Distributive Justice 3.65 .85
DJ_1 ―My work schedule is fair‖ 3.87 1.09
DJ_2 ―I think that my level of pay is fair‖ 3.49 1.13
DJ_3 ―I consider my work load to be quite fair‖ 3.59 1.08
DJ_4 ―Overall, the rewards I receive here are quite fair‖ 3.49 1.11
DJ_5 ―I feel that my job responsibilities are fair‖ 3.82 .94
Front-line employees‘ ratings dispersions from the average scores for distributive justice
perceptions were a bit different. For instance, the lowest standard deviation was found in
indicator DJ_5 i.e. ―I feel that my job responsibilities are fair‖. Thus, front-line
employees were mostly in agreement about the ―fairness in job responsibilities‖. Contrary
to this, the highest score of dispersion was found in DJ_2: ―I think that my level of pay is
fair‖ indicating a higher level of disagreement amongst employees‘ responses compared
to the other indicators of distributive justice.
4.4.2.2 Procedural Justice
Table 4.8 illustrates the breakdown of responses by front-line employees on each item of
procedural justice. Procedural justice perceptions of front-line employees were gauged by
using the items given in Table 4.8. They were asked to give their response for each
indicator of procedural justice on a five-point Likert scale ranging from ―1 = strongly
disagree‖ to ―5 = strongly agree‖.
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The descriptive statistics for procedural justice measures indicated a higher level of
agreement regarding the existence of procedural justice perceptions among front-line
employees participated in this study. Front-line employees tended to report a score above
the mid-point on a five-point scale for the indicators of procedural justice. On average,
the overall score of procedural justice rated by front-line employees was 3.76. Further,
the mean score of all the items of procedural justice was above 3.50 indicating agreement
amongst front line employees regarding procedural justice indicators. Mean score of
procedural justice (3.76) was greater compared to the mean score of distributive justice
(3.65) indicating that employees‘ agreement about procedural justice perceptions was
stronger than their perceptions regarding distributive justice. A higher mean score for an
item of procedural justice indicated strong agreement of front-line employee with the
statement and vice versa.
Table 4.8: Descriptive Statistics for Procedural Justice Items
Sr. No. Variables and Items Mean Standard
Deviation
Procedural Justice 3.76 .71
PJ_1 ―Job decisions are made by the branch manager in an
unbiased manner‖ 3.64 1.09
PJ_2 ―My branch manager makes sure that all employee
concerns are heard before job decisions are made‖ 3.79 .95
PJ_3 ―To make job decisions, my branch manager collects
accurate and complete information‖ 3.86 .97
PJ_4 ―My branch manager clarifies decisions and provides
additional information when requested by employees‖ 3.91 .94
PJ_5 ―All job decisions are applied consistently across all
affected employees‖ 3.79 .90
PJ_6 ―Employees are allowed to challenge or appeal job
decisions made by the branch manager‖ 3.58 1.06
As shown in Table 4.8, ―My branch manager clarifies decisions and provides additional
information when requested by employees‖ (PJ_4) showed the highest mean score (3.91)
of all the items used to measure procedural justice perceptions of front-line employees.
The lowest mean score (3.58) was found for ―Employees are allowed to challenge or
appeal job decisions made by the branch manager‖ (PJ_6). These findings indicated that
employees‘ perceptions about the ―right to challenge or appeal job decisions made by
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branch manager‖ were least evident than other indicators of procedural justice. Moreover,
all indicators of procedural justice perceptions had a mean score above 3.50.
Moreover, front-line employees‘ ratings dispersions from the average scores for
procedural justice perceptions were not much different. For instance, the lowest standard
deviation was found in PJ_4 i.e. ―Branch manager clarifies decisions and provides
additional information when requested by employees‖, thus, front-line employees were
mostly in agreement about this indicator of procedural justice. Furthermore, the highest
score of dispersion was found in PJ_1: ―job decisions are made by branch manager in an
unbiased manner‖ indicating a higher level of disagreement amongst employees‘
responses for this indicator compared to the other indicators of procedural justice.
4.4.2.3 Interactional Justice
Table 4.9 presents the breakdown of responses by front-line employees on each item of
interactional justice. Interactional justice perceptions of front-line employees were
measured by using the items given in Table 4.9. They were asked to give their response
for each indicator on a five-point Likert scale ranging from ―1 = strongly disagree‖ to ―5
= strongly agree‖.
The descriptive statistics for interactional justice measures indicated a higher degree of
agreement regarding the interactional justice perceptions prevailing among front-line
employees under study. Front line employees tended to report a score above the mid-
point on a five-point scale for the indicators of interactional justice. On average, the
overall score of interactional justice reported by front-line employees was 3.82. Further,
the average score of all the indicators was above 3.70 indicating agreement amongst front
line employees regarding interactional justice indicators. Mean score of interactional
justice (3.82) was greater than procedural justice score (3.76) and also than the mean
score of distributive justice (3.65) indicating that employees‘ agreement about existence
of interactional justice was stronger than their perceptions regarding distributive justice
or procedural justice. A higher mean score for an item of interactional justice indicated
strong agreement of front-line employee with the statement and vice versa.
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As can be seen in Table 4.9, ―When decisions are made about my job, branch manager
treats me with respect and dignity‖ (IJ_2) showed the highest mean score (3.91) of all the
items used to measure interactional justice perceptions. The lowest mean score (3.72) was
found for ―When decisions are made about my job, the branch manager is sensitive to my
personal needs‖ (IJ_3). These findings indicated that employees‘ perceptions about the
―branch managers‘ sensitivity for employees‘ personal needs when making decisions
about their jobs‖ was less evident than other indicators of interactional justice. Moreover,
all indicators of interactional justice perceptions had a mean score above 3.70.
Table 4.9: Descriptive Statistics for Interactional Justice Items
Sr. No. Variables and Items Mean Standard
Deviation
Interactional Justice 3.82 .71
IJ_1 ―When decisions are made about my job. The branch
manager treats me with kindness and consideration‖ 3.87 .93
IJ_2 ―When decisions are made about my job. The branch
manager treats me with respect and dignity‖ 3.91 .93
IJ_3 ―When decisions are made about my job, the branch
manager is sensitive to my personal needs‖ 3.72 .99
IJ_4 ―When decisions are made about my job, the branch
manager deals with me in a truthful manner‖ 3.87 .96
IJ_5
―When decisions are made about my job, the branch
manager shows concern for my rights as an
employee‖
3.81 .97
IJ_6
―Concerning decisions made about my job. The
branch manager discusses the implications of the
decisions with me‖
3.77 .96
IJ_7 ―The branch manager offers adequate justification for
decisions made about my job‖ 3.79 .93
IJ_8 ―When making decisions about my job. The branch
manager offers explanations that make sense to me‖ 3.76 .94
IJ_9 ―My branch manager explains very clearly any
decision made about my job‖ 3.85 .97
Moreover, front-line employees‘ ratings dispersions from the average scores for
interactional justice indicators were not much different. Standard deviation scores for all
nine indicators of interactional justice ranged within .93 to .99 indicating a similar level
of agreement amongst employees‘ responses for all the indicators of interactional justice
perceptions.
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4.4.2.4 Employee Engagement
Table 4.10 illustrates the breakdown of responses by front-line employees on each item
of employee engagement used in this study. Engagement level of front-line employees
was accessed through the items given in Table 4.10. They were asked to give their
response for each indicator on a five-point Likert scale ranging from ―1 = strongly
disagree‖ to ―5 = strongly agree‖.
Table 4.10: Descriptive Statistics for Employee Engagement Items
Sr. No. Variables and Items Mean Standard
Deviation
Employee Engagement 3.87 .58
EE_1 ―At my work, I feel that I am full of energy‖ 4.08 .89
EE_2 ―I find the work that I do full of meaning and purpose‖ 3.96 .86
EE_3 ―Time flies when I am working‖ 3.99 .87
EE_4 ―At my job, I feel strong and energetic‖ 3.95 .91
EE_5 ―I am passionate about my job‖ 3.93 .93
EE_6 ―When I am working, I forget everything else around
me‖ 3.76 1.04
EE_7 ―My job inspires me‖ 3.77 .97
EE_8 ―When I get up in the morning, I feel like going to work‖ 3.79 .99
EE_9 ―I feel happy when I am working intensely‖ 3.88 .93
EE_10 ―I am proud of the work that I do‖ 3.88 .95
EE_11 ―At my work, I feel deeply involved in my work‖ 3.94 .88
EE_12 ―I can continue working for very long periods at a time‖ 3.84 .95
EE_13 ―To me, my job is challenging‖ 3.87 .94
EE_14 ―I get carried away (forget everything else) when I am
working‖ 3.78 .95
EE_15 ―At my job, I am very resilient (ability to come back in
crisis), mentally‖ 3.81 .91
EE_16 ―It is difficult to detach (disconnect) myself from my
job‖ 3.71 .95
EE_17 ―At my work, I am always consistent, even when things
do not go well‖ 3.84 .88
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The descriptive statistics for employee engagement measures indicated a higher level of
agreement regarding employee engagement among the employees participated in the
study. Front-line employees tended to report a score above the mid-point on a five-point
scale for the indicators of employee engagement. On average, the overall score of
employee engagement by front-line employees was found 3.87. Further, the average
score of all the indicators was above 3.70 indicating agreement amongst front-line
employees regarding employee engagement indicators. As shown in Table 4.10, ―At my
work, I feel that I am full of energy‖ (EE_1) showed highest mean score (4.08) of all the
items used to measure engagement level of front-line employees. The lowest mean score
(3.71) was found for ―It is difficult to detach (disconnect) myself from my job‖ (EE_16).
Front-line employees‘ ratings dispersions from the average scores for employee outcomes
were not much similar. For instance, in case of employee engagement, the lowest
standard deviation was found in indicator EE_2 i.e. ―I find the work that I do full of
meaning and purpose.‖, thus, front line employees were mostly in agreement about this
indicator of employee engagement. Contrary to this, the highest score of dispersion was
found in EE_6: ―When I am working, I forget everything else around me‖ indicating a
higher level of disagreement amongst employees‘ responses for this indicator compared
to the other indicators of employee engagement.
4.4.2.5 Employee Service Performance
Table 4.11 exhibits the breakdown of responses by front-line employees on each item of
service performance behavior. Service performance of front-line employees was
measured by using the items given in Table 4.11. They were asked to give their response
for each indicator on a five-point Likert scale ranging from ―1 = strongly disagree‖ to ―5
= strongly agree‖.
In case of employee service performance, descriptive statistics for measures indicated a
higher level of agreement regarding service performance among the employees
participated in this study. Front-line employees tended to choose a score above the mid-
point on a five-point scale for the indicators of service performance. On average, the
overall score of service performance reported by front-line employees was 4.00. Further,
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the average score of all the indicators of service performance was above 3.85 indicating a
high level of agreement amongst front-line employees regarding service performance
indicators. Further, ―I am friendly and helpful to customers‖ (ESP_1) showed the highest
mean score (4.07) of all the items used to measure service performance of front-line
employees. In addition to this, the lowest mean score (3.87) was found for two indicators
of service performance including ―I suggest items customers might like but did not think
of‖ (ESP_6) and ―I explain an item‘s features and benefits to overcome a customer‘s
objections‖ (ESP_7).
Table 4.11: Descriptive Statistics for Employee Service Performance Items
Sr. No. Variables and Items Mean Standard
Deviation
Employee Service Performance 4.00 .65
ESP_1 ―I am friendly and helpful to customers‖ 4.07 .86
ESP_2 ―I always try to approach customers quickly‖ 4.03 .86
ESP_3 ―I ask good questions and listening to find out what a
customer wants‖ 4.02 .86
ESP_4 ―I am always willing to help customers when needed‖ 4.05 .86
ESP_5 ―I point out and relating item features to a customer‘s
needs‖ 4.00 .86
ESP_6 ―I suggest items customers might like but did not think
of‖ 3.87 .88
ESP_7 ―I explain an item‘s features and benefits to overcome a
customer‘s objections‖ 3.87 .83
Further, in case of service performance, the dispersions of employees‘ responses from
mean score for all seven indicators of the construct were not much different. All values of
standard deviation for service performance indicators were within the range of .83 and
.86 with five indicators had a standard deviation value of .86.
4.4.2.6 Employee Service Oriented OCB
Table 4.12 portrays the breakdown of responses by front-line employees on each item of
service related discretionary behavior. Service related OCB of front-line employees was
measured by using the items given in Table 4.12. They were asked to give their response
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for each indicator on a five-point Likert scale ranging from ―1 = strongly disagree‖ to ―5
= strongly agree‖.
Table 4.12 Descriptive Statistics for Employee Service Related OCB Items
Sr. No. Variables and Items Mean Standard
Deviation
Employee Service Oriented OCB 3.98 .59
SOCB_1 ―I often tell outsiders this is a good place to work‖ 3.84 .95
SOCB_2 ―I say good things about the branch to others‖ 3.92 .91
SOCB_3 ―I Generate favorable goodwill for the branch‖ 3.99 .86
SOCB_4 ―I encourage friends and family to use the branch‘s
products and services‖ 3.99 .90
SOCB_5 ―I actively promote the branch‘s products and
services‖ 4.02 .86
SOCB_6 ―I Follow customer service guidelines with extreme
care‖ 4.03 .86
SOCB_7 ―I conscientiously follow guidelines for customer
promotion‖ 3.99 .86
SOCB_8 ―I follow up in a timely manner to customer requests
and problems‖ 4.02 .81
SOCB_9 ―I perform duties with unusually few mistakes‖ 3.76 .96
SOCB_10 ―I always have a positive attitude at work‖ 4.09 .81
SOCB_11 ―Regardless of circumstances, I am exceptionally
courteous and respectful to customers‖ 4.03 .81
SOCB_12 ―I encourage my co-workers to contribute ideas and
suggestions for service improvement‖ 3.99 .88
SOCB_13 ―I contribute many ideas for customer promotions and
communications‖ 3.95 .89
SOCB_14 ―I make constructive suggestions for service
improvement‖ 3.94 .85
SOCB_15 ―I frequently present others creative solutions to
customer problems‖ 3.91 .84
SOCB_16 ―I usually take home brochures to read up on products
and services‖ 3.64 1.04
In case of employees‘ service oriented OCB, descriptive statistics for 16 items of the
construct indicated a higher level of agreement regarding service oriented OCB indicators
among front-line employees participated in this study. Front-line employees reported a
score above the mid-point on a five-point scale for the indicators of service oriented
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OCB. On average, the overall score of service related OCB reported by front-line
employees was 3.98. Further, the average score of all the indicators of service oriented
OCB was found above 3.60 indicating a high level of agreement amongst front line
employees regarding service oriented OCB indicators.
Last, in case of service oriented OCB, ―I always have a positive attitude at work‖
(SOCB_10) showed the highest mean (4.09) and the lowest mean (3.64) was found for ―I
usually take home brochures to read up on products and services‖ (SOCB_16). In the last,
three indicators of service oriented OCB (SOCB_8, SOCB_10, SOCB_11) showed the
lowest dispersion value i.e. .81. Whereas, ―I usually take home brochures to read up on
products and services‖ (SOCB_16) reflected the highest value of dispersion amongst all
the indicators of service oriented OCB.
4.5 Confirmatory Factor Analysis (CFA)
This section illustrates confirmatory factor analysis (CFA) conducted to ensure the
validity of instruments used to measure the variables of the study. Due to multilevel
nature of the study, branch level measurement model (Section 4.5.1) and individual
employee level measurement model (Section 4.5.2) were separately analyzed.
Construct validity refers to the process by which a researcher infer the hypotheses from a
theory that is relevant to the concept. The construct validity of the measures is required to
be gauged by its convergent and discriminant validity (Hair, et al., 2010) before
hypotheses testing. Researchers have used CFA to assess convergent and discriminant
validity of already established measures (e.g. Alfes, et al., 2013; Pak & Kim, 2016). In
other words, the CFA was carried out to measure convergent and discriminant validity of
the variable used in the study to establish their construct validity. Convergent validity
refers to the degree to which the elements of a variable show convergence or agreement.
Second, discriminant validity refers to whether the elements representing different
concepts actually captured the constructs distinct from each other as proposed in the
theory.
The objective of CFA was to confirm that the indicators had an appropriate fit within
their respective construct. Various indices of goodness-of-fit were considered to evaluate
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the measurement model fit as recommended by Tabachnick and Fidell (2007). These
indices included normed chi-square (χ2/d.f.) (Wheaton, et al., 1977), root mean square
error of approximation (RMSEA) (Browne et al., 1993) and root mean square residual
(RMR) (Kline, 2005), comparative fit index (CFI) (Bentler, 1990; Hu & Bentler, 1999),
incremental fit index (IFI) (Bollen, 1989), Tucker-Lewis Index (TLI) (Bentler & Bonett,
1980). A brief detail of the acceptable values of these model fit indices generated by CFA
is as follows and also summarized in the Table 4.13. First, the value of normed chi-square
(χ2/d.f.) should be less than 3 to represent good model fit (Browne & Cudeck, 1993; Hall,
Snell & Foust, 1999; Hu & Bentler, 1999; Kline, 2005). Further, a value of 0.90 or above
for incremental fit index (IFI), Tucker-Lewis index (TLI) and comparative fit index (CFI)
indicate a good model fit (Bentler, 1990; Kline, 2005). In the last, a value less than 0.08
for root mean square error of approximation (RMSEA) and standardized root mean
square residual (RMR) represents a good model fit (Browne & Cudeck, 1993; Hu &
Bentler, 1999). Further, factor loading score of individual items on their respective
construct generated by CFA was also considered and evaluated. According to
Schumacker & Lomax (2004) and Hair, et al. (2009), each element of a construct should
load onto its latent variable as proposed with a factor loading score of 0.50 or above.
Therefore, only those items which reflected a factor loading score of 0.50 or above were
considered for further data analysis.
Table 4.13: Model Fit Criteria
Model Fitness Indices Acceptable Values
Normed chi-square (χ2/d.f.) Less than 03
Incremental fit index (IFI) 0.9 and above
Tucker Lewis index (TLI) 0.9 and above
Comparative fit index (CFI) 0.9 and above
Root mean square error of approximation (RMSEA) Less than 0.08
Root mean square residual (RMR) Less than 0.08
Notes.χ2;Chi-square discrepancy, d.f.; Degrees of freedom.
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4.5.1 Branch Level Measurement Model (CFA)
As proposed in the theory, the manager-HPWS was accounted for as second order
construct where all the items were first loaded on their respective high performance work
practice and then these eight practices were further loaded onto the main construct i.e.
manager-HPWS. For instance, the first six items were loaded on the work practice called
extensive service training. Likewise, next eight items were loaded on the construct they
represented i.e. information sharing and so on. After this, all the eight work practices
were further loaded onto the latent variable called manager-HPWS. All other variables at
branch level of analysis (collective human capital and branch performance) were taken as
first order construct as proposed in the theory.
For proposed three-factor branch level measurement model, the values of goodness of fit
are presented in Table 4.14. These results demonstrated a good model fit as all the model
fitness indices scores were above cutoff values criteria as given in Table 4.12. The value
of TLI (.89) was slightly below the required value of 0.90. Overall, the goodness-of-fit
indices of the branch level measurement model showed a good model fit.
Further, the factor loadings for the individual items towards their respective branch level
variable were also assessed as per the criteria of factor loading score of 0.50 or above
(Schumacker & Lomax, 2004; Hair, et al., 2009). In case of manager-HPWS, all the
items, except one (―All business memos of this branch are shared with employees‖ IS_3)
from the information sharing dimension of manager-HPWS, showed a factor loading
score above 0.50. This indicator of information sharing had a factor loading score of 0.47,
slightly below the criteria and therefore discarded and did not used for further data
analysis. Further, in the case of second order construct, all eight high performance work
practices also met factor loading criteria of 0.5 or above with a factor loading score
ranging from 0.67 to 0.90.
Further, all five items used to measure branch level collective human capital
demonstrated a factor loading score well above the cutoff value of 0.50. The lowest factor
loading score by any of the collective human capital item was 0.67. In the last, all four
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indicators of bank branch performance also showed a factor loading score above 0.50
with lowest factor loading score of 0.61.
In the second stage, a series of competing measurement models was conducted to
compare the three-factor hypothesized model with the alternative ones. The CFA results
indicated that the three factor hypothesized measurement model which included manager-
HPWS, branch level collective human capital and bank branch performance showed
better model fit (χ2 = 1521.34, d.f. = 921, χ
2/d.f. = 1.65 p < .05, IFI = .91, TLI = .89, CFI
= .90, RMSEA = .049, RMR = .045) compared to the alternative models where the
elements of different constructs were considered to load together as a single variable. For
instance, compared to proposed three-factor model, another two factor model where
items of collective human capital and branch performance were considered to load as
single variable showed a bad model fit (χ2 = 1791.23, d.f. = 923, χ
2/d.f. = 1.94 p < .05, IFI
= .85, TLI = .84, CFI = .85, RMSEA = .054, RMR = .051). Similarly, a one factor
measurement model in which all the indicators were loaded on single construct fit the
data even worst (χ2 = 1892.73, d.f. = 924, χ
2/d.f. = 2.05 p < .05, IFI = .84, TLI = .82 CFI
= .84, RMSEA = .054, RMR = .057). A summary of the model fitness indices for three-
factor proposed model and the alternative models is presented in Table 4.14. These
findings from CFA provided empirical evidence for the construct validity of the
constructs used to measure manager-HPWS, collective human capital and branch
performance as branch level variables.
Table 4.14: Measurement Models Comparisons (Branch Level)
Models χ2/d.f. IFI TLI CFI RMSEA RMR
Proposed Three-Factor
Model 1.65 .91 .89 .90 .049 .045
Two-Factor Modela 1.94 .85 .84 .85 .054 .051
One-Factor Modelb 2.05 .84 .82 .84 .054 .057
Notes.χ2;Chi-square discrepancy, df; Degrees of freedom, IFI; Incremental fit index, TLI; Tucker–Lewis
index, CFI; Comparative fit index, RMSEA; Root mean square error of approximation. a Collective human capital and branch performance combined into single factor,
b all variables combined into single factor.
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4.5.2 Individual Employee Level Measurement Model (CFA)
For Employee level data, all the variables were taken as first order constructs as proposed
in the study. The results of goodness-of-fit indices for individual level measurement
model as generated by CFA are demonstrated in Table 4.15. These results showed a good
model fit for six factor proposed measurement model where all the fitness indices were
satisfying the model fitness criteria as given in Table 4.13. Overall, the six factor
measurement model showed good psychometric properties of the measures employed to
gauge individual level variables (see Table 4.15).
Further, the factor loadings for the individual items towards their respective variable were
also assessed as per the criteria of factor loading score of 0.50 or above (Schumacker &
Lomax, 2004; Hair, et al., 2009). The findings illustrated that all the items loaded onto
their respective latent variable with a factor loading score of 0.5 or above. Only two items
of service oriented OCB out of 16 did not load onto the latent variable well. First ―I
perform duties with unusually few mistakes‖ (SOCB_9) showed a factor loading score of
0.38. Whereas, the second item of service oriented OCB i.e. ―I usually take home
brochures to read up on products and services‖ (SOCB_16) demonstrated a factor loading
score of 0.40 onto its latent variable and discarded from data and did not consider for
further data analysis. Overall, all six variables at individual level of analysis
demonstrated a good measurement model with factor loading scores above 0.5 except for
two items of service oriented OCB.
Further, a series of CFA was also conducted to generate and compare model fitness
indices of the proposed six factor measurement model with alternative measurement
models. First, a six-factor hypothesized measurement model was tested and compared it
with several alternative models. As can be seen in Table 4.15, model fitness indices for
proposed six-factor model showed that model fit the data well (χ2 = 4455.28, d.f. = 1562,
χ2/d.f. = 2.85 p < .05, IFI = .92, TLI = .92, CFI = .93, RMSEA = .037, RMR = .033)
compared to various alternative measurement models. For example, relative to proposed
model, a five factor measurement model where the items of employee engagement and
service performance were set to load on one construct showed poor model fit (χ2
=6173.74, d.f. =1567, χ2/d.f. = 3.94 p < .05, IFI = .88, TLI = .87, CFI = .86, RMSEA =
126
.046, RMR = .042). Further, in case of four factor model in which employee engagement,
service performance and service oriented OCB were considered as one construct, the data
showed a worst model fit (χ2 =6912.14, d.f. =1571, χ
2/d.f. = 4.40 p < .05, IFI = .86, TLI =
.85, CFI = .85, RMSEA = .050, RMR = .047). Next, while testing a three factor model
where the items of interactional justice, employee engagement, service performance and
service oriented OCB were loaded as a single construct, the data demonstrated even worst
model fit (χ2 = 10419.69, d.f. =1576, χ
2/d.f. =6.62 p < .05, IFI = .77, TLI = .75, CFI =
.77, RMSEA = .064, RMR = .066). Further, a two factor model in which the items of all
the variables except distributive justice were loaded on a single factor showed poor
model fit (χ2 =11532.17, d.f. =1576, χ
2/d.f. =7.32 p < .05, IFI = .74, TLI = .72, CFI = .74,
RMSEA = .068, RMR = .068). In the last, when only one factor was considered for CFA,
where all the items of six individual level variables were loaded on a single factor, the
model fitness became the worst (χ2 =12776.48, d.f. =1577, χ
2/d.f. =8.10 p < .05, IFI = .70,
TLI = .69, CFI = .70, RMSEA = .072, RMR = .072).
Table 4.15: Measurement Models Comparisons (Individual Level)
Models χ2/d.f. IFI TLI CFI RMSEA RMR
Proposed Six-Factor Model 2.85 .92 .92 .93 .037 .033
Five-Factor Modela 3.94 .88 .87 .88 .046 .042
Four-Factor Modelb 4.40 .86 .85 .85 .50 .047
Three-Factor Modelc 6.62 .77 .75 .77 .064 .066
Two-Factor Modeld 7.32 .74 .72 .74 .068 .068
One-Factor Modele 8.10 .70 .69 .70 .072 .072
Notes.χ2;Chi-square discrepancy, df; Degrees of freedom, IFI; Incremental fit index, TLI; Tucker–Lewis
index, CFI; Comparative fit index, RMSEA; Root mean square error of approximation. a Employee engagement and service performance combined into single factor,
b Employee engagement, service performance and service oriented OCB combined into single factor,
c Employee engagement, service performance, service oriented OCB and interactional justice combined
into single factor, d Employee engagement, service performance, service oriented OCB, interactional justice and procedural
justice combined into single factor, e all variables combined into single factor.
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A summary of the model fitness indices for six-factor proposed model and the alternative
models is presented in Table 4.15. These findings of CFA empirically confirmed
construct validity of the six constructs used at individual level of analysis.
Overall, the results of CFA reflected good psychometric properties of measures employed
to gauge the constructs used in this study. Only three items demonstrated a factor loading
score below 0.50 and therefore discarded from further analysis. In addition to this, the
hypothesized models demonstrated a good model fit compared to the alternative
measurement models. In sum, these findings confirmed the validity of measures used in
study and warrant the appropriateness of data for hypotheses testing.
4.6 Reliability of Variables
This section presents the reliability results of all the variables used in this study. This
study used Cronbach‘s alpha reliability measure to gauge the reliability of the variables
used in this study. According to Spector (1992), the Cronbach‘s alpha score should be
above 0.70 for a measurement scale to be reliable. However, according to Moss, et al.,
(1998), the value of 0.60 for reliability alpha (Cronbach‘s alpha) is also acceptable.
Reliability values for each construct of this study were calculated and are given in Table
4.16. The reliability alpha score for all the variables of the study ranged from .79 to .92
which well qualified the cutoff value of 0.70. Specifically, the reliability values of
manager-HPWS, collective human capital and bank branch performance were .92, .84
and .79, respectively. Further, Cronbach‘s alpha reliability scores for distributive justice,
procedural justice, interactional justice, employee engagement, service performance and
service oriented OCB were found .86, .81, .90, .90, .87 and .91 respectively.
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Table 4.16: Reliability Scores of the Variables
Sr. No. Variables and Items Cronbach‘s
Alpha
1 High Performance Work System .92
1.1 Employee Service Training .79
1.2 Information Sharing .79
1.3 Interdepartmental Services .66
1.4 Service Teams & Participation .77
1.5 Service Discretion .77
1.6 Compensation Contingent to Service Performance .77
1.7 Job Design for Quality Work .77
1.8 Service Performance Based Appraisals .83
2 Collective Human Capital .84
3 Bank Branch Performance .79
4 Distributive Justice .86
5 Procedural Justice .81
6 Interactional Justice .90
7 Employee Engagement .90
8 Employee Service Performance .87
9 Service Oriented OCB .91
In addition to this, Cronbach‘s alpha scores for each sub dimension of manager-HPWS
were also calculated separately to determine the degree to which the items of each
dimension shared common aspect. In case of sub dimensions of manager-HPWS, the
Cronbach‘s alphas ranged from .66 to .83. In specific, Cronbach‘s alpha value was .79 for
extensive service training, .79 for information sharing, .66 for interdepartmental services,
.77 for service teams and participation, .77 for service discretion, .77 for pay contingent
to service performance, .77 for job design and .83 for service based employee evaluation.
Of eight dimensions of manager-HPWS, only interdepartmental services had a reliability
score 0.66 which was slightly less than the cutoff value of 0.70 (Spector, 1992).
However, this also falls in the generally acceptable range of construct reliability i.e. 0.60
and above (Moss, et al., 1998). Therefore, reliability results showed that the reliability of
129
measures is not an issue in current study as all the constructs demonstrated a good
reliability score. Detail of the reliability values for each variable and also the dimensions
of manager-HPWS are illustrated in Table 4.16.
4.7 Means, Standard Deviations and Correlation Results
This section presents mean and standard deviation scores along with the correlation
between the variables of this study. In case of branch level of analysis, branch size
(number of employees), branch age (in years) and ownership type (Public = 0, Private =
1) were taken as control variables along with manager-HPWS, bank branch level human
capital and branch performance. In addition to this, distributive justice, procedural
justice, interactional justice, employee engagement, service performance and service
oriented OCB were the variables used at individual level of analysis. The control
variables used at individual level of analysis included employee gender (Female = 0,
Male = 1), age (in years) and tenure with current employer (in years). Descriptive
statistics (mean and standard deviation) and correlation results of branch level and
individual employee level of analysis are presented in Table 4.17 and Table 4.18,
respectively.
As can be seen in Table 4.17, branch size was significantly related only with bank branch
performance (r = .11, p < .05) indicating that bank branches with more number of
employees had better market performance compared to the branches with few employees.
Further, branch age was negatively related with both manager-HPWS (r = -.18, p < .01)
and branch human capital (r = -.15, p < .01). These findings were interesting as these
indicated that the level of implemented HPWS and human capital decreased as bank
branch became older and older. Moreover, manager-HPWS was related significantly with
bank branch human capital (r = .66, p < .01) and bank branch performance (r = .37, p <
.01). In the last, bank branch level collective human capital was also significantly linked
with bank branch performance (r = .34, p < .01).
Further, Table 4.18 illustrates the means, standard deviations and correlation results for
the variables conceptualized at individual level of analysis. In case of control variables
(employee gender, age and tenure with current bank), no control variable was found to be
130
significantly related with the key variables of the study. Further, distributive justice
perceptions of front-line employees were related significantly with procedural justice (r =
.54, p < .01), interactional justice (r = .45, p < .01), employee engagement (r = .45, p <
.01), service performance (r = .24, p < .01) and service oriented OCB (r = .31, p < .01).
Next, procedural justice perceptions of front-line employees were also found to be
significantly related with interactional justice (r = .74, p < .01), employee engagement (r
= .53, p < .01), service performance (r = .38, p < .01) and service oriented OCB (r = .45,
p < .01). Moreover, interactional justice perceptions of front-line employees were also
related significantly with employee engagement (r = .54, p < .01), service performance (r
= .41, p < .01) and service oriented OCB (r = .48, p < .01). Similarly, employee
engagement was also found to be associated significantly with service performance (r =
.59, p < .01) and service oriented OCB (r = .65, p < .01) of front-line employees. In the
last, service performance and service oriented OCB were also related significantly (r =
.76, p < .01). Amongst the three justice perceptions, interactional justice was found to be
strongly related with all three employee outcome variable (employee engagement, service
performance and service oriented OCB.
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Table 4.17: Means, Standard Deviations and Correlation Results (Branch Level)
Variables Mean S.D 1 2 3 4 5
1. Branch Size 12.92 6.07
2. Branch Age 14.03 11.92 .10
3. Ownership
(Public or Private) - - -.11 -.16**
4. Manager-HPWS 3.92 .50 .11 -.18** .10
5. Collective Human
Capital 3.89 .67 -.04 -.15** .11* .66**
6. Branch Performance 4.06 .59 .11* -.04 .07 .37** .34**
Notes. Branch size is in terms of number of employees; Branch age in years; Ownership Type: Public = 0, Private = 1.
*p <0.05. **p <0.01.
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Table 4.18: Means, Standard Deviations and Correlation Results (Individual Level)
Variables Mean S.D 1 2 3 4 5 6 7 8
1. Gender - -
2. Age 29.70 5.82 .18**
3. Tenure 2.50 2.05 .08** .27**
4. Distributive Justice 3.65 .85 .01 .01 .02
5. Procedural Justice 3.76 .71 -.01 -.02 -.03 .54**
6. Interactional
Justice 3.82 .71 .01 -.01 -.06 .45** .75**
7. Employee
Engagement 3.87 .58 .04 -.03 .01 .45** .53** .54**
8. Service
Performance 4.00 .65 -.01 .01 -.02 .24** .38** .41** .59**
9. Service Oriented
OCB 3.98 .59 .02 -.01 -.02 .31** .45** .48** .65** .76**
Notes. Gender: Female = 0, Male = 1; Age in years; Tenure in years.
*p <0.05. **p <0.01.
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4.8 Hypotheses Testing: Branch Level Relationships
This section presents the findings of branch level hypotheses of this study. First two
hypotheses of the study were branch level hypotheses with all the variables from same
level of analysis. First hypothesis of this study stated that manager-HPWS is related
significantly with bank branch performance. Further, hypothesis 2 of the study suggested
that branch level human capital mediates the relationship of manager-HPWS with bank
branch performance. Moreover, at branch level of analysis, bank branch size (number of
employees), branch age and the ownership status (public or private bank) were taken as
control variables. Structural equation modeling (SEM) was used to examine the first two
hypotheses of this study as all the variables in these hypotheses were branch level
variables. To maintain an appropriate item to sample size ratio, all the variables were
taken as single observed variable. Estimation model, as given in Figure 4.1, demonstrated
a good model fit (χ2 = 7.47, df = 3, χ
2/d.f. = 2.49 p > .05, GFI = .99, AGFI = .95, IFI =
.98, TLI = .92, CFI = .98, RMSEA = .068, RMR = .012). The results showed that
manager-HPWS was significantly related (β = .29, p < .01) to bank branch performance,
thereby empirically supported the hypothesis 1 of this study. Further, the path from
manager-HPWS to collective human capital was also found to be significant (β = .89, p <
.01). Similarly, collective human capital and bank branch performance were also related
(β = .16, p < .01).
Now, to further test the hypothesis 2 that whether collective human capital fully or
partially mediated manager-HPWS and bank branch performance relationship, another
estimation model was calculated without assuming the direct effect of manager-HPWS
on bank branch performance (as shown in Figure 4.2). The values of model fitness
indices for this estimation model reduced significantly (χ2 = 19.29, df = 4, χ2/d.f. = 4.82 p
< .05, GFI = .98, AGFI = .90, IFI = .94, TLI = .78, CFI = .94, RMSEA = .11, RMR =
.015) compared to the previous estimation model with direct effects, highlighting that
branch level human capital partially mediated the relationship. These findings revealed
that bank branch level human capital partially mediated the positive linkage of manager-
HPWS and bank branch performance, thus empirically supported H2 of the study.
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Manager
HPWS
Collective
Human Capital
Branch
Performance
Branch
Age
Ownership
Type
Branch
Size
.29** .08
.89** .16**
.02 .06
.11*
.89** .30**
.01 .07
Manager
HPWS
Collective
Human Capital Branch
Performance
Branch
Age
Ownership
Type
Branch
Size
Figure 4.1: Structural Equation Modeling, Direct Effects
Figure 4.2: Structure Equation Modeling, Indirect Effects
135
Further, first two hypotheses were also tested by using hierarchical linear regression in
SPSS 20. The results of hierarchical linear regression are illustrated in Table 4.17. Table
4.17, Model 2 elaborates that manager-HPWS was related significantly with bank branch
performance (β = .43, p < .01), thus empirically confirmed the hypothesis 1 of the study.
Further, the mediation effects of collective human capital were tested through the steps
prescribed by Baron and Kenny, (1986). According to them, in order to confirm the
mediation effects, the predictor variable should be related with the dependent variable in
the first step. In second step, the independent variable should also be related significantly
with the mediating variable. In third step, the mediating variable must be significantly
related with the outcome variable. Finally, in the last step, upon entering independent and
mediating variables together in regression equation, the independent variable either
reduce in its effects (partial mediation) or it becomes insignificant (full mediation).
Table 4.19: Regression Results for Manager-HPWS, Collective Human Capital and
Branch Performance
Variables Branch Performance
Model 1 Model 2 Model 3 Model 4 Model 5
Branch Size .11* .07 -.11* .11* .08
Branch Age -.02 .01 -.01 .01 .02
Ownership
(Public or Private) .12 .07 .06 .07 .06
Manager-HPWS .43** .90** .29**
Collective Human
Capital .30** .16**
Adjusted R2 .01 .13 .44 .11 .15
∆ R2 .12 .42 .12 .14
F Value 2.16 13.32** 237.6** 11.96** 12.60**
Notes. Branch size is in terms of number of employees; Branch age in years; Ownership Type: Public =0,
Private =1
*p <0.05. **p <0.01.
As shown in the Model 2 of Table 4.19, manager-HPWS (independent variable) was
related significantly to bank branch performance (dependent variable), thereby, fulfilling
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the first condition of mediation analysis. Next, as shown in Model 3 of Table 4.19,
manager-HPWS was also significantly related to collective human capital, the mediating
variable, (β = .90, p < .01), thus satisfied the second requirement of the mediation
analysis. Further, as illustrated in Model 4 of Table 4.19, collective human capital was
also significantly related with bank branch performance (β = .30, p < .01), thereby
fulfilled third condition of mediation analysis. In the last step (Model 5 of Table 4.19),
upon entering manager-HPWS and collective human capital together in the regression
equation, the effect of manager-HPWS reduced (from β = .43, to β = .29) but remained
significant indicating partial mediation. In sum, all these findings showed that the
relationship between manager-HPWS and bank branch performance is partially mediated
by branch human capital and therefore empirically supported the hypothesis 2 of the
study.
4.9 Hypotheses Testing: Cross-Level Relationships
This section presents the results of hypotheses testing for the cross-level direct and
indirect (mediation effects) relationships of variables in this study. In specific, section
4.9.1 illustrates the findings of cross-level direct relationships between manager-HPWS
and employee outcomes (employee engagement, service performance and service
oriented OCB). Whereas, section 4.9.2 presents the findings of cross-level mediation
effect of distributive, procedural and interactional justice for manager-HPWS and
employee outcomes relationship. According to Mossholder and Bedeian (1983), in cross-
level relationships, constructs at one level of analysis are conceptualized to effect
constructs at other level of analysis. The cross-level relationships of this study are
depicted in Figure 4.3. In this study, branch level variables were proposed to impact the
variables at individual level. All the proposed relationships in the study, except for H1
and H2, were cross level relationships. Therefore, HLM was used which has several
advantages over conventional regression analysis when testing cross-level hypotheses
(Bryk & Raudenbush, 1992), discussed already in last chapter.
137
Branch Level
H3 (a-c)
Individual Level
For HLM analysis, null model for each dependent variable is required to be tested before
hypotheses testing in order to identify between-group variance to decide about the
appropriateness of the use of HLM for cross-level relationships (Mathieu & Taylor, 2007;
Hox, 2010). Therefore, separate null models for each of the three outcome variable of the
study including employee engagement, service performance and service oriented OCB
were tested to measure between-group variance (between bank branches in case of this
study). In a null model, a model is tested where there is only outcome variable and no
predictor variable in the equation. The null model is run to measure the intra-class
correlation (ICC) value for each of the outcome variables by using formula given below.
ICC value represents percentage variance in outcome variable (employee engagement,
service performance and service oriented OCB in case of this study) that is between bank
branches.
Manager
HPWS
Distributive
Justice
H4 (a-c)
Interactional
Justice
H6 (a-c)
Procedural
Justice
H5 (a-c)
Employee Engagement
Service Performance
Service Oriented OCB
Figure 4.3: Cross-level Relationships
138
ICC = τ00
τ00+ σ2
Where
τ00 = variance between group
σ2
= variance within groups
The results of null models for each of three dependent variables (employee engagement,
service performance and service oriented OCB) are reported in Table 4.20. These results
demonstrated significant chi-squared values for employee engagement (χ2 = 1291.20, p <
.01), employee service performance (χ2 = 1022.17, p < .01) and their service oriented
OCB (χ2 = 1041.91, p < .01). These chi-squared values indicated significant between-
branches variance in the dependent variables and warrant the use of HLM rather than
regression by using aggregation or disaggregation of data. Along with this, the ICC
values for the three outcomes variables were calculated by using formula given above.
The ICC value for employee engagement, employee service performance and employee
service oriented OCB were found .41, .33 and .34, respectively. These ICC values
demonstrated that 41 % variance existed between-branches in case of employee
engagement. Further, in case of employee service performance, 33 % variance existed
between bank branches. Whereas, 34 % between bank branches variance was observed in
case of employee service oriented OCB. In other words, the intercept terms significantly
varied across branches in case of all three outcome variables. Overall, these results
implied that significant between-group variance existed in case of all three dependent
variables which justified the use of HLM instead of simple regression by aggregation or
disaggregation of data.
4.9.1 Cross-Level Direct Relationships
This section presents the findings of hypotheses testing for cross-level direct relationships
between manager-HPWS and employee engagement, service performance and service
oriented OCB. Cross-level direct relationships hypothesized in this study stated that
manager-HPWS would be related with employee engagement (H3a), service performance
(H3b) and service oriented OCB (H3c) respectively. In these cross-level relationships,
139
manager-HPWS was conceptualized at branch level of analysis and employee outcomes
including employee engagement, service performance and service oriented OCB were
conceptualized at individual level of analysis. Therefore, for these cross-level hypotheses,
HLM was used for which the preliminary requirement of null model was already tested
which justified the use of HLM for testing these hypotheses.
HLM results for cross-level direct relationships are demonstrated in Table 4.20. In
specific, the HLM results revealed that manager-HPWS significantly impacted employee
engagement (γ = .38, p < .01) after controlling for employee gender, age and tenure at
Level-1 and branch size, branch age and ownership type at Level-2. These results
provided empirical support for H3a of the study which demonstrated that manager-
HPWS is related with employee engagement. Similarly, as can be seen in Model 4 of
Table 4.20, after controlling for individual and branch level variables, manager-HPWS
significantly influenced service performance (γ = .36, p < .01), thus statistically
supported the H3b of the study. In the same way, Model 6 of Table 4.20 showed that after
controlling for control variables at both levels, manager-HPWS significantly related with
service oriented OCB (γ = .37, p < .01), thereby, empirically substantiated H3c of the
study.
Overall, these HLM results presented in Table 4.20 revealed that all three direct cross-
level relationships between manager-HPWS and employee outcomes (H3a, H3b, H3c)
were empirically supported. In other words, HPWS implemented by branch managers in
their respective branches had significant impact on employee engagement, service
performance and service oriented OCB (employee outcomes). Effectively implemented
HPWS by bank branch managers has the potential to improve the engagement level of
front-line employees in their workplaces along with superior service performance and
discretionary behaviors while serving customers.
140
Table 4.20: HLM Results of Manager-HPWS and Employee Outcomes
Level &
Variables
Employee Engagement Employee Service Performance Service Oriented-OCB
Null
Model Model 1 Model 2
Null
Model Model 3 Model 4
Null
Model Model 5 Model 6
Intercept 3.87(.02)** 3.73(.10)** 2.29(.2)** 4.00(.03)** 3.98(.10)** 2.59(.2)** 3.98(.02)** 3.93(.09)** 2.53(.2)**
Level 01 (n = 1369)
Gender .05(.03) .05(.03) -.02(.04) -.02(.04) .04(.03) .04(.03)
Age -.03(.02) -.02(.02) .01(.02) .02(.02) -.02(.02) -.01(.02)
Tenure .01(.03) .01(.03) -.01(.03) -.01(.03) -.01(.03) -.01(.03)
Level 02 (n = 323)
Branch Size .09(04)* .05(.03) .08(.04)* .05(.04) .07(.04)* .03(.03)
Branch Age -.05(.02)* -.01(.02) -.06(.02)** -.03(.02) -.07(.02)** -.04(.02)*
Ownership
(Public or
Private)
.10(.07) .06(.06) .01(.07) -.03(.07) .10(.06) .07(.06)
Manager-
HPWS .38(.05)** .36(.06)** .37(.05)**
σ2 .20 .28 .23
τ00 .14 .14 .12
χ2 1291.20** 1225.46** 990.06** 1022.17** 979.26** 826.17** 1041.91** 980.89** 796.64**
Notes. Level-2 = Branch Level; Level-1 = Individual Employee Level; Branch size is in terms of number of employees; Branch age in years; Ownership
Type (Private = 1, Public = 0); Gender (1= male, 0 = female); Age and Tenure of employees in years; Standard errors are reported in parentheses; σ2
represents variance in Level-1 residuals; τ00 represents variance in Level-2 residuals.
*p <0.05. **p <0.01.
141
4.9.2 Cross-Level Mediation Analysis
This section illustrates and discusses empirical findings of cross-level mediation
hypotheses of the study. In addition to measure the relationship between manager-HPWS
and employee outcomes, this study also tested for the mediating mechanisms that might
explain these direct relationships. In specific, distributive justice perceptions, procedural
justice perceptions and interactional justice perceptions were proposed as intermediary
mechanisms to explain the direct relationship between manager-HPWS and employee
outcomes.
This study tested multilevel mediations using the process prescribed by Krull and
MacKinnon (2001) and Zhang, Zyphur and Preacher (2009) for investing mediation
involving two levels of analysis. These researchers have developed this procedure for
testing cross-level mediations based upon the process of mediation analysis prescribed by
Baron and Kenny (1986). In case of this study, the predictor (manager-HPWS) was
Level-2 variable, whereas the mediators (distributive justice, procedural justice and
interactional justice) as well as employee outcome variables (employee service
performance and service oriented OCB) were at conceptualized at Level-1. This type of
model is called 2-1-1 model where numbers are representing the level of analysis at
which variables are conceptualized in the model. According to Zhang, et al. (2009), for
cross-level mediation effects, the Level-2 predictor should be significantly linked with
the outcome variable at Level-1 (step 1). In step 2, the Level-2 predictor must be
significantly related with the Level-1 mediating variable. Next, the Level-1 mediator
must be related significantly with the Level-1 outcome variable (step 3). In the last step,
while adding the Level-2 predictor and Level-1 mediator simultaneously in the HLM
equation, either the effect of the independent variable on the outcome variable reduces
(partial mediation) or it becomes insignificant (full mediation).
HLM results for mediation effects of organizational justice dimensions between manager-
HPWS and employee outcomes are reported in Table 4.21, Table 4.22 and Table 4.23,
respectively. In specific, Table 4.21 presents the mediation effects of distributive justice
142
between the relationship of manager-HPWS and employee engagement (H4a), service
performance (H4b) and service oriented OCB (H4c). Next, Table 4.22 demonstrates the
mediation effects of procedural justice for manager-HPWS and employee engagement
(H5a), service performance (H5b) and service oriented OCB (H5c) relationships. In the
last, Table 4.23 illustrates the mediation effects of interactional justice for manager-
HPWS and employee engagement (H6a), service performance (H6b) and service oriented
OCB (H6c) relationships.
4.9.2.1 Mediation Effects of Distributive Justice
Table 4.21 illustrates HLM results for manager-HPWS, distributive justice and employee
outcomes (employee engagement: H4a, service performance: H4b and service oriented
OCB: H4c) relationship. First, in case of testing the mediation effects of distributive
justice between manager-HPWS and a) employee engagement, b) service performance
and c) service oriented OCB, the procedure discussed in previous section for conducting
cross-level mediation effects was followed. As can be seen in Table 4.20, manager-
HPWS was significantly related with employee engagement (γ = .38, p < .01), employee
service performance (γ = .36, p < .01) and service oriented OCB (γ = .37, p < .01). These
direct relationships were already tested as H3a, H3b and H3c of this. Therefore, the first
condition of mediation analysis was satisfied that Level-2 predictor should be related
with Level-1 outcome variable. Next, as shown in Model 2 of Table 4.21, manager-
HPWS was also significantly related with the distributive justice perceptions of front line
employees (γ = .34, p < .01). This, therefore, satisfied the second condition of cross-level
mediation analysis i.e. Level-2 predictor must be significantly related to Level-1
mediator. Further, as illustrated in Model 3, Model 5 and Model 7 of Table 4.21,
distributive justice perceptions were found to be significantly related with employee
engagement (γ = .26, p < .01), service performance (γ = .16, p < .01) and service oriented
OCB (γ = .18, p < .01). These findings statistically supported the third condition of cross-
level mediation that Level-1 mediator must be significantly related with Level-1
dependent variable. Distributive fairness perceptions of front-line employees were found
143
to be significantly related with all three employee outcome variables. In the last step of
cross-level mediation analysis, manager-HPWS and distributive justice were
simultaneously entered in HLM equation in case of each employee outcome variable
(Model 4, Model 6 and Model 8 of Table 4.21). In case of employee engagement, the
effects of manager-HPWS reduced (from γ = .38 to γ = .29) but remained significant
indicating partial mediation (supported H4a). Further, in employee service performance
case, the effects of manager-HPWS reduced (from γ = .36 to γ = .32) but did not turned to
insignificant revealing partial mediation (supported H4b). Last, similar to previous two
cases, in case of service-oriented OCB also, the effects of manager-HPWS reduced (from
γ = .37 to γ = .31) but remained significant indicating partial mediation (supported H4c).
In summary, these findings revealed that distributive justice partially mediated all the
three relationships between manager-HPWS and employee engagement (H4a), service
performance (H4b) and service oriented OCB (H4c). These empirical findings indicated
that properly implemented HPWS by bank branch managers shape the perceptions of
employees regarding outcomes related fairness (distributive justice) as result of
organizational HR system which further yield into favorable employees‘ reactions at jobs
in form of employee engagement, their service related performance and also discretionary
behaviors while serving customers.
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Table 4.21: HLM Results of Manager-HPWS, Distributive Justice (Mediator) and Employee Outcomes
Level &
Variables
Distributive Justice Employee Engagement Employee Service
Performance Service Oriented-OCB
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Intercept 3.50(.1)** 2.20(.3)** 3.77(.09)** 2.64(.2)** 4.01(.10)** 2.79(.25)** 3.96(.09)** 2.76(.23)**
Level 01 (n = 1369)
Gender -.02(.05) -.02(.05) .06(.03)* .06(.03)* -.02(.04) -.02(.02) .04(.03) .04(.03)
Age .02(.03) .03(.03) -.03(.02) -.03(.02) .01(.02) .01(.02) -.02(.02) -.01(.02)
Tenure -.01(.04) -.01(.04) .01(.02) .01(.02) -.01(.03) -.01(.03) -.01(.02) -.01(.03)
Distributive
Justice .26(.03)** .24(.03)** .16(.03)** .14(.03)** .18(.03)** .16(.03)**
Level 02 (n = 323)
Branch Size .12(.05)* .09(.05) .06(.03) .03(.03) .06(.04) .03(.04) .05(.03) .02(.03)
Branch Age -.07(.03)* -.04(.03) -.03(.02) -.01(.02) -.05(.02)* -.03(.02) -.06(.02)** -.03(.02)
Ownership
(Public or
Private)
.08(.1) .05(.09) .08(.06) .05(.06) -.01(.07) -.04(.07) .09(.06) .06(.06)
Manager-
HPWS .34(.06)** .29(.05)** .32(.06)** .31(.05)**
χ2 1114.36** 1027.24** 1014.22** 865.39** 946.21** 829.88** 898.54** 767.34**
Notes. Level-2 = Branch Level; Level-1 = Individual Employee Level; Branch size is in terms of number of employees; Branch age in years; Ownership
Type (Private = 1, Public = 0); Gender (1= male, 0 = female); Age and Tenure of employees in years; Standard errors are reported in parentheses; σ2
represents variance in Level-1 residuals; τ00 represents variance in Level-2 residuals.
*p <0.05. **p <0.01.
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4.9.2.2 Mediation Effects of Procedural Justice
Table 4.22 demonstrates HLM results for manager-HPWS, procedural justice and
employee outcomes (employee engagement: H5a, service performance: H5b and service
oriented OCB: H5c) relationship. First, in case of testing the mediation effects of
procedural justice between manager-HPWS and a) employee engagement, b) service
performance and c) service oriented OCB, the procedure discussed in section 4.9.2 was
followed. As given in Table 4.20, manager-HPWS was significantly related with
employee engagement (γ = .38, p < .01), employee service performance (γ = .36, p < .01)
and service oriented OCB (γ = .37, p < .01), already tested as H3a, H3b and H3c.
Therefore, the first condition of mediation analysis was satisfied stated that Level-2
predictor should be related with Level-1 outcome variable. Next, as given in Model 2 of
Table 4.22, manager-HPWS was also related significantly with procedural justice
perceptions (γ = .42, p < .01), thus satisfied the second condition of cross-level mediation
analysis i.e. Level-2 predictor must be significantly related to Level-1 mediator. Further,
as illustrated in Model 3, Model 5 and Model 7 of Table 4.22, procedural justice was
found to be significantly related with employee engagement (γ = .38, p < .01), service
performance (γ = .30, p < .01) and service oriented OCB (γ = .32, p < .01). These
findings statistically supported the third condition of cross-level mediation i.e. Level-1
mediator should be significantly related with Level-1 outcome variable. In the last step,
manager-HPWS and procedural justice were simultaneously entered in HLM in case of
each of the three employee outcome variables (Model 4, Model 6 and Model 8 of Table
4.22). In case of employee engagement, the effects of manager-HPWS reduced (from γ =
.38 to γ = .23) but remained significant indicating partial mediation (supported H5a).
Further, in service performance case, the effects of manager-HPWS reduced (from γ =
.36 to γ = .25) but did not turned to insignificant revealing partial mediation (supported
H5b). Last, in case of service-oriented OCB, the effects of manager-HPWS reduced
(from γ = .37 to γ = .24) but remained significant indicating partial mediation (supported
H5c). In summary, these findings revealed that procedural justice partially mediated all
the three relationships between manager-HPWS and employee engagement (H5a),
service performance (H5b) and service oriented OCB (H5c).
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Table 4.22: HLM Results of Manager-HPWS, Procedural Justice (Mediator) and Employee Outcomes
Level &
Variables
Procedural Justice Employee Engagement Employee Service
Performance Service Oriented-OCB
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Intercept 3.68(.13)** 2.08(.26)** 3.76(.08)** 2.89(.18)** 4.01(.09)** 3.05(.24)** 3.96(.08)** 3.03(.21)**
Level 01 (n = 1369)
Gender -.02(.04) -.02(.04) .06(.03)* .06(.03)* -.02(.03) -.02(.03) .04(.03) .04(.03)
Age -.01(.03) -.01(.03) -.02(.02) -.02(.02) .02(.02) .02(.02) -.01(.02) -.01(.02)
Tenure -.04(.03) -.04(.03) .02(.02) .02(.02) .01(.03) -.01(.03) .01(.02) -.01(.02)
Procedural
Justice .38(.03)** .36(.03)** .30(.03)** .27(.03)** .32(.03)** .29(.03)**
Level 02 (n = 323)
Branch Size .06(.06) .02(.04) .07(.03)* .05(.03) .06(.03)* .04(.03) .05(.03) .03(.03)
Branch Age -.06(.02)* -.02(.02) -.03(.02) -.01(.02) -.04(.02)* -.03(.02) -.05(.02)** -.03(.02)
Ownership
(Public or
Private)
.11(.09) .07(.08) .06(.05) .04(.05) -.02(.06) -.05(.06) .07(.05) .05(.05)
Manager-
HPWS .42(.06)** .23(.04)** .25(.06)** .24(.05)**
χ2 1216.02** 1011.77** 917.49** 835.52** 836.78** 772.85** 782.22** 710.77**
Notes. Level-2 = Branch Level; Level-1 = Individual Employee Level; Branch size is in terms of number of employees; Branch age in years; Ownership
Type (Private = 1, Public = 0); Gender (1= male, 0 = female); Age and Tenure of employees in years; Standard errors are reported in parentheses; σ2
represents variance in Level-1 residuals, τ00 represents variance in Level-2 residuals.
*p <0.05. **p <0.01.
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4.9.2.3 Mediation Effects of Interactional Justice
Table 4.23 illustrates HLM results for manager-HPWS, interactional justice and
employee outcomes (employee engagement, service performance and service oriented
OCB) relationship. First, in case of testing the mediation effects of interactional justice
between manager-HPWS and a) employee engagement (H6a), b) service performance
(H6b) and c) service oriented OCB (H6c), the procedure discussed in section 4.9.2 was
followed. As can be seen in Table 4.20, manager-HPWS was significantly related with
employee engagement (γ = .38, p < .01), employee service performance (γ = .36, p < .01)
and service oriented OCB (γ = .37, p < .01). These direct relationships were already
tested as H3a, H3b and H3c of current study. Therefore, the first condition of mediation
analysis satisfied stated that Level-2 predictor should be significantly related with Level-
1 outcome variable. Next, as shown in Model 2 of Table 4.23, manager-HPWS was also
related significantly with interactional justice perceptions of the employees (γ = .39, p <
.01). This satisfied the second condition of cross-level mediation analysis i.e. Level-2
predictor must be significantly related to Level-1 mediator. Further, as illustrated in
Model 3, Model 5 and Model 7 of Table 4.23, interactional justice was found to be
significantly related with employee engagement (γ = .39, p < .01), service performance (γ
= .32, p < .01) and service oriented OCB (γ = .33, p < .01). These findings statistically
supported the third condition of cross-level mediation i.e. Level-1 mediator should be
significantly related with Level-1 outcome variable. In the last, manager-HPWS and
interactional justice were simultaneously entered in HLM in case of each employee
outcome variable (Model 4, Model 6 and Model 8 of Table 4.23). In case of employee
engagement, the effects of manager-HPWS reduced (from γ = .38 to γ = .23) but
remained significant indicating partial mediation (supported H6a). Further, in service
performance case, the effects of manager-HPWS reduced (from γ = .36 to γ = .25) but did
not turned to insignificant revealing partial mediation (supported H6b). Last, not different
from previous two cases, in case of service-oriented OCB, the effects of manager-HPWS
reduced (from γ = .37 to γ = .24) but remained significant indicating partial mediation
(supported H6c).
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Table 4.23: HLM Results of Manager-HPWS, Interactional Justice (Mediator) and Employee Outcomes
Level &
Variables
Interactional Justice Employee Engagement Employee Service
Performance Service Oriented-OCB
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8
Intercept 3.79(.11)** 2.29(.25)** 3.74(.08)** 2.85 (.08)** 3.99(.09)** 3.05(.23)** 3.94(.08)** 3.01(.20)**
Level 01 (n = 1369)
Gender .01(.04) .01(.04) .05(.03) .05(.03) -.03(.03) -.03(.03) .03(.03) .03(.03)
Age -.01(.03) -.01(.03) -.03(.02) -.02(.02) .01(.02) .02(.02) -.01(.02) -.01(.02)
Tenure -.06(.03) -.06(.03)* .03(.02) .03(.02) .01(.03) .01(.03) .01(.03) .01(.02)
Interactional
Justice .39(.03)** .37(.04)** .32(.04)** .30(.04) .33(.03)** .31(.03)**
Level 02 (n = 323)
Branch Size .04(.04) -.01(.04) .08(.03)** .05(.03)* .07(.03)* .05(.03) .05(.03)* .03(.03)
Branch Age -.06(.02)* -.03(.02) -.02(.02) -.01(.02) -.04(.02)* -.02(.02) -.05(.02)** -.03(.02)
Ownership
(Public or
Private)
.11(.08) .07(.07) .06(.05) .04(.05) -.03(.06) -.05(.06) .06(.05) .04(.05)
Manager-
HPWS .39(.05)** .23(.04)** .25(.05)** .24(.05)**
χ2 1097.51** 929.85** 899.43** 811.48** 780.25** 720.07** 718.23** 649.65**
Notes. Level-2 = Branch Level; Level-1 = Individual Employee Level; Branch size is in terms of number of employees; Branch age in years; Ownership
Type (Private = 1, Public = 0); Gender (1= male, 0 = female); Age and Tenure of employees in years; Standard errors are reported in parentheses; σ2
represents variance in Level-1 residuals, τ00 represents variance in Level-2 residuals.
*p <0.05. **p <0.01.
In summary, these results revealed that interactional justice partially mediated all the
three relationships between manager-HPWS and employee engagement (H6a), service
performance (H6b) and service oriented OCB (H6c). These findings were not much
different from the findings of mediating role of distributive justice and procedural justice
where these two also partially mediated all the direct relationships between manager-
HPWS and employee engagement, service performance and service oriented OCB.
4.10 Summary of Hypotheses Testing Results
Table 4.24 presents the summary of the results of all the hypotheses proposed and
empirically tested in this study.
Table 4.24: Summary of Hypotheses Testing Results
Sr. No. Hypotheses Results
H1 Manager-HPWS is positively related with bank branch
performance. Accepted
H2 Collective human capital mediates the relationship between
manager-HPWS and bank branch performance.
Accepted
(Partial Mediation)
H3a Manager-HPWS is positively related with employee engagement. Accepted
H3b Manager-HPWS is positively related with service performance. Accepted
H3c Manager-HPWS is positively related with service oriented OCB. Accepted
H4a Distributive justice mediates the relationship of manager-HPWS
with employee engagement.
Accepted
(Partial Mediation)
H4b Distributive justice mediates the relationship of manager-HPWS
with service performance.
Accepted
(Partial Mediation)
H4c Distributive justice mediates the relationship of manager-HPWS
with service oriented OCB.
Accepted
(Partial Mediation)
H5a Procedural justice mediates the relationship of manager-HPWS
with employee engagement.
Accepted
(Partial Mediation)
H5b Procedural justice mediates the relationship of manager-HPWS
with service performance.
Accepted
(Partial Mediation)
H5c Procedural justice mediates the relationship of manager-HPWS
with service oriented OCB.
Accepted
(Partial Mediation)
H6a Interactional justice mediates the relationship of manager-HPWS
with employee engagement.
Accepted
(Partial Mediation)
H6b Interactional justice mediates the relationship of manager-HPWS
with service performance.
Accepted
(Partial Mediation)
H6c Interactional justice mediates the relationship of manager-HPWS
with service oriented OCB.
Accepted
(Partial Mediation)
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4.11 Conclusion
This chapter presented the descriptive statistics, reliability analysis, CFA and correlation
results between the variables of study. Bank branch level proposed relationships were
tested by using structural equation modeling and results were reported. The findings
revealed that manager-HPWS has direct positive relationship with bank branch
performance as well as through bank branch collective human capital (mediator). Further,
the linkage between manager-HPWS and bank branch performance is partially mediated
by bank branch human capital. The findings of cross-level direct relationships suggested
that manager-HPWS was positively related with employee engagement, service
performance and service oriented OCB. Further, the findings of cross-level mediation
analysis revealed that all the three mediators i.e. distributive fairness, procedural fairness
and interactional fairness perceptions partially mediated the relationships between
manager-HPWS and a) employee engagement, b) service performance and c) service
related OCB. In other words, all nine cross-level mediation relationships demonstrated
partial mediation. Thus, all the proposed relationships in this research were empirically
supported. The discussion of results will be presented in next chapter.
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Chapter 05:
Discussion of Results, Implications and Conclusion
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5. Discussion of Results, Implications and Conclusion
5.1 Introduction
In this research study, a conceptual model was developed demonstrating the effects of
implemented HPWS on bank branch performance as well as employee outcomes and the
intermediary mechanisms explaining these relationships. First, bank branch level
collective human capital was conceptualized as mediating mechanism explaining the
relationship between manager-HPWS and bank branch performance. Further, employees‘
perceptions of distributive justice, procedural justice and interactional justice were
proposed as mediating mechanisms for cross-level relationships between manager-HPWS
and employee outcomes. Empirical findings are also reported in last chapter for all the
proposed relationship of the study. Now, this chapter will present the discussion of the
study findings in accordance with the existing literature. Findings of branch level
proposed relationships will be discussed first followed by the discussion of cross-level
hypothesized relationships. Theoretical, methodological and practical implications will
also be presented along with study limitations and future research avenues. The chapter
will end with the conclusion drawn from this research endeavor.
5.2 Discussion of Results
This section presents the interpretations and discussion of the empirical findings reported
in previous chapter. Section 5.2.1 illustrates the discussion on the empirical findings of
branch level relationships. Further, section 5.2.2 presents the discussion of the empirical
results of cross-level direct and indirect relationships.
5.2.1 Branch Level Relationships
First aim of this study was to examine the effects of manager-HPWS, implemented by the
bank branch managers, on bank branch performance in banking industry operating in
Punjab, Pakistan. Empirical results of H1 demonstrated that manager-HPWS is positively
related with bank branch performance (β = .29, p < .01) indicating that one unit increase
in manager-HPWS would cause 0.29 units increase in bank branch performance. These
findings imply that bank branches demonstrated better market performance where HPWS
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was implemented in more extensive way by branch managers. These findings confirm the
preposition of SHRM that HR practices in form of bundle have positive relationship with
organizational performance. These findings are also consistent with the results of
previous studies reported positive effects of HPWS on organizational performance
outcomes (e.g. Huselid, 1995; MacDuffie 1995; Becker & Gerhart, 1996; Guthrie, 2001;
Batt, 2002; Datta, et al., 2005; Guthrie, et al., 2009; Agarwal & Farndale, 2017).
However, this finding of current research is different from previous research studies in a
way that this study tested the relationship between implemented HPWS by branch
manager and bank branch performance at branch level of analysis. Moreover, the
previous research studies, mentioned above, investigated the relationship of intended
HPWS with organizational performance at establishment level. Thus, these findings
provided empirical support for the relationship between implemented, instead of
intended, HPWS and performance. To date, there has been limited focus by researchers
on examining implemented HPWS with performance outcomes.
Next, H2 of this study stated that branch level human capital mediates manager-HPWS
and bank branch performance relationship. This proposed relationship was empirically
supported and the SEM results indicated that branch level collective human capital
transmits the effects of implemented HPWS to bank branch performance in the banking
industry operating in Pakistan. Exactly, empirical findings revealed that branch level
collective human capital partially mediates the relationship between manager-HPWS and
bank branch performance. These findings empirically supported the argument of resource
based view of the firm (Barney, 1991). According to resource based view of the firm,
HPWS would be associated with collective human capital of the bank branch based upon
the competitive advantage organizations gain through HPWS by developing valuable,
rare, non-substitutable and difficult to inimitable human capital (Barney, 1991; Barney, &
Wright, 1998). This human capital, in turn, assists organizations in the achievement of
competitive advantage through superior performance. In other words, properly
implemented HPWS has the potential to impact bank branches performance by arranging,
developing and especially utilizing the human capital of the employees required to
achieving competitive advantage. Previously, Liao, et al. (2009) conceptualized
individual employees‘ human capital as mediating variable between employees‘
154
perceived HPWS and their performance at individual level of analysis. Problem with
individual employee-reported human capital is that employees are reporting the KSAs
they have but they may not be using them in their workplaces. This research, therefore,
focused on collective human capital implied that the focus should also be on utilization of
organizational human capital rather than just arranging and developing which may not be
utilizing for organizational purposes. Because, may be employees have the required
KSAs but they may not be using it in their workplace. Therefore, the use of collective
human capital as mediator indicated the utilization of human capital as result of properly
implemented HPWS along with its acquisition and development.
5.2.2 Cross-Level Relationships
Another aim of this research was to study the cross-level direct effects of HPWS
implemented by branch managers on employee outcomes including employee
engagement (H3a), service performance (H3b) and service oriented OCB (H3c). These
cross-level relationships, where manager-HPWS was conceptualized at branch level of
analysis and employee outcomes at individual level of analysis, were tested by using
HLM. Statistical findings showed that manager-HPWS was significantly related with
employee engagement (γ = .38, p < .01), employee service performance (γ = .36, p < .01)
and service oriented OCB (γ = .37, p < .01). These findings indicated that one unit
increase in implemented HPWS causes 0.38 units increase in employee engagement, 0.36
units increase in service performance and 0.37 units increase in service oriented OCB.
The findings from cross-level relationship between manager-HPWS and employee
outcomes also address the issue of potential trade-off between firm performance and
employee outcomes raised and identified by Peccei‘s (2004). This research was based
upon the mutual gains perspective of HRM (i.e. HPWS is beneficial for both the
organization and employees). In other words, HPWS implemented by the organizations
through their line managers has positive relationship with organizational performance
along with favorable impact on employee outcomes. Empirical findings supported the
argument by indicating that manager-HPWS has favorable relationships with both bank
branch performance and employee outcomes in case of banking sector operating in
Pakistan.
155
These results imply that bank branches where HPWS was implemented intensively,
employees reported improved engagement in their workplace, service performance and
discretionary behaviors while serving the customers. In specific, HPWS implemented by
branch managers increases the engagement level of the front line employees working in
the banks. Employee engagement is identified as important antecedent for several
workplace attitudes and behaviors of the employees (Saks, 2006). Next, properly
implemented HPWS also increases the service performance of the employees which is
identified as one of the important determinants of service quality (Subramony & Pugh,
2015). Lastly, various authors reported positive relationship between HPWS and
discretionary behaviors of the employees (GONG & CHANG, 2008; Snape & Redman,
2010; Messersmith et al., 2011; Zhang & Morris, 2014). However, Borman & Motowidlo
(1993) reported that ―some types of OCB are probably more appropriate for certain types
of organizations than others. Service companies have special requirements on dimensions
related to dealing with customers and representing the organization to outsiders‖ (1993:
90). Therefore, this study used service related discretionary behavior, instead of general
OCB, to investigate its relationship with implemented HPWS. The results indicated that
HPWS implemented by line managers enhances the discretionary behaviors of
employees, a determinant of superior service quality, while serving customers.
Overall, these results supported the argument of Bowen and Ostroff (2004), pointed that
properly implemented HPWS establishes a social environment in the organization where
employees feel positive about the organization. These results are consistent with the
findings of previous studies reported positive relationship between HPWS and employee
outcomes (e.g. Liao, et al., 2009; Snape & Redman, 2010; Alfes, et al., 2013). However,
these findings of current study are distinct from previous studies in a way that this study
investigated the linkage between implemented HPWS and employee outcomes, a new
stream of research in SHRM where researchers are linking line managers implemented
HRM with organizational and employee outcomes (Aryee, et al., 2012; Pak & Kim,
2016). Whereas previous studies, mentioned above, either examined the effects of
intended HPWS (organizational level) or employees‘ perceived HPWS on employee
outcomes. Furthermore, employee outcomes used in this study (employee engagement,
156
service performance and service oriented OCB) are less investigated while examining the
effects of HPWS on employee outcomes.
In the last, one major objective of this study was to investigate the mediating role of
organizational justice dimensions (distributive justice: H4, procedural justice: H5 and
interactional justice: H6) between manager-HPWS and employee outcomes. The
following section will discuss the results of mediating role of distributive fairness
perceptions, procedural fairness perceptions and interactional justice perceptions
separately between manager-HPWS and employee outcomes.
First, H4 of the study posited that distributive justice perceptions of front-line employees
mediate the relationship between manager-HPWS and employee engagement (H4a),
service performance (H4b) and service oriented OCB (H4c). The findings demonstrated
that manager-HPWS was positively linked with distributive justice perceptions of front
line employees (γ = .34, p < .01) indicating that one unit increase in implemented HPWS
caused 0.34 units increase in the perceptions of distributive justice. Further, distributive
justice perceptions were also related significantly with employee engagement (γ = .26, p
< .01), service performance (γ = .16, p < .01) and service oriented OCB (γ = .18, p < .01).
These findings indicated that one unit increase in distributive justice perceptions caused
0.26 units increase in employee engagement, 0.16 units increase in service performance
and 0.18 units increase in service oriented OCB. Of three employee outcomes (employee
engagement, service performance and service oriented OCB), the highest variance was
found for employee engagement due to distributive justice perceptions. Finally, the
results of cross-level mediation analysis revealed that distributive justice perceptions
partially mediated the positive association between manager-HPWS and all three
employee outcomes (employee engagement, service performance and service oriented
OCB). These results of the study indicated that properly implemented HPWS by line
managers shapes employees fairness perceptions regarding the outcomes of
organizational distributive decisions which results into favorable employee reactions in
the workplace. In other words, when employees perceive that distribution decisions are
fair as a result of organizational HR policies, they exhibit more favorable behaviors at
workplace including increased engagement, better service performance and more
frequently involved in OCB while serving customers.
157
Further, H5 of the study claimed that procedural justice perceptions of front-line
employees mediate the relationship of manager-HPWS with employee engagement
(H5a), service performance (H5b) and service oriented OCB (H5c). Empirical findings
demonstrated that manager-HPWS was positively linked with procedural justice
perceptions of the front line employees (γ = .42, p < .01) indicating that one unit increase
in implemented HPWS caused 0.42 units increase in the employees‘ perceptions of
procedural justice. Further, procedural justice perceptions were also related significantly
with employee engagement (γ = .38, p < .01), service performance (γ = .30, p < .01) and
service oriented OCB (γ = .32, p < .01). These findings indicated that one unit increase in
procedural justice perceptions caused 0.38 units increase in employee engagement, 0.30
units increase in service performance and 0.32 units increase in service oriented OCB. Of
three employee outcomes, the highest variance was found for employee engagement due
to procedural justice perceptions. Finally, the results of cross-level mediation analysis
revealed that procedural justice perceptions partially mediated the positive linkage
between manager-HPWS and all three employee outcomes (employee engagement,
service performance and service oriented OCB). These findings revealed that effectively
implemented HPWS by line managers spread signals in organizational environment
which effects employees‘ perceptions regarding the fairness or unfairness of
organizational procedures and decision making related to employees upon which
employees exhibit favorable or unfavorable reactions towards their employer.
Lastly, H6 of the study proposed that interactional justice perceptions of front-line
employees mediate the relationship of manager-HPWS with employee engagement
(H6a), service performance (H6b) and service oriented OCB (H6c). Empirical findings
illustrated that manager-HPWS was positively linked with interactional justice
perceptions of front line employees (γ = .39, p < .01) indicating that one unit increase in
implemented HPWS caused 0.39 units increase in the perceptions of interactional justice.
Further, interactional justice perceptions were also related significantly with employee
engagement (γ = .39, p < .01), service performance (γ = .32, p < .01) and service oriented
OCB (γ = .33, p < .01). These findings revealed that one unit increase in perceptions of
interactional justice caused 0.39 units increase in employee engagement, 0.32 units
increase in service performance and 0.33 units increase in service oriented OCB. Of three
158
employee outcomes, the highest variance was found for employee engagement due to
interactional justice perceptions. Finally, the results of cross-level mediation analysis
revealed that interactional justice perceptions partially mediated the positive association
between manager-HPWS and all three employee outcomes (employee engagement,
service performance and service oriented OCB).
In sum, results for mediation role of distributive fairness, procedural fairness and
interactional fairness perceptions between manager-HPWS and employee outcomes were
not much different from each other. All three dimensions of justice perceptions partially
mediated the manager-HPWS and employee outcomes relationship. However, of these
three employee outcomes, the strongest effects were found for employee engagement in
case of all three justice dimensions. On the other hand, in case of the variance in justice
perceptions caused by implemented HPWS, procedural justice was found as the strongest
contributor when transmitting the effects of manager-HPWS to employee outcomes. Not
different from these findings, the procedural justice perceptions showed the highest level
of variation in employee outcomes compared to other two forms of justice. Thus, it can
be inferred that all three forms of justice perceptions mediated the relationships between
manager-HPWS and employee outcomes but procedural justice was emerged as the
strongest mediator compared to distributive justice and interactional justice perceptions
of front-line employees. In other words, employees give importance to all three justice
perceptions when evaluate HR system implemented by their employer which further
determine their reactions in their workplaces in case of banking sector operating in
Punjab, Pakistan.
These results of cross-level mediation analysis provided support for the claims of various
researchers i.e. organizational HPWS influence employee attitudes and behaviors through
their psychological processes. For instance, researchers concluded that employees‘
perceptions of HPWS mediate the relationship between organizational HPWS and
employee outcomes (Liao, et al., 2009; Aryee, et al., 2012). Similarly, Nishii, et al.,
(2008) concluded that employees‘ attributions regarding organizational HPWS
determined their reactions towards employer. Study results imply that employee
engagement, service performance and service related discretionary behaviors will
increase when they feel that the practices of HPWS implemented are procedurally fair,
159
distribution of rewards and resources is justified and their supervisor treats them with
dignity and respect. Overall, these findings also support social exchange theory (Blau,
1964) argued that employees reciprocate in form of favorable workplace attitudes and
behaviors when organizational work practices are perceived fair by the employees.
5.3 Implications of the Study
This section presents the implications drawn from empirical results of this study. In
specific, section 5.3.1, 5.3.2 and 5.3.3 discuss theoretical, methodological and practical
implications of this study respectively.
5.3.1 Theoretical Implications
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the impact of HPWS. Therefore, considering both, organizational performance and
employee outcomes, provides clear picture about how same organizational HPWS is
related and beneficial (mutual gains) for both the organization and employees.
Third, this study contributed to the literature by incorporating employees‘ perspective, in
form of their fairness evaluation of HRM, while studying HPWS-performance
relationship (Boxall & Macky, 2014). Extant SHRM research has been criticized for
being managerially biased because of using management-centric approach while
examining HPWS-performance linkage (Paauwe, 2009; Kaufman, 2010; Boxall &
Macky, 2014). These authors stressed upon including employees‘ perspective while
investigating HPWS-performance relationship to have more meaningful insights about
this relationship. Appelbaum (2002) argued and suggested to study and understand
employees‘ verdict of HRM in order to understand how and why HPWS influence
employee outcomes. Moreover, some HPWS-performance studies, which have included
employees, treated employees as objects (like other organizational resources) rather than
as active subjects (who think and evaluate), thus, provide inadequate information about
their reactions towards organizational HRM. Therefore, examining employees‘
perspective of HRM added meaningful insights about how and why employees react to
certain organizational HR systems. This investigation also provided support to the claim
of Bowen and Ostroff (2004) that employees can have different verdict about
organizational HRM because they experience and interpret same HR practices
differently.
Fourth, this study added to SHRM literature by using implemented, instead of intended,
HPWS as the former is argued to be a more proximal and appropriate antecedent for
employee outcomes in HPWS-performance causal chain (e.g. Wright & Nishii, 2007;
Chuang, et al., 2013; Pak & Kim, 2016; Jiang, & Messersmith, 2018). These findings
have added to the SHRM literature by linking implemented, instead of intended, HPWS
with employee outcomes (Nishii & Wright, 2007). Extant HPWS-performance literature
has also been criticized for using organization-level data, assuming that intended HPWS
is implemented in the same manner throughout the organization as intended (Wright &
Nishii, 2013). Whereas, in reality, these top management/ HR departments reported HR
practices representing their espoused/ intended HR policies, which may not be
161
implemented in the same way across the organization (Khilji & Wang, 2006; Nishii &
Wright, 2007). Line managers are people responsible for implementation of
organizational intended HR practices within their respective departments and, therefore,
are main source of determining quality of implementation and effectiveness of HR
practices. Therefore, it is argued that focusing on implemented, instead of intended,
HPWS with performance outcomes would have more meaningful insights about HPWS-
performance relationship.
5.3.2 Methodological Implications
This study also has some methodological contributions for HPWS-performance research
area. Literature has highlighted several methodological shortcomings in HPWS-
performance research (Paauwe, 2009). For instance, over emphasis on management
perspective while investigating HPWS-performance relationship, single respondent
surveys and level of analysis. This study also tried to address these methodological issues
by including multiple respondents and using multilevel modeling approach while
investigating complex HPWS-performance relationship.
Previous studies, mainly, relied on one source for data while investigating HPWS-
performance relationship. They either investigated management reported HPWS
(intended HPWS) and its relationship with the management reported performance data.
Or, they tried to connect employees‘ perceived HPWS with their attitudes and behaviors
(employee self-reported). This study, however, considered multiple stake holders
involved in HPWS-performance relationship. This study collected data from branch
managers for being real implementers of organizational HPWS and front line employees
in order to overcome the methodological issues because of the reliance on single
respondent (Gerhart, et al., 2000). Further, according to Wright and Boswell (2002), the
ideal approach of understanding organizational HR system is to consider multiple
respondents for information rather than relying on single source. Therefore, this research
involved branch managers for information on implemented HPWS whereas fairness
perceptions about organizational HPWS and attitudes and behaviors were recorded from
employees.
162
Second contribution made by this study is the use of multilevel approach to investigate
complex and distant HPWS-performance relationship (Shen et al., 2017). In their HR
causal chain framework, Wright and Nishii (2007) pointed that HR policy is intended at
organizational level and then implemented at departmental, group or team level by line
managers, then how employees perceive and experience organizational HRM further
influences their attitudes, behaviors (individual level of analysis) and performance
outcomes. Paauwe and Boselie (2005) argued that the use of multilevel frameworks while
examining this distant and complex HPWS-performance relationship is unavoidable.
Thus, this study successfully used multilevel approach to gauge the impact of
implemented HPWS by bank branch managers (bank branch level of analysis) on
employees‘ fairness perceptions along with their attitudes and behaviors (individual level
of analysis). Although, some researchers have used multilevel approach to investigated
HPWS-performance relationship (e.g. Liao, et al., 2009; Aryee, et al., 2012; Pak & Kim,
2016), hardly any study in Pakistan has applied this approach. In sum, involving multiple
respondents, multiple stakeholders and the use of multi-level approach assisted in
discovering the deep insights about HPWS-performance relationship and explained the
processes by which HPWS influences organizational performance and employee
outcomes.
5.3.3 Practical Implications
Along with theoretical and methodological contributions of current study, findings of this
study also have several important implications for practitioners and organizations. For
instance, study findings revealed that HPWS implemented through branch managers is
critical aspect for organizational success as it has positive impact on bank branch
performance as well as employee outcomes (attitudes and behaviors). Organizations can
use the learning and insights from this research to design and implement HR systems and
policies of organizations that will be capable of enhancing and utilizing the human capital
and viewed as fair in order to get benefited from them. Moreover, the role of line
managers (branch managers in case of this study) is also highlighted in the administration
of more effective HR system. In specific, following are some of the implications for
practitioners drawn from the findings of this study.
163
One important implication is the highlighted role of line managers in the effectiveness of
organizational HPWS. According to Purcell and Hutchinson (2007), understanding that
line managers have a role as real implementers of HR practices within their respective
departments, HR professionals should work closely with them in order to ensure effective
implementation of organizational intended HPWS to obtain the maximum benefit for
their organization. Therefore, the key challenge for organizations is to enhance the
interest, motivation and participation of bank branch managers to implement
organizational intended HR systems in ways that enhance the utilization of human capital
and also regarded as fair. This can be done through trainings of line managers to have
knowledge about organizational HR practices and how these practices could be used to
utilize human capital of the organization and to influence the justice perceptions of the
employees. Along with this, motivation and involvement of line managers into HRM
could be increased by making it part of their formal job descriptions, gauge their abilities
and interest for managing people during hiring process, give it appropriate weightage in
their performance evaluations and incentivize them for good people management.
Another implication for organizations emerges from empirical findings of this study
regarding the importance of organizational investments and efforts for HPWS. These
findings revealed that bank branches experienced increase in market performance where
organizational intended HPWS was more effectively implemented by branch managers.
In other words, effectively implemented HR practices by branch managers bring more
profitability, sale and improved market performance for the bank branches.
In addition to highlighting the importance of properly implemented HPWS for bank
branch performance, this study also provides insights about the processes through which
implemented HPWS influence bank branch performance and employee outcomes. Study
findings imply that implemented HPWS by branch managers improves the utilization of
human capital which in turns boosts the market performance of the bank branches. This
study also highlighted employees‘ perspective in HPWS-performance relationship which
was an ignored area previously (Boxall & Macky, 2014). The findings showed that
employees‘ fairness perceptions act as intermediary mechanisms through which
implemented HPWS influence engagement level of the employees, their service
performance and also service related discretionary behavior (service oriented OCB).
164
These findings imply that branch managers, being implementers of HR practices, should
consider employees‘ fairness perspective of organizational HPWS in order to enhance
their level of engagement, service performance and service related discretionary
behaviors. These employee outcomes are identified as important determinants of service
quality in service organizations (Subramony & Pugh, 2015).
5.4 Limitations and Future Research Avenues
Even though it is believed that this study has made several contributions to the field of
SHRM, like all other research studies, it also has few limitations, which may, however,
provide avenues for future researchers.
First, this study used cross-sectional research design to test the proposed relationships
among variables. Therefore, causal inference could be drawn with caution from the
relationships among study variables because of its cross-sectional nature. Future research
studies with a longitudinal design would authenticate the causal relationships proposed
and tested in this study. Second, this study used a sample from bank branches located in
the Punjab province of Pakistan. So, the findings of this study may not be generalized to
other organizations and sectors. Similar research studies in future should, therefore, be
conducted in different organizations, industries and cultures to verify the scope of the
findings of this study in other settings.
Third, although this study has proposed and empirically tested mediators for both the
relationships: between manager-HPWS and bank branch performance and between
manager-HPWS and employee outcomes. There might be a number of other mediating
mechanisms which could explain these relationships. Thus, future studies would be
needed to use different theoretical perspectives to hypothesize and empirically test other
potential mediators for explaining HPWS-performance relationship. Fourth, basing their
investigations on cross-level methodology, future researchers would have the opportunity
to advance the literature on HPWS-performance linkage by proposing and testing the
relationships among variables which were ignored previously because of being limited to
a single level of analysis, especially in the case of Pakistan. Therefore, future researchers,
especially in Pakistan, have the opportunity to advance the theory on HPWS-performance
relationship by using multilevel modeling approach.
165
Last of all, this study has used subjective measures of branch performance because of the
difficulties in obtaining objective performance data (Gupta, 1987). Even though Wall, et
al. (2004) reported the construct, convergent and discriminant validity of relative
performance, these performance measures do not permit momentous conversions like the
dollar change associated with the degree of change in HPWS, and therefore they limit the
practical significance of HPWS (Huselid, 1995). Future researchers are, therefore,
recommended to bring into play objective parameters for performance.
Despite aforementioned limitations, this study has made several important contributions
for the literature around HPWS-performance relationship. For instance, this study
contributed into literature by providing an integrative model linking implemented HPWS
with organizational performance and employee outcomes along with the mediating
mechanisms to explain these relationships. Next, this contributed by incorporating the
perspective of management and employees, simultaneously, regarding organizational
HPWS to better understand HPWS-performance relationship. Moreover, this study also
highlighted the role of line managers in effective implementation of organizational
HPWS. Further, based upon a large data set from banking sector operating in Punjab, the
results of this study have significant implications (mentioned in practical implications of
the study section) not only for the targeted population but the findings of the study may
also be generalize to other similar industrial settings and to the banking sector of
developing countries having context similar to the banking sector of Pakistan.
5.5 Conclusions
The aim of current study was to examine the effects of implemented HPWS on bank
branch performance and employee outcomes along with the processes explaining these
relationships. First, based upon resource based view of firm (RBV), bank branch
collective human capital was hypothesized as mediating variable between manager-
HPWS and bank branch performance. Further, organizational fairness perceptions
(distributive fairness, procedural fairness and interactional fairness) were posited as
mediating mechanism between implemented HPWS and employee outcomes at cross-
level of analysis. To test the proposed relationships of this study, data were obtained from
323 branch managers and 1369 front-line employees of 30 commercial banks operating in
166
Punjab, Pakistan. Study findings showed that HPWS implemented by branch managers
has impact on bank branch performance as well as employee outcomes. These findings
supported the arguments of mutual gains i.e. HPWS is favorable for both the employer
and employees. Study results also revealed that the linkage between manager-HPWS and
bank branch performance is partially mediated by branch level collective human capital.
Further, empirical findings also demonstrated that distributive justice, procedural justice
and interactional justice perceptions of front-line employees partially mediated the
relationships between manager-HPWS and employee outcomes. Implemented and
perceived HPWS differentiation, role of line manager as being implementer of
organizational HPWS and the intermediary mechanisms to link HPWS with
organizational performance and employee outcomes emerged as the main issues from the
findings of this study. These themes are reflected as the key challenges for future
research investigations and practitioners in the area of SHRM. This study advanced the
theory on SHRM and its application in banking sector. The findings also shed light on the
processes through which implemented HPWS influence bank branch performance and
employee. In the end, this study also bridged the gap between management (macro) and
employees‘ (micro) perspectives of HRM.
167
Chapter 06:
References
168
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Appendices
APPENDIX A: Details of Bank Branches
Sr.
No. Categories of Banks Total Banks
Total Branches
in Pakistan
Branches in Punjab
Province
1 Public Sector Banks 05 2100 1147
2 Private Banks 16 8119 4566
3 Islamic Banks 05 1021 497
4 Specialized Banks 04 603 371
Grand Total 30 11843 6581
210
APPENDIX B: Branch Manager Survey
211
212
213
214
APPENDIX C: Front-Line Employee Survey
215
216
217
218