variant conflict management: conceptualizing and
TRANSCRIPT
Variant Conflict Management: Conceptualizing and Investigating Team Conflict Management as a Configural Construct
Yunzi Tan
Submitted in partial fulfillment of the
requirements for the degree of Doctor of Philosophy
under the Executive Committee of the Graduate School of Arts and Sciences
COLUMBIA UNIVERSITY
2013
© 2013
Yunzi Tan All Rights Reserved
ABSTRACT
Variant Conflict Management: Conceptualizing and Investigating Team Conflict Management as a Configural Construct
Yunzi Tan
The key purpose of this dissertation was to empirically test a new conceptual model of
team conflict management (Tan, 2011). Central to this model is a configural team-level construct
called variant conflict management (VCM), which refers to the relative levels of cooperative and
competitive conflict management among members in a team. This model also identifies three key
antecedent categories likely to predict VCM in teams: salient conflict-relevant member
characteristics, team contextual determinants, and divergent team dynamics. Three archetypal
profiles of VCM, i.e., distinct distributional patterns in members’ conflict management
approaches, are also proposed: minimum, moderate and maximum VCM profiles. These three
profiles are further organized into five sub-types: minimum cooperative, minimum competitive,
moderate cooperative, moderate competitive, and maximum VCM profiles.
Specifically, this study sought to assess whether the proposed VCM profiles are present
in 79 student project teams. It also compared the effects of VCM (based on teams’ standard
deviation scores) and of mean team conflict management (based on teams’ means scores) on
three team outcomes: team conflict efficacy, members’ satisfaction with their teams’ conflict
management process, and team effectiveness. This study also investigated the relative effects of
the proposed VCM profiles on each of the three team outcomes. Three indicators representing
each of the antecedent categories, i.e., gender role diversity, team goal interdependence, and
subgroup formation, were also examined as potential predictors of VCM.
Using qualitative content coding analyses, it was revealed that all five VCM profiles
proposed in the model, i.e., minimum cooperative, minimum competitive, moderate cooperative,
moderate competitive, and maximum VCM profiles, were indeed evident in the teams sampled.
Three additional profiles described as ‘distributed,’ ‘multiple clusters’ and ‘midpoint cluster’
were also uncovered in the content coding analyses. In the supplementary latent class analyses,
four latent classes were identified. Two of these classes corresponded with two of the five
proposed VCM profiles: the moderate cooperative and moderate competitive VCM profiles. The
third latent class was aligned with the new ‘distributed’ profile identified in the content coding
analyses. As for the fourth latent class, it consisted of the other three proposed VCM profiles,
i.e., minimum cooperative, minimum competitive and maximum VCM profiles, as well as the
two additional profiles uncovered in the content coding analyses, i.e., ‘multiple clusters’ and
‘midpoint cluster’ profiles.
Comparisons among the five proposed VCM profiles of their effects on the three team
outcomes showed that teams with minimum cooperative VCM profiles reported higher levels of
team conflict efficacy than teams with moderate competitive VCM profiles, and they were also
more effective than teams with minimum competitive VCM profiles. Teams with minimum
competitive VCM profiles, on the other hand, reported the lowest levels of member satisfaction
compared to teams with the four other proposed VCM profiles; teams with minimum
competitive VCM profiles were also less effective than teams with minimum cooperative and
moderate cooperative VCM profiles. Teams with moderate cooperative VCM profiles, relative to
those with moderate competitive VCM profiles reported greater team conflict efficacy and team
effectiveness.
The study results also found no significant effects of VCM (based on teams’ standard
deviation scores) and of mean team conflict management (based on teams’ means scores on
cooperative and competitive conflict management respectively) on team conflict efficacy,
members’ satisfaction with their teams’ conflict management process, and team effectiveness.
Additionally, no significant associations were found between the three proposed predictor
variables, i.e., gender role diversity, team goal interdependence and subgroup formation, and
VCM.
Implications of these findings for theory, research and practice, along with limitations
and future research directions, were also discussed.
i
TABLE OF CONTENTS
PAGE
LIST OF TABLES vii
LIST OF FIGURES ix
ACKNOWLEDGEMENTS x
CHAPTER I: INTRODUCTION 1
Overview 1
Study Purpose 3
Study Contributions 4
Key Perspectives Underlying the Variant Conflict Management Model
5
The ‘Interactionist’ Perspective: Person versus Situation 5
The ‘Process’ Perspective: Team Dynamics Matter 6
The ‘Levels’ Perspective: “The Whole does not Equal the Sum of its Parts”
8
Dissertation Structure 9
CHAPTER II: LITERATURE REVIEW 10
Overview 10
Team Conflict Management: A Critical Review 10
Common Theories and Typologies in Team Conflict Management Research
11
Antecedents of Team Conflict Management 15
Effects of Team Conflict Management 17
Conceptualizing Variant Conflict Management 19
ii
TABLE OF CONTENTS (Continued)
PAGE
Variant Conflict Management Profiles 22
Minimum VCM 22
Moderate VCM 23
Maximum VCM 23
Effects of Variant Conflict Management 24
Relative Effects of VCM and Mean Cooperative Team Conflict Management
24
Relative Effects of VCM and Mean Competitive Team Conflict Management
27
Relative Effects of Various VCM Profiles 29
Antecedents of Variant Conflict Management 35
Salient Conflict-Relevant Member Characteristics 35
Gender Role Diversity 37
Team Contextual Determinants 39
Goal Interdependence 40
Divergent Team Dynamics 43
Subgroup Formation 44
CHAPTER III: METHODOLOGY 46
Overview 46
Participants 46
Sample 46
iii
TABLE OF CONTENTS (Continued)
PAGE
Design and Procedures 48
Measures 49
Conflict Management Measures 49
VCM Profiles 49
Variant Conflict Management 50
Cooperative and Competitive Team Conflict Management
51
Predictor Measures 51
Gender Role Diversity
51
Team Goal Interdependence 52
Mixed Goal Interdependence 53
Subgroup Formation 53
Outcome Measures 54
Team Conflict Efficacy 54
Member Satisfaction with the Team Conflict Management Process
54
Team Effectiveness 54
Controls and Other Measures 54
Intra-Team Conflict Types 54
Perceived Conflict Importance and Intensity 55
Course Affiliation and Team Size 56
iv
TABLE OF CONTENTS (Continued)
PAGE
Participant Demographics 56
CHAPTER IV: RESULTS 57
Overview 57
Preliminary Analyses 57
Descriptive Statistics 57
Team-Level Reliability and Data Aggregation Indices 57
Common Method Variance 59
Intercorrelational Analyses 59
Main Analyses
61
Assessing Presence of VCM Profiles in Teams 61
Hypothesis 1: Presence of Proposed VCM Profiles
61
Assessing Relative Effects of VCM and Mean Team Conflict Management on Team Outcomes
63
Hypotheses 2a to 2c: Cooperative Team Conflict Management versus VCM
63
Hypotheses 3a to 3c: Competitive Team Conflict Management versus VCM
67
Assessing Relative Effects of VCM Profiles on Team Outcomes
70
Hypotheses 4a to 4c: Minimum Cooperative VCM versus All Other VCM Profiles
70
Hypotheses 5a to 5c: Minimum Competitive VCM versus All Other VCM Profiles
72
Hypotheses 6a to 6c: Moderate Cooperative VCM versus Moderate Competitive VCM Profiles
73
v
TABLE OF CONTENTS
(Continued)
PAGE
Hypotheses 7a to 7c: Maximum VCM versus Moderate Competitive VCM Profiles
74
Assessing Potential Antecedents of VCM 76
Hypothesis 8: Gender Role Diversity and VCM 76
Hypothesis 9: Team Goal Interdependence and VCM
76
Hypothesis 10: Subgroup Formation as A Mediator
77
Supplementary Analyses 78
Assessing VCM Profiles using Latent Class Analyses 78
Exploring Group Differences among VCM Categories on Team Outcomes
81
VCM Categories on Team Conflict Efficacy
82
VCM Categories on Member Satisfaction with Team Conflict Management Process
83
VCM Categories on Team Effectiveness
83
CHAPTER V: DISCUSSION 84
Theoretical Implications 92
Research Implications 94
Practical Implications 95
Study Limitations 96
Future Research Directions 97
Conclusion
98
vi
TABLE OF CONTENTS (Continued)
PAGE
REFERENCES 100
APPENDICES 145
Appendix A: Email Requests for Study Recruitment and Participation
145
Appendix B: Study Questionnaire 147
Appendix C: Study Measures 159
vii
LIST OF TABLES
TABLE DESCRIPTION PAGE
1 Descriptive Statistics for all Key Team Variables 120
2 Reliability and Aggregation Indices for all Team Measures
121
3 Intercorrelations for all Key Team Variables 122
4 Coding Definitions of VCM Profiles used in the Content Coding Analyses
124
5 Classification of Teams based on the Content Coding Analyses
125
6 Hierarchical Regression Analysis Predicting Team Conflict Efficacy from Cooperative Team Conflict Management and VCM
126
7 Hierarchical Regression Analysis Predicting Member Satisfaction with Team Conflict Management Process from Cooperative Team Conflict Management and VCM
127
8 Hierarchical Regression Analysis Predicting Team Effectiveness from Cooperative Team Conflict Management and VCM
128
9 Hierarchical Regression Analysis Predicting Team Conflict Efficacy from Competitive Team Conflict Management and VCM
129
10 Hierarchical Regression Analysis Predicting Member Satisfaction with Team Conflict Management Process from Competitive Team Conflict Management and VCM
130
11 Hierarchical Regression Analysis Predicting Team Effectiveness from Competitive Team Conflict Management and VCM
131
12 Medians and Number of Cases for the Effects of VCM Profiles on Team Conflict Efficacy
132
13 Means and Standard Deviations for the Effects of VCM Profiles on Member Satisfaction with the Team’s Conflict Management Process and Team Effectiveness
132
14 Simple Regression Analysis Predicting VCM with Gender Role Diversity
133
viii
LIST OF TABLES (Continued)
TABLE DESCRIPTION PAGE
15 Polynomial Regression Analysis Predicting VCM with Team Goal Interdependence Variables
134
16 Simple Regression Analysis Predicting Subgroup Formation with Gender Role Diversity
135
17 Hierarchical Regression Analysis Predicting Subgroup Formation as a Mediator between Gender Role Diversity and VCM
135
18 Model Fit Statistics for the Latent Class Analyses 136
19 Classification of VCM Profiles based on Latent Class Memberships
137
20 Medians and Number of Cases for the Effects of VCM Categories (Identified in the Latent Class Analyses) on Team Conflict Efficacy
138
21 Means and Standard Deviations for the Effects of VCM Categories (Identified in the Latent Class Analyses) on Member Satisfaction with the Team’s Conflict Management Process and Team Effectiveness
138
22 Summary Findings for the Main and Supplementary Analyses
139
ix
LIST OF FIGURES
FIGURE DESCRIPTION PAGE
1 Conceptual Model of Variant Conflict Management 113
2 Minimum VCM Profiles 114
3 Moderate VCM Profiles 115
4 Maximum VCM Profiles 116
5 VCM Profiles Identified from Content Coding 117
6 Graph showing Estimated Conditional Probabilities for the Four-Class Model Solution
118
7 VCM Profiles Identified from Latent Class Analyses 119
x
ACKNOWLEDGEMENTS
First and foremost, I would like to express my deepest gratitude to my two primary
program advisors and mentors, Dr. Loriann Roberson and Dr. Peter T. Coleman, for their
ongoing advisement and guidance, throughout my years as a Ph.D. student in the Social-
Organizational Psychology Program at Teachers College. Thank you both, for your positive
encouragement and support over the years, and for making my doctoral student experience a
most rewarding and fulfilling one. I would also like to thank the rest of my dissertation
committee, Dr. Madhabi Chatterji, Dr. James Westaby, Dr. Joel Brockner, and Dr. Lyle Yorks,
for their thoughtful questions and insightful comments, and for making my defense a truly
memorable and intellectually stimulating event.
Special thanks go to the sponsor of the Lim Kim San Fellowship for Ph.D. Students, i.e.,
the Lee Kong Chian School of Business at the Singapore Management University, for awarding
me this competitive fellowship, and in turn, for making the data collection and funding of my
dissertation possible. I would also like to express my thanks to my fellowship faculty host, Dr.
Hwee Hoon Tan, the rest of the Organizational Behavior and Human Resources Division faculty,
and the student participants, for making my fellowship visit a productive and engaging
experience.
I am also greatly indebted to my Ph.D. program community, particularly Dr. Marina
Field, Dr. Frank Golom, Mekayla Castro, Nishita Rai, and Apiwat Hanvongse. Thank you all for
your friendship, love and support throughout my Ph.D. journey, and I could never have made it
this far without having all of you along the way. To my closest friends and allies in life, Dr. Cui
Su, Dr. Thiam Hui Lee, Arwa Jumkawala, Lisa Choo, Lynn Jiang, Winston Len, Karen Frank,
Laurie Barrueta, and Dr. June Lee, this dissertation would never have been possible without your
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tireless encouragement and deep support for me as well. I would also like to thank Hui Hui
Chong and Lily Ng for volunteering to code data for my study.
To my immediate and extended family in Singapore: thank you for your continuing
support in my pursuit of the doctorate over the years, despite being thousands of miles away. I
finally did it – becoming the first Dr. in our family!
To my husband, Sebastian Christoph Wagner, and my son, Leo Rui Hao Wagner: Thank
you both for being the two greatest pillars of strength, joy, inspiration and love in my life!
Completing this Ph.D. journey would also never have been possible without you two by my side.
Ich liebe dich beide!
Last but not least, to my parents, Tan Beng Soon and Ling Lee Keow: I dedicate this
dissertation to both of you. Thank you for all that you have done for me, and for giving me your
best in support of my doctoral goals! (爸,妈：我把这本论文典献给你们。感谢你们多年以来
所为我做的一切，也感谢你们支持我当博士的目标!)
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CHAPTER I: INTRODUCTION
Overview
For decades, organizational scholars and researchers have expended much effort studying
the antecedents, dynamics and consequences of conflict and its management (Lewicki, Weiss, &
Lewin, 1992). Today, we have amassed a considerable body of knowledge about how, when and
why conflict occurs, and at various levels of analysis; a significant portion of this knowledge has
also been dedicated to understanding how conflicts are managed or resolved (De Dreu &
Gelfand, 2008; Rahim, 2001). Despite this substantial attention to conflict management, most of
the research in this area has been directed at the individual and interpersonal levels (e.g.,
Deutsch, 1973; Rahim, 1983; Thomas, 1992), and to some extent, at the organizational level
(e.g., Pondy, 1967). By contrast, relatively little research has been conducted on conflict
management at the team level. This is particularly noteworthy given the increasing use of work
teams in organizations today (Ilgen, 1999). In light of this, researchers have begun to focus on
team-level conflict management in recent years (e.g., Alper, Tjosvold, & Law, 2000; Behfar,
Peterson, Mannix, & Trochim, 2008; De Dreu & Van Vianen, 2001; DeChurch, Hamilton, &
Haas, 2007; Kuhn & Poole, 2000).
However, in spite of this promising trend, current research in team conflict management
remains subject to several limitations. Arguably, one of the most significant limitations concerns
the heavy reliance on existing conflict management theories and typologies (e.g., Blake &
Mouton, 1964; Deutsch, 1949, 1973; Rahim, 1983; Thomas & Kilmann, 1974; Van de Vliert &
Euwema, 1994) that are typically conceptualized at the individual level. More specifically,
existing studies in team conflict management have tended to assume similar or shared conflict
management approaches among individual members in the team (e.g., Alper, et al., 2000;
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DeChurch & Marks, 2001; Jordan & Troth, 2004; Somech, Desivilya, & Lidogoster, 2008). For
example, a team may be characterized as having a cooperative, competitive, or avoidant conflict
management approach (Chen & Tjosvold, 2002a; De Dreu & Van Vianen, 2001; Tjosvold, Yu &
Wu, 2009). While a few studies in the literature have also looked at teams with two or more
conflict management approaches, such approaches were still assessed at the team rather than the
individual level; in other words, these multiple approaches within the team were still assumed to
be displayed by all individual members (e.g., Behfar, et al., 2008; Kuhn & Poole, 2000; Poole &
Dobosh, 2010).
Overall, this over-reliance on existing individual-level conflict management theories and
typologies inadvertently constrains our current understanding of team conflict management. So
far, we know very little about what causes individual team members to vary, rather than
converge, in their conflict management approaches within a given team. What are the critical
factors shaping variability in team conflict management, and what consequences might such
variability lead to? These are questions yet to be addressed in current team conflict management
research.
Further, some team conflict management scholars have highlighted the need for future
research to improve or refine our theorizing about conflict management at the team level (e.g.,
Behfar, et al., 2008; DeChurch & Marks, 2001). Research in other team-related domains, such as
group dynamics and social influence processes (e.g., Abrams, Wetherell, Cochrane, Hogg, &
Turner, 1990; Asch, 1952, 1956; Cialdini & Goldstein, 2004; Isenberg, 1986; Mackie, 1987;
Nemeth, 1986), and group composition (e.g., Earley & Mosakowski, 2000; Kanter, 1977; Lau &
Murnighan, 1998, 2005; Li & Hambrick, 2005) have also demonstrated evidence of instances in
which individuals may differ from others in their perceptions, attitudes and behaviors within a
3
group context. Accordingly, such findings reinforce the importance of exploring when and how
variability in conflict management may occur in teams, and how such variability in turn affects
critical outcomes for individuals, teams or organizations.
Study purpose
Considering the above discussion, the purpose of this dissertation study was to begin
addressing the aforementioned limitations in existing team conflict management research.
Specifically, this study tested a new conceptual model of team-level conflict management
proposed by Tan (2011). Central to this model is a team-level construct, known as variant
conflict management (VCM), which refers to the distribution of cooperative and competitive
conflict approaches (Deutsch, 1949, 1973) among individual members of a team (Tan, 2011). In
this model, it is argued that conflict management behaviors, approaches or strategies can vary
among individual members when they handle conflicts within a team, and such variability can be
attributed to three key antecedent categories: salient conflict-relevant member characteristics,
team contextual determinants, and divergent team dynamics (Tan, 2011). Once VCM develops in
a team, it is in turn expected to lead to differential effects on important outcomes, such as team
performance and member satisfaction (Tan, 2011). It is also posited that such differential effects
will be a function of how cooperative and competitive conflict approaches are distributed among
team members, assuming that team members exert similar efforts in conflict handling with their
teams. Tan’s (2011) model suggests that these distributional patterns in conflict management
among individual members may be further organized into distinct profiles, that is, minimum,
moderate and maximum VCM profiles (see Figure 1 for this conceptual model).
To empirically test this model, content coding and latent class analyses were conducted to
assess the construct validity of the proposed VCM profiles (i.e., the patterns of variability in
4
individual conflict management) in actual teams. Once the VCM profiles were established,
regression analyses and planned comparisons were carried out to examine the relationships
proposed in the model. In particular, I investigated the relative effects of VCM and mean
cooperative and competitive team conflict management in teams on three specific team outcome
variables: team conflict efficacy, member satisfaction with the team’s conflict management
process, and team effectiveness. This study also examined the relationships between different
VCM profiles and these three team outcomes. Additionally, specific variables representing each
of the three antecedent categories predicting the development of VCM were identified, and the
relationships between these variables and VCM were assessed. Namely, these variables were
gender role diversity (as an indicator of ‘salient member characteristics’), perceived goal
interdependence among members (as a type of ‘team contextual determinant’), and subgroup
formation (as a form of ‘divergent team dynamics’).
Study contributions
This study contributed to the research literature in a number of ways. First, it added to
existing knowledge about team conflict management by assessing the presence of the VCM
profiles as conceptualized in Tan’s (2011) model. By assessing the relative effects of VCM and
mean team conflict management on team conflict efficacy, member satisfaction with the team’s
conflict management process, and team effectiveness, this study also investigated whether and
the extent to which VCM may predict outcomes above and beyond traditional notions of team
conflict management in the literature. Further, this study helped broaden our understanding about
possible impacts of team conflict management by examining how different VCM profiles may
exert differential effects on critical outcomes for teams. Last but not least, this study identified
and examined specific factors that represent the three antecedent categories proposed in the
5
model, and that are likely to cause variation in individual conflict management approaches
within teams.
In the following paragraphs, three key perspectives underlying the VCM model are
discussed. I refer to these as the ‘interactionist,’ ‘process,’ and ‘levels’ perspectives. It is
important to discuss these three perspectives, as they have been pivotal to the development of the
VCM model. An understanding of how these perspectives relate to the model should also allow
the reader to gain insights into the overall structure of the model, as well as how proposed
relationships among concepts in the model are organized.
Key perspectives underlying the variant conflict management model
The ‘interactionist’ perspective: Person versus Situation
The first perspective, that is, the ‘interactionist’ perspective, concerns the interaction
between person and situational factors in influencing human cognition, attitudes and behavior
(Lewin, 1946; Ross & Nisbett, 1991). In the conflict management literature, this ‘interactionist’
perspective has been dominant in shaping how conflict management scholars and researchers
theorize and conduct empirical inquiry on the topic. Today, most academics and practitioners
would agree that how people manage conflict is dependent on both person or individual factors
as well as situational characteristics. Examples of person-related factors predicting conflict
management include personality traits, such as self-monitoring (Baron, 1989), agreeableness
(Graziano, Jensen-Campbell, & Hair, 1996), extraversion, openness and conscientiousness (e.g.,
Antonioni, 1998; Moberg, 1998). Still, others involve cultural orientations (Ting-Toomey, et al.,
1991) and demographic attributes, such as race (Smith, Harrington, & Neck, 2000) and gender
(e.g., Gross & Guerrero, 2000; Rosenthal & Hautaluoma, 1988). As for situational predictors of
conflict management, these include power or status differences (e.g., Brewer, Mitchell, &
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Weber, 2002; Holt & DeVore, 2005; Renwick, 1975; Utley, Richardson, & Pilkington, 1989),
goal interdependence (Somech, 2008; Tjosvold, 1998), the opponent’s conflict approaches (e.g.,
Gross & Guerrero, 2000; Park & Antonioni, 2007), and trust (Davidson, McElwee, & Hannan,
2004).
Consistent with prior research on conflict management, the VCM model also draws from
the ‘interactionist’ perspective by suggesting that variability in team conflict management is also
likely to be a function of both person and situational factors. In this model, ‘salient conflict-
relevant member characteristics’ denote the category that captures possible person-related factors
while ‘team contextual determinants’ characterize situational factors within the team context.
Salient conflict-relevant member characteristics refer to the nature of and the extent to which
individual characteristics, such as demographic attributes, personality traits and cultural values,
are obvious or meaningful to members in conflict within the team, whether physically,
psychologically or both. Team contextual determinants, on the other hand, relate to the type and
strength of objective or subjective features in the team context that can affect how team members
think, feel or behave. For the empirical purposes of this study, I identified gender role diversity
as an internal team factor indicating salient conflict-relevant member characteristics, and
perceived goal interdependence as another variable denoting a type of team contextual
determinant. More detailed discussions on these variables, along with their proposed effects on
VCM, are provided in the next chapter.
The ‘process’ perspective: Team dynamics matter
The second key perspective, which I call the ‘process’ perspective, takes into account
aspects related to team dynamics. While it is important to know what person and/or situational
factors are likely to affect conflict management, it may be equally important to understand the
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underlying mechanisms through which these factors affect conflict management. The conflict
management literature has provided some evidence noting the importance of temporal and
process aspects in influencing conflict management behaviors in individuals and in groups (e.g.,
Baxter, 1982; Behfar, et al., 2008; Farmer & Roth, 1998; Jarboe & Witteman, 1996; Kuhn &
Poole, 2000; Poole & Dobosh, 2010; Rogers, 1987; Witteman, 1991). Other existing research,
especially in the group dynamics and group composition literatures, has also identified specific
processes or mechanisms through which individuals in groups may differ from one another in
terms of perceptions, attitudes and behaviors. In the area of group dynamics, such mechanisms
include majority and minority influence (e.g., Asch, 1952, 1956; Deutsch & Gerard, 1955;
Moscovici, 1976; Nemeth, 1986), group polarization (Isenberg, 1986), groupthink (Janis, 1972),
and group norms (e.g., Bettenhausen & Murnighan, 1985, 1991; Feldman, 1984). As for the
group composition literature, subgroup size and status (e.g., Blau, 1977; Kanter, 1977) and
coalition formation (e.g., Earley & Mosakowski, 2000; Gebhardt & Meyers, 1995; Lau &
Murnighan, 1998, 2005; Li & Hambrick, 2005) exemplify other aspects of the team interaction
process that have demonstrated effects on cognitive, affective or behavioral outcomes.
Following this ‘process’ perspective then, the VCM model considers the role of team
dynamics in predicting VCM by suggesting a third antecedent category, i.e., ‘divergent team
dynamics,’ in addition to salient conflict-relevant member characteristics and team contextual
determinants. Divergent team dynamics refer to aspects of the team interactions or mechanisms
through which individual members are influenced to deviate from others in the team. For this
study, I identified subgroup formation as an indicator of divergent team dynamics. Similar to
gender role diversity and goal interdependence, relevant literature and the hypothesized
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relationships between subgroup formation and VCM are discussed in greater detail in the next
chapter.
The ‘levels’ perspective: “The whole does not equal the sum of its parts”
The third perspective that underlies the VCM model, i.e., the ‘levels’ perspective,
involves determining the levels of analysis at which model constructs are specified. Given the
complexities often associated with the study of individual and group behavior in organizations,
levels theorists and scholars have reasoned and provided empirical support for the importance of
specifying the levels at which organizational phenomena are conceptualized, analyzed and
measured (e.g., Harrison & Klein, 2007; Klein, Dansereau, & Hall, 1994; Kozlowski & Klein,
2000). In the case of studying conflict management in teams, the levels at which this construct is
construed and measured are sometimes unclear or even unspecified (e.g., Desivilya & Yagil,
2005; Jarboe & Witteman, 1996; Jones & White, 1985). Even in instances where team conflict
management is explicitly construed and measured at the team level, researchers have generally
assumed that the construct of team conflict management possesses shared properties (Kozlowski
& Klein, 2000), and consequently, the aggregation of individual-level data to the team level is
often deemed as appropriate for measuring such constructs (e.g., Alper, et al., 2000; DeChurch &
Marks, 2001; Somech, 2008; for an exception, see Park & Park, 2008).
Contrary to such conventional assumptions and measurement practices, the VCM model
proposes an alternative way of conceptualizing and measuring team conflict management (Tan,
2011). Specifically, it suggests that team conflict management may be construed as a team-level
construct with configural properties (Kozlowski & Klein, 2000). This means that individual
members’ approaches in conflict management are not assumed to converge within the team;
rather, differences in these individual approaches may produce variability in conflict
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management at the team level, i.e., VCM, which will in turn lead to different effects on outcomes
(Tan, 2011). I expound on the conceptualization of VCM further in the following chapter.
Dissertation structure
The remainder of this dissertation is organized as follows. The next chapter critically
reviews existing research on team conflict management, followed by a discussion of the
conceptualization of VCM. In this chapter, I also present the theoretical and research-based
arguments supporting the research question and hypotheses examined in this study.
Following the literature review chapter, the methodology for the study is discussed. Here,
I provide detailed descriptions of the sampling strategy, research design, study procedures and
measures that were used. Next, I discuss preliminary, main, and supplementary analyses that
were conducted in this study. Finally, I conclude with a list of cited references and a set of
appendices containing materials that were used in the study.
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CHAPTER II: LITERATURE REVIEW
Overview
This chapter begins with a critical review of existing literature concerning team conflict
management. Next, the configural concept of team conflict management, i.e., variant conflict
management (VCM), is presented and discussed. Then, relative effects of VCM and mean team
conflict management on team conflict efficacy, member satisfaction with the team’s conflict
management process, and team effectiveness are considered and discussed. Following that, the
predicted effects of VCM profiles on the same three outcomes are also presented. Finally,
relevant literature on three antecedent variables of VCM, i.e., gender role diversity, perceived
goal interdependence, and subgroup formation, are reviewed. The hypothesized relationships
among these antecedent variables and VCM are also discussed at the end of the literature review
associated with each variable.
Team conflict management: A critical review
Team conflict management refers to the strategies, approaches or behaviors used by
individual members of a team to resolve or handle disagreements, tensions or incompatible
activities among one another (DeChurch & Marks, 2001). Despite an extensive and longstanding
research interest in conflict and its management (Lewicki, et al., 1992; Wall Jr. & Callister,
1995), empirical work on team conflict management has only garnered attention over the last
thirty years or so. Nevertheless, in this relatively short span of time, we have gathered a
considerable amount of knowledge about the antecedents, dynamics and effects of conflict
management in teams. In the subsequent paragraphs, existing theories and typologies of conflict
management that were frequently used in present team conflict management research will first be
11
discussed, followed by summary reviews of the antecedents and consequences of team conflict
management that have been studied in the literature.
Common theories and typologies in team conflict management research
The conflict management literature abounds with conceptual frameworks characterizing
how conflict is managed (Rahim, 2001). In the narrower domain of team conflict management,
however, the most commonly used theories of conflict management in empirical research are
Deutsch’s (1949, 1973) theory of cooperation and competition, and Rahim and Bonoma’s (1979)
two-dimensional model of interpersonal conflict handling styles (for the former theory, e.g.,
Alper, et al., 2000; Chen, Liu & Tjosvold, 2005; Hempel, Zhang, & Tjosvold, 2008; Tjosvold,
Law, & Sun, 2006; for the latter theory, e.g., Desivilya & Yagil, 2005; Jordan & Troth, 2004;
Somech, et al., 2008).
Deutsch’s (1949, 1973) theory of cooperation and competition exemplified one of the
early one-dimensional models in conflict management. Specifically, he dichotomizes conflict
management into two mutually exclusive modes: cooperation and competition. When individuals
use a cooperative process during conflict management, they may view the conflict situation as a
mutual problem to be resolved, perceive similar interests and concerns with the other, adopt a
more trusting and friendly attitude toward the other, as well as communicate more and seek to
understand the other’s perspectives and needs (Deutsch, 2006). On the other hand, when
individuals use a competitive approach toward the conflict, they tend to view the conflict as a
zero-sum or win-lose situation, perceive less similarities in interests and concerns with the other,
adopt a less trusting and friendly attitude, as well as communicate less with the other party
(Deutsch, 2006).
12
By contrast, Rahim and Bonoma’s (1979) model of conflict handling styles built upon
earlier conflict management models developed by Blake and Mouton (1964) and Thomas and
Kilmann (1974). This model differentiates conflict management styles in terms of two
dimensions: concern for self (the extent to which one attempts to satisfy one’s concerns) and
concern for others (the extent to which one attempts to satisfy others’ concerns). The modes of
interpersonal conflict handling styles proposed by Rahim and Bonoma (1979) include integrating
(high self- and other-concerns), obliging (low self- but high other-concerns), avoiding (low self-
and other-concerns), compromising (intermediate self- and other-concerns) and dominating (high
self- but low other-concerns). Furthermore, it has been noted that these five conflict styles could
also be organized along two other types of dimensions: integrative and distributive (Rahim,
2001). The integrative dimension (integrating – avoiding) refers to the degree to which both
one’s and others’ concerns are satisfied, while the distributive dimension (dominating – obliging)
refers to the ratio of satisfaction obtained for either one’s or others’ concerns (Rahim, 2001).
Another frequently applied model of conflict management in many team conflict
management studies is Van de Vliert and Euwema’s (1994) meta-taxonomy of conflict
management (e.g., Chou & Yeh, 2007; DeChurch, et al., 2007; DeChurch & Marks, 2001). Van
de Vliert and Euwema (1994) developed this meta-taxonomy to integrate the multiple conflict
management taxonomies and to offer a more parsimonious framework for assessing conflict
management behaviors. To that end, they identified two dimensions—agreeableness and
activeness—as common factors that interrelate the different typologies of conflict handling (Van
de Vliert & Euwema, 1994). In other words, the integration of the conflict taxonomies meant that
previously described conflict styles (e.g., cooperative, competitive, integrative, avoiding,
dominating, obliging and compromising) are interrelated in terms of their positive or negative
13
relations with agreeableness and activeness. Van de Vliert & Euwema (1994) defined
agreeableness as “the extent to which conflict [management] behaviors make a pleasant and
relaxed rather than unpleasant and strainful impression” and activeness as “the extent to which
conflict [management] behaviors make a responsive and direct rather than inert and indirect
impression” (p. 676).
While the aforementioned theories and typologies (viz., Deutsch, 1949, 1973; Rahim &
Bonoma, 1979; Van de Vliert & Euwema, 1994) have been applied in most of team conflict
management research, still, other studies have chosen a different approach to conceptualize and
measure the construct. Instead of relying on a specific theory or framework, these studies used a
combination of conflict management theories and typologies in their conception and
measurement of team conflict management (e.g., Boros, et al., 2010; Farmer & Roth, 1998;
Jarboe & Witteman, 1996; Jones & White, 1985; Kuhn & Poole, 2000). Boros and associates
(2010), for instance, conceptualized team conflict management based on a combination of Rahim
and Bonoma’s (1979) model and a fourth dimension—third party intervention—identified by De
Dreu and Van Vianen (2001), but measured the same construct using a mix of scale items
developed by Rahim (1983), Janssen, Van de Vliert, and Veenstra (1999), and Putnam and
Wilson (1982). Jarboe and Witteman (1996), in a different study, construed team conflict
management as involving three modes: integrative, distributive, avoidance communication; these
modes were based on a number of conflict management typologies developed by Kilmann and
Thomas (1977), Putnam and Wilson (1982), and Rahim (1983).
Undoubtedly, the various existing conflict management theories in the literature have
aided greatly to our understanding of conflict management in teams. Yet, almost all current team
conflict management studies that rely on one or more existing conflict management theories do
14
not take such within-team differences in conflict management approaches into account. Since
existing conflict management theories are largely conceptualized at the individual level, most
team conflict management researchers have, in turn, assumed that individual conflict
management styles will likely converge at the team level. As a result, there is little knowledge
about when and how differences in individual conflict management contribute, if at all, to
outcomes such as team effectiveness and satisfaction.
Fortunately, team conflict management researchers have begun to recognize such
limitations associated with the use of individual-level conflict management theory in team-level
research (e.g., Behfar, et al., 2008; DeChurch & Marks, 2001; Tekleab, et al., 2009). In recent
years, a number of them have also begun to use exploratory methods and emergent data, rather
than rely on existing models or theories, to extend our understanding of the antecedents,
dynamics and effects of team conflict management (e.g., Behfar, et al., 2008; Poole & Dobosh,
2010). For instance, Behfar and colleagues (2008) applied a number of exploratory methods,
such as concept mapping, multidimensional scaling and cluster analysis, and uncovered different
conflict management strategies used by 65 MBA student teams. They also found that these
strategies were associated with differing patterns of team performance and member satisfaction
over time. In another example, Poole and Dobosh (2010) studied the emergence of conflict
management patterns in jury deliberations and the effects of such patterns on jury decisions,
using interactional analysis on archival data. In their analyses, they found that different conflict
management approaches and norms developed in each deliberation, which in turn led to different
decision outcomes. Specifically, in one deliberation, conflicts were often held in check through
suppression of explicit disagreements and emphasis on the task at hand, which subsequently
resulted in quick decisions being made. In the other deliberation, disagreements were handled
15
openly and for longer durations; however, most of these disagreements were left unresolved and
eventually led to an impasse in the final decision. Though these studies remain few and far in
between, they nevertheless indicate a need for new conceptions of team conflict management to
be developed in the literature.
Antecedents of team conflict management
Several antecedent factors that are likely to influence how individuals in teams manage
conflict have been identified in the literature. These factors may be further organized into two
general categories: ‘individual differences’ and ‘team contextual characteristics.’ The former
category concerns variables that stem from individual team members’ natural or innate
predispositions, preferences or orientations. Such variables include personality traits (e.g., Jones
& White, 1985; Kleinman, Palmon, & Lee, 2003), emotional intelligence (Jordan & Troth,
2004), self-efficacy (e.g., Desivilya & Eizen, 2005; Leon-Perez, Medina, & Munduate, 2011),
and cultural orientations (e.g., Boros, et al., 2010; Paul, Samarah, Seetharaman, & Mykytyn Jr.,
2004). As for context, variables that belong in this category describe specific characteristics or
aspects associated with the team context. These characteristics include team task type (e.g., Kuhn
& Poole, 2000; Oetzel, 1999; Poole & Dobosh, 2010), team size (Farmer & Roth, 1998), team
conflict types (e.g., DeChurch & Marks, 2001; Desivilya & Yagil, 2005; Tekleab, et al., 2009),
hierarchical positions among team members (Kleinman, et al., 2003), team identification (e.g.,
Desivilya & Eizen, 2005; Somech, et al., 2008), and perceived interdependence among members
(e.g., Desivilya & Eizen, 2005; Somech, 2008; Somech, et al., 2008).
Additionally, and to a limited extent, the literature also reveals another group of
antecedents that may be best described as factors relating to the dynamical or temporal aspects of
a team’s interaction or lifespan. Examples of these factors include team development stages
16
(Baxter, 1982), team norms (Behfar, et al., 2008), team interaction periods (Witteman, 1991),
and time (Farmer & Roth, 1998; Poole & Dobosh, 2010). In spite of the few number of studies
available, this subset of research suggests that aside from individual differences and team
contextual factors, it is also important to examine the interactional patterns and dynamics that
characterize team conflict management over time. This is consistent with the views of group
development theorists (e.g., Bales, 1950; Gersick, 1988; Tuckman, 1965) and some group
conflict researchers (e.g., Behfar, et al., 2008; Greer, Jehn, & Mannix, 2008; Jehn & Mannix,
2001) as well.
Considering the antecedents discussed above, it is clear that a substantial amount of
research has been conducted to help us understand the predictors of team conflict management.
However, despite such research progress, it remains difficult to draw more systematic
conclusions about how these predictors influence team conflict management in general. One
reason for this difficulty may be attributed to the myriad ways in which the construct of team
conflict management has been conceptualized and measured. For example, Desivilya & Eizen
(2005) examined the effects of self-efficacy and team identification on team conflict
management. In their study, team conflict management is construed using Rahim’s (1983) five-
modal typology of conflict styles: integrating, obliging, avoiding, compromising and dominating
conflict styles. By contrast, Boros and colleagues (2010), in their study assessing the impact of
cultural member diversity on team conflict management, they conceptualized team conflict
management based on De Dreu and Van Vianen’s (2001) approach, which suggests only three
types of conflict styles: avoiding, contending and cooperating. Still, other researchers have used
different existing conflict management theories and frameworks to conceptualize team conflict
17
management (e.g., Farmer & Roth, 1998; Hempel, Zhang, & Tjosvold, 2009; Jarboe &
Witteman, 1996; Jones & White, 1985; Kleinman, et al., 2003).
Accordingly, such research points to the need for new directions in the conception of
team conflict management so that more consistent conceptualizations of the construct can be
adopted by researchers, and in turn, more systematic conclusions can be made about the effects
different predictors may exert on conflict management at the team level.
Effects of team conflict management
When it comes to studying the impact of team conflict management on outcomes, a large
number of studies have focused on two types of outcomes: team effectiveness or performance
(e.g., Alper, et al., 2000; Behfar, et al., 2008; Chen & Tjosvold, 2002a; De Dreu & Van Vianen,
2001; DeChurch & Marks, 2001; Jones & White, 1985; Quigley, Tekleab, & Tesluk, 2007;
Tjosvold, Law, & Sun, 2006) and overall member satisfaction (e.g., Behfar, et al., 2008; De Dreu
& Van Vianen, 2001; DeChurch & Marks, 2001; Kleinman, et al., 2003; Quigley, et al., 2007).
Other outcomes of team conflict management include team functioning (i.e., voice, compliance
and helping behavior, De Dreu & Van Vianen, 2001), perceived warmth and productivity in
team atmosphere (Kleinman, et al., 2003), team innovativeness (Tjosvold, Yu, & Wu, 2009),
team cohesion (Tekleab, Quigley, & Tesluk, 2009), team justice (Chen & Tjosvold, 2002a),
organizational innovation (Chen, Liu, & Tjosvold, 2005), and organizational performance (Liu,
Fu, & Liu, 2009).
As discussed earlier, differences in how team conflict management has been construed in
the literature also pose challenges in comparing its effects across studies and gathering more
systematic observations about its benefits and drawbacks on outcomes (e.g., Behfar, et al., 2008;
De Dreu & Van Vianen, 2001; DeChurch & Marks, 2001; Kuhn & Poole, 2000; Quigley, et al.,
18
2007). DeChurch & Marks (2001), for instance, examined the effects of team conflict
management and task conflict on group performance and member satisfaction. In their study,
team conflict management was conceptualized using Van de Vliert and Euwema’s (1994) meta-
taxonomy of conflict management; here, conflict management behaviors were described as
active or agreeable among team members. Their findings noted that active team conflict
management had no effect on team performance, while agreeable team conflict management
exerted a direct positive effect on member satisfaction (above and beyond the effects of task
conflict). Another study by Quigley, Tekleab, & Tesluk (2007), which also looked at the impact
of team conflict management and group conflict on team performance and satisfaction, used a
different approach to conceptualize the construct. In this case, team conflict management was
construed as the degree to which team members engaged in conflict management processes,
based on Cosier and Dalton’s (1990) approach. In their findings, they noted that team conflict
management was positively related to team satisfaction.
At first glance, the findings on the team conflict management-satisfaction relationship in
both studies may appear consistent or similar. However, a closer examination would reveal that
the results from DeChurch and Mark’s (2001) study indicated that it was the quality of team
conflict management (i.e., agreeable or active conflict management behaviors) that accounted for
its effects on member satisfaction, and not just the level of team conflict management present
(i.e., the extent of conflict management processes used), as suggested in Quigley, Tekleab &
Tesluk’s (2007) findings. As such, and in line with the earlier discussion on the antecedents of
team conflict management, this review of existing research on the effects of team conflict
management also highlights the need for further developments in our conception of team conflict
management, so we can understand its effects on critical outcomes more clearly and consistently.
19
Following the above discussion on the need for new conceptions of team conflict
management to be developed in the literature, I discuss one such concept of team conflict
management, i.e., variant conflict management, in the next section.
Conceptualizing variant conflict management
Variant conflict management (VCM) is defined as the degree to and manner in which
conflict management approaches differ among individual members of a team (Tan, 2011).
Inherent in this definition is the emphasis on within-team variability, rather than similarity, in
how individual members manage team conflict. In the subsequent sections, I provide detailed
descriptions of the conceptualization of VCM, followed by a discussion of how VCM may in
turn affect important team outcomes.
In conceptualizing VCM, Tan (2011) draws from relevant theory and research in the
levels literature (Klein, et al., 1994; Kozlowski & Klein, 2000), including recent theory on group
diversity conceptualizations posited by Harrison and Klein (2007). Kozlowski and Klein (2000),
in their book on multilevel theory and research in organizations, argued that group phenomena
could be construed as unit-level constructs possessing global, shared or configural unit properties
(p. 29). Of these three construct types, configural constructs are most applicable to our
discussion of VCM here. Specifically, they explained that configural constructs “capture patterns
of individual perceptions or behavior within a unit” (p. 31). In other words, these constructs
describe the differential contributions of individual cognitions, emotions or behaviors and how
they combine to yield a team-level phenomenon. Team creativity, for example, may be construed
as a configural construct, in terms of the varying number of novel ideas or information individual
members contribute toward the collective creative output. Here, the individual contributions of
creative output are distinct among team members (e.g., some team members tend to produce
20
more creative ideas than others) and depending on the compilation of these individual
contributions, the level of creativity for the team as a whole will in turn differ.
Based on Kozlowski and Klein’s (2000) notion of configural constructs, VCM is thus
conceptualized as a team-level construct with configural unit properties, as it too, is concerned
with varying patterns of individual conflict management approaches in a given team (Tan, 2011).
For instance, a team that is experiencing internal conflict may be characterized by most, if not
all, individual members being highly cooperative or competitive in their conflict management
approaches. Alternatively, it may comprise of two evenly sized subgroups of members that
employ markedly different conflict management approaches: one subgroup being highly
cooperative, and the other being highly competitive. Such differences in individual members’
display of conflict management reflect different patterns or distributions at the team level, and
hence, the emergence of VCM.
To further specify the construct of VCM, Tan (2011) applied a recent theoretical
framework on group diversity typologies, proposed by Harrison and Klein (2007). Harrison and
Klein (2007) defined group diversity as “the distribution of differences among the members of a
unit with respect to a common attribute” (p. 1200). They argued that group diversity may be
conceptualized and specified in terms of three types: separation, variety and disparity. Of these
three, separation-based diversity constructs are most relevant in the theorizing of VCM.
According to Harrison and Klein (2007), separation-based diversity constructs indicate the
distribution of specific attitudes, values or behaviors, in terms of similarity or dissimilarity, along
a single continuum. Akin to the concept of separation-based diversity constructs then, VCM
denotes a separation-based construct of diversity in conflict management (Tan, 2011). It
describes how individual conflict management approaches are distributed to a lesser (more
21
similar) or greater (more dissimilar) extent along a single continuum. Here, Deutsch’s (1949,
1973) theory of cooperation and competition is applied in construing VCM as the distribution of
individual conflict management in terms of cooperative and competitive approaches along a one-
dimensional bi-polar continuum. In other words, members in a team may differ from one another
in their positions along the cooperation-competition continuum. For example, members may be
co-located closely with one another on the far ends of cooperation or competition, or they may
be evenly distributed along the continuum in terms of their cooperative and competitive
approaches to conflict.
There are several reasons supporting the application of Deutsch’s (1949, 1973) theory in
conceptualizing VCM. First, unlike other existing two-dimensional conflict management theories
and multi-modal typologies, Deutsch’s (1949, 1973) theory describes a one-dimensional
framework that is compatible with the notion of separation-based constructs in Harrison and
Klein’s (2007) framework. His theory also allows for greater parsimony in the conceptual
development of VCM given its focus on two fundamental modes of conflict management:
cooperation and competition. These two fundamental modes have also been found in other
existing conflict management typologies, e.g., the integrative and distributive dimensions in
Rahim and Bonoma’s (1979) model of conflict handling styles.
Second, as one of the most commonly used theoretical models in existing team conflict
management research, the application of Deutsch’s (1949, 1973) theory in the conceptualization
of VCM also contributes to our current knowledge of team conflict management by enhancing
consistency and interpretability of possible antecedents of VCM and the potential effects of
VCM on important outcomes.
22
Third, from an empirical standpoint, Deutsch’s (1949, 1973) propositions have also been
tested extensively and received substantial support in the literature (Johnson & Johnson, 2005).
In a recent monograph, Johnson and Johnson (2005) noted that over 750 research studies have
been conducted to examine the relative effects of cooperation and competition on a wide range
of dependent variables (e.g., task achievement, interpersonal relationships, and self-esteem), and
the conditions under which they operate (p.325). They also found that the mean effect sizes for
the impact of cooperation and competition on various dependent variables were relatively strong
(0.57 to 0.93; see p.304). The majority of these studies also involved experimental research with
highly controlled conditions and random assignment procedures, thus suggesting high internal
validity of the findings observed (Johnson & Johnson, 2005).
Taken altogether, the aforementioned reasons suggest that the application of Deutsch’s
(1949, 1973) theory allows for the conceptualization of VCM to be based not just on sound
theory but also on significant empirical research.
Variant conflict management profiles
Variant conflict management (VCM) may be characterized in terms of three profiles:
minimum, maximum and moderate VCM (Tan, 2011). It is important to note that the first two
profiles—minimum and maximum VCM—represent ‘pure’ forms of how differential
distributions of individual conflict management approaches may be compiled in a team. In
reality, however, most work teams are likely to be characterized by the third profile, i.e.,
moderate VCM. More detailed discussions on each of these three profiles are offered in the
following paragraphs.
Minimum VCM. The minimum VCM profile describes a team in which its members are
co-located altogether on a given position along the conflict management continuum (see Figure
23
2, Tan, 2011). This profile can be further organized into two sub-types: minimum cooperative
VCM and minimum competitive VCM. Minimum cooperative VCM exists when all members of
a team are cooperative in handling conflict, whereas minimum competitive VCM occurs when
all members are competitive in their individual conflict management approaches. Of the three
profiles, the minimum VCM profile is analogous to shared or homogeneous team conflict
management (Tan, 2011).
Moderate VCM. A moderate VCM profile describes a team where its members are
distributed unevenly along the conflict management continuum (see Figure 3, Tan, 2011). There
are also two possible sub-types depicting moderate VCM: the first sub-type describes a team
whereby the majority of its members are cooperative. The second sub-type depicts the opposite:
a team that consists of a competitive majority (Tan, 2011).
Maximum VCM. A team that possesses the maximum VCM profile is comprised of
members who are strongly and evenly split toward either end of the conflict management
continuum (see Figure 4, Tan, 2011). In other words, such a team consists of two evenly sized
subgroups: one that is highly cooperative, and the other highly competitive. The maximum VCM
profile also describes what Lau and Murnighan (1998) have proposed as a group ‘faultline’, i.e.,
a “hypothetical line that may split[s] a group into subgroups based on one or more attributes ” (p.
328). A team with the maximum VCM profile is analogous to a team with a strong faultline that
separates its members into two subgroups, based on how they manage conflict (Tan, 2011).
Considering the above discussion of VCM and the typology of its profiles, the first
objective of this dissertation study, then, was to investigate the presence and prevalence of the
proposed VCM profiles in actual teams. To that end, this study examined the following
hypothesis:
24
H1: The five proposed VCM profiles, i.e., minimum cooperative, minimum
competitive, moderate cooperative, moderate competitive, and maximum VCM
profiles, will be present in teams.
Effects of variant conflict management
Earlier in this chapter, I provided arguments to support the case for assessing whether
differences among individual members’ conflict management approaches can be observed within
teams. More importantly, it is also reasoned that such differences in members’ conflict
management strategies within teams may affect team processes and outcomes in ways that may
not be explained by traditional concepts of team conflict management, i.e., similar or shared
conflict management approaches among members within teams. Specifically, it is expected that
the effects of VCM (based on teams’ standard deviation scores), relative to those of mean
cooperative team conflict management (based on teams’ mean cooperative conflict management
scores), will likely lead to lower levels of team outcomes, specifically team conflict efficacy,
members’ satisfaction with their teams’ conflict management process, and overall team
effectiveness (Hypotheses 2a to 2c). It is also posited that the effects of VCM, when compared to
those of mean competitive team conflict management (based on teams’ mean competitive
conflict management scores), will be associated with higher levels of team conflict efficacy,
members’ satisfaction with the team conflict management process, and team effectiveness
(Hypotheses 3a to 3c). I expound on my reasoning for the above hypotheses in the following
paragraphs.
Relative effects of VCM and mean cooperative team conflict management. The first team
outcome of interest, i.e., team conflict efficacy, may be defined as the extent to which members
believe they may successfully handle different conflict situations within the team (Alper, et al.,
25
2000). Alper and colleagues (2000), in a field study with 61 self-managed production teams,
found that teams that were characterized as cooperative in their conflict management approaches,
based on their mean scores in cooperative conflict management, were more likely to report
higher levels of conflict efficacy (Alper, et al., 2000). Such findings suggest that similarly
cooperative members in a given team are able to handle disagreements constructively, address
one another’s concerns and interests, and ultimately create a shared sense of efficacy in dealing
with conflicts among themselves.
By contrast, a team with both cooperative and competitive members, i.e., a team with
VCM, is likely to experience greater difficulties in reaching shared consensus or bridging
opposing viewpoints to resolve the conflict at hand. Prior research examining the cooperative
and competitive dynamics in social interactions has found competition to be a more potent force
than cooperation (e.g., Kelley & Stahelski, 1970). Kelley and Stahelski (1970), for instance,
conducted a series of experiments about interpersonal interactions using the Prisoner’s Dilemma
game. Their findings concluded that cooperative parties are likely to be influenced by their
competitive opponents’ behaviors, and as a result, adopt more competitive strategies themselves.
Consequently, these interpersonal interactions become more competitive in nature, and in turn,
lead to more negative eventual outcomes for both parties.
Considering these findings, it is thus plausible that teams with VCM are also likely to
experience more competitive dynamics, as competitive members in such teams are more inclined
toward exerting their ideas and opinions over others, while cooperative members within the
teams are likely to struggle to find common ground with their competitive peers in order to
develop integrative solutions for the team as a whole. Over time, the interactions between the
cooperative and competitive members in the team will likely become more competitive in nature
26
(Kelley & Stahelski, 1970). Therefore, this should also result in teams with VCM feeling less
confident in their ability to resolve conflicts effectively, i.e., experiencing lower levels of conflict
efficacy, compared to teams whose members share similar cooperative conflict management
approaches (Hypothesis 2a).
The second team outcome, member satisfaction with the team’s conflict management
process, is concerned with the degree to which team members feel satisfied with how their teams
handle internal conflicts. Prior research has shown that group members’ preferences for
cooperative conflict management approaches were positively related to higher levels of
satisfaction with their group processes, including conflict management (Park & Park, 2008).
Moreover, this relationship between members’ conflict management approaches and satisfaction
with group processes was stronger when members were more similar in their cooperative
approaches within the group (Park & Park, 2008). Such findings suggest that, relative to
members who share similar cooperative conflict management approaches within the team, teams
whose members differ in their conflict management approaches, i.e., teams with VCM, are
therefore more likely to experience lower levels of satisfaction with their team processes,
including their team’s conflict management process (Hypothesis 2b).
The third team outcome, team effectiveness, is defined in this study as the extent to
which team members perceive themselves as being satisfied with their work, committed to the
goals of their work, and successful in managing their work (Alper, et al., 2000). Evidence from
the team conflict management literature has consistently revealed that cooperative teams were
associated with higher levels of team effectiveness, when compared to competitive teams (e.g.,
Alper et al., 2000; Somech, et al., 2008; Tjosvold, Law & Sun, 2006). In cooperative teams,
members were more likely to perceive less detrimental conflict within the team (Tjosvold, et al.,
27
2006) and to hold higher levels of affective trust with one another (Hempel et al., 2008), thus
leading to greater team effectiveness. When it comes to teams whose members differ in their
conflict handling approaches (i.e., teams with VCM), the differences in which cooperative and
competitive members approach the same conflict within the same teams are likely to be
accompanied by differing perceptions and feelings toward the conflict issues involved.
Cooperative members may be motivated to seek out solutions that satisfy everyone, while
competitive members may be more concerned with addressing their own interests or motives.
Over time, the interplay between cooperative and competitive members will likely become more
competitive in nature (Kelley & Stahelski, 1970), and thus impair the team’s ability to perform
or function effectively. As such, a team with VCM will likely be less effective than a team
whose members share similar approaches in conflict management (Hypothesis 2c).
H2a: VCM (based on teams’ standard deviation scores) will be negatively associated
with team conflict efficacy, with mean cooperative team conflict management
scores being held constant.
H2b: VCM (based on teams’ standard deviation scores) will be negatively associated
with member satisfaction with the team’s conflict management process, with mean
cooperative team conflict management scores being held constant.
H2c: VCM (based on teams’ standard deviation scores) will be negatively associated
with team effectiveness, with mean cooperative team conflict management scores
being held constant.
Relative effects of VCM and mean competitive team conflict management. When it comes
to competitive teams, researchers have found that such teams, compared with cooperative ones,
were more likely to report lower levels of conflict efficacy (Alper et al., 2000). Competitive
28
teams have also been found to be associated with lower levels of team effectiveness (e.g., Alper
et al., 2000; Somech, et al., 2008; Tjosvold, Law & Sun, 2006). Teams with all or mostly
competitive members approach internal conflicts from a ‘win-lose’ mindset, adopt more
combative stances, and seek to attain their own interests and goals at the expense of others’
(Deutsch, 1949, 1973). Members of competitive teams were also more likely to perceive more
detrimental conflict (Tjosvold et al., 2006) and to hold lower levels of cognitive trust with one
another (Hempel et al., 2008), thus resulting in lower levels of team effectiveness. In competitive
teams, it is possible that at least some members in these teams will feel less confident and able to
deal with the team’s conflicts as they may feel that they have ‘lost’ in the arguments and debates,
with their concerns remaining unmet or voices going unheard. Feelings about their team’s
conflict management process are also more likely to be negative. In these teams then, the overall
sense of conflict efficacy, member satisfaction about the team’s conflict management process,
and team effectiveness are thus likely to be adversely affected.
Teams with a mix of cooperative and competitive members, i.e., teams with VCM, on the
contrary, may benefit from having some cooperative members within them. Cooperative
members in these teams, assuming they are consistent and confident in their approaches, may be
able to elicit some degree of cooperation from their peers within the teams, in the form of
minority influence (Moscovici & Nemeth, 1974). While such minority influence of cooperative
members may be unlikely to overcome more potent and negative impact of their competitive
peers within the same team, it may nonetheless still be able to buffer some of the negative effects
associated with competitive approaches in the team. As such, it is possible that relative to
competitive teams, teams with VCM will experience lower levels of conflict efficacy, member
satisfaction with the team’s conflict management process, and team effectiveness respectively.
29
H3a: VCM (based on teams’ standard deviation scores) will be negatively associated
with team conflict efficacy, with mean competitive team conflict management
scores being held constant.
H3b: VCM (based on teams’ standard deviation scores) will be negatively associated
with member satisfaction with the team’s conflict management process, with mean
competitive team conflict management scores being held constant.
H3c: VCM (based on teams’ standard deviation scores) will be negatively associated
with team effectiveness, with mean competitive team conflict management scores
being held constant.
Relative effects of various VCM profiles. Much research has been conducted to
understand the effects of team conflict management on various outcomes and at different levels
of analysis. Findings in the literature indicate that cooperative team conflict management is
generally associated with positive team outcomes, such as increased team efficacy (Alper, et al.,
2000), higher levels of affect-based trust among team members (Hempel, et al., 2008), and
enhanced team performance (e.g., Behfar, et al., 2008; Kuhn & Poole, 2000; Somech, et al.,
2008). Competitive team conflict management, on the other hand, has been linked to more
detrimental effects on outcomes such as lower team efficacy (Alper, et al., 2000), lower levels of
cognition-based trust among members (Hempel, et al., 2008), and reduced team performance
(e.g., Behfar, et al., 2008; Hempel, et al., 2008; Kuhn & Poole, 2000; Somech, et al., 2008).
Given the conceptual similarities between shared cooperative and competitive conflict
management and minimum cooperative and competitive VCM respectively, it is expected that
the minimum cooperative VCM profile is also likely to be associated with positive team
outcomes, whereas the minimum competitive VCM profile will likely be related to negative team
30
outcomes. More specifically, I postulate that relative to all other VCM profiles, a minimum
cooperative VCM profile will likely lead to the highest levels of team conflict efficacy, member
satisfaction with the team’s conflict management process, and team effectiveness (Hypotheses
4a-4c); by contrast, when compared with all other VCM profiles, a minimum competitive VCM
profile will likely lead to the lowest levels of team conflict efficacy, member satisfaction with the
team’s conflict management process, and team effectiveness (Hypotheses 5a-5c).
Unlike all other profiles with some or mostly competitive members, a minimum
cooperative VCM suggests that the cooperative approaches shared by all members in a team
should reinforce mutual active listening among members, the seeking of one another’s ideas and
concerns, and a shared motivation to identify and uncover important concerns that underlie the
team’s conflict (Deutsch, 1949, 1973). As a result, such open exchange of ideas and perspectives
that is engaged in a supportive climate should lend itself to more integrative solutions to the
conflict at hand (Deutsch, et al., 2006), and in turn, produce more positive team outcomes, e.g.,
higher team conflict efficacy (Alper, et al., 2000), greater member satisfaction with the team’s
conflict management process, and increased team effectiveness (Behfar, et al., 2008):
H4a: Minimum cooperative VCM profiles will be most positively associated with team
conflict efficacy.
H4b: Minimum cooperative VCM profiles will be most positively associated with
member satisfaction with the team’s conflict management process.
H4c: Minimum cooperative VCM profiles will be most positively associated with team
effectiveness.
As for minimum competitive VCM, when compared with all other profiles with some or
mostly cooperative members, the competitive approaches shared by all members in the team
31
serve to reinforce a ‘fixed-pie’ or ‘win-lose’ mentality among members, and create a highly
hostile and suspicious climate whereby members may view one another as barriers toward their
individual goals and motives (Deutsch, 1949, 1973). Such competitive dynamics should in turn
lead to reduced information sharing and decreased mutual understanding that could potentially
result in conflict resolution (Deutsch, et al., 2006); furthermore, levels of hostility may be
maintained or even escalated in ways that will hinder the team’s ability to resolve conflict
effectively or produce positive output (Behfar, et al., 2008; Pruitt & Kim, 2004). Accordingly,
this suggests more negative outcomes, such as lower levels of member satisfaction with the
team’s conflict management process, reduced team conflict efficacy (Alper, et al., 2000), and
decreased team effectiveness for a team with a minimum competitive VCM profile:
H5a: Minimum competitive VCM profiles will be most negatively associated with team
conflict efficacy.
H5b: Minimum competitive VCM profiles will be most negatively associated with
member satisfaction with the team’s conflict management process.
H5c: Minimum competitive VCM profiles will be most negatively associated with team
effectiveness.
When it comes to moderate VCM profiles, their effects on team performance and
member satisfaction will depend on the specific moderate VCM profile scenario involved. Recall
that moderate VCM profiles may be categorized into two sub-types: one that is characterized by
a cooperative majority, and the other by a competitive majority. These two sub-types
representing moderate VCM are expected to produce different impacts on team performance and
satisfaction. In this study, it is predicted that relative to a moderate VCM with a competitive
majority, a moderate VCM with a cooperative majority will contribute to higher levels of team
32
conflict efficacy, member satisfaction with the team’s conflict management process, and team
effectiveness (Hypotheses 6a-6c).
In a team where most of its members are cooperative (cooperative majority) and the
remaining few are competitive (competitive minority), it is likely that the cooperative majority
will be able to exert its majority influence given its numerical advantage within the team,
especially early on in the team’s lifecycle (Moscovici, 1976, Nemeth, 1986). Accordingly, this
provides more structural stability for cooperative norms and standards to emerge and guide
member perceptions and behavior within the team (Axelrod, 1984; Bettenhausen & Murnighan,
1991; Deutsch & Gerard, 1955). At the same time, the competitive minority within the team is
likely to assert its position and viewpoints during the team discussion and interactions as well.
Considering the cooperative nature of the majority, it is likely that majority subgroup members
will be inclined to integrate the competitive minority’s concerns and perspectives, as part of their
attempt to achieve integrative and mutually shared outcomes for all. Furthermore, assuming that
the competitive minority is consistent and confident in conveying its position or differing
perspectives, some degree of minority influence is likely to occur (Moscovici & Nemeth, 1974),
and as a result, the integration of differing ideas into the overall team process will likely lead to
higher quality outcomes. With enhanced team output, members are likely to feel more confident
in their ability to manage internal conflicts, and to feel more satisfied with their conflict
management process as well.
On the other hand, a team with a competitive majority (and a cooperative minority) is
likely to experience relatively negative cognitive, affective and performance outcomes. Here, the
competitive majority is also likely to exert significant majority influence, given its larger
numerical size and representation within the team (Moscovici, 1976, Nemeth, 1986). This
33
influence exerted by the competitive majority is likely to create more competitive dynamics
within the team as a whole over time, as cooperative minorities are likely to adapt their
cooperative approaches toward more competitive ones (Kelley & Stahelski, 1970). As
competitive dynamics dominate the nature of member interactions within the team, the overall
levels of team conflict efficacy, member satisfaction with the team’s conflict management
process, and team effectiveness are in turn likely to suffer as a result. Taken altogether, it is thus
reasonable to expect that a moderate VCM with a cooperative majority, when compared with a
moderate VCM with a competitive majority, will likely hold stronger conflict efficacy beliefs,
generate greater levels of satisfaction with the team’s conflict management process, and work
more effectively:
H6a: Moderate VCM with a cooperative majority, relative to a moderate VCM with a
competitive majority, will be more positively associated with team conflict
efficacy.
H6b: Moderate VCM with a cooperative majority, relative to a moderate VCM with a
competitive majority, will be more positively associated with member satisfaction
with the team’s conflict management process.
H6c: Moderate VCM with a cooperative majority, relative to a moderate VCM with a
competitive majority, will be more positively associated with team effectiveness.
Finally, as for maximum VCM, it is posited that when compared to a moderate VCM
profile consisting of a competitive majority, a maximum VCM profile will contribute to more
positive, rather than negative, effects on team conflict efficacy, member satisfaction with the
team conflict management process, and overall team effectiveness (Hypotheses 7a-7c). Based on
Lau and Murnighan’s (1998) group faultline theory, a team with a maximum VCM profile may
34
be described as having a strong faultline that separates its members into two even subgroups
based on their conflict management approaches. A team with a moderate competitive VCM
profile, on the other hand, would be described as possessing a relatively weaker faultline given
the uneven subgroup sizes of a competitive majority and a cooperative minority. In an empirical
test of their group faultline model, Lau and Murnighan (2005) found that contrary to their model
predictions and to prior research (e.g., Molleman, 2005; Thatcher, Jehn, & Zanutto, 2003),
groups with strong faultlines experienced less relationship conflict, more psychological safety
and increased satisfaction with their groups, relative to groups with weak faultlines (pp. 653-
654). They also found that cross-subgroup communications improved outcomes for groups with
weak faultlines, but not those with strong faultlines (Lau & Murnighan, 2005).
In a related study, O’Leary and Mortensen (2010), who sampled 62 geographically
dispersed teams and looked at how their different geographical configurations affected team
dynamics, noted that teams with subgroups reported less identification with the whole team,
lower transactive memory, increased conflict, and greater coordination problems, when
compared to teams without subgroups. Additionally, they also observed that these negative
effects were exacerbated for teams with minority subgroups (i.e., subgroups of uneven sizes) as
compared to those with non-minority subgroups (i.e., subgroups of comparable sizes).
Taken altogether, these research findings suggest that compared to teams with moderate
competitive VCM profiles, members in teams with maximum VCM profiles are likely to
experience more positive interactions with others in their own subgroups, and to connect less
with members of the other subgroup within the broader team as well. When dealing with conflict
situations, members in these teams may choose to minimize or avoid overt cross-subgroup
disagreements or contentions, and instead, prefer to handle the conflicts constructively within the
35
psychologically safe boundaries of their own subgroups. Teams with moderate competitive
profiles, by contrast, are likely to experience more detrimental interactions between the
competitive majority and cooperative minority (Kelley & Stahelski, 1970; O’Leary &
Mortensen, 2010), which are in turn likely to contribute to lower levels of team conflict efficacy,
less member satisfaction with the team’s conflict management process, and decreased team
effectiveness.
H7a: Maximum VCM, relative to a moderate VCM with a competitive majority, will be
more positively associated with team conflict efficacy.
H7b: Maximum VCM, relative to a moderate VCM with a competitive majority, will be
more positively associated with member satisfaction with the team’s conflict
management process.
H7c: Maximum VCM, relative to a moderate VCM with a competitive majority, will be
more positively associated with team effectiveness.
Antecedents of variant conflict management
Three antecedent categories are likely to contribute to the development of VCM in teams.
These categories are salient conflict-relevant member characteristics, team contextual
determinants, and divergent team dynamics. Further, in this study, I have identified specific
variables representing each of these three categories: gender role diversity, goal interdependence,
and subgroup formation. In the subsequent sections, I describe how the three antecedent
categories relate to VCM, followed by discussions of the hypothesized relationships between the
specific variables representing these categories and VCM, which were empirically examined in
the study.
Salient conflict-relevant member characteristics
36
As noted earlier, salient conflict-relevant member characteristics refer to the degree in
which individual attributes, e.g., demographic dimensions, personality traits and cultural
orientations, are obvious or meaningful to members within a team during conflict situations.
Theories about similarity-attraction (Byrne, 1971; Newcomb, 1961), social identity (Hogg &
Terry, 2000; Tajfel & Turner, 1986) and social categorization processes (Tajfel, 1978; Turner,
1985) have generally argued that people tend to be attracted to or are more inclined to connect
with others deemed similar to them, and are less likely to relate to or interact with those
perceived as different from them.
Additionally, Swann’s self-verification theory (1983) has also reasoned that individuals
are motivated to seek verification about their thoughts and feelings (i.e., self-views) in a group
setting. As such, aligning oneself with similar others who presumably also hold similar values,
beliefs and worldviews (and at the same time, distancing oneself from perceived different others)
should increase the likelihood of validating one’s own self-views and enhance the sense that
one’s perspectives are heard and understood by others in the group.
Empirically, research in the team diversity and intergroup relations literatures have
provided substantial support for these theories (e.g., Brewer, 1995; Van Knippenberg &
Schippers, 2007; Williams & O'Reilly, 1998). In a team where individual characteristics or social
identity memberships (e.g., ethnicity, age and gender) are salient among individual team
members, members may be more drawn toward others possessing similar attributes or belonging
to the same social identity group. These members begin to interact more with one another,
establish stronger relational bonds, and eventually, develop or share similar perspectives,
attitudes or behaviors as a subgroup.
37
Considering the above reasoning then, in a team conflict situation, members who align
themselves into subgroups based on salient and conflict-relevant individual characteristics, due
to social categorization, attraction-similarity and/or self-verification processes, may also be
likely to adopt relatively similar approaches in handling the team conflict within their subgroups
(Deutsch, 1985).
Gender role diversity. To test the proposed relation between salient conflict-relevant
member characteristics and VCM discussed above, I examine a specific indicator of salient and
conflict-relevant member characteristics, that is, gender role diversity, and its hypothesized
relationship with VCM in the proposed study. Gender role diversity may be described as the
extent to which individual members’ gender role orientations differ from one another within the
team. By gender role orientations, these refer to individuals’ psychological tendencies toward
masculine or instrumental traits (e.g., aggressiveness, analytical, and assertiveness), feminine or
expressive traits (e.g., affectionate, gentle, and understanding), or both traits, i.e., being
androgynous (Bem, 1974). Specifically, Bem (1974) reasoned that contrary to conventional
notions of masculinity and femininity being opposite ends of a one-dimensional continuum, both
concepts may be considered as independent dimensions. Not only could individuals be
characterized as being masculine or feminine, but they may also be characterized as being
androgynous, i.e., having both masculine and feminine personality characteristics (Bem, 1974).
Based on Bem’s (1974) early work on gender role orientations, many researchers have
examined the concept of gender role orientations and its relation with a variety of constructs,
including that of individual conflict management styles (e.g., Brewer, Mitchell & Weber, 2002;
Jurma & Powell, 1994; Portello & Long, 1994; Yelsma & Brown, 1985). Portello and Long
(1994), for example, found that masculine managers tend to use more dominating (competitive)
38
conflict styles, while androgynous managers were more likely to use integrating (cooperative)
conflict styles. Jurma and Powell (1994), in another study, noted that organizational managers
who were perceived by their subordinates as displaying more androgynous behaviors were rated
as being most effective in managing conflict situations. Managers perceived as more masculine
by their subordinates, on the other hand, were rated as least effective in conflict management.
More recently, a survey study conducted by Brewer and colleagues (2002) reported that
individuals with masculine gender role orientations were more likely to use dominating styles,
those with feminine orientations were more likely to use avoiding styles, and those with
androgynous orientations were more likely to use integrating styles. Brewer et al.’s (2002)
findings were particularly noteworthy as they also demonstrated that these effects of gender role
orientations on conflict management styles were above and beyond those of physical gender or
biological sex differences. As such, this suggests that gender role orientation may be a better
predictor of conflict management than physical gender or biological sex (Brewer et al., 2002).
Given the above evidence on gender role orientation and conflict management, it is
therefore expected that differences in gender role orientations among members of a team, i.e.,
gender role diversity, will also likely affect the ways members handle conflict situations within
the team. Further, it is reasoned that gender role diversity in teams may have a positive
relationship with VCM. A low level of gender role diversity within a team indicates that all
members of a team are highly similar in their gender role orientations respectively. Such high
levels of similarity along gender role orientations further suggest that there is minimal basis for
members to categorize one another along this specific diversity attribute (Brewer, 1993; Tajfel &
Turner, 1986). Instead, highly similar members are likely to be drawn toward one another, in part
due to similarity/attraction processes (Byrne, 1971; Newcomb, 1961). If most, if not all,
39
members are similar in a given type of gender role orientation, e.g., masculine gender roles, then
it is plausible that they are also likely to use similar conflict approaches, e.g., competitive
conflict handling strategies, in dealing with conflicts with one another within the team. In other
words, low levels of gender role diversity among team members should reduce the likelihood for
divergent individual behaviors, including variation in individuals’ conflict management
approaches during team conflict (Hempel, et al., 2008).
By contrast, high levels of gender role diversity will be more likely to contribute to the
formation of VCM instead. When team members perceive some differences in gender role
orientations as salient and meaningful among themselves, VCM should be more likely to develop
in the team when internal conflicts occur. Here, categorization processes will likely be activated,
as members become inclined to align with others who share their gender role orientations within
the team (Brewer, 1993; Tajfel & Turner, 1986). As members align with some but not others,
based on salient differences in gender role orientations activated during team conflict, this in turn
suggests weaker member identification at the team level, and thus a stronger likelihood for
members to rely on their own different conflict management approaches associated with their
specific gender role orientations, thus increasing the likelihood of VCM occurring within the
team.
H8: Gender role diversity will be positively associated with VCM.
Team contextual determinants
Aside from salient conflict-relevant member characteristics, team contextual
determinants are expected to be another key antecedent category likely to contribute to the
development of VCM. Further, theorists and researchers have shown that when the strength of
contextual influence on individuals is weak, individuals may be more inclined to perceive or
40
behave in ways that reflect their personal predispositions, motives or attitudes (Meyer, Dalal, &
Hermida, 2010; Mischel, 1977).
In a team with contextual factors that exert relatively weak influence on its members
(e.g., one that lacks a strong raison d’être or a compelling team purpose), individual interests or
motivations may end up playing a larger role in influencing members’ perspectives, attitudes and
even behaviors. When such a team encounters conflict, members in the team may therefore rely
more on their own proclivities in conflict management. Some members may try to handle the
conflict more cooperatively, while others may do so in a more competitive fashion. Collectively
then, these differences should reflect variable conflict management approaches among individual
members, and thus, predict the occurrence of VCM.
Goal interdependence. The prominent social psychologist, Kurt Lewin (1939), once
noted that “[it] is not the similarity or dissimilarity of individuals that constitute a group, but
rather interdependence of fate” (pp. 165-166). Since Lewin’s observation, researchers have
found a considerable amount of support for the concept of interdependence, and its effects on a
variety of outcomes (see Johnson, 2003; Johnson & Johnson, 1989; Johnson, Maruyama,
Johnson, Nelson, & Skon, 1981; Tjosvold, 1986, 1998). While interdependence may be
construed in various ways, e.g., task, role, and outcome interdependence (Wageman, 1995), I
focus on perceived goal interdependence here, which can be defined as the extent and manner to
which members of a team perceive themselves as dependent on one another to achieve their
individual and/or team goals (Deutsch, 1949, 1973; Tjosvold, 1986, 1998). In other words, goal
interdependence is concerned with how goals are interlinked between two or more members in a
given team context.
41
This definition of goal interdependence is also derived from Deutsch’s (1949, 1973)
theory of cooperation and competition, which includes a central proposition about the ways
individual goals are structured (i.e., goal interdependence), and how these ways in turn guide the
dynamics and outcomes of interpersonal interactions. Specifically, Deutsch (1949, 1973)
reasoned that there are three ways in which goals may be structured between individuals:
positive, negative and independent. Positive interdependence refers to the situation in which
individuals perceive their goals as positively correlated, i.e., individuals would achieve their
goals only if others achieve theirs as well. By contrast, negative interdependence refers to the
situation in which individual goals are negatively correlated: individuals would achieve their
goals only if others fail to achieve theirs. As for the third type of goal structure, independent
goals, this refers to the situation in which individuals perceive their goals to be independent of
one another. In this case, how and whether individuals achieve their goals is of little or no
concern to others (Deutsch, 1949, 1973; Tjosvold, 1986).
Although much of the empirical research supporting Deutsch’s propositions on goal
interdependence has been conducted at the individual level and in educational settings (Johnson,
Johnson, & Maruyama, 1983; Johnson, et al., 1981), Tjosvold and his colleagues have studied
this phenomenon in teams and in organizations (e.g., Alper, Tjosvold, & Law, 1998; Lu,
Tjosvold, & Shi, 2010; Tjosvold, 1986). For individuals and teams in organizations, they found
that positive interdependence or cooperative goals tend to predict higher levels of constructive
controversy (i.e., the open-minded discussion of intellectual conflicts, Tjosvold, 1998), which in
turn lead to enhanced outcomes such as greater team effectiveness (Alper, et al., 1998), improved
relationships (Tjosvold, 2002), and increased team innovation (Chen & Tjosvold, 2002b).
Negative interdependence or competitive goals, on the other hand, has been linked to lower
42
levels of constructive controversy (e.g., Alper, et al., 1998), and consequently, more detrimental
team outcomes such as lower team effectiveness (Tjosvold, Wong, Nibler, & Pounder, 2002),
greater negative affect and reduced innovation (Chen, Tjosvold, & Su, 2005). As for independent
goals, research has also uncovered generally negative findings: independent goals have been
found to predict lower levels of constructive controversy (Chen & Tjosvold, 2002b), less open-
mindedness among team members (Tjosvold, 2002), less positive affect and reduced confidence
in future collaborations (Tjosvold, 1990). Overall, these findings suggest a critical role that goal
interdependence plays as a team contextual factor when it comes to understanding important
individual and team processes, including conflict management.
So far, prior research on goal interdependence has focused mainly on the ‘pure’ forms of
cooperative, competitive and/or independent goals (e.g., Alper, et al., 1998; Tjosvold, Law, &
Sun, 2006; Tjosvold, et al., 2002). Research and real-life observations, however, suggest that
individuals often also perceive the co-occurrence of positive and negative goals with one
another, i.e., mixed goal interdependence (Johnson & Johnson, 2005; Tjosvold, 1998). When
both cooperative and competitive goals exist in a team, individual differences in conflict
management approaches becomes likely to emerge among members as the contextual influence
of ‘pure’ cooperative or competitive goal interdependence on them is likely to be weakened.
Consequently, teams with mixed goals are also more likely to experience VCM compared to
cooperatively or competitively interdependent teams, since teams with cooperatively
interdependent members are more likely to manage conflicts similarly in a cooperative manner,
while teams with competitively interdependent members are also more likely to manage conflicts
similarly but competitively; such convergence in conflict management approaches suggest the
43
reduced likelihood of VCM occurring in either cooperatively or competitively interdependent
teams.
H9: Cooperative and competitive goal interdependence among members will be
negatively associated with VCM, while mixed goal interdependence among
members will be positively associated with VCM.
Divergent team dynamics
The third antecedent category of VCM, divergent team dynamics, concerns the nature of
interaction processes and behavioral patterns in a team. Team dynamics that steer members’
cognition, attitudes or behaviors toward different directions, such as group polarization
(Isenberg, 1986; Myers & Lamm, 1976), subgroup formation and dynamics (Lau & Murnighan,
1998, 2005), and majority/minority influence (e.g., Cialdini & Goldstein, 2004; Deutsch &
Gerard, 1955; Moscovici, 1976; Nemeth, 1986), are likely to contribute to the development of
VCM in a team.
An example of divergent team dynamics includes the presence and strength of norms that
form within a team. Norms refer to informal rules that guide and regulate behavioral patterns
among members of a group (Feldman, 1984). In a team where its members have aligned
themselves into subgroups, the norms supporting these subgroups are likely to exert a powerful
effect on reinforcing certain attitudes and behaviors among subgroup members (Hackman,
1976). Strong norms in a subgroup can hold significant sway on how subgroup members’ behave
as they provide a clear sense of identity and belonging for subgroup members, guide shared
codes of conduct, and allow members to predict and interpret behaviors within the subgroup
(e.g., Bettenhausen & Murnighan, 1985, 1991; Chatman, 2010; Feldman, 1984). Suppose a team
that consists of a subgroup with relatively strong norms supporting collaborative behaviors and
44
another subgroup with equally strong norms supporting competitive behaviors. In a conflict
situation, team members who identify with either subgroup are likely to display conflict
management behaviors that align with their subgroup norms. Members of the subgroup with
collaborative norms will display cooperative conflict management while those of the subgroup
with competitive norms will display competitive conflict management. For the team as a whole,
this should therefore lead to VCM development.
Subgroup formation. For this study, I focus on subgroup formation as an indicator of
divergent team dynamics in predicting the emergence of VCM. In the earlier sections, I have
alluded to how subgroup formation is likely to occur when individuals align themselves into
smaller entities or ‘cliques’ within a team, based on social categorization (Tajfel, 1978; Turner,
1985), similarity-attraction (Byrne, 1971; Newcomb, 1961), and/or faultline activation (Lau &
Murnighan, 1998, 2005). This suggests that the formation of subgroups in teams indicates the
presence of divergent team dynamics that are likely to influence individual and team behaviors.
As such, it may also be inferred that subgroup formation, only when it is based on salient
conflict-relevant member characteristics, would represent an important form of divergent team
dynamics in shaping the development of VCM in teams. In particular, I postulate that subgroup
formation is likely to mediate the predicted effects of gender role diversity on VCM (Hypothesis
10).
When member differences along gender role orientations are sufficiently salient and
meaningful during team conflict situations, it is likely that this specific diversity dimension will
in turn trigger social categorization processes (Tajfel, 1978; Turner, 1985), leading to in-
group/out-group distinction among members within the team, or in other words, subgroup
formation (Lau & Murnighan, 1998, 2005). Consequently, this process of in-group alignment
45
and out-group differentiation may in turn encourage differences in conflict management styles to
emerge between subgroups. A subgroup that consists of more masculine members, for instance,
may use more competitive strategies to handle the team conflict situation, compared to strategies
used by another subgroup with more feminine members. For the team as a whole, it is therefore
likely that VCM will emerge.
H10: Subgroup formation will mediate the relationship between gender role diversity
and VCM.
46
CHAPTER III: METHODOLOGY
Overview
This chapter describes the research design, sampling strategy, and study procedures that
were employed to empirically test the research questions and hypotheses discussed in the earlier
chapter. Measures that were used to collect data on the variables to be examined in this study are
also discussed here.
Participants
Sample. 884 undergraduate students majoring in business administration were recruited
for voluntary participation from several sections of two core courses titled, “Leadership and
Team Building (LTB)” and “Managing People at Work (MPW),” that were offered by the
Organizational Behavior and Human Resource Management (OBHR) division at the Singapore
Management University. 470 (53.2%) students enrolled in the LTB course were invited to
participate in this study via their course instructors, while 414 (46.8%) students enrolled in the
MPW course were invited to participate via the university’s subject pool system. A total of 417
students participated in this study, constituting a 47% response rate. 88 (18.7%) participants were
enrolled in the LTB course, while 329 (79.5%) participants were enrolled in the MPW course.
Since this study dealt with multilevel data (i.e., individuals nested within teams), the
traditional method of conducting a power analysis to estimate required sample sizes in single-
level designs cannot be directly translated to multilevel research (Scherbaum & Ferreter, 2009).
Instead, I follow recommendations from the multilevel literature which have suggested that
Level 2 sample sizes approaching 100 are appropriate if the variance components for the Level 2
variables are of interest in the study; such conclusions are based on simulation studies that have
47
examined statistical power for variance components in a variety of sample sizes with different
effect sizes and intraclass correlations, and at various levels (Maas & Hox, 2005).
To be included in the final sample, participating teams also needed to meet two criteria:
first, the teams should already be established in the courses, and team members should have had
some level of interaction at the time of recruitment for this study. To assess the level of
interaction among team members, participants were asked to indicate the frequency of their
interactions with their team members throughout the semester (e.g., five or less times per week,
more than ten times per week) in the study. This is to ensure that team members have had
sufficient opportunities to interact with one another, and that they would have experienced
certain team processes, such as conflicts, within their teams. Second, members in the teams were
expected to work on a team project together for the academic semester. This is to ensure that
participants are members of “real” teams (Alderfer, 1977), rather than loosely defined work
groups.
As this study was concerned with within-team variance, it was also important to have
teams that were numerically large enough for member variability to emerge. Therefore, at least
three members from a given team were deemed to constitute one team unit. Researchers who
study groups have found that dyads possess different dynamics when compared to teams that
comprise of three or more members (Levine & Moreland, 1990).
Participating students from the LTB and MPW courses were required to work in the same
teams and each team had to work on a final team project throughout the academic semester.
Also, the team projects assigned to the student teams were identical across all the sections in
each course. Each individual participant was matched with their respective teams within the
course section that they were enrolled in, based on the team information he or she provided in the
48
study. A total of 104 teams were identified from the participating students. 21 (20.2%) teams
were from the LTB course and 83 (79.8%) teams were from the MPW course.
After screening all 104 teams based on the team selection criteria described earlier, a total
of 79 teams were identified and included in the final analyses. These teams ranged from three to
eight members, with an average of four members per team (SD = 1.09, S2 = 1.19). Eight of these
teams were from the LTB course while the remaining 71 teams were from the MPW course.
Since the participating teams were recruited from two different courses, a series of t-tests (and
chi-square tests for categorical variables) was conducted between the eight LTB teams and a
random sample of eight MPW teams to determine whether there were any significant group
differences for various measures between teams based on course affiliation. No significant group
differences were found between both groups on measures assessing key variables for this study.
Design and procedures
This study was conducted using an online survey design. To recruit participants from the
MPW course, the study description was posted in the university’s subject pool system so that
students enrolled in the MPW course could sign up for voluntary participation in the second half
of the academic semester. This posting included general survey instructions, deadline for
participation, and a direct link to the online survey for this study. Participants from the MPW
course were also informed that they would receive their course credit upon completion of the
survey via the subject pool system.
At the same time, to recruit participants from the LTB course, I contacted all LTB course
instructors, via email, for their permission to recruit student teams from their courses for
voluntary participation in this study. Both the course instructors and participants were informed
of the study objectives at a general level, i.e., to understand how team characteristics affect team
49
interactions, and how these interactions in turn affect team outcomes. Once the instructors’
permission had been obtained, the course instructors were asked to forward an email invitation to
their students, informing them of this research participation opportunity. Included in the email
was a link that would direct each participant to a set of online survey questionnaires via a secure
electronic survey hosting software program. Participants were then asked to complete the
questionnaires and to return their responses online. Participants were also assured that their
information would be kept strictly confidential, and used for the sole research purposes of this
study. At the end of the online survey, LTB participants were also informed of a specific location
where they could collect a small monetary incentive for their participation from the researcher.
Appendix A contains the emails for participant recruitment and study participation that
were distributed to the LTB course instructors and participants respectively, as described above.
See Appendix B for the full survey questionnaire.
Measures
In the following sections, I describe the measures that were used to assess the variables
involved in this study: conflict management approaches, gender role diversity, team goal
interdependence, mixed goal interdependence, subgroup formation, team conflict efficacy,
member satisfaction with the team’s conflict management process, and team effectiveness. I
discuss the measures for assessing conflict management first, followed by the predictor
measures, and then the outcome measures. Other measures assessing control variables and
participant demographics are also discussed. All study measures are included in Appendix C.
Conflict management measures
VCM profiles. To assess the VCM profiles, I first gathered individual-level data on how
members manage conflict within their teams. To do so, I measured individual members’ conflict
50
management approaches within their teams, based on adapted items from Chen, Liu and
Tjosvold’s (2005) measure for cooperative and competitive conflict management approaches in
teams. This measure consisted of two sub-scales: cooperative conflict management and
competitive conflict management. Both sub-scales were scored on a scale of 1 to 5 (1 = never; 3
= sometimes; 5 = always). The cooperative conflict management sub-scale comprised of five
items (e.g., “I work with my teammates to find a solution that will be good for all of us.”), while
the competitive conflict management sub-scale comprised of four reverse-coded items (e.g., “I
tend to overstate my position to get my way.”). One item from the cooperative sub-scale and two
items from the competitive sub-scale were omitted from the final analyses, due to low item-total
correlations. These omitted items were “I treat conflict as a mutual problem to solve with my
teammates,” “I try to get my teammates to agree with my position (reverse coded),” and “I tend
to view conflict as a win-lose contest (reverse coded).” The Cronbach’s alphas based on
individual ratings for the adapted cooperative sub-scale, competitive sub-scale, and overall scale
were .67, .65 and .60 respectively. Since VCM profiles were construed at the team level, it was
important to assess the group-level reliability of the construct as well (Snijders & Bosker, 1999,
p. 26). While the Cronbach’s alphas based on individual ratings for both subscales and the
overall scale were all below .70, the Cronbach’s alphas based on the teams’ mean scores for the
adapted cooperative sub-scale, competitive sub-scale, and overall scale were .70 and higher (see
Table 2). These suggest that reasonable levels of internal consistency were met at the team level.
As such, the overall conflict management scale was used in the final analyses.
Variant conflict management. Since the VCM construct was conceptualized as a
separation-based construct, I followed Harrison and Klein’s (2007) recommendation for
operationalizing separation-based constructs by calculating the standard deviation (SD) score for
51
each team. In this case, the SD score on the overall conflict management scale was calculated for
each team to assess VCM. The within-team SD score was computed using the following
formula: √[Σ(Si-Smean)2/n], where S refers to the individual score on the conflict management
continuum, i refers to the ith member, and n refers to the total number of members within the
team (Harrison & Klein, 2007). The within-team SD scores ranged from a minimum value of 0
to a maximum value of 5.18, based on the formula: [(u-l)/2], where u and l represent the lower
and upper bounds of the conflict management continuum.
Cooperative and competitive team conflict management. Cooperative and competitive
team conflict management, on the other hand, were operationalized using teams’ means scores
on the cooperative and competitive conflict management sub-scales respectively. This is
consistent with the common approach of operationalizing team conflict management in the
literature (e.g., Alper, et al., 2000; DeChurch & Marks, 2001; Somech, 2008).
In order to justify data aggregation using teams’ means scores for cooperative and
competitive team conflict management, it was also necessary to establish reasonable levels of
group-level reliability, within-team agreement and between-team variability for the construct.
Further discussions of the group-level reliability and data aggregation indices for cooperative
team conflict management and all other team-level measures (viz., team goal interdependence,
subgroup formation, team conflict efficacy, member satisfaction with the team’s conflict
management process, team effectiveness, intra-team conflict types, team conflict intensity, and
team conflict importance) involved in this study are provided in the following chapter.
Predictor measures
Gender role diversity. To measure gender role diversity in teams, participants’
perceptions of their individual gender role orientations had to be assessed first. To assess gender
52
role orientations, I used items based on the short-form version of the Bem Sex Role Inventory
(BSRI, Bem, 1981). Since the focus is on individuals’ gender role orientations within teams,
participants were asked to rate how well each of the 30 short-form BSRI items describes them
within the team on a seven-point scale (1 = never or almost never true; 7 = always or almost
always true). Once all the individual scores were gathered, I then used the median split method
to determine individuals’ gender role orientations. Individuals were identified as masculine if
their masculine and feminine scores were above and below the median respectively. The
opposite pattern, i.e., masculine and feminine scores below and above the median respectively,
was used to identify feminine individuals. Individuals with both masculine and feminine scores
above the median were identified as androgynous and those with both scores below the median
were classified as undifferentiated.
When all participants’ gender role orientations have been identified, I then calculated the
gender role diversity for each team, using Blau’s (1977) heterogeneity index. This index has
been commonly used in past team diversity research as an objective measure of diversity in
teams (e.g., Bantel & Jackson, 1989; Harrison, Price & Bell, 1998; Mohammed & Angell, 2004).
The following formula is used in calculating the Blau’s index: 1-Σpk2, where p refers to the
proportion of team members in the kth category. The Blau’s index ranges from 0 to 1, where a
value of 0 indicates complete team homogeneity and a value of 1 indicates the opposite, i.e.,
complete team heterogeneity.
Team goal interdependence. To measure members’ perceptions of goal interdependence
within teams, I used Lu, Tjosvold and Shi’s (2010) measure for assessing cooperative and
competitive goals in the teams. Items were scored on a five-point scale (1 = strongly disagree to
5 = strongly agree). This measure also consisted of two sub-scales: positive goal
53
interdependence and negative goal interdependence. The positive goal interdependence sub-scale
comprised of five items (e.g., “In this team, members want each other to succeed.”) and the
negative goal interdependence sub-scale also comprised of five reverse-coded items (e.g., “In
this team, members like to show that they are superior to each other.”). The Cronbach’s alphas
based on individual ratings for the positive goal interdependence sub-scale, the negative goal
interdependence sub-scale and the overall scale were .67, .70 and .76 respectively. As for the
Cronbach’s alphas based on the team mean scores for both sub-scales and the overall scale, these
were all above .70 (see Table 2). Given that the overall scale had the highest alpha values based
on individual ratings and on teams’ mean scores, it was therefore used in the final analyses.
Mixed goal interdependence. The variable, mixed goal interdependence, was computed
using a subset of the team mean scores for team goal interdependence. Specifically, the score
distribution for the goal interdependence variable was divided into three parts, with the middle
part of the score distribution being selected as scores for mixed goal interdependence. In other
words, teams whose mean scores for the team goal interdependence measure lie between the
values of 34.90 (one standard deviation below the group mean in the distribution) and 40.22 (one
standard deviation above the group mean) were identified as having mixed goal interdependence.
Subgroup formation. To assess for the presence of subgroups within the team, I adapted
items from Cronin, Bezrukova, Weingart, et al.’s (2011) measure for subgroup formation in
teams (Cronbach’s alpha based on individual ratings = .80). This measure included the following
four items: “To what extent has your team split into subgroups?” “To what extent has your team
split into multiple or smaller cliques?” “To what extent has your team split into unevenly
balanced subgroups?” and “To what extent has your team split into two balanced subgroups?”
54
These items were scored on a 1 to 5 scale (1 = not at all or to a very small extent; 5 = to a very
large extent).
Outcome measures
Team conflict efficacy. To measure members’ levels of conflict efficacy within teams, I
used an existing five-item measure developed by Alper et al. (2000). This measure was rated on
a five-point scale (1 = strongly disagree; 5 = strongly agree). The Cronbach’s alpha based on
individual ratings for this measure was .79, thus indicating high levels of internal consistency
reliability.
Member satisfaction with the team’s conflict management process. To assess members’
levels of satisfaction with how their teams manage internal conflicts, I adapted and used one of
the sub-scales in the Subjective Value Inventory developed by Curhan, Elfenbein, and Xu
(2006). This measure consisted of four items and was rated on a seven-point scale (1 = not at all;
4 = moderately; 7 = perfectly). The Cronbach’s alpha based on individual ratings for this
measure was .73.
Team effectiveness. Team members’ perceptions of their teams’ effectiveness were
measured using an existing five-item measure derived from prior studies (Alper et al., 1998;
Barker et al., 1988; Tjosvold, Law & Sun, 2006). This measure was rated on a five-point scale (1
= strongly disagree; 5 = strongly agree). The measure also exhibited very high levels of internal
consistency reliability based on individual ratings, with a Cronbach’s alpha of .90.
Controls and other measures
Intra-team conflict types. In this study, it was also important to control for the effects of
intra-team conflict types, as studies have shown that intra-team conflicts could significantly
affect the impact of conflict management on team functioning and outcomes (e.g., Behfar, et al.,
55
2008; DeChurch & Marks, 2001; Desivilya & Yagil, 2005, Tjosvold, Law & Sun, 2006).
Tjosvold and colleagues (2006), for instance, reported that team perceptions of intra-team
conflicts, such as task and relational conflicts, could mediate the relationship between the teams’
conflict management approaches and their levels of team effectiveness. Specifically, they found
that teams with competitive conflict management approaches were likely to perceive more task
and relational conflicts, whereas teams with cooperative conflict management approaches were
likely to perceive less task and relational conflicts; Higher levels of task conflicts were also
related to more negative managerial ratings of team effectiveness (Tjosvold, Law & Sun, 2006).
So, to assess members’ perceptions of conflicts within the team, I applied Jehn and
Mannix’s (2001) scale to measure three types of within-team conflicts: task, relationship and
process conflicts. The overall measure comprised of nine items and the three sub-scales consisted
of three items each. All items for this measure are rated on a five-point scale. The Cronbach’s
alpha based on individual ratings for the overall measure was .88.
Perceived conflict importance and intensity. Past research has found that individual
perceptions of conflict importance and intensity could affect their conflict management
approaches as well (for the former, e.g., Jehn, 1997; Rosenthal & Hautaluoma, 1988; for the
latter, e.g., Andrews & Tjosvold, 1983, Barker, Tjosvold & Andrews, 1988). As such, it was also
important to measure and control for potential effects of members’ perceptions of the importance
and intensity of conflicts experienced within their teams. So, to assess individual perceptions of
conflict importance, participants were asked to rate the extent to which they view conflict within
the team as important, on a five-point scale (1 = not at all or to a very small extent; 5 = to a large
extent).
56
As for the measure on conflict intensity in teams, this was assessed using participants’
scores on four items in the Jehn and Mannix’s (2001) intra-team conflict type measure. Together,
these four items assessed the extent to which overall conflict (i.e., task, relationship and process
conflicts combined) occurs within the team (see items 1, 4, 6 and 8 of the “Intra-team Conflict
Types” measure under Appendix C). The Cronbach’s alpha based on individual ratings for this
measure was .78.
Course affiliation and team size. Given that the participating teams were recruited from
two different courses, participants’ course affiliations would be controlled for in the analyses. In
this study, team size would also be controlled for, since team size can affect team functioning
and outcomes differently (Brewer & Kramer, 1986; Steiner, 1972).
Participant demographics. Members of the participating teams were also asked to
provide information on the following demographic and team-related characteristics: age, gender,
ethnicity, country of origin, years of living in Singapore, area of specialization for the degree,
years of prior and current work experience, team name, and course affiliation (see Section V of
Appendix B for the survey items that were used to gather this data). In the final sample, the
participants’ ages ranged from 17 to 27 (M = 21.7, SD = 1.65, S2 = 2.71). 53.9% of the
participants were female (n = 179), 45% were male (n = 151), and 0.6% identified with “other,
e.g., transgender” (n = 2). As for ethnicity, 86.4% of the participants identified themselves as
Chinese (n = 286), 5.4% as Indian (n = 18), 1.8% as biracial or multiracial (n = 6), 1.5% as
Malay (n = 5), and 4.8% as Other (n = 16). On average, participants had 25 years of living in
Singapore, and 1.5 years of prior and current work experience.
57
CHAPTER IV: RESULTS
Overview
In this chapter, I discuss the preliminary, main and supplementary analyses that were
conducted to address the research questions and hypotheses stated in this study. First,
preliminary analyses, which included descriptive statistics and correlational analyses among all
key variables, are presented. Next, the main analyses used to assess the VCM construct and
proposed relationships among model variables are reported: qualitative content coding analyses
to assess the presence and prevalence of the proposed VCM profiles in teams; hierarchical
regressions to compare the relative effects of standard deviations-based VCM scores and means-
based cooperative and competitive team conflict management scores on team conflict efficacy,
member satisfaction with the team’s conflict management process, and team effectiveness
respectively; planned comparisons to compare the effects of various VCM profiles on the three
team outcomes; simple, curvilinear and mediational regressions to examine gender role diversity,
team goal interdependence and subgroup formation as possible antecedents of VCM
respectively. Finally, supplementary analyses that assessed the VCM construct using latent class
analyses and group differences among identified latent classes on the three team outcomes are
also presented and discussed.
Preliminary analyses
Descriptive statistics
Table 1 shows the means, standard deviations and variances for all key team-level
variables. The means for these variables ranged from .62 to 37.57, the standard deviations ranged
from .15 to 3.57, and the variances ranged from .02 to 12.71.
Team-level reliability and data aggregation indices
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Since this study was concerned with team-level constructs, sufficient levels of team-level
reliability, within-team agreement, and between-team variability were needed in order to justify
data aggregation for all relevant team-level measures. To do so, I calculated the team-level
reliability scores based on the teams’ means (Snijders & Bosker, 1999, p. 26), within-group
interrater agreement indices or rwgs (James, Demaree, & Wolf, 1984, 1993), and intraclass
correlations (Bliese, 2000) using the aggregated team-level data for each measure. The rwg
measures the degree to which individual ratings within a group are interchangeable, and values
of rwgs that are greater or equal to .70 are considered good indicators of sufficient within-team
agreement (George & Bettenhausen, 1990). As for intraclass correlations, these are measured in
two forms: ICC (1), which assesses the extent to which variability in individual ratings is
explained by group membership, and ICC (2), which is concerned with estimating the reliability
of group means. ICC (l) values of .12 or higher and ICC (2) values of .70 or higher would
indicate sufficient support for within-team agreement and between-team variability respectively
(Bliese, 2000).
Table 2 shows the team-level reliability scores and data aggregation indices for all the
team-level measures. All measures exhibited reasonable to high levels of reliability according to
the group means-based Cronbach’s alphas (range of .70 to 94). As for the aggregation indices,
the median rwgs for all measures were .70 or greater, thus indicating acceptable levels of within-
team agreement. The ICC (1) values for all the measures also met the recommended value of .12
or higher, except for the masculine sub-scale and the overall gender role orientation measure.
The ICC (2) values, on the other hand, ranged from .45 to .93. This indicated that some of the
measures did not exhibit reasonable levels of between-team variability (see Table 2 for these
59
measures). Nonetheless, since the team reliabilities and rwgs for all the team measures were
acceptable, it was determined that data aggregation for the team-level variables was justified.
Common method variance
Considering that all variables were assessed using self-report measures in the same
survey, it is important to determine whether common method variance, i.e., variance that stems
from the measurement method rather than from the intended constructs to be assessed
(Podsakoff, et al., 2003), may be present. One common statistical technique used in diagnosing
the presence of common method variance is the Harman’s single-factor test (Podsakoff & Organ,
1986; Podsakoff et al., 2003). In this test, an exploratory or confirmatory factor analysis is
conducted in which all variables in the study are loaded. The unrotated factor solution is then
examined to determine the number of factors accounting for the variance in the variables. The
Harman’s single-factor test assumes that if a significant amount of variance was present, a single
factor would therefore emerge from the factor analysis. Alternatively, one single factor would
account for most of the co-variance among the variables (Podsakoff & Organ, 1986; Podsakoff et
al., 2003).
Based on this approach, I therefore conducted the Harman’s single-factor test to assess
whether common method variance would pose an issue in the interpretation of the study results.
To do so, scale items for all the team-level predictor and outcome variables involved in this
study were loaded into a principal-components factor analysis. The results revealed 18 factors
with eigenvalues of one or greater that were extracted from the unrotated solution. Further, the
first and largest factor to emerge from the solution accounted for only 24.5% of the total
variance. As such, it was concluded that common method variance did not pose a problem in this
research.
60
Intercorrelational analyses
Zero-order correlations among all key continuous and dichotomous team-level variables
using Pearson product-moment coefficients were also conducted (see Table 3). Cooperative team
conflict management, based on teams’ means scores for the cooperative conflict management
sub-scale, was significantly correlated with three predictor variables, team goal interdependence
(r = .48, p < .001), mixed goal interdependence (r = .56, p < .001) and subgroup formation (r = -
.31, p < .01). It was also correlated with all three team outcomes: team conflict efficacy (r = .36,
p < .01), members’ satisfaction with their teams’ conflict management process (r = .23, p < .05),
and team effectiveness (r = .46, p < .001). Higher levels of cooperative team mean conflict
management were also found to be significantly associated with lower levels of intra-team
conflict (r = -.39, p < .001) and lower levels of team conflict intensity (r = -.49, p < .001). By
contrast, VCM, based on teams’ standard deviation scores for the overall conflict management
scale, was uncorrelated with any of the team-level variables. Accordingly, these correlational
findings suggested that initial support for Hypotheses 2a to 2c, which predicted effects of VCM
on team conflict efficacy, members’ satisfaction with team conflict management process, and
team effectiveness, above and beyond those of cooperative team conflict management was not
found.
Competitive team conflict management, based on teams’ means scores for the
competitive conflict management sub-scale, was significantly correlated with two of the
predictor variables: team goal interdependence (r = -.39, p < .01) and subgroup formation (r =
.41, p < .01). It was, however, not related to any of the three outcome variables. As such, initial
support for Hypotheses 3a to 3c, which predicted the effects of VCM on team conflict team
conflict efficacy, members’ satisfaction with team conflict management process respectively, and
61
team effectiveness above and beyond those of competitive team conflict management was also
not established.
Gender role diversity, one of the proposed predictors of VCM, was only significantly
related to course affiliation (r = .23, p < .05). This suggests that initial support for Hypothesis 8,
which predicted a positive relationship between gender role diversity and VCM, was also not
found.
The second proposed predictor of VCM, team goal interdependence, was negatively
correlated with subgroup formation (r = -.45, p < .001), and positively correlated with all three
team outcomes: team conflict efficacy (r = .44, p < .001), members’ satisfaction with team
conflict management process (r = .47, p < .001), and team effectiveness (r = .55, p < .001).
Cooperative team goal interdependence (i.e., higher team goal interdependence scores) was also
related to lower levels of intra-team conflict (r = -.55, p < .001) and team conflict intensity (r = -
.61, p < .001). Accordingly, this indicates that initial support for Hypothesis 9, which predicted a
curvilinear relationship between team goal interdependence and VCM, was also not established.
Finally, as for subgroup formation, the third antecedent that was predicted to mediate the
relationship between gender role diversity and VCM in Hypothesis 10, it was found to be
uncorrelated with gender role diversity (r = -.18, ns) and VCM (r = -.04, ns). Given these
findings, initial support for Hypothesis 10 was thus not provided.
Main analyses
Assessing presence of VCM profiles in teams
Presence of proposed VCM profiles. Hypothesis 1 states that the five proposed VCM
profiles, i.e., minimum cooperative, minimum competitive, moderate cooperative, moderate
competitive, and maximum VCM profiles, will be present in teams. To test this hypothesis, I
62
conducted a content coding analysis. To do so, the individual-level responses to all items in the
overall conflict management scale were first aggregated for each member within a team. Then,
the aggregated conflict management score for each individual member was plotted along a one-
dimensional continuum for all members in each team. A Microsoft Excel worksheet was created
to visually plot the distribution of individual conflict management scores for each team along a
single row. Since 79 teams were included in the analyses, 79 rows were created, with each row
representing the spread of individual scores per team.
Using the VCM profile descriptions as a coding scheme, three trained coders who were
blind to the study questions and hypotheses reviewed these rows for all teams, and were
instructed to classify each team into one of five proposed VCM profiles: minimum cooperative
VCM, moderate cooperative VCM, maximum VCM, moderate competitive VCM, and minimum
competitive VCM. If the team’s row of scores did not characterize any one of the five VCM
profiles, coders were instructed to classify the team under a sixth category labeled as “other”.
Whenever a team was classified as “other”, the coder also provided detailed comments to
describe the specific distribution of individual scores for that team. The specific definitions of
the coding categories are provided in Table 4.
In cases where coding discrepancies among coders occurred, the majority rule was
applied. For example, if two of the three coders rated a “3” and the remaining coder rated a “1”,
the former was applied as the coding category for the given team. Once the coding from all three
coders has been completed, Cohen’s Kappas were calculated between pairs of coders to
determine the level of inter-rater agreement on the coding. The Cohen’s Kappas were .96, .96
and .96, thus indicating high levels of consistency across coders’ ratings.
63
Table 5 shows the final counts of teams that were classified across the six coding
categories. Based on these counts, it was observed that in this sample, most teams exhibited
moderate cooperative VCM profiles, followed by moderate competitive VCM, minimum
cooperative VCM, maximum VCM, and minimum competitive VCM profiles. As for the teams
that were classified under the “other” category, a closer examination of the comments provided
by coders suggested that these teams may be further organized into three new profiles:
‘distributed,’ ‘multiple clusters,’ and ‘midpoint cluster.’ Teams that may be described as
‘distributed’ contained individual scores that were relatively spread out throughout the entire
conflict management continuum. Teams described as ‘multiple clusters’ contained score
distributions where there was an absence of a majority cluster; instead, multiple small clusters
were observed along the conflict management continuum. Finally, for teams that may be
described as ‘midpoint cluster’, these contained score distributions where all scores were co-
located around the midpoint of the continuum. See Figure 5 for all eight profiles identified.
In summary, to address Hypothesis 1 based on the findings from the content coding
analysis, it was therefore concluded that the various proposed VCM profiles are indeed present
in teams. Furthermore, other types of team profiles such as those characterized as ‘distributed,’
‘multiple clusters,’ and ‘midpoint cluster’ profiles that were not previously conceptualized in the
proposed VCM theory were also present in the teams sampled. In the analyses, teams with
moderate cooperative VCM profiles were most common, followed by those with moderate
competitive, minimum cooperative, maximum, and minimum competitive VCM profiles.
Assessing relative effects of VCM and mean team conflict management on team outcomes
Cooperative team conflict management versus VCM. The next set of hypotheses, i.e.,
Hypotheses 2a-2c, is concerned with comparing the relative effects of cooperative team conflict
64
management scores (based on teams’ means scores) and VCM (based on teams’ standard
deviation scores) on team conflict efficacy, members’ satisfaction with their team’s conflict
management process, and team effectiveness respectively. Specifically, Hypothesis 2a stated that
VCM scores will be associated with lower levels of team conflict efficacy, with cooperative team
conflict management scores being held constant. Hypothesis 2b predicted that VCM scores will
be associated with lower levels of members’ satisfaction with their teams’ conflict management
process, with cooperative team conflict management scores being held constant. As for
Hypothesis 2c, VCM scores will also be associated with lower levels of team effectiveness, with
cooperative team conflict management scores being held constant. Hierarchical multiple
regression analyses were used to test these three hypotheses.
Prior to testing Hypothesis 2a, preliminary analyses were first performed to test
assumptions of homoscedasticity, independence, linearity, normality, and multicollinearity
among the variables involved in this analysis. The variables included cooperative team conflict
management, VCM, team conflict efficacy, intra-team conflict, team conflict intensity, team
conflict importance, team goal interdependence, mixed goal interdependence, and team subgroup
formation. The variables, intra-team conflict and team conflict intensity, were found to be highly
intercorrelated, indicating the presence of multicollinearity. To address this, team conflict
intensity, and not intra-team conflict, was used as a control variable in the hypothesis test, given
the former’s stronger correlation with the dependent variable, team conflict efficacy. Team goal
interdependence and mixed goal interdependence were also highly multicollinear, and both were
correlated with team conflict efficacy as well. In this case, only team goal interdependence was
included as a control variable since it was more strongly associated with team conflict efficacy
than mixed goal interdependence. Team subgroup formation was also included as a control
65
variable in this analysis as it, too, was significantly correlated with the team conflict efficacy.
Course affiliation and team size were not included as control variables in this analysis as they
were found to be uncorrelated with team conflict efficacy.
In the hierarchical regression analysis, the control variables, i.e., team conflict intensity,
team conflict importance, team goal interdependence and team subgroup formation, were entered
at Step 1 in the regression model. Both cooperative team conflict management and VCM were
entered as predictor variables at Step 2 in the model.
Table 6 presents the findings for the hierarchical regression analysis. The regression
results showed that the four control variables, team conflict intensity, team conflict importance,
team goal interdependence and team subgroup formation, explained 33.3% of the variance in
team conflict efficacy, F (4, 74) = 9.25, p < .01. The entry of cooperative team conflict
management and VCM at Step 2 explained an additional 2.9% of the variance in team conflict
efficacy; however, this additional variance was not a significant contribution in the model, F (2,
72) = 6.83, ns. In the final model, only team goal interdependence (β = .28, p < .05) and team
conflict importance (β = .27, p < .05) were statistically significant predictors of team conflict
efficacy. Neither cooperative team conflict management (β = .14, ns) nor VCM (β = -.14, ns)
significantly predicted team conflict efficacy. Overall, these findings suggest that Hypothesis 2a
was not supported.
To test Hypothesis 2b, preliminary analyses were also first conducted to ensure that no
variables involved in this analysis violated the assumptions of homoscedasticity, independence,
linearity, normality, and multicollinearity. At Step 1 of the hierarchical regression, the variables,
team mean age, team conflict intensity, and team goal interdependence were entered as controls
in the regression model. Team mean age and team goal interdependence were controlled for in
66
this analysis as both were significantly correlated with the dependent variable, member
satisfaction with team conflict management process. Course affiliation, team size, and team
conflict importance were omitted in this analysis since they were uncorrelated with member
satisfaction with team conflict management process. Despite significant associations with
member satisfaction, mixed goal interdependence and intra-team conflict were also excluded as
control variables in the model due to their high multicollinearity with team goal interdependence
and team conflict intensity respectively. Cooperative team conflict management and VCM were
entered as predictor variables at Step 2 in the model equation.
Table 7 shows the results of the hierarchical regression analysis. In Model 1, the control
variables explained 28.2% of the total variance in predicting satisfaction with team conflict
management process, F (3, 75) = 9.84, p < .01. The inclusion of cooperative team conflict
management and VCM as predictors in Model 2 accounted for an additional variance of 0.6% in
the final model; however, this additional variance was not a statistically significant contribution,
F (2, 73) = 5.90, ns. Only team mean age (β = .21, p < .05) and team goal interdependence (β =
.39, p < .01) significantly predicted satisfaction with team conflict management process in the
final model. Accordingly, this indicates that neither cooperative team conflict management nor
VCM were significant predictors of member satisfaction with team conflict management, after
controlling for the effects of team mean age, team conflict intensity, and team goal
interdependence. As such, Hypothesis 2b was not supported.
Finally, Hypothesis 2c was also tested using a hierarchical regression analysis.
Preliminary analyses were also conducted to ensure that no variables involved in this analysis
violated the assumptions of homoscedasticity, independence, linearity, normality, and
multicollinearity. Three control variables, i.e., team conflict intensity, team goal
67
interdependence, and subgroup formation, were entered in the first block of the regression
model. Team goal interdependence and subgroup formation were added as controls due to their
significant correlations with team effectiveness. Despite their significant correlations with team
effectiveness, mixed goal interdependence and intra-team conflict were not included as control
variables due to their high multicollinearity with team goal interdependence and team conflict
intensity respectively. Since course affiliation, team size and team conflict importance were not
correlated with team effectiveness, these were also not controlled for in the analysis. Cooperative
team conflict management and VCM were entered as predictor variables in the second block.
The hierarchical regression results revealed that the three control variables accounted for
36.8% of the variance in team effectiveness, F (3, 75) = 14.54, p < .01, while the two predictor
variables contributed an additional 5.3% of the variance in team effectiveness, F (2, 73) = 5.90, p
< .01 (see Table 8). A closer look at the coefficients in the final model showed that only
cooperative team conflict management (β = .25, p < .05) significantly predicted team
effectiveness, even after team conflict intensity, team goal interdependence, and subgroup
formation were controlled for. VCM, on the other hand, did not have a significant effect on team
effectiveness (β = .05, ns). Accordingly, these findings suggest that Hypothesis 2c was not
supported.
Competitive team conflict management versus VCM. The third set of hypotheses, i.e.,
Hypotheses 3a-3c, is concerned with comparing the relative effects of competitive team conflict
management scores (based on teams’ means scores) and VCM (based on teams’ standard
deviation scores) on team conflict efficacy, members’ satisfaction with their team’s conflict
management process, and team effectiveness respectively. Specifically, Hypothesis 3a stated that
VCM scores will be associated with higher levels of team conflict efficacy, with competitive
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team conflict management scores being held constant. Hypothesis 3b predicted that VCM scores
will be associated with higher levels of members’ satisfaction with their teams’ conflict
management process, with competitive team conflict management scores being held constant. As
for Hypothesis 3c, VCM scores will also be associated with higher levels of team effectiveness,
with competitive team conflict management scores being held constant. Similar to Hypotheses 2a
to 2c, a series of hierarchical multiple regression analyses were also used to test Hypotheses 3a
to 3c.
Prior to testing Hypothesis 3a, preliminary analyses were also performed to test
assumptions of homoscedasticity, independence, linearity, normality, and multicollinearity
among the variables involved in this analysis. Four control variables, i.e., team conflict intensity,
team conflict importance, team goal interdependence and team subgroup formation, were entered
at Step 1 in the regression model. Both competitive team conflict management and VCM were
entered as predictor variables at Step 2 in the model.
Table 9 presents the findings for the hierarchical regression analysis. In the final model,
the entry of competitive team conflict management and VCM at Step 2 explained an additional
2.5% of the variance in team conflict efficacy; however, this additional variance was not a
significant contribution in the model, F (2, 72) = 6.69, ns. In the final model, only team goal
interdependence (β = .35, p < .05) and team conflict importance (β = .26, p < .05) were
statistically significant predictors of team conflict efficacy. Neither competitive team conflict
management (β = .11, ns) nor VCM (β = -.13, ns) significantly predicted team conflict efficacy.
Overall, these findings suggest that Hypothesis 3a was not supported.
To test Hypothesis 3b, preliminary analyses were also first conducted to ensure that no
variables involved in this analysis violated the assumptions of homoscedasticity, independence,
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linearity, normality, and multicollinearity. At Step 1 of the hierarchical regression, the variables,
team mean age, team conflict intensity, and team goal interdependence were entered as controls
in the regression model. Competitive team conflict management and VCM were entered as
predictor variables at Step 2 in the model equation.
Table 10 shows the results of the hierarchical regression analysis. The inclusion of
competitive team conflict management and VCM as predictors in Model 2 accounted for an
additional variance of 3.7% in the final model; however, this additional variance was not a
statistically significant contribution, F (2, 73) = 6.84, ns. Only team mean age (β = .21, p < .05)
and team goal interdependence (β = .44, p < .01) significantly predicted satisfaction with team
conflict management process in the final model. Accordingly, this indicates that neither
competitive team conflict management nor VCM were significant predictors of member
satisfaction with team conflict management, after controlling for the effects of team mean age,
team conflict intensity, and team goal interdependence. As such, Hypothesis 3b was not
supported.
Finally, Hypothesis 3c was also tested using a hierarchical regression analysis.
Preliminary analyses were also conducted to ensure that no variables involved in this analysis
violated the assumptions of homoscedasticity, independence, linearity, normality, and
multicollinearity. Three control variables, i.e., team conflict intensity, team goal
interdependence, and subgroup formation, were entered in the first block. Competitive team
conflict management and VCM were entered as predictor variables in the second block.
The hierarchical regression results revealed that the entry of competitive team conflict
management and VCM as predictors in Model 2 accounted for an additional variance of 2.1% in
the final model; however, this additional variance was also not a statistically significant
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contribution, F (2, 73) = 9.27, ns (see Table 11). Accordingly, these findings suggest that
Hypothesis 3c was also not supported.
Assessing relative effects of VCM profiles on team outcomes
Minimum cooperative VCM versus all other VCM profiles. The next set of hypotheses,
i.e., Hypotheses 4a-4c, was concerned with the relative effects of minimum cooperative VCM
profiles and all other VCM profiles on team conflict efficacy, member satisfaction with the
team’s conflict management process, and team effectiveness respectively. Hypothesis 4a stated
that relative to teams with all other VCM profiles, teams with minimum cooperative VCM
profiles are likely to report the highest levels of team conflict efficacy. Similarly, Hypothesis 4b
predicted that relative to teams with all other VCM profiles, teams with minimum cooperative
VCM profiles are likely to report the highest levels of members’ satisfaction with the team’s
conflict management process. As for Hypothesis 4c, it stated that relative to teams with all other
VCM profiles, teams with minimum cooperative VCM profiles are also likely to report the
highest levels of team effectiveness.
Prior to testing Hypotheses 4a to 4c, preliminary analyses were performed to test the
assumptions of homoscedasticity, independence, linearity, normality, and multicollinearity. The
preliminary analyses revealed that the distribution of team conflict efficacy scores for teams with
moderate competitive VCM profiles was significantly non-normal, W (10) = .77, p < .01. As
such, Hypothesis 4a was tested using the Mann-Whitney test. Hypotheses 4b and 4c, on the other
hand, were each tested using planned comparisons. To test all three hypotheses, the VCM
profiles as identified in the earlier content coding analysis were entered as a grouping variable of
five levels, with each level representing one VCM profile.
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Prior to testing Hypothesis 4a, dummy variables were first created to compare the
minimum cooperative VCM profiles (“1”) against the four other VCM profiles (“0”) in four
Mann-Whitney U Tests. A Bonferroni correction was applied, so all effects were reported at a
.0125 level of significance. Based on the Mann-Whitney U test findings, it was observed that the
team conflict efficacy scores for teams with minimum cooperative VCM profiles (Mdn = 19.45,
n = 6) were not significantly higher than those for teams with moderate cooperative VCM
profiles (Mdn= 19.71, n = 38), U = 101.50, z = -.43, ns, teams with maximum VCM profiles
(Mdn = 19.25, n = 5), U = 12.00, z = -.55, ns, or teams with minimum competitive VCM profiles
(Mdn = 18.33, n = 3), U = 1.50, z = -1.95, ns. However, teams with minimum cooperative VCM
profiles did report significantly higher levels of team conflict efficacy compared to those with
moderate competitive VCM profiles (Mdn = 18.58, n = 10), U = 5.00, z = -2.71, p < .01, r = .68.
These findings thus suggest that Hypothesis 4a was partially supported (see Table 12).
Results of Hypothesis 4b indicated the planned comparison test contrasting minimum
cooperative VCM against the other four VCM profiles was also not significant: t (57) = 1.30, ns
(see Table 13 for the group means and standard deviations). Accordingly, this suggests that
Hypothesis 4b was not supported.
Finally, for the test of Hypothesis 4c, the planned comparison test contrasting minimum
cooperative VCM against the other four VCM profiles was significant: t (57) = 2.47, p < .05, r =
.31 (see Table 13). Further post-hoc comparisons, using a Bonferroni’s correction, indicated that
the mean team effectiveness scores for teams with minimum cooperative VCM profiles (M =
19.80, SD = 1.15) were only significantly higher than those for teams with minimum competitive
VCM profiles (M = 15.47, SD = 1.53). Overall, this suggests that Hypothesis 4c was only
partially supported.
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Minimum competitive VCM profile versus all other VCM profiles. Hypotheses 5a to 5c
were concerned with comparing the effects of minimum competitive VCM profiles against all
other VCM profiles on team conflict efficacy, members’ satisfaction with the team’s conflict
management process, and team effectiveness respectively. As noted earlier, given the non-
normal distribution of team conflict efficacy scores for teams with moderate competitive VCM
profiles, Hypothesis 5a was therefore tested using the the Mann-Whitney test. Hypotheses 5b and
5c were each tested using planned comparisons.
To test Hypothesis 5a, dummy variables were created to compare the minimum
competitive VCM profiles (“1”) against the four other VCM profiles (“0”) in four Mann-
Whitney U Tests. A Bonferroni correction was applied, so all effects were reported at a .0125
level of significance. Finding from the Mann-Whitney U tests indicated that none of the
comparisons were significant: team conflict efficacy scores for teams with minimum competitive
VCM profiles (Mdn = 18.33, n = 3) were not significantly lower than those for team with
minimum cooperative VCM profiles (Mdn = 19.45, n = 6), U = 1.50, z = -1.95, ns, teams with
moderate cooperative VCM profiles (Mdn= 19.71, n = 38), U = 101.50, z = -.43, ns, teams with
maximum VCM profiles (Mdn = 19.25, n = 5), U = 12.00, z = -.55, ns, or teams with moderate
competitive VCM profiles (Mdn = 18.58, n = 10), U = 12.50, z = -.42, ns (see Table 12). These
findings thus suggest that Hypothesis 5a was not supported.
Results of Hypothesis 5b indicated that the planned comparison test contrasting minimum
competitive VCM against the other four VCM profiles was significant: t (73) = -2.14, p < .05, r
= .27 (see Table 13). Teams with minimum competitive VCM profiles (M = 19.19, SD = 2.17)
reported lowest levels of member satisfaction with the team’s conflict management process,
relative to those with minimum cooperative VCM (M = 22.55, SD = 1.75), moderate cooperative
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VCM (M = 21.88, SD = 2.30), maximum VCM (M = 22.60, SD = 3.10), and moderate
competitive VCM (M = 21.27, SD = 1.69). Accordingly, these results suggest that Hypothesis 5b
was supported.
Finally, for the test of Hypothesis 5c, the planned comparison test contrasting minimum
competitive VCM against the other four VCM profiles was also significant: t (57) = -3.44, p <
.01, r = .41 (see Table 13). Specifically, the mean team effectiveness scores for teams with
minimum competitive VCM profiles (M = 15.47, SD = 1.53) were only significantly lower than
those for teams with minimum cooperative VCM (M = 19.80, SD = 1.15), and than those for
teams with moderate cooperative VCM profiles (M = 19.04, SD = 1.75). Overall, this suggests
that Hypothesis 5c was only partially supported.
Moderate cooperative VCM profiles versus moderate competitive VCM profiles. The next
set of hypotheses, i.e., Hypotheses 6a to 6c, compared the effects of moderate cooperative VCM
profiles and moderate competitive VCM profiles on team conflict efficacy, members’
satisfaction with the team’s conflict management process, and team effectiveness respectively.
Given the non-normal distributions of team efficacy scores for teams with moderate competitive
VCM profiles, Hypothesis 6a was thus examined using the Mann-Whitney U tests. Hypotheses
6b and 6c were each tested using planned comparison tests instead.
Hypothesis 6a stated that compared to teams with moderate competitive VCM profiles,
teams with moderate cooperative VCM profiles will be associated with higher levels of team
conflict efficacy. A dummy variable was created and used to compare teams with moderate
cooperative VCM profiles (“1”) and those with moderate competitive VCM profiles (“0”) in the
Mann-Whitney U test. Results of the Mann-Whitney U test was significant: U = 101.00, z = -
2.26, p < .05, r = .33 (see Table 12). This indicated that the team conflict efficacy scores for
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teams with moderate cooperative VCM profiles (Mdn = 19.71, n = 38) were significantly higher
than those for teams with moderate competitive VCM profiles (Mdn = 18.58, n = 10). Therefore,
Hypothesis 6a was supported.
Hypothesis 6b predicted that relative to teams with moderate competitive VCM profiles,
teams with moderate cooperative VCM profiles are likely to report higher levels of members’
satisfaction with their team’s conflict management process. Results of the planned comparison
test contrasting moderate cooperative VCM profiles against moderate competitive VCM profiles
on member satisfaction with the team’s conflict management process scores was non-significant:
t (57) = .77, ns (see Table 13). In other words, teams with moderate cooperative VCM profiles
(M = 21.88, SD = 2.30) were not significantly more satisfied with their conflict management
process than teams with moderate competitive VCM profiles (M = 21.27, SD = 1.69).
Hypothesis 6b was therefore not supported.
When it comes to Hypothesis 6c, this indicated that relative to teams with moderate
competitive VCM profiles, teams with moderate cooperative VCM profiles are also likely to
report higher levels of team effectiveness. Results of the planned comparison test contrasting
moderate cooperative VCM profiles against moderate competitive VCM profiles on team
effectiveness was significant: t (57) = 2.02, p < .05, r = .26 (see Table 13). The mean team
effectiveness scores for teams with moderate cooperative VCM profiles (M = 19.04, SD = 1.75)
were thus significantly higher than those for teams with moderate competitive VCM profiles (M
= 17.83, SD = 1.29). As such, Hypothesis 6c was supported.
Maximum VCM profiles versus moderate competitive VCM profiles. Hypotheses 7a to 7c
were concerned with comparing the effects of maximum VCM profiles and moderate
competitive VCM profiles on team conflict efficacy, members’ satisfaction with the team’s
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conflict management process and team effectiveness respectively. Hypothesis 7a was analyzed
using the Mann-Whitney U Test due to a violation of the non-normality assumption for teams
with moderate competitive VCM profiles, while Hypotheses 7b and 7c were each examined with
planned comparisons.
Hypothesis 7a stated that relative to teams with moderate competitive VCM profiles,
teams with maximum VCM profiles are likely to report higher levels of team conflict efficacy.
To test this hypothesis, a dummy variable was created to compare teams with moderate
competitive VCM profiles (“1”) and those with maximum VCM profiles (“0”) and applied in the
Mann-Whitney U test. Results of the Mann-Whitney U test revealed a marginally significant
difference in team conflict efficacy scores between teams with maximum VCM profiles (Mdn =
19.25, n = 5) and those with moderate competitive VCM profiles (Mdn = 18.58, n = 10), U =
9.50, z = -1.91, p < .10 (see Table 12). Therefore, this indicated that Hypothesis 7a was not
supported.
Hypothesis 7b predicted that relative to teams with moderate competitive VCM profiles,
teams with maximum VCM profiles are also likely to report higher levels of members’
satisfaction with team conflict management process. Results of the planned comparison test
contrasting teams with moderate competitive VCM profiles against teams with maximum VCM
profiles on member satisfaction with the team’s conflict management process scores was non-
significant: t (57) = -1.09, ns (see Table 13). In other words, teams with maximum VCM profiles
(M = 22.60, SD = 3.10) were not significantly more satisfied with their conflict management
process than those with moderate competitive VCM profiles (M = 21.27, SD = 1.69).
Accordingly, Hypothesis 7b was not supported.
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Finally, for Hypothesis 7c, it was hypothesized that relative to teams with moderate
competitive VCM profiles, teams with maximum VCM profiles are also likely to report higher
levels of team effectiveness. Results of the planned comparison test contrasting teams with
maximum VCM profiles against teams with moderate competitive VCM profiles on team
effectiveness were also non-significant: t (57) = -1.54, ns (see Table 13). The mean team
effectiveness scores for teams with maximum VCM profiles (M = 19.25, SD = 2.38) were not
significantly higher than those for teams with moderate competitive VCM profiles (M = 17.83,
SD = 1.29). As such, Hypothesis 7c was also not supported.
Assessing potential antecedents of VCM
Gender role diversity. Hypothesis 8 predicted a positive relationship between gender role
diversity and VCM (i.e., The higher the levels of gender role diversity, the more likely VCM will
occur in teams). To test Hypothesis 8, a simple regression analysis was conducted. Table 14
shows the findings for the simple regression analysis. The findings revealed that gender role
diversity did not predict VCM significantly, F (1, 76) = .77, ns. As such, Hypothesis 8 was not
supported.
Team goal interdependence. Hypothesis 9 predicted an inverted U-shaped curvilinear
relationship between different types of goal interdependence and VCM (i.e., cooperative and
competitive goal interdependence will be negatively associated with VCM, while mixed goal
interdependence will be positively associated with VCM). A polynomial regression analysis was
used to test this hypothesis.
A higher order variable of team goal interdependence (squared team goal
interdependence) was created in order to test the nonlinear relationship proposed. Next, both
team goal interdependence and squared team goal interdependence variables were then centered
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and entered into the model to improve interpretability of parameter estimates and to reduce
multicollinearity between predictor variables.
Table 15 shows the findings for the polynomial regression analysis. The findings
revealed that neither team goal interdependence nor its higher order variable significantly
predicted VCM, F (2, 76) = 1.35, ns. Therefore, Hypothesis 9 was also not supported.
Subgroup formation as a mediator. Hypothesis 10 predicted the mediating role of
subgroup formation between gender role diversity and VCM. It was tested using mediational
regression analyses, based on Baron and Kenny’s (1986) approach. According to Baron and
Kenny (1986), three conditions need to be established in order to demonstrate mediation effects:
(1) the antecedent has to be related to the outcome; (2) the antecedent has to be related to the
mediator; (3) the relationship between the antecedent and the outcome will be partially or fully
removed when the mediator is controlled for (p.1177).
To test Hypothesis 10, the first mediational condition that gender role diversity is related
to VCM has to be established. Since Hypothesis 8 was not supported and earlier correlational
analyses also indicated that gender role diversity was not correlated with VCM, this first
condition was therefore not established.
The second mediational condition stated that gender role diversity has to be related to
subgroup formation. A simple regression analysis was conducted to test this relationship. Results
from the regression analysis indicated that gender role diversity was unrelated to subgroup
formation, F (1, 76) = 2.29, ns (see Table 16). Therefore, the second mediational condition was
also not established.
Finally, the third mediational condition required the full or partial elimination of the
relationship between gender role diversity and VCM is removed when subgroup formation is
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controlled for. A hierarchical multiple regression analysis was conducted to test this condition.
Subgroup formation was entered as the first predictor in Step 1 of the model, and gender role
diversity as the second predictor in Step 2. Results from the hierarchical regression analysis
noted that both subgroup formation and gender role diversity did not contribute significantly in
the final model, F (2, 75) = .51, ns (see Table 17). Considering these findings, Hypothesis 10
was therefore not supported.
Supplementary analyses
Given the preliminary, exploratory and main findings reported above, I also conducted
additional supplementary analyses to empirically assess the presence of the various VCM
profiles uncovered in the content coding process, using a series of latent class analyses. Based on
the categories identified in the latent class analyses, I further explored possible group differences
among these VCM categories on the three key outcome variables involved in this study, i.e.,
team conflict efficacy, member satisfaction with the team’s conflict management process, and
team effectiveness.
Assessing VCM profiles using latent class analyses
In addition to the qualitative content coding analyses described earlier, a series of latent
class analyses (LCA) was also conducted to examine whether the distinctly different
distributional patterns of conflict management in the teams, i.e., the proposed VCM profiles, may
be observed in the teams sampled. Lawrence and Zyphur (2011) recently argued and
demonstrated the utility of using LCA for identifying and measuring organizational faultlines in
work groups. More importantly, they argued that LCA may be particularly useful when “the
central concept involves a profile, such as a profile of individuals’ personality traits, a profile of
high- versus low-performing groups or a profile of the network attributes of industries” (p. 52).
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LCA can be used as a measurement model to uncover latent clusters or distinct subgroups that
may exist in teams (Lawrence & Zyphur, 2011). As such, it is expected that the LCA technique
should be a useful analytical tool for uncovering the presence of different VCM profiles in
teams.
To conduct the LCAs, I first created eight binary indicators or items (with values of “0”
and “1”), based on all the VCM profile categories identified in the content coding analysis. For
example, one of the eight items would represent the minimum cooperative VCM profile, with
teams characterizing this profile coded as “1” and teams that do not coded as “0”. When it comes
to the “other” VCM profile category, three items were created, with each representing one of the
three types identified in the content coding analysis: ‘distributed,’ ‘multiple clusters,’ and
‘midpoint cluster.’
A series of LCAs were then conducted to compare models with two- through eight-class
solutions using the software, Mplus Version 6.1 (Muthén & Muthén, 1998 – 2010). The two-
class solution represents the simplest possible solution that aligns with Deutsch’s (1949, 1973)
one-dimensional conceptual framework of cooperative and competitive conflict management,
while the eight-class solution represents the maximum possible number of latent classes
identified in the content coding analysis.
Overall, the LCA literature recommends using a combination of information criteria and
fit indexes (or likelihood-based tests) in determining the most appropriate number of latent
classes in LCA modeling (Finch & Bronk, 2011; Nylund, Asparouhov & Muthén, 2007).
Statistical Information Criteria (IC), such as the Akaike Information Criterion (AIC), the
Bayesian Information Criterion (BIC) and the Sample-size Adjusted Bayesian Information
Criterion (aBIC), are typical indices used to guide the decision on the number of latent classes
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identified in LCA modeling (Nylund, et al., 2007). Generally, the lower the value of these
indices, the better the model fit. Of the three, aBIC has been found to be superior to the other two
ICs in LCA modeling simulation studies (Yang, 2006).
The Lo-Mendell-Rubin adjusted Likelihood Test (LMRT) and the Bootstrap Likelihood
Ratio Test (BLRT) are two recommended fit indexes used to perform significance testing in
evaluating model fit (Nylund et al., 2007). The LMRT compares two neighboring class models
and determines whether there is improvement in model fit with the addition of one more class.
When the test value for LMRT is significant at the p-value of .05, this indicates that the model
with k classes fits the data better than the model with k – 1 classes. As for the BLRT, this test
uses bootstrap samples to estimate log likelihood difference distribution between the k – 1 and k
class models (Nylund et al., 2007). Similar to the LMRT, when the test value for the BLRT is
significant at p-value of .05, this also suggests that the k class model is sufficient in fitting the
observed data compared to the k – 1 class model.
Table 18 shows the fit statistics for the various model comparisons in the LCAs. Based
on the fit statistics, the model with a four-class solution appears to fit the data best. The four-
class model solution has the second lowest aBIC value, coupled with both significant LMRT and
BLRT results. Both the significant LMRT and BLRT results suggest that four (k) classes fit the
observed data better than three (k - 1) classes.
Figure 6 shows a graph depicting the estimated conditional probabilities for the four-class
solution. The x-axis represents the eight binary items, while the y-axis represents the range of
conditional probabilities for each class. Each line on the graph represents a distinct latent class
identified in the analysis. The estimated conditional probabilities are specific to each class and
provide information on the probability of each team as belonging in that class. For example, the
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conditional probability for Class 1 is 26.6%, and this indicates that 26.6% of all the teams are
most likely to belong to Class 1 rather than to the other three classes.
Table 19 shows how the various proposed VCM profiles corresponded with the four
distinct latent classes identified in the analysis (for a graphical depiction, see Figure 7). The
“Count” and “Proportions” columns refer to the number and percentage of teams that are
classified into each latent class respectively. This four-class model solution identified four
distinct latent classes or categories, three of which aligned with the VCM profiles identified in
the content coding analysis. These three categories were moderate cooperative VCM, moderate
competitive VCM, and ‘distributed’ profiles. Consistent with earlier observations in the content
coding analysis, the highest number of teams also had moderate cooperative VCM profiles. The
next most prevalent profiles were moderate competitive VCM and ‘distributed’ profiles. The last
latent class identified in the analysis consisted of all the teams that were described as having
minimum cooperative VCM, maximum VCM, minimum competitive VCM, ‘multiple clusters,’
and ‘midpoint cluster’ profiles (for simplicity, I refer to this class as the ‘combination’ category).
There were 17 such teams in this category, and together, they made up 26.6% of all the teams
examined.
The “Threshold estimate” column in Table 7 refers to the threshold values of teams
belonging to the binary items for the four-class model. Larger positive threshold values indicate
a lower likelihood of teams belonging to a given item (i.e., having a value of “1” instead of “0”
for that item), while large negative values indicate the opposite (Finch & Bronk, 2011). Three of
the four latent classes each had threshold estimates of -15.000. These estimates indicated the
highest possible likelihood of teams belonging to each class or VCM profile.
Exploring group differences among VCM categories on team outcomes
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VCM categories on team conflict efficacy. Using the four VCM categories identified in
the LCAs, I then proceeded to explore possible group differences among these four categories in
terms of their effects on the three team outcomes: team conflict efficacy, member satisfaction
with the team’s conflict management process, and team effectiveness. Preliminary analyses were
conducted to assess the assumptions of homoscedasticity, independence, linearity, normality, and
multicollinearity, and it was found that the distributions of team conflict efficacy scores for
teams with moderate competitive VCM profiles, W (10) = .26, p < .01, and teams with profiles
that fall under the ‘combination’ category were significantly non-normal, W (21) = .89, p < .05.
As a result, the Kruskall-Wallis Test and a series of Mann-Whitney U tests were used to assess
group differences in team conflict efficacy scores among the four VCM categories identified in
the latent class analyses. On the other hand, group differences in member satisfaction with the
team’s conflict management process and team effectiveness scores among the four VCM
categories were explored using one-way between-groups ANOVAs.
Findings from the Kruskall-Wallis test showed that there was no significant overall
difference in team conflict efficacy scores across all four VCM categories: H (3) = 5.74, ns (see
Table 20). To follow-up on this finding, dummy variables were created to compare each of the
four VCM categories with one another in six Mann-Whitney U tests. Two of the six Mann-
Whitney U test findings were significant: Teams with profiles under the ‘combination’ category
(i.e., minimum cooperative, maximum, minimum competitive, ‘multiple clusters,’ and ‘midpoint
cluster’; Mdn = 19.25, n = 21) reported significantly higher levels of team conflict efficacy than
teams with moderate competitive VCM profiles (Mdn = 18.58, n = 10), U = 54.00, z = -2.16, p <
.05, r = .39; Teams with the moderate cooperative VCM profiles (Mdn = 19.71 n = 37) also
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reported significantly higher levels of team conflict efficacy than teams with moderate
competitive VCM profiles (Mdn = 18.58, n = 10), U = 101.00, z = -2.26, p < .05, r = .33.
VCM categories on member satisfaction with the team’s conflict management process.
Results from the one-way ANOVA revealed that there was no significant group difference in
member satisfaction with the team’s conflict management process scores across all four VCM
categories, F (3, 75) = .29, ns (see Table 21).
VCM categories on team effectiveness. The ANOVA findings showed that there was no
significant overall group difference in team effectiveness scores across all four VCM categories
as well, F (3, 75) = 1.03, ns (see Table 21).
Table 22 provides a summary of all the findings reported in the main and supplementary
analyses in this chapter.
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CHAPTER V: DISCUSSION
The overall purpose of this dissertation study was to empirically test Tan’s (2011)
conceptual model, which proposes a new team-level construct of conflict management, known as
variant conflict management (VCM). In this model, VCM is defined as the degree and pattern of
differences in the ways individual members handle conflicts cooperatively and/or competitively
among themselves within teams. Further, VCM is posited to consist of five distributional
patterns or ‘profiles’ that characterize member differences in conflict handling: minimum
cooperative, minimum competitive, moderate cooperative, moderate competitive and maximum
VCM profiles. Tan’s (2011) model also suggests that factors within three antecedent categories,
namely salient conflict-relevant member characteristics, team contextual determinants and
divergent team dynamics, will predict the development of VCM. The model further notes that the
various VCM profiles are likely to exert differential effects on key team outcomes, such as
member satisfaction and team effectiveness; the effects of VCM (based on teams’ standard
deviation scores) are also likely to be above and beyond those of traditional concepts of team
conflict management, i.e., homogeneous or means-based team conflict management (Tan, 2011).
This study sought to accomplish four key research objectives. The first objective was to
assess whether the five proposed VCM profiles (minimum cooperative, minimum competitive,
moderate cooperative, moderate competitive and maximum VCM profiles) are evident in the
student project teams sampled. Based on findings from the qualitative content coding analyses, it
was observed that within-team differences in members’ conflict management approaches could
indeed be organized into distinct configurations aligned with the five VCM profile types
proposed in Tan’s (2011) model. Moreover, it was also noted that among the teams sampled, a
majority of them exhibited moderate cooperative VCM profiles, followed by moderate
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competitive, minimum cooperative, maximum, and minimum competitive VCM profiles. Such
frequency distributions of VCM profiles are understandable given the nature of the sampled
teams. Since this study involved teams comprised of students who needed to rely on one another
in order to complete their team projects, it is reasonable to expect that team members would be
relatively cooperative with one another when handling team conflict situations in the process of
working on their projects. Additionally, the interdependent nature of the team task would also
preclude most teams from developing minimum competitive VCM profiles, since it would be
challenging for highly competitive members to work together effectively toward their team
goals.
Aside from the five VCM profiles discussed above, the content coding analyses also
revealed other VCM profiles that were not included in Tan’s (2011) conceptual model. This set
of VCM profiles were tentatively described as ‘distributed,’ ‘multiple clusters,’ and ‘midpoint
cluster.’ Teams with the ‘distributed’ VCM profiles were characterized by members who were
relatively spread out along the conflict management continuum; in these teams, no discernible
clusters were observed along the continuum as well. As for teams with the ‘multiple clusters’
VCM profiles, these were characterized by the presence of smaller subgroups or clusters that
were distributed along the conflict management continuum; no single majority subgroup was
observed in such profiles. When it comes to teams described with the ‘midpoint cluster’ VCM
profiles, these were characterized by all members being co-located around the midpoint of the
conflict management continuum.
One possible explanation for the emergence of the ‘distributed’ and ‘multiple clusters’
VCM profiles could be that team members were not subject to relatively strong situational or
team-level pressures that would sway them to act more similarly with most of their teammates
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(Meyer, et al., 2010; Mischel 1977). As a result, members in such teams may be free to rely on
their own natural proclivities in conflict management when conflict situations arise in their
teams, thus leading to more diversity or spreading out of individual conflict approaches within
the teams. More research would certainly be needed to better understand the conditions under
and mechanisms through which ‘distributed’ and ‘multiple clusters’ VCM profiles are likely to
occur.
Further, the presence of ‘midpoint cluster’ VCM profiles among some of the teams
observed suggests that individual members may not always veer toward the cooperative or
competitive end of the one-dimensional conflict management continuum, as postulated in Tan’s
(2011) model. Rather, it is possible for teams to comprise of all members whose preferences
involve using conflict management strategies that lie somewhere in between cooperative and
competitive conflict management. Such conflict management strategies also parallel the concepts
of compromising, accommodating or obliging styles of conflict management, as discussed in
other existing conflict management theories or typologies (e.g., Rahim & Bonoma, 1979;
Thomas & Kilmann, 1974). As such, the presence of ‘midpoint cluster’ VCM profiles in teams
suggests that the proposed VCM theory would also require more development and refinement in
order to better explain and predict the possibilities of such distributional patterns in conflict
management approaches among team members.
From an empirical standpoint, the supplementary latent class analyses (LCAs) provided
further validation to some of the VCM profiles proposed in the model, as well as the need to
consider additional profiles in the model. Specifically, the LCAs identified two of the proposed
VCM profiles, i.e., moderate cooperative and moderate competitive VCM profiles, as distinct
latent classes in the data. The new ‘distributed’ profile was also identified as a distinct latent
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class in the LCAs, thus supporting the discovery of this profile in the content coding analyses.
The LCA results were also consistent with those from the content coding analyses in noting that
the moderate cooperative VCM profiles were most prevalent in the teams sampled.
The LCA findings supported the conclusion that other profiles that are not currently
included in Tan’s (2011) model may be present in teams as well. In particular, the analyses
revealed a “combination” category that encompasses three of the proposed VCM profiles (i.e.,
minimum cooperative, maximum and minimum competitive VCM profiles) and two of the new
profiles (i.e., ‘multiple clusters’ and ‘midpoint cluster’) identified in the content coding. While
these findings may, in part, be due to the small sample sizes associated with these profiles, they
nonetheless indicate the need for future research to assess the possibility of new profiles that may
emerge by using larger team samples in comparable settings.
The second research objective of this study was to examine whether the overall degree of
variability in team members’ conflict management approaches, i.e., VCM based on teams’
standard deviation scores, would predict team outcomes (team conflict efficacy, members’
satisfaction with the team’s conflict management process, and team effectiveness) above and
beyond conventional measures of team conflict management, i.e., cooperative and competitive
team conflict management based on group means’ scores respectively. Preliminary correlational
analyses showed that consistent with prior research (e.g., Alper et al., 2000), mean cooperative
team conflict management was positively associated with team outcomes, i.e., team conflict
efficacy, member satisfaction and team effectiveness. In the main hypothesis tests, however,
these effects of cooperative team conflict management on team conflict efficacy and member
satisfaction were removed when control variables, such as team goal interdependence and
conflict intensity, were included. Such findings also supported earlier research in noting that the
88
effects of mean cooperative team conflict management on team outcomes are, in part, dependent
on other factors such as goal interdependence (e.g., Alper et al., 1998) and conflict intensity
(e.g., Barker et al., 1988).
When it comes to competitive team conflict management, however, findings from both
the correlations and main hypothesis tests contradicted those of prior research (e.g., Alper et al.,
2000; Tjosvold, Law & Sun, 2006): mean competitive team conflict management was found to
be uncorrelated with team conflict efficacy, member satisfaction, and team effectiveness. This
absence of effects may be explained by the relatively cooperative nature of the teams sampled.
Since the teams in this study were found to be generally cooperative, the individual and team
scores obtained on the competitive conflict management sub-scale were therefore likely to be
lower (i.e., less competitive) compared to other teams sampled in earlier studies. As such, the
relatively cooperative team sample in this study would also result in a reduced likelihood of
detecting significant effects of competitive team conflict management on team outcomes.
As for overall VCM, the correlational analyses indicated that it was uncorrelated with
team conflict efficacy, member satisfaction with the team’s conflict management process, and
team effectiveness. Overall VCM was also uncorrelated with cooperative and competitive team
conflict management. Results from the main hypothesis tests also indicated that it did not predict
all three team outcome variables above and beyond mean cooperative or competitive team
conflict management. This lack of effects of overall VCM on team outcomes, above and beyond
those of mean team conflict management may be partly due to the fact that the same measure
was used to assess the team conflict management and VCM variables. Since the conflict
management measure was adapted to assess individual perceptions about individuals’ conflict
handling approaches within the team, rather than individual perceptions about the team’s conflict
89
handling approaches as a whole, this adjustment may have affected the construct validity of team
conflict management as well (Chan, 1998). As such, future research should attempt to assess the
team conflict management and VCM constructs using separate and different measures or
instruments. Other reasons that may explain the absence of effects of overall VCM on team
outcomes include the generally cooperative nature of the teams sampled and the collectivistic
cultural context (Singapore) in which these teams were embedded. Such team and contextual
characteristics are thus likely to lower the degree of overall variability in members’ conflict
management approaches, and as such, also reduce the likelihood of finding significant effects of
overall VCM on team outcomes.
Additionally, the lack of associations between overall VCM and team outcomes also
suggests that VCM may be better construed as a categorical rather than a continuous variable.
This observation is further supported by the significant associations between specific VCM
profiles and the various team outcomes examined in the planned comparisons. Findings from the
planned comparisons and correlational analyses seem to suggest that how variability in
members’ conflict management strategies are organized within their teams, i.e., VCM profiles,
may be associated with distinctly different dynamics and interaction patterns (e.g., different
numbers of subgroups formed or the amount of intense conflicts experienced) that, in turn, can
produce differential effects on important team outcomes. When only the impact on the overall
degree of members’ conflict management differences within their teams, i.e., overall VCM, was
examined, then, it is possible that the distinctly different dynamics and processes associated with
different VCM profiles would have been masked or overlooked in the analyses, thus leading to
possible ‘canceling out’ of opposing effects in the findings.
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Accordingly, the definition of the VCM construct should be revised to indicate only the
patterns, and not the degree, of differences in which members handle conflicts within their
teams.
The third research objective of this study was to compare the effects of various VCM
profiles on team conflict efficacy, member satisfaction with the team’s conflict management
process, and team effectiveness. Results from the study revealed that teams with minimum
cooperative or moderate cooperative VCM profiles reported higher levels of conflict efficacy
than those with moderate competitive VCM profiles. Teams with minimum competitive VCM
profiles reported the lowest levels of member satisfaction, when compared to teams with the
other four VCM profiles proposed in Tan’s (2011) model. Teams with minimum cooperative
VCM profiles were found to be more effective than those with minimum competitive VCM
profiles. Teams with moderate cooperative profiles were also more effective than those with
minimum competitive VCM profiles, as well as those with moderate competitive VCM profiles.
As for comparisons between teams with maximum and moderate competitive VCM profiles, no
significant effects were observed between these two types of teams on all three outcomes.
Taken altogether, it can be concluded that these findings on various VCM profiles’
impact on team outcomes also paralleled prior research on the effects of cooperative and
competitive conflict management in teams (e.g., Alper et al., 2000; Tjosvold, Law & Sun, 2006).
Overall, teams with VCM profiles that are more cooperative in nature (i.e., minimum
cooperative and moderate cooperative VCM profiles) are more likely to experience positive team
outcomes (i.e., higher levels of team conflict efficacy, member satisfaction with the team conflict
management process, and team effectiveness), when compared to those with VCM profiles that
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are more competitive in nature (i.e., minimum competitive and moderate competitive VCM
profiles).
As for the absence of effects comparing maximum and moderate competitive VCM
profiles, this may be due to the relatively small group sizes involving teams with these two
profile types. It was also observed in the data, based on the qualitative content coding analyses,
that some of the teams that were coded as having maximum VCM profiles may not have enough
“distance” between the opposing subgroups within them. In other words, the two subgroups in
these teams may not be far apart enough for opposing cooperative and competitive dynamics to
truly emerge and significantly influence team outcomes. Future investigations should attempt to
identify large enough samples of teams with “true” maximum VCM profiles and to replicate the
comparison study of how these teams may differ from those with moderate competitive VCM
profiles in affecting team outcomes.
Last but not least, the fourth research objective of this study was to investigate whether
gender role diversity, team goal interdependence and subgroup formation are likely to predict the
development of VCM in teams. Contrary to the hypotheses, all three predictor variables were
found to be unrelated to VCM in both the correlations and main hypothesis tests. For the lack of
association between gender role diversity and VCM, one possible explanation may be that at the
team level, differences in members’ gender role orientations among two or more members within
the teams were simply not salient enough to affect team functioning and outcomes. The
relatively low standard deviation and variance scores obtained for gender role diversity (SD =
.15, S2 = .02) in Table 1 also suggest that there was limited variability in this variable across the
teams sampled, thus perhaps making the construct less salient than expected. Prior studies have
suggested that saliency in member differences may play a role in determining whether diversity
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in member attributes affect important outcomes (e.g., Zellmer-Bruhn, Maloney, Bhappu, et al.,
2010). Further research should therefore examine whether team members perceive salient
differences in gender role orientations among one another in their teams, and in turn, whether
such salient differences influence team outcomes.
The absence of relationship between team goal interdependence and VCM was
surprising, given the consistently strong associations between goal interdependence and conflict
management that have been noted in past research (e.g., Tjosvold, 1998). This absence of
associations may be traced back to the earlier conclusion that the VCM construct would be better
conceived as a categorical rather than a continuous variable. In a similar vein, possible opposing
effects of cooperative and competitive goal interdependence on overall VCM may have been
masked by the continuous nature of the VCM construct conceptualized here. Future research
should therefore examine whether team goal interdependence would significantly predict the
various VCM profiles instead.
As for the lack of evidence supporting subgroup formation as a mediator in the gender
role diversity-VCM relationship, this may in part be due to the ‘generic’ nature of the subgroup
formation measure. Since the measure items only surveyed for the presence and nature of
subgroups in the teams, it was unclear whether the subgroups formed were, in fact, relevant or
specific to the team conflicts experienced within the teams. Future research should adapt the
subgroup formation measure such that it is conflict-specific. Additional research is also needed
to identify other potential mediating factors that may influence possible antecedent-VCM
linkages.
Theoretical implications
93
From a theoretical perspective, this study contributed to existing theory on conflict
management by examining Tan’s (2011) VCM model, which is the first theoretical model that
was formulated to describe and explain conflict management at the team level. Study results also
provided initial support for the presence of VCM profiles as proposed in Tan’s (2011) model,
corroborated prior research on team conflict management and on existing conflict management
theories, as well as provided insights into possible extensions or refinements of the VCM model
with the discovery of ‘new’ VCM profiles.
Most notably, findings from this study offered preliminary support to the argument that
the present study of team conflict management based on teams’ means scores limits our
understanding of the phenomenon. While some of the findings did support prior research
regarding the impact of mean cooperative and competitive team conflict management on team
outcomes (e.g., Alper et al., 2000; Tjosvold, Law & Sun, 2006), it was also observed that
individual members do not always converge or share similar conflict management approaches
within their teams. This divergence or diversity of individual differences in conflict management
approaches was evidenced by the presence of distinct VCM profiles uncovered in both the
content coding and latent class analyses in this study. Findings from this study also indicated that
different VCM profiles could exert differential effects on important outcomes, such as team
conflict efficacy, member satisfaction and team effectiveness. The uncovering of ‘new’ VCM
profiles in these analyses also indicates the need to further refine or extend the proposed VCM
model.
From the study results, it was also inferred that VCM might be better conceptualized in
terms of the distributional patterns of individual conflict management approaches within teams
(i.e., VCM profiles), rather than the extent of such differences within teams (i.e., standard
94
deviations-based VCM). This inference is supported by the fact that some of the VCM profiles
were found to influence critical team outcomes differently, whereas VCM, when based on team
standard-deviation scores, did not have a significant effect on the same team outcomes
examined. Accordingly, assessing the degree to which members differ in the ways they handle
team conflicts alone is insufficient in advancing our knowledge in team conflict management.
Researchers need to explore beyond shared team conflict management, and to further assess the
patterns in which differences in members’ conflict management approaches are or can be
manifested within teams.
Research implications
From an empirical standpoint, this study was one of the first to examine the presence of
variability in individual conflict management at the team level, how such variability may impact
team outcomes differently from traditional concepts of team conflict management, as well as
how such variability may form distinct and meaningful patterns that have consequential effects
on important team outcomes. Furthermore, this study also investigated whether gender role
diversity, team goal interdependence, and subgroup formation predicted variability in individual
conflict management within teams.
By examining these relationships, this study contributed to our current knowledge of
team conflict management with preliminary evidence supporting the presence of member
differences in conflict management within teams, in terms of distinct configurations, that could,
in turn, exert varying effects on team conflict efficacy, member satisfaction and team
effectiveness. The study findings also indicated that there are nuanced differences in terms of
how cooperative or competitive conflict management in teams may influence certain team
outcomes. For instance, it was noted that teams with minimum cooperative VCM profiles were
95
more effective than teams with minimum competitive VCM profiles, but not those with moderate
competitive VCM profiles. On the other hand, teams with moderate cooperative VCM profiles
were more effective than both teams with minimum and moderate competitive VCM profiles.
What, then, are some reasons that may account for such differences?
One possible direction to explore would be the interplays among within-team conflicts
(especially intense and important ones), team goal interdependence, and subgroup formation, in
the VCM profile-team outcome linkages. Based on the correlational findings, it was noted that
both cooperative and competitive conflict management were strongly correlated with team goal
interdependence, subgroup formation, within-team conflict and conflict intensity. Specifically,
these correlations suggest that cooperative teams are likely to have more positive interdependent
goals among members, fewer opposing subgroups, less within-team conflicts (especially intense
ones), and improved eventual team outcomes. By contrast, competitive teams are likely to have
more negative interdependent goals among members, more conflicting subgroups, and increased
within-team conflicts that are also experienced as intense and important. As such, it may be
inferred from these correlations that whether a team’s VCM profile is relatively cooperative or
competitive in nature and how the nature of the profile is patterned (i.e., whether there is a
cooperative or competitive majority subgroup, or no majority subgroups at all) can significantly
influence the team’s dynamics and processes, which can in turn lead to improvements or
detriments on team functioning and effectiveness. Accordingly, these observations and
conclusions help extend our current understanding about the mechanisms and factors that explain
how individual differences in conflict management within teams affect team process and outputs.
Practical implications
96
As for practice-related implications, findings from this study may be able to help
managers, team leaders or self-managed teams better understand how differences in the ways
their team members handle conflict situations can significantly impact effective team processes
and outcomes. For example, a team may recognize that when its members are organized into a
cooperative majority subgroup and a competitive minority subgroup in their conflict
management approaches; this configuration may actually facilitate its performance compared to
when all its members are highly competitive in handling conflict situations.
Furthermore, by identifying specific VCM profiles that are likely to enhance rather than
undermine effectiveness or team functioning, managers, team leaders or self-managed teams
may also be better able to steer their teams away from more ‘detrimental’ VCM profiles or
promote the development of more ‘productive’ ones in their teams. Encouraging a team to shift
from a moderate competitive VCM profile to a minimum cooperative or moderate cooperative
VCM profile by providing opportunities for team members to learn and apply more cooperative
conflict management skills, for instance, may in turn help increase the team’s effectiveness.
Last but not least, results from this study may also help inform managers, team leaders or
self-managed teams about specific factors that are likely to influence the development of specific
VCM profiles in teams. For example, promoting positive interdependent goals among its
members and discouraging the formation of member ‘cliques’ or subgroups may help reduce the
likelihood of the team developing a minimum competitive or moderate competitive VCM
profile.
Study limitations
As with all research, this study was also subject to a number of limitations. As a cross-
sectional field study, it is important to note that the results obtained in this study only indicate
97
correlational, and not causal, relationships among the variables examined. The teams sampled in
this study were also comprised of student project teams with relatively young members, and with
clear team goals that existed for a relatively short period of time (i.e., an academic semester).
Although such a sample may suggest limited generalizability of the results, prior research has
shown that studies using student teams often found comparable findings to those using
organizational teams (see Van Vianen & De Dreu, 2001).
Since the teams involved in this study were identified based on available member
responses, and that a considerable number of the teams included in the analyses were not
complete teams, the variance of scores within the teams may have been restricted, and thereby
reducing the likelihood of detecting more significant effects. The sizes of teams sampled were
also relatively small (i.e., 3 to 8). Future investigations should attempt to use complete intact
teams and with larger team samples.
The use of unequal and relatively small group sizes used in the group comparison
analyses among VCM profiles, and the application of less powerful non-parametric tests also
suggest a lower likelihood in detecting significant effects. As such, the results obtained from
these analyses should also be interpreted with caution.
Future research directions
Considering the findings obtained in this study, there are numerous questions that may be
answered and addressed in future research. For instance, researchers should attempt to further
refine Tan’s (2011) VCM theory, given the discovery of other possible VCM profiles in teams.
Specifically, one may develop additional theorizing to explain the occurrence and impact of the
‘distributed,’ ‘multiple clusters,’ and ‘midpoint cluster’ VCM profiles.
98
Researchers should also consider developing new measures or methods to assess VCM
profiles instead of relying on existing survey instruments. For example, using objective
measures, such as behavioral observations of participants’ conflict management approaches in
teams over time, may help reduce potential self-report biases and better assess the presence and
nature of VCM profiles formed within teams. The use of other research designs, such as
experiments and longitudinal surveys, may also help better establish the validity and causality of
relationships among the VCM construct, various VCM profiles, with their potential predictors
and outcomes.
Other variables representing each of the three antecedent categories (viz., salient conflict-
relevant member characteristics, team contextual determinants, and divergent team dynamics) of
VCM and its profiles should also be identified and examined in future investigations. For
example, investigators may want to consider examining the impact of cultural diversity among
team members, as another possible indicator of salient member characteristics, on various VCM
profiles. Cultural differences among members within teams have been found to influence team
conflict management (Boros et al., 2010), and as such, these differences may also be likely to
influence patterns of variability in how members manage internal team conflicts.
Future studies should also look into using organizational team samples or other types of
teams in various organizational settings, such that the predictors and outcomes of VCM profiles
may be better understood across a broader range of teams and contexts.
Conclusion
As the formation and use of work teams continue to accelerate in contemporary
organizations, the need to understand the conditions and mechanisms that can either enhance or
undermine effective team conflict management will undoubtedly also increase in both
99
importance and relevance to organizational scholars, managers and team leaders. To that end, I
urge both current and future researchers to advance the VCM theory, by taking on the challenges
of further examining the nature and impact of VCM profiles. It is with much hope that we may
begin to take further strides on our journey to deepen our knowledge of team conflict
management, particularly as it relates to enriching our understanding of how differences in
individual conflict handling approaches may develop and in turn affect team process and
important outcomes.
100
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Table 1
Descriptive Statistics for All Key Team Variables (N = 79)
Variable M SD S2 Min Max Predictors
1. Cooperative team conflict management
15.72 1.24 1.54 11.33 19.00
2. Competitive team conflict management
4.19 0.95 0.91 2.33 6.90
3. Variant conflict management
2.25 0.92 0.84 0 5.18
4. Gender role diversity 0.62 0.15 0.02 0 0.86 5. Team goal
interdependence 37.56 2.66 7.09 30.67 44.00
6. Mixed goal interdependencea
37.57 1.45 2.11 35.00 40.00
7. Subgroup formation 7.67 1.92 3.67 4.00 12.00 Outcomes
8. Team conflict efficacy 19.38 1.49 2.23 16.00 23.67 9. Satisfaction with team
conflict management process
21.85 2.24 5.01 17.00 26.40
10. Team effectiveness 18.74 1.96 3.86 13.33 22.75 Controls
11. Intra-group conflict 17.54 3.57 12.71
12.33 28.75
12. Team conflict intensity 7.95 1.74 3.01 5.25 14.25 13. Team conflict importance 2.33 0.59 0.35 1.00 3.75 14. Team sizeb 4.22 1.00 0.99 3.00 8.00
Other 15. Team agec 21.72 0.95 0.90 19.33 25.75 16. Team interactiond 1.51 0.42 0.17 1.00 3.00
Note. a n = 56. b Team size is based on the number of members who participated from each team. c Team age is calculated using the average age of members in each team. d Team interaction is calculated using the mean scores for reported level of interaction among members in each team.
121
Table 2
Reliability and Aggregation Indices for All Team Measures (N = 79)
Variable α Median rWG (J)
ICC (1) ICC (2)
Predictors 1. Conflict management .70 .92 .18 .57
Cooperation .73 .91 .21 .51 Competition .70 .74 .32 .48
2. Team goal interdependence .81 .96 .17 .68 Positive .78 .95 .40 .77 Negative .73 .89 .16 .49
3. Gender role orientationa .78 .97 .06 .56 Masculine .84 .95 .11 .54 Feminine .87 .94 .27 .77
4. Subgroup formation .82 .80 .45 .76 Outcomes 5. Team conflict efficacy .78 .95 .38 .75 6. Satisfaction with team conflict
management process .74 .92 .37 .79
7. Team effectiveness .94 .95 .74 .93 Controls 8. Intra-team conflict .88 .96 .31 .80 9. Team conflict intensitya .79 .91 .17 .45
Note. a n = 78, due to missing data. α = Cronbach’s alpha based on the group means of individual ratings for each measure. ICC (1) = intra-class correlation for individual ratings based on a one-way random effects ANOVA. ICC (2) = intra-class correlation for team mean ratings based on a one-way random effects ANOVA.
122 (R
ae) Y
unzi
Tan
“V
aria
nt C
onfli
ct M
anag
emen
t: C
once
ptua
lizin
g an
d In
vest
igat
ing
Team
Con
flict
Man
agem
ent a
s a C
onfig
ural
Con
stru
ct”
Rev
ised
Dis
serta
tion
Ana
lyse
s and
Fin
ding
s – O
ctob
er 2
012
!
13!
Tabl
e 3
Inte
rcor
rela
tions
for a
ll K
ey T
eam
Var
iabl
es
Var
iabl
e 1
2 3
4 5
6 7
8 9
Pred
icto
rs
1.
C
oope
rativ
e te
am c
onfli
ct
man
agem
ent
!
2.
Com
petit
ive
team
con
flict
m
anag
emen
t -.4
3***
!
3.
Var
iant
con
flict
man
agem
ent
.04
-.02
!
4.
Gen
der r
ole
dive
rsity
.1
5 -.1
1 -.1
2 !
5.
Team
goa
l int
erde
pend
ence
.4
8***
-.3
9***
.0
2 .0
9 !
6.
M
ixed
goa
l int
erde
pend
ence
a .5
6***
-.2
5 .0
9 -.0
5 1.
00**
* !
7.
Subg
roup
form
atio
n -.3
1**
.41*
**
-.07
-.18
-.45*
**
-.22
!
Out
com
es
8.
Te
am c
onfli
ct e
ffic
acy
.36*
* -.1
1 -.2
1 .1
8 .4
4***
.3
6**
-.24*
!
9.
Satis
fact
ion
with
team
co
nflic
t man
agem
ent p
roce
ss
.23*
-.0
6 .0
9 -.0
3 .4
7***
.4
0**
-.09
.52*
** !
10. T
eam
eff
ectiv
enes
s .4
6***
-.1
8 .0
1 .2
0 .5
5***
.4
3***
-.3
1**
.62*
**
.65*
**
Con
trol
s
11. C
ours
e af
filia
tionb
.15
-.06
.01
.23*
.1
6 .2
3 -.1
5 .2
0 .0
3 12
. Tea
m si
ze
.05
-.04
.11
-.07
.06
.05
.18
.15
.19
13. I
ntra
-team
con
flict
-.3
9***
.3
8***
.1
5 -.0
9 -.5
5***
-.3
9**
.53*
**
-.27*
-.3
0**
14. T
eam
con
flict
inte
nsity
-.4
9***
.4
2***
.1
3 -.1
2 -.6
1***
-.4
6***
.5
2***
-.3
3**
-.34*
* 15
. Tea
m c
onfli
ct im
porta
nce
-.11
.27*
.0
1 .0
5 -.0
4 -.0
5 .4
1***
.2
4*
.15
Oth
er
16
. Tea
m a
ge
.23*
-.1
9 .0
7 -.0
8 .0
4 -.0
1 -.0
3 .0
4 .2
7*
17. T
eam
ass
ignm
entc
.06
-.07
.05
.14
.18
-.14
.07
-.02
.05
18. T
eam
inte
ract
ion
.15
.02
-.03
.16
.06
.23
.12
.09
-.01
Not
e. T
he N
var
ies f
rom
72
– 79
due
to o
mis
sion
of o
utlie
rs. a
n =
53 –
56
due
to o
mis
sion
of o
utlie
rs. b
Cou
rse
affil
iatio
n =
1, “
Man
agin
g Pe
ople
at W
ork”
cou
rse;
2, “
Lead
ersh
ip a
nd T
eam
-bui
ldin
g” c
ours
e. c
Team
ass
ignm
ent =
1, “
yes”
; 0, “
no”.
* p
< 0
5. *
* p
< .0
1. *
** p
< .0
01.
123 (R
ae) Y
unzi
Tan
“V
aria
nt C
onfli
ct M
anag
emen
t: C
once
ptua
lizin
g an
d In
vest
igat
ing
Team
Con
flict
Man
agem
ent a
s a C
onfig
ural
Con
stru
ct”
Rev
ised
Dis
serta
tion
Ana
lyse
s and
Fin
ding
s – O
ctob
er 2
012
!
14!
Tabl
e 3
(Con
tinue
d)
Inte
rcor
rela
tions
for a
ll K
ey T
eam
Var
iabl
es
Var
iabl
e 10
11
12
13
14
15
16
17
18
10
. Tea
m e
ffec
tiven
ess
!
Con
trol
s
11. C
ours
e af
filia
tionb
.16
!
12
. Tea
m si
ze
.18
-.06
!
13. I
ntra
-team
con
flict
-.4
2***
.0
3 .1
8 !
14. T
eam
con
flict
inte
nsity
-.4
8***
-.0
1 .1
8 .9
5***
!
15
. Tea
m c
onfli
ct im
porta
nce
.22
.12
.25*
.4
2***
.3
7**
!
O
ther
16. T
eam
age
.1
9 -.4
1***
.1
1 -.1
2 -.1
2 -.0
1 !
17
. Tea
m a
ssig
nmen
tc .1
0 -.2
1 .1
5 -.0
6 -.0
7 .1
2 .1
5 !
18. T
eam
inte
ract
ion
.10
.17
-.03
.04
.03
.18
-.17
.25*
!
N
ote.
The
N v
arie
s fro
m 7
2 –
79 d
ue to
om
issi
on o
f out
liers
. a n =
53
– 56
due
to o
mis
sion
of o
utlie
rs. b
Cou
rse
affil
iatio
n =
1, “
Man
agin
g Pe
ople
at W
ork”
cou
rse;
2, “
Lead
ersh
ip a
nd T
eam
-bui
ldin
g” c
ours
e. b
Team
ass
ignm
ent =
1, “
yes”
; 0, “
no”.
* p
< 0
5. *
* p
< .0
1. *
** p
< .0
01.
124
Table 4
Coding Definitions of Variant Conflict Management Profiles for the Content Coding Analysis
Coding category Variant conflict management profile
Definition
1 Minimum cooperative When all scores are clustered between the midpoint and the high end of the cooperative conflict management continuum.
2 Moderate cooperative When a majority cluster of scores is observed between the midpoint and the high end of the cooperative conflict management continuum.
3 Maximum When two distinct and evenly sized clusters are observed along the continuum.
4 Moderate competitive When a majority cluster of scores is observed between the midpoint and the low end of the cooperative conflict management continuum.
5 Minimum competitive When all scores are clustered between the midpoint and the low end of the cooperative conflict management continuum.
6 Other When the distribution of individual scores for the team does not fall into any of the above five categories. (If a team falls under this category, each coder also provides detailed comments describing the specific nature of the score distribution for the given team.)
125
Table 5
Classification of Teams Based on the Content Coding Analysis
Coding category Variant conflict management profile N 1 Minimum cooperative 6 2 Moderate cooperative 38 3 Maximum 5 4 Moderate competitive 10 5 Minimum competitive 3 6 Other
‘Distributed’ ‘Multiple clusters’ ‘Midpoint cluster’
17 10 4 3
Note. The Cohen’s Kappas for the coders’ ratings were .96, .96, and .96.
126
Table 6
Hierarchical Regression Analysis Predicting Team Conflict Efficacy from Cooperative Team Conflict Management and Variant Conflict Management (N = 79)
Team conflict efficacy Model 1 Model 2
Predictor B SE B β B SE B β Step 1:
Team goal interdependence .17 .07 .30* .16 .08 .28* Subgroup formation -.12 .09 -.16 -.14 .10 -.18 Team conflict intensity -.25 .13 -.29 -.17 .14 -.20 Team conflict importance .70 .30 .28* .69 .30 .27*
Step 2: Cooperative team conflict management .17 .13 .14
Variant conflict management -.23 .17 -.14
R .58** .60 R2 .33** .36 Adj. R2 .30** .31 ΔR2 .33** .03
* p < .05. ** p < .01.
127
Table 7
Hierarchical Regression Analysis Predicting Member Satisfaction with Team Conflict Management Process from Cooperative Team Conflict Management and Variant Conflict Management (N = 79)
Member satisfaction with team conflict management process
Model 1 Model 2 Predictor B SE B β B SE B β
Step 1: Team goal interdependence .36 .11 .43** .33 .12 .39** Team conflict intensity -.08 .17 -.07 -.13 .18 -.10 Team age .53 .23 .23* .49 .24 .21*
Step 2: Cooperative team conflict management .06 .20 .03
Variant conflict management .18 .26 .07
R .53** .54 R2 .28** .29 Adj. R2 .25** .24 ΔR2 .28** .01
* p < .05. ** p < .01.
128
Table 8
Hierarchical Regression Analysis Predicting Team Effectiveness from Cooperative Team Conflict Management and Variant Conflict Management (N = 79)
Team effectiveness Model 1 Model 2
Predictor B SE B β B SE B β Step 1:
Team goal interdependence .32 .09 .44** .24 .09 .33* Subgroup formation .00 .11 .00 .05 .11 .05 Team conflict intensity -.26 .15 -.23 -.29 .16 -.26
Step 2: Cooperative team conflict management .39 .16 .25*
Variant conflict management .11 .21 .05
R .61** .65* R2 .37** .42* Adj. R2 .34** .38* ΔR2 .37** .05*
* p < .05. ** p < .01.
129
Table 9
Hierarchical Regression Analysis Predicting Team Conflict Efficacy from Competitive Team Conflict Management and Variant Conflict Management (N = 79)
Team conflict efficacy Model 1 Model 2
Predictor B SE B β B SE B β Step 1:
Team goal interdependence .17 .07 .30* .19 .08 .35* Subgroup formation -.12 .09 -.16 -.16 .10 -.21 Team conflict intensity -.25 .13 -.29 -.19 .14 -.23 Team conflict importance .70 .30 .28* .67 .30 .26*
Step 2: Competitive team conflict management .18 .17 .11
Variant conflict management -.20 .17 -.13
R .58** .60 R2 .33** .36 Adj. R2 .30** .30 ΔR2 .33** .03
* p < .05. ** p < .01.
130
Table 10
Hierarchical Regression Analysis Predicting Member Satisfaction with Team Conflict Management Process from Competitive Team Conflict Management and Variant Conflict Management (N = 79)
Member satisfaction with team conflict management process
Model 1 Model 2 Predictor B SE B β B SE B β
Step 1: Team goal interdependence .36 .11 .43** .37 .11 .44** Team conflict intensity -.08 .17 -.07 -.21 .18 -.16 Team age .53 .23 .23* .51 .24 .21*
Step 2: Competitive team conflict management .46 .25 .20
Variant conflict management .23 .26 .09
R .53** .57 R2 .28** .32 Adj. R2 .25** .27 ΔR2 .28** .04
* p < .05. ** p < .01.
131
Table 11
Hierarchical Regression Analysis Predicting Team Effectiveness from Competitive Team Conflict Management and Variant Conflict Management (N = 79)
Team effectiveness Model 1 Model 2
Predictor B SE B β B SE B β Step 1:
Team goal interdependence .32 .09 .44** .32 .09 .44** Subgroup formation .00 .11 .00 -.01 .12 -.01 Team conflict intensity -.26 .15 -.23 -.34 .16 -.30*
Step 2: Competitive team conflict management .29 .21 .14
Variant conflict management .18 .21 .08
R .61** .62 R2 .37** .39 Adj. R2 .34** .35 ΔR2 .37** .02
* p < .05. ** p < .01.
132
(Rae
) Yun
zi T
an
“Var
iant
Con
flict
Man
agem
ent:
Con
cept
ualiz
ing
and
Inve
stig
atin
g Te
am C
onfli
ct M
anag
emen
t as a
Con
figur
al C
onst
ruct
” R
evis
ed D
isse
rtatio
n A
naly
ses a
nd F
indi
ngs –
Oct
ober
201
2 !
26!
Tabl
e 12
Med
ians
and
Num
ber
of C
ases
for
the
Effe
cts
of V
aria
nt C
onfli
ct M
anag
emen
t Pro
files
on
Team
Con
flict
Effi
cacy
V
aria
nt c
onfli
ct m
anag
emen
t pro
files
M
inim
um
coop
erat
ive
M
oder
ate
coop
erat
ive
M
axim
um
M
oder
ate
com
petit
ive
M
inim
um
com
petit
ive
Var
iabl
e M
dn
n
Mdn
n
M
dn
n
Mdn
n
M
dn
n
Team
con
flict
eff
icac
y 19
.45
6
19.7
1 38
19.2
5 5
18
.58
10
18
.33
3
! Tabl
e 13
Mea
ns a
nd S
tand
ard
Dev
iatio
ns fo
r th
e Ef
fect
s of
Var
iant
Con
flict
Man
agem
ent P
rofil
es o
n M
embe
r Sa
tisfa
ctio
n w
ith th
e Te
am’s
C
onfli
ct M
anag
emen
t Pro
cess
and
Tea
m E
ffect
iven
ess
V
aria
nt c
onfli
ct m
anag
emen
t pro
files
M
inim
um
coop
erat
ive
M
oder
ate
coop
erat
ive
M
axim
um
M
oder
ate
com
petit
ive
M
inim
um
com
petit
ive
Var
iabl
e M
SD
M
SD
M
SD
M
SD
M
SD
M
embe
r sat
isfa
ctio
n w
ith
the
team
’s c
onfli
ct
man
agem
ent p
roce
ss
22.5
5 1.
75
21
.88
2.30
22.6
0 3.
10
21
.27
1.69
19.1
9 2.
17
Team
eff
ectiv
enes
s 19
.80
1.15
19.0
4 1.
75
19
.25
2.38
17.8
3 1.
29
15
.47
1.53
!
133
Table 14
Simple Regression Analysis Predicting Variant Conflict Management with Gender Role Diversity
Variable B SE B β t p Gender role diversity -.70 .80 -.10 -.88 .38
Note. R2 = .01 (N = 78, ns).
134
Table 15
Polynomial Regression Analysis Predicting Variant Conflict Management with Team Goal Interdependence Variables
Variable B SE B β t p Team goal interdependence -.01 .04 -.02 -.15 .88 Team goal interdependence2 .02 .01 .18 1.63 .11
Note. Centered variables were used in this analysis. R2 = .03 (N = 79, ns).
135
Table 16
Simple Regression Analysis Predicting Subgroup Formation with Gender Role Diversity
Variable B SE B β t p Gender role diversity -2.51 1.66 -.17 -1.51 .13
Note. R2 = .03 (N = 78, ns).
Table 17
Hierarchical Regression Analysis Predicting Subgroup Formation as a Mediator between Gender Role Diversity and Variant Conflict Management (N = 78)
Variant conflict management Model 1 Model 2
Predictor B SE B β B SE B β Step 1:
Subgroup formation -.02 .06 -.04 -.03 .06 -.06 Step 2:
Gender role diversity -.78 .82 -.11
R .04 .12 R2 .00 .01 Adj. R2 -.01 -.01 ΔR2 .00 .01
* p < .05. ** p < .01.
136
Table 18
Model Fit Statistics for the Latent Class Analyses
Model AIC BIC aBIC LMRT BLRT 8-class 401.944 570.175 346.308 p < .05 p < .05 7-class 392.262 539.168 343.678 p < .05 p > .05 6-class 382.061 507.642 340.530 p < .05 p > .05 5-class 373.588 477.843 339.109 p < .05 p > .05 4-class 367.023 449.954 339.597 p < .05 p < .05 3-class 367.063 428.669 346.689 p < .05 p < .05 2-class 368.198 408.479 354.877 p < .05 p < .05
Note. The LCAs were conducted with 100 random starts and 100 optimizations.
137
Table 19
Classification of Variant Conflict Management Profiles Based on Latent Class Memberships (N = 79)
Latent class Variant conflict management profilea Count Proportion Threshold
estimate 1 Minimum cooperative
Maximum Minimum competitive ‘Multiple clusters’ ‘Midpoint cluster’
6 5 3 4 3
7.6% 6.3% 3.8% 5.1% 3.8%
0.916 1.163 1.792 1.447 1.792
2 ‘Distributed’ 10 12.7% -15.000
3 Moderate cooperative 38 48.1% -15.000
4 Moderate competitive 10 12.7% -15.000
Note. aThese profiles were identified in the content coding analyses.
138 (R
ae) Y
unzi
Tan
“V
aria
nt C
onfli
ct M
anag
emen
t: C
once
ptua
lizin
g an
d In
vest
igat
ing
Team
Con
flict
Man
agem
ent a
s a C
onfig
ural
Con
stru
ct”
Rev
ised
Dis
serta
tion
Ana
lyse
s and
Fin
ding
s – O
ctob
er 2
012
!
30!
Tabl
e 20
Med
ians
and
Num
ber
of C
ases
for
the
Effe
cts
of V
aria
nt C
onfli
ct M
anag
emen
t Cat
egor
ies
(Ide
ntifi
ed in
the
Late
nt C
lass
Ana
lyse
s)
on T
eam
Con
flict
Effi
cacy
V
aria
nt c
onfli
ct m
anag
emen
t cat
egor
ies
‘C
ombi
natio
n’
M
oder
ate
coop
erat
ive
‘D
istri
bute
d’
M
oder
ate
com
petit
ive
Var
iabl
e M
dn
n
Mdn
n
M
dn
n
Mdn
n
Team
con
flict
eff
icac
y 19
.25
21
19
.71
38
19
.25
10
18
.58
10
! Tabl
e 21
Mea
ns a
nd S
tand
ard
Dev
iatio
ns fo
r th
e Ef
fect
s of
Var
iant
Con
flict
Man
agem
ent C
ateg
orie
s (I
dent
ified
in th
e La
tent
Cla
ss
Anal
yses
) on
Mem
ber
Satis
fact
ion
with
the
Team
’s C
onfli
ct M
anag
emen
t Pro
cess
and
Tea
m E
ffect
iven
ess
V
aria
nt c
onfli
ct m
anag
emen
t cat
egor
ies
‘C
ombi
natio
n’
M
oder
ate
coop
erat
ive
‘D
istri
bute
d’
M
oder
ate
com
petit
ive
Var
iabl
e M
SD
M
SD
M
SD
M
SD
Mem
ber s
atis
fact
ion
with
th
e te
am’s
con
flict
m
anag
emen
t pro
cess
21
.96
2.30
21.8
8 2.
30
22
.13
2.56
21.2
7 1.
69
Team
eff
ectiv
enes
s 18
.69
2.04
19.0
4 1.
75
18
.63
2.92
17.8
3 1.
29
! !
139 !
1!
Tabl
e 22
Sum
mar
y Fi
ndin
gs fo
r th
e M
ain
and
Supp
lem
enta
ry A
naly
ses
Res
earc
h H
ypot
hese
s St
atis
tical
Ana
lyse
s Fi
ndin
gs
H1:
Th
e fiv
e pr
opos
ed V
CM
pro
files
, i.e
., m
inim
um
coop
erat
ive,
min
imum
com
petit
ive,
mod
erat
e co
oper
ativ
e, m
oder
ate
com
petit
ive,
and
max
imum
V
CM
pro
files
, will
be
pres
ent i
n te
ams.
Qua
litat
ive
cont
ent
codi
ng
Yes
. All
five
prop
osed
VC
M p
rofil
es
wer
e id
entif
ied
in th
e co
nten
t cod
ing
anal
ysis
. Add
ition
al p
rofil
es w
ere
also
un
cove
red;
thes
e w
ere
desc
ribed
as
‘dis
tribu
ted,
’ ‘m
ultip
le c
lust
ers,’
and
‘m
idpo
int c
lust
er’ V
CM
pro
files
. See
Ta
bles
4 &
5.
H
2a:
VC
M w
ill b
e ne
gativ
ely
asso
ciat
ed w
ith te
am c
onfli
ct
effic
acy,
with
mea
n co
oper
ativ
e te
am c
onfli
ct
man
agem
ent s
core
s bei
ng h
eld
cons
tant
.
Hie
rarc
hica
l mul
tiple
re
gres
sion!
Not
supp
orte
d. S
ee T
able
6.
H2b
: V
CM
will
be
nega
tivel
y as
soci
ated
with
mem
ber
satis
fact
ion
with
the
team
’s c
onfli
ct m
anag
emen
t pr
oces
s, w
ith m
ean
coop
erat
ive
team
con
flict
m
anag
emen
t sco
res b
eing
hel
d co
nsta
nt.
Hie
rarc
hica
l mul
tiple
re
gres
sion!
Not
supp
orte
d. S
ee T
able
7.
H2c
: V
CM
will
be
nega
tivel
y as
soci
ated
with
team
ef
fect
iven
ess,
with
mea
n co
oper
ativ
e te
am c
onfli
ct
man
agem
ent s
core
s bei
ng h
eld
cons
tant
.
Hie
rarc
hica
l mul
tiple
re
gres
sion!
Not
supp
orte
d. S
ee T
able
8.
! !
140
!
2!
Tabl
e 22
(Con
tinue
d)
Sum
mar
y Fi
ndin
gs fo
r th
e M
ain
and
Supp
lem
enta
ry A
naly
ses
Res
earc
h H
ypot
hese
s St
atis
tical
Ana
lyse
s Fi
ndin
gs
H3a
: VC
M w
ill b
e po
sitiv
ely
asso
ciat
ed w
ith te
am c
onfli
ct
effic
acy,
with
mea
n co
mpe
titiv
e te
am c
onfli
ct
man
agem
ent s
core
s bei
ng h
eld
cons
tant
.
Hie
rarc
hica
l mul
tiple
re
gres
sion!
Not
supp
orte
d. S
ee T
able
9.
H3b
: VC
M w
ill b
e po
sitiv
ely
asso
ciat
ed w
ith m
embe
r sa
tisfa
ctio
n w
ith th
e te
am’s
con
flict
man
agem
ent
proc
ess,
with
mea
n co
mpe
titiv
e te
am c
onfli
ct
man
agem
ent s
core
s bei
ng h
eld
cons
tant
.
Hie
rarc
hica
l mul
tiple
re
gres
sion!
Not
supp
orte
d. S
ee T
able
10.
H3c
: VC
M w
ill b
e po
sitiv
ely
asso
ciat
ed w
ith te
am
effe
ctiv
enes
s, w
ith m
ean
com
petit
ive
team
con
flict
m
anag
emen
t sco
res b
eing
hel
d co
nsta
nt.
Hie
rarc
hica
l mul
tiple
re
gres
sion!
Not
supp
orte
d. S
ee T
able
11.
H4a
: M
inim
um c
oope
rativ
e V
CM
pro
files
will
be
mos
t po
sitiv
ely
asso
ciat
ed w
ith te
am c
onfli
ct e
ffic
acy.
Man
n-W
hitn
ey U
Te
sts
Parti
ally
supp
orte
d. T
eam
s with
m
inim
um c
oope
rativ
e V
CM
pro
files
re
porte
d hi
gher
leve
ls o
f tea
m c
onfli
ct
effic
acy
than
team
s with
mod
erat
e co
mpe
titiv
e V
CM
pro
files
. See
Tab
le
12.
H4b
: M
inim
um c
oope
rativ
e V
CM
pro
files
will
be
mos
t po
sitiv
ely
asso
ciat
ed w
ith m
embe
r sat
isfa
ctio
n w
ith
the
team
’s c
onfli
ct m
anag
emen
t pro
cess
.
Plan
ned
com
paris
ons
Not
supp
orte
d. T
able
13.
H4c
: M
inim
um c
oope
rativ
e V
CM
pro
files
will
be
mos
t po
sitiv
ely
asso
ciat
ed w
ith te
am e
ffec
tiven
ess.
Plan
ned
com
paris
ons
Parti
ally
supp
orte
d. T
eam
s with
m
inim
um c
oope
rativ
e V
CM
pro
files
w
ere
mor
e ef
fect
ive
than
team
s with
m
inim
um c
ompe
titiv
e V
CM
pro
files
. Se
e Ta
ble
13.
141
!
3!
Tabl
e 22
(Con
tinue
d)
Sum
mar
y Fi
ndin
gs fo
r th
e M
ain
and
Supp
lem
enta
ry A
naly
ses
Res
earc
h H
ypot
hese
s St
atis
tical
Ana
lyse
s Fi
ndin
gs
H5a
: M
inim
um c
ompe
titiv
e V
CM
pro
files
will
be
mos
t ne
gativ
ely
asso
ciat
ed w
ith te
am c
onfli
ct e
ffic
acy.
Man
n-W
hitn
ey U
Te
sts
Not
supp
orte
d. S
ee T
able
12.
H5b
: M
inim
um c
ompe
titiv
e V
CM
pro
files
will
be
mos
t ne
gativ
ely
asso
ciat
ed w
ith m
embe
r sat
isfa
ctio
n w
ith
the
team
’s c
onfli
ct m
anag
emen
t pro
cess
.
Plan
ned
com
paris
ons
Supp
orte
d. S
ee T
able
13.
H5c
: M
inim
um c
ompe
titiv
e V
CM
pro
files
will
be
mos
t ne
gativ
ely
asso
ciat
ed w
ith te
am e
ffec
tiven
ess.
Plan
ned
com
paris
ons
Parti
ally
supp
orte
d. T
eam
s with
m
inim
um c
ompe
titiv
e V
CM
pro
files
w
ere
less
eff
ectiv
e th
an te
ams w
ith
min
imum
coo
pera
tive
and
mod
erat
e co
oper
ativ
e V
CM
pro
files
. See
Tab
le
13.
H6a
: M
oder
ate
coop
erat
ive
VC
M p
rofil
es, r
elat
ive
to
mod
erat
e co
mpe
titiv
e V
CM
pro
files
, will
be
mor
e po
sitiv
ely
asso
ciat
ed w
ith te
am c
onfli
ct e
ffic
acy.
Man
n-W
hitn
ey U
Te
sts
Supp
orte
d. S
ee T
able
12.
H6b
: M
oder
ate
coop
erat
ive
VC
M p
rofil
es, r
elat
ive
to
mod
erat
e co
mpe
titiv
e V
CM
pro
files
, will
be
mor
e po
sitiv
ely
asso
ciat
ed w
ith m
embe
r sat
isfa
ctio
n w
ith
the
team
’s c
onfli
ct m
anag
emen
t pro
cess
.
Plan
ned
com
paris
ons
Not
supp
orte
d. S
ee T
able
13.
H6c
: M
oder
ate
coop
erat
ive
VC
M p
rofil
es, r
elat
ive
to
mod
erat
e co
mpe
titiv
e V
CM
pro
files
, will
be
mor
e po
sitiv
ely
asso
ciat
ed w
ith te
am e
ffec
tiven
ess.
Plan
ned
com
paris
ons
Supp
orte
d. S
ee T
able
13.
!
142
!
4!
Tabl
e 22
(Con
tinue
d)
Sum
mar
y Fi
ndin
gs fo
r th
e M
ain
and
Supp
lem
enta
ry A
naly
ses
Res
earc
h H
ypot
hese
s St
atis
tical
Ana
lyse
s Fi
ndin
gs
H7a
: M
axim
um V
CM
pro
files
, rel
ativ
e to
mod
erat
e co
mpe
titiv
e V
CM
pro
files
, will
be
mor
e ne
gativ
ely
asso
ciat
ed w
ith te
am c
onfli
ct e
ffic
acy.
Man
n-W
hitn
ey U
Te
sts
Not
supp
orte
d. S
ee T
able
12.
H7b
: M
axim
um V
CM
pro
files
, rel
ativ
e to
mod
erat
e co
mpe
titiv
e V
CM
pro
files
, will
be
mor
e ne
gativ
ely
asso
ciat
ed w
ith m
embe
r sat
isfa
ctio
n w
ith th
e te
am’s
co
nflic
t man
agem
ent p
roce
ss.
Plan
ned
com
paris
ons
Not
supp
orte
d. S
ee T
able
13.!
H7c
: M
axim
um V
CM
pro
files
, rel
ativ
e to
mod
erat
e co
mpe
titiv
e V
CM
pro
files
, will
be
mor
e ne
gativ
ely
asso
ciat
ed w
ith te
am e
ffec
tiven
ess.
Plan
ned
com
paris
ons
Not
supp
orte
d. S
ee T
able
13.!
H8:
G
ende
r rol
e di
vers
ity w
ill b
e po
sitiv
ely
asso
ciat
ed
with
VC
M.
Sim
ple
regr
essi
on
Not
supp
orte
d. S
ee T
able
14.
H9:
C
oope
rativ
e an
d co
mpe
titiv
e go
al in
terd
epen
denc
e w
ill b
e ne
gativ
ely
asso
ciat
ed w
ith V
CM
, whi
le m
ixed
go
al in
terd
epen
denc
e w
ill b
e po
sitiv
ely
asso
ciat
ed
with
VC
M.
Poly
nom
ial m
ultip
le
regr
essi
on
Not
supp
orte
d. S
ee T
able
15.
H10
: Su
bgro
up fo
rmat
ion
will
med
iate
the
rela
tions
hip
betw
een
gend
er ro
le d
iver
sity
and
VC
M.
Med
iatio
nal
regr
essi
ons b
ased
on
Bar
on &
Ken
ny’s
(1
986)
app
roac
h
Not
supp
orte
d. S
ee T
able
s 16
and
17.
!
143
!
5!
Tabl
e 22
(Con
tinue
d)
Sum
mar
y Fi
ndin
gs fo
r th
e M
ain
and
Supp
lem
enta
ry A
naly
ses
Res
earc
h Q
uest
ions
St
atis
tical
ana
lyse
s Fi
ndin
gs
Supp
lem
enta
ry a
naly
ses:
A
sses
sing
the
pres
ence
of t
he
prop
osed
VC
M p
rofil
es in
the
mod
el
empi
rical
ly
Late
nt c
lass
ana
lyse
s Th
e be
st fi
tting
mod
el in
the
anal
yses
iden
tifie
d fo
ur la
tent
cl
ass c
ateg
orie
s. Tw
o of
thes
e ca
tego
ries c
orre
spon
ded
with
the
prop
osed
VC
M p
rofil
es: m
oder
ate
coop
erat
ive
and
mod
erat
e co
mpe
titiv
e V
CM
pro
files
. The
oth
er tw
o id
entif
ied
cate
gorie
s wer
e ‘d
istri
bute
d’ a
nd a
com
bina
tion
of ‘m
ultip
le c
lust
ers,’
‘mid
poin
t clu
ster
,’ m
inim
um
coop
erat
ive,
max
imum
, and
min
imum
com
petit
ive
VC
M
prof
iles.
See
Figu
re 5
, Tab
les 1
8 an
d 19
.
Expl
orin
g gr
oup
diff
eren
ces i
n te
am
conf
lict e
ffic
acy
scor
es a
mon
g th
e fo
ur V
CM
cat
egor
ies i
dent
ified
in
the
late
nt c
lass
ana
lyse
s
Kru
skal
l-Wal
lis T
est;
M
ann-
Whi
tney
U T
ests
for
follo
w-u
p co
mpa
rison
s
No
sign
ifica
nt o
vera
ll gr
oup
diff
eren
ce in
team
con
flict
ef
ficac
y sc
ores
acr
oss t
he fo
ur V
CM
cat
egor
ies;
How
ever
, tw
o of
the
six
Man
n-W
hitn
ey U
test
com
paris
ons w
ere
sign
ifica
nt:
1.
Team
s with
pro
files
und
er th
e ‘c
ombi
natio
n’ c
ateg
ory
(i.e.
, min
imum
coo
pera
tive,
max
imum
, min
imum
co
mpe
titiv
e, ‘m
ultip
le c
lust
ers,’
and
‘mid
poin
t clu
ster
’; M
dn =
19.
25, n
= 2
1) re
porte
d hi
gher
leve
ls o
f tea
m
conf
lict e
ffic
acy
than
team
s with
mod
erat
e co
mpe
titiv
e V
CM
pro
files
(Mdn
= 1
8.58
, n =
10)
, U =
54.
00, z
= -
2.16
, p <
.05,
r =
.39.
See
Tab
le 2
0.
2.
Team
s with
the
mod
erat
e co
oper
ativ
e V
CM
pro
files
(M
dn =
19.
71 n
= 3
7) a
lso
repo
rted
high
er le
vels
of
team
con
flict
eff
icac
y th
an te
ams w
ith m
oder
ate
com
petit
ive
VC
M p
rofil
es (M
dn =
18.
58, n
= 1
0), U
=
101.
00, z
= -2
.26,
p <
.05,
r =
.33.
See
Tab
le 2
0.
144
!
6!
Tabl
e 22
(Con
tinue
d)
Sum
mar
y Fi
ndin
gs fo
r th
e M
ain
and
Supp
lem
enta
ry A
naly
ses
Res
earc
h Q
uest
ions
St
atis
tical
ana
lyse
s Fi
ndin
gs
Expl
orin
g gr
oup
diff
eren
ces i
n m
embe
r sat
isfa
ctio
n w
ith te
am
conf
lict m
anag
emen
t pro
cess
scor
es
amon
g th
e fo
ur V
CM
cat
egor
ies
iden
tifie
d in
the
late
nt c
lass
ana
lyse
s
One
-way
AN
OV
A
N
o si
gnifi
cant
ove
rall
grou
p di
ffer
ence
in m
embe
r sa
tisfa
ctio
n w
ith th
e te
am’s
con
flict
man
agem
ent
proc
ess s
core
s acr
oss a
ll fo
ur V
CM
cat
egor
ies,
F (3
, 75
) = .2
9, n
s. Se
e Ta
ble
21.
Expl
orin
g gr
oup
diff
eren
ces i
n te
am
effe
ctiv
enes
s sco
res a
mon
g th
e fo
ur
VC
M c
ateg
orie
s ide
ntifi
ed in
the
late
nt c
lass
ana
lyse
s
One
-way
AN
OV
A
No
sign
ifica
nt o
vera
ll gr
oup
diff
eren
ce in
team
ef
fect
iven
ess s
core
s acr
oss a
ll fo
ur V
CM
cat
egor
ies,
F (3
, 75)
= 1
.03,
ns.
See
Tab
le 2
1.
!
145
Appendix A
Email Request for Recruiting Study Participants
Subject Line: Request for Recruiting Participants for a Dissertation Study on Teamwork Experiences
Dear Professor [NAME],
I am writing to request for your assistance in recruiting participants for my dissertation study on teamwork experiences. This dissertation research is being conducted as part of the Lim Kim San Research Fellowship at the Singapore Management University, under the supervision of Dr. Tan Hwee Hoon, Associate Professor of Organizational Behavior and Human Resources, and at Teachers College, Columbia University, under the supervision of Dr. Peter T. Coleman, Associate Professor of Psychology and Education.
The main purpose of this study is to investigate the effects of team characteristics on teamwork processes, and how these processes may in turn affect important outcomes. For this study, I am interested in recruiting intact student teams whose members are expected to work together on a final team project throughout the academic semester.
Based on the description of the course that you are currently teaching, it appears that the students in your course would meet the sample criterion for my study. As such, I would greatly appreciate it if you would allow me to invite your students to participate in this study. This study will be administered in the form of a short online survey, and all information obtained will be kept strictly confidential and will only be used solely for the purposes of this research.
Your assistance in my efforts to recruit participants would be greatly appreciated, and it would help me tremendously in completing my dissertation.
THANK YOU for considering my request above, and I look forward to hearing from you soon.
Sincerely,
(Rae) Yunzi Tan Visiting Lim Kim San Research Fellow Organizational Behavior and Human Resources Lee Kong Chian School of Business Singapore Management University Doctoral Candidate Program in Social-Organizational Psychology Department of Organization and Leadership Teachers College, Columbia University
146
Appendix A (Continued)
Email Request for Study Participation
Dear Professor [NAME],
Thank you very much for agreeing to assist me in recruiting participants for my dissertation study.
Please feel free to forward the following message with your students, so they can be made aware of this voluntary opportunity for research participation:
************************************************************************
Subject Line: Request for Participation in a Study on Teamwork Experiences
Dear [PARTICIPANT NAME],
This is an email to inform you of a voluntary opportunity for research participation. The main purpose of this research is to investigate the effects of team characteristics on teamwork processes, and how these processes may in turn affect important outcomes. Your participation is important because the results will help us better understand individuals’ teamwork experiences and team effectiveness.
This study is being administered in the form of a short online survey. To begin this survey, please click on the following link: [INSERT LINK HERE].
This survey will take approximately 20 minutes to complete. All information gathered in this study will be kept strictly confidential and used solely for the purposes of this research. You will receive more information on how you may collect the monetary incentive offered for your participation on the Informed Consent Form prior to beginning the survey, and again at the end of the survey.
Please complete this survey no later than 11.59pm, March 31, 2012. If you have any questions or would like to receive a copy of the study results, please do not hesitate to email me. Thank you again for your participation!
Sincerely,
(Rae) Yunzi Tan Visiting Lim Kim San Research Fellow Organizational Behavior and Human Resources Lee Kong Chian School of Business Singapore Management University Doctoral Candidate Program in Social-Organizational Psychology Department of Organization and Leadership Teachers College, Columbia University
147
Appendix B
Study Questionnaire
Teamwork Experiences Survey
Thank you for participating in this survey study on teamwork experiences. In this survey, you will be asked to respond to questions concerning your perceptions of and experiences in working with your peers on a specific team project this semester.
As you complete this survey, please provide your responses pertaining to the team you have been working with in the course: OBHR 001 – Leadership and Team Building / OBHR 101 – Management of People at Work.
Please complete this survey by no later than 11:59pm on March 31, 2012.
The survey consists of five sections, and would take approximately 30 minutes to complete. Your participation is entirely voluntary. Any information gathered will be kept strictly confidential and used solely for the purposes of this research.
On the next page, you will see the Informed Consent Form related to this research. Please read this information carefully and indicate your consent to participate in this study where noted.
Thank you once again for your participation!
148
Appendix B (Continued)
Informed Consent Form
DESCRIPTION OF THE RESEARCH: You are invited to participate in a research study on teamwork experiences. Specifically, this study is intended to investigate the effects of team characteristics on teamwork processes, and how these processes may in turn affect important outcomes. You will be asked to complete a short online survey questionnaire that assesses your perceptions of, and experiences in working with a project team throughout the academic semester. All information gathered in this study will be kept strictly confidential and will be used solely for the purposes of this research.
The research is conducted by (Rae) Yunzi Tan, a doctoral candidate in the Social-Organizational Psychology program at Teachers College, Columbia University, under the supervision of Dr. Peter T. Coleman, Associate Professor of Psychology and Education. This research is also conducted at the Lee Kong Chian School of Business at the Singapore Management University, as part of the Lim Kim San Research Fellowship program offered by the Organizational Behavior and Human Resources Division, and under the supervision of Dr. Tan Hwee Hoon, Associate Professor of Organizational Behavior and Human Resources.
TIME INVOLVEMENT: Your participation will involve completing an online questionnaire that will take approximately 20 minutes.
RISKS AND BENEFITS: The risks and possible benefits associated with this study are minimal, as the probability of encountering harm or discomfort in this study is no greater than what is typically encountered in a classroom activity or discussion on an important team-related issue. Some of the questions are of a sensitive nature and may cause some discomfort as you reflect on your team experiences.
However, there are also potential benefits that you may gain from this research. By responding to questions about their perceptions of and experiences with working in teams, you may gain novel and valuable insights about your team experiences. You will also be offered access to the results upon completion of the study.
Participation in this study is entirely voluntary. You may refuse to participate in the study, or withdraw at any time by closing your browser. Refusal or withdrawal from participation at any time will involve no penalty or no loss of accrued benefits to which you are otherwise entitled.
PAYMENTS: (For LTB participants) You will receive a small monetary incentive of $5.00 as payment for your participation. You may collect this payment at Room 5031 between 1:00 to 5:00pm from March 15 to 30, 2012 (Mon-Fri only). (For MPW participants) You will receive a research credit value of 0.5 for your participation.
149
Appendix B (Continued)
DATA STORAGE TO PROTECT CONFIDENTIALITY: All responses to this survey will be kept completely confidential. Your responses will be entered into a database that can only be accessed by the researcher. Any personal or identifying information will be recoded using pseudonyms or non-identifiers as soon as the data is collected, so that responses cannot be linked directly back to individual participants in the database.
HOW WILL RESULTS BE USED: The results of this study will be used to fulfill the partial requirements for a Doctor of Philosophy degree from Teachers College, Columbia University. The reporting of the results will be done in a manner to ensure that all participants’ identities are completely anonymous.
FOR QUESTIONS OR WHOM TO CONTACT: If, at any time, you have questions regarding the research or your participation, you may contact the investigator, Ms. (Rae) Yunzi Tan, at 6828-0597. The project has been reviewed and approved by the Teachers College, Columbia University Human Subjects Committee. If, at any time, you have comments or concerns regarding the conduct of the research or questions about your rights as a research subject, you may contact the Teachers College, Columbia University Institutional Review Board /IRB. The phone number for the IRB is (212) 678-4105. Or, you can write to the IRB at Teachers College, Columbia University, 525 West 120th Street, New York, NY, 10027, Box 151. (SMU IRB contact info: Institutional Review Board Secretariat, Ms. Stephanie Tan, at 6828-1925, or email [email protected])
By clicking on the link below, and by submitting your responses, it is understood that you have consented to participate in the research.
[INSERT LINK HERE]
Principal Investigator’s Signature: Date: February 15, 2012
(Rae) Yunzi Tan Visiting Lim Kim San Research Fellow Organizational Behavior and Human Resources Lee Kong Chian School of Business Singapore Management University Doctoral Candidate Program in Social-Organizational Psychology Department of Organization and Leadership Teachers College, Columbia University
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Appendix B (Continued)
Participant’s Rights Form
Principal Investigator: (Rae) Yunzi Tan Research Title: Teamwork Experiences
• I have read the Research Description described in the preceding page. I have had the opportunity to ask questions about the purposes and procedures, via email, regarding this study. I have received a copy of the Research Description/Informed Consent Form and this Participant's Rights document.
• I understand that my participation is voluntary. Refusal to participate will involve no penalty. I understand that I may discontinue participation at any time without penalty or loss of accrued benefits (Benefits are accrued in proportion to the amount of study complete or otherwise stated by the researcher) to which I am otherwise entitled. I declare that I am at least 18 years of age.
• The researcher may withdraw me from the research at his/her professional discretion. • If, during the course of the study, significant new information that has been developed
becomes available which may relate to my willingness to continue to participate, the investigator will provide this information to me.
• Any information derived from the research project that personally identifies me will not be voluntarily released or disclosed without my separate consent, except as specifically required by law.
• If at any time I have any questions regarding the research or my participation, I can contact the investigator, who will answer my questions. The investigator's phone number is 6828-0597.
• If at any time, I have comments or concerns regarding the conduct of the research or questions about my rights as a research subject, I should contact the Teachers College, Columbia University Institutional Review Board /IRB. The phone number for the IRB is (212) 678-4105. Or, I can write to the IRB at Teachers College, Columbia University, 525 W. 120th Street, New York, NY, 10027, Box 151. (SMU IRB contact info: Institutional Review Board Secretariat, Ms. Stephanie Tan, at 6828-1925, or email [email protected])
• The written materials will be viewed only by the principal investigator and members of the research team. Written materials ( ) may be viewed in an educational setting outside the research OR ( ) may NOT be viewed in an educational setting outside the research.
• My signature below means that I agree to participate in this study.
Participant's signature (please type your name): _______________Date: ____/____/____
For the Principal Investigator: “I have explained and defined in detail the research procedures in which the participant has consented to participate.”
Principal Investigator’s signature: Date: February 15, 2012
To begin the survey, please click on the link below: [INSERT LINK HERE]
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Appendix B (Continued)
Section I: Team Characteristics
This section contains several characteristics pertaining to individual attributes and traits within your project team for the course: OBHR 001 - Leadership and Team Building / OBHR 101 - Management of People at Work.
Please rate how well each of the following describes you in this team, on a scale of 1 (never or almost never true) to 7 (always or almost always true):
Characteristics
1 = Never to Almost Never True to 7 = Always to Almost Always True
1. Tender 1 2 3 4 5 6 7 2. Defends own beliefs 1 2 3 4 5 6 7 3. Aggressive 1 2 3 4 5 6 7 4. Willing to take risks 1 2 3 4 5 6 7 5. Compassionate 1 2 3 4 5 6 7 6. Understanding 1 2 3 4 5 6 7 7. Gentle 1 2 3 4 5 6 7 8. Warm 1 2 3 4 5 6 7 9. Assertive 1 2 3 4 5 6 7 10. Sympathetic 1 2 3 4 5 6 7 11. Sensitive to the needs of others 1 2 3 4 5 6 7 12. Independent 1 2 3 4 5 6 7 13. Strong personality 1 2 3 4 5 6 7 14. Affectionate 1 2 3 4 5 6 7 15. Dominant 1 2 3 4 5 6 7 16. Forceful 1 2 3 4 5 6 7 17. Eager to soothe hurt feelings 1 2 3 4 5 6 7 18. Leadership ability 1 2 3 4 5 6 7 19. Willing to take a stand 1 2 3 4 5 6 7
152
Appendix B (Continued)
Section II: Team Functioning
This section contains several statements assessing your perceptions of how your project team has functioned throughout the semester for the course: OBHR 001 - Leadership and Team Building / OBHR 101- Management of People at Work.
Please rate how strongly you agree or disagree with each of the statements below.
1 2 3 4 5 Strongly
Agree Agree Neither Agree
nor Disagree Disagree Strongly
Disagree
1. In this team, members ‘swim or sink’ together. 1 2 3 4 5
2. In this team, members give high priority to the things they want to accomplish and low priority to the things other team members want to accomplish.
1 2 3 4 5
3. In this team, members seek compatible goals. 1 2 3 4 5
4. In this team, members like to show that who is superior to one other.
1 2 3 4 5
5. In this team, members want one other to succeed.
1 2 3 4 5
6. When members work together in this team, they usually have common goals.
1 2 3 4 5
7. In this team, members structure things in ways that favor each member’s own goals rather than the goals of other team members.
1 2 3 4 5
8. In this team, members have a ‘win-lose’ relationship.
1 2 3 4 5
9. In this team, members’ goals go together. 1 2 3 4 5
10. In this team, members’ goals are incompatible with one other.
1 2 3 4 5
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Appendix B (Continued)
Section II: Team Functioning (Continued)
This section contains several statements assessing your perceptions of how your project team has functioned throughout the semester for the course: OBHR 001 - Leadership and Team Building / OBHR 101 - Management of People at Work.
Please rate the frequency or intensity to which each of the statement describes your team.
Never Occasionally Sometimes Often Always 1 2 3 4 5
Not At All or To a Very Small
Extent
To a Small Extent
To a Moderate Extent
To a Large Extent
To a Very Large Extent
11. How much conflict of ideas is there in this team? 1 2 3 4 5
12. To what extent has your team split into subgroups? 1 2 3 4 5
13. How much relationship tension is there in this team? 1 2 3 4 5
14. How frequently do members have disagreements within this team about the task of the project?
1 2 3 4 5
15. How much conflict is there in this team about task responsibilities?
1 2 3 4 5
16. How much emotional conflict is there in this team? 1 2 3 4 5
17. To what extent has your team split into uneven subgroups?
1 2 3 4 5
18. How often do your teammates have conflicting opinions about the project you are working on?
1 2 3 4 5
19. To what extent has your team split into multiple or smaller cliques?
1 2 3 4 5
20. How often are there disagreements about who should do what in this team?
1 2 3 4 5
21. How often do members get angry while working in this team?
1 2 3 4 5
22. To what extent has your team split into two balanced subgroups?
1 2 3 4 5
23. How often do members disagree about resource allocation in this team?
1 2 3 4 5
24. To what extent do members view conflict in this team as important?
1 2 3 4 5
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Appendix B (Continued)
Section III: Team Interactions
This section contains several statements pertaining to your perceptions of how you have interacted with your teammates throughout the semester for the course: OBHR 001 - Leadership and Team Building / OBHR 101 - Management of People at Work.
Please rate the extent to which each of the following statement describes you in this team.
1 2 3 4 5 Never Occasionally Sometimes Often Always
1. I encourage a “we are in it together” attitude
with my teammates. 1 2 3 4 5
2. I tend to view conflict as a win-lose contest. 1 2 3 4 5
3. I try to get my teammates to agree with my position.
1 2 3 4 5
4. I work with my teammates to find a solution that will be good for all of us.
1 2 3 4 5
5. I try to persuade my teammates to make concessions without necessarily making concessions myself.
1 2 3 4 5
6. I tend to overstate my position to get my way. 1 2 3 4 5
7. I treat conflict as a mutual problem to solve with my teammates.
1 2 3 4 5
8. I work in a way that will enable everyone to get what he or she really wants.
1 2 3 4 5
9. I work with my teammates to combine the best of positions to make an effective decision.
1 2 3 4 5
155
Appendix B (Continued)
Section IV: Team Outcomes
This section assesses your beliefs and feelings toward your teamwork experiences for the course: OBHR 001 - Leadership and Team Building / OBHR 101 - Management of People at Work.
For each question below, please select a number from 1-7 that most accurately reflects your opinion. If you encounter a particular question that is not applicable to your teamwork experience, simply select “N/A.”
1 2 3 4 5 6 7 N/A Not At All Moderately Perfectly Not
Applicable
Please rate how strongly you agree or disagree with each of the following statements by selecting the appropriate number.
1 2 3 4 5 Strongly
Agree Agree Neither Agree
nor Disagree Disagree Strongly
Disagree
1. Do you feel that your teammates listened to your concerns?
1 2 3 4 5 6 7 N/A
2. How satisfied are you with the ease (or difficulty) of reaching an agreement within the team?
1 2 3 4 5 6 7 N/A
3. Would you characterize the team conflict management process as fair?
1 2 3 4 5 6 7 N/A
4. Did your teammates consider your wishes, opinions, or needs?
1 2 3 4 5 6 7 N/A
5. Generally speaking, team members are very satisfied with their work.
1 2 3 4 5
6. The way this team manages its work inspires its team members to enhance team performance.
1 2 3 4 5
7. Team members feel a strong commitment to their work. 1 2 3 4 5
8. All things considered, this team is highly pleased with the way it manages its work.
1 2 3 4 5
9. Team members feel highly committed to the goals of their work.
1 2 3 4 5
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Appendix B (Continued)
Section IV: Team Outcomes (Continued)
This section assesses your beliefs and feelings toward your teamwork experiences for the course: OBHR 001 - Leadership and Team Building / OBHR 101 - Management of People at Work.
Please rate how strongly you agree or disagree with each of the following statements by selecting the appropriate number.
1 2 3 4 5 Strongly
Agree Agree Neither Agree
nor Disagree Disagree Strongly
Disagree
10. I believe that this team will manage the following conflicts in an effective manner: a. Among team members concerning personality differences 1 2 3 4 5 b. Among team members concerning work habits 1 2 3 4 5 c. Among team members concerning work roles 1 2 3 4 5 d. Among team members concerning scheduling 1 2 3 4 5 e. Among team members concerning the best way to get the
project done 1 2 3 4 5
157
Appendix B (Continued)
Section V: Participant Demographics
Please answer the following questions about yourself and your team. All information collected will be kept strictly confidential and will be used solely for the purposes of this research.
Your name: ________________________________________________________________
Course title and section number: ________________________________________________
Name of your team (if any): ____________________________________________________
Number of members in your team (including yourself): ______________________________
Names of members in your team (including yourself): _______________________________
Were you assigned to your team by the course instructor (select one)? Yes / No
In general, how often do you interact with your teammates throughout the semester in person, phone and/or online (select one below)?
• Rarely (Less than 5 times a week) • Moderately (5-10 times a week) • Frequently (More than 10 times a week)
Age: _____________ Years of prior and current work experience: _____________________
Gender (select one): Male Female Other (e.g., transgender)
Ethnicity (select one): Chinese Malay Indian Biracial/Multiracial Other (please indicate): _______________________________________
Country of origin (where you were born): _________________________________________
Years of living in Singapore: ___________________________________________________
Area of specialization for your degree: ___________________________________________
158
Appendix B (Continued)
Debriefing Message
Debrief
You have reached the end of the survey. Thank you again for your participation in this study. The specific objective of this research is to examine how team member characteristics and team contextual factors affect the development of variability in team conflict management, and how such variability in turn affect team outcomes.
Once again, please note that all your responses in this survey will be kept strictly confidential and will only be used for the purposes of this research.
(For LTB participants) You will receive $5.00 as payment for your participation. To collect your payment, please go to Room 5031 between 1:00 to 5:00 PM, from March 15 to 30, 2012 (Mon-Fri only). A member of the research team for this study will be available to assist with your collection.
(For MPW participants) You will receive a research credit value of 0.5 for your participation.
If you have any further questions or concerns about this study, please do not hesitate to contact me at [email protected] or call 6828-0597.
Sincerely,
(Rae) Yunzi Tan Visiting Lim Kim San Research Fellow Organizational Behavior and Human Resources Lee Kong Chian School of Business Singapore Management University Doctoral Candidate Program in Social-Organizational Psychology Department of Organization and Leadership Teachers College, Columbia University
159
Appendix C
Study Measures
Conflict Management Approaches (Chen, Liu, & Tjosvold, 2005)
All items are rated on a five-point scale (1 = “never”; 3 = “sometimes”; 5 = “always”).
Cooperation
1. I encourage a “we are in it together” attitude with my teammates. 2. I work with my teammates to find a solution that will be good for all of us. 3. I treat conflict as a mutual problem to solve with my teammates 4. I work in a way that will enable everyone to get what they really want. 5. I work with my teammates to combine the best of positions to make an effective decision.
Competition
6. I try to get my teammates to agree with my position. 7. I try to persuade my teammates to make concessions without necessarily making
concessions myself. 8. I tend to view conflict as a win-lose contest. 9. I tend to overstate my position to get my way.
Gender Role Orientations (Bem, 1981)
How well does each of the following describe you in this team? (Items are rated on a scale of 1 = “never or almost never true” to 7 = “always or almost always true”)
Goal Interdependence (Lu, Tjosvold, & Shi, 2010)
All items are rated on a five-point scale (1 = “strongly disagree”; 5 = “strongly agree”).
Positive Interdependence
1. In this team, members ‘swim or sink’ together. 2. In this team, members want each other to succeed.
Masculinity Femininity 1. Assertive 1. Understanding 2. Leadership ability 2. Sympathetic 3. Dominant 3. Eager to soothe hurt feelings 4. Strong personality 4. Sensitive to needs of others 5. Forceful 5. Compassionate 6. Aggressive 6. Affectionate 7. Willing to take a stand 7. Gentle 8. Independent 8. Warm 9. Defends own beliefs 9. Tender 10. Willing to take risks
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Appendix C (Continued)
3. In this team, members seek compatible goals. 4. In this team, the goals of team members go together. 5. When we work together in this team, we usually have common goals. Negative Interdependence
6. In this team, members structure things in ways that favor their own goals rather than the goals of other team members.
7. In this team, members have a ‘win-lose’ relationship. 8. In this team, members like to show that they are superior to each other. 9. In this team, members’ goals are incompatible with each other. 10. In this team, members give high priority to the things they want to accomplish and low
priority to the things other team members want to accomplish.
Subgroup Formation (Cronin, Bezrukova, Weingart, & Tinsley, 2011)
All items are rated on a five-point scale (1 = “not at all or a very small extent”; 5 = “to a very large extent”).
1. To what extent has your team split into subgroups? 2. To what extent has your team split into multiple or smaller cliques? 3. To what extent has your team split into uneven subgroups? 4. To what extent has your team split into two balanced subgroups?
Team Conflict Efficacy (Alper, Tjosvold & Law, 2000)
All items are rated on a five-point scale (1 = “strongly disagree”; 5 = “strongly agree”).
I believe that our team will manage the following conflicts in an effective manner:
1. Among team members concerning personality differences 2. Among team members concerning work habits 3. Among team members concerning work roles 4. Among team members concerning scheduling 5. Among team members concerning the best way to get the project done
Satisfaction with Team Conflict Management Process (Curhan, Elfenbein, & Xu, 2006)
All items are rated on a seven-point scale (1 = “not at all”; 4 = “moderately”; 7 = frequently)
1. Do you feel your teammate(s) listened to your concerns? 2. Would you characterize the team conflict management process as fair? 3. How satisfied are you with the ease (or difficulty) of reaching an agreement within the
team? 4. Did your teammate(s) consider your wishes, opinions, or needs?
161
Appendix C (Continued)
Perceived Team Effectiveness (Alper, Tjosvold, & Law, 1998; Barker, Tjosvold, & Andrews, 1988; Tjosvold, Law, & Sun, 2006)
All items are rated on a five-point scale (1 = “strongly disagree”; 5 = “strongly agree”).
1. Generally speaking, team members are very satisfied with their work. 2. Team members feel a strong commitment to their work. 3. Team members feel highly committed to the goals of their work. 4. The way this team manages its work inspires its teammates to enhance team
performance. 5. All things considered, this team is highly pleased with the way it manages its work.
Intra-team Conflict Types (Jehn & Mannix, 2001)
All items are rated on a five-point scale (1 = “never”; 3 = “sometimes”; 5 = “always”), except items 1, 4, 6 and 8, which are rated on a scale of 1 = “not at all or to a very small extent” to 5 = “to a very large extent”.
Task Conflict
1. How much conflict of ideas is there in this team? 2. How frequently do members have disagreements within this team about the task of the
project? 3. How often do your teammates have conflicting opinions about the project you are
working on?
Relationship Conflict
4. How much relationship tension is there in this team? 5. How often do members get angry while working in this team? 6. How much emotional conflict is there in this team?
Process Conflict
7. How often are there disagreements about who should do what in this team? 8. How much conflict is there in this team about task responsibilities? 9. How often do members disagree about resource allocation in this team?
Intra-team Conflict Importance
To what extent do members view conflict in this team as important? (Item is rated on a scale of 1 = “not at all or a very small extent” to 5 = “to a very large extent”)