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Demographic diversity, team process, and team performance: Assessing moderator effects of cognitive conflict management practices and task interdependence

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Demographic diversity, team process, and team performance: Assessing moderator effects of cognitive conflict management practices and task interdependence

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DEMOGRAPHIC DIVERSITY, TEAM PROCESS, AND TEAM
PERFORMANCE: ASSESSING MODERATOR EFFECTS OF COGNITIVE
CONFLICT MANAGEMENT PRACTICES AND TASK INTERDEPENDENCE
Copyright 2004
by
Nobuyuki Ainoya
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PUBLIC ADMINISTRATION
May 2004
Nobuyuki Ainoya
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UMI Number: 3140427
Copyright 2004 by
Ainoya, Nobuyuki
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ACKNOWLEDGEMENTS
On writing this section of my dissertation, I rejoice in expressing my sincere
gratitude to Professors Peter J. Robertson and Robert C. Myrtle. They gave me a
tremendous amount of intellectual guidance and moral support for my scholarly
development. Robertson has guided me throughout the years at a doctoral program
with the sense of care and value that he showed for all doctoral students. We
discussed a lot about my research and his research on “a new paradigm of
collaborative organizing”. It was really an enjoyable moment. Like other doctoral
students, I deeply appreciate for his high involvement in our school’s doctoral
education. Also, Myrtle has been more than generous to me with his wisdom, time,
and passion for research. As I closely worked with him on a conference paper and a
journal article, he showed me the standard of excellence in professional work and
ethical behavior. By driving with me to several research sites including one located
in San Diego, he made it possible for me to access to healthcare organizations and to
get data there. If it had not been for his help, my dissertation research might not be
completed yet. I could never express my sufficient gratitude to him.
In addition, I would like to extend my gratitude to Professors Nicholas
Argyres and Ramon Salcido. This dissertation benefited from Argyres’ seminar
where he beautifully demonstrated his mastery over the field of strategic
management. Salcido willingly accepted to be a member of my dissertation
committee, after Argyres left the University of Southern California.
ii
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Rissho Kosei-Kai, a lay Buddhist organization in Japan founded by Rev.
Nikkyo Niwano, enabled my master and doctoral studies as well. It is my hope to
make scholarly contribution to it with the guidance of Buddha and Niwano.
Finally, I conclude my acknowledgments with the expression of gratitude and
love for my wife, Tomoko, my daughter, Miyuki, and to my new born baby son,
Hironaga. Tomoko has always supported me with her encouragement and cheerful
personality when I face challenges in doing my dissertation research. My
accomplishment certainly owes to her devotion.
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TABLE OF CONTENTS
ACKNOWLEDGEMENTS ii
LIST OF TABLES vi
LIST OF FIGURES viii
ABSTRACT ix
CHAPTER I: INTRODUCTION
Background of the Study 1
Objective of the Study 4
CHAPTER II: THEORETICAL FRAMEWORK
Team 7
Demographic Diversity and Team Performance 8
Team Process 9
Moderators 14
Demographic Diversity 17
CHAPTER III: HYPOTHESES
Demographic Diversity and Cognitive Conflict 21
Demographic Diversity and Affective Conflict 28
Cognitive Conflict and Team Performance 35
Affective Conflict and Team Performance 39
Moderator Effects of
Cognitive Conflict Management Practices 43
Moderator Effects of Task Interdependence 54
CHAPTER IV: METHODOLOGY
Sample 61
Research Sites and Survey Procedures 61
Measures 65
Analysis 72
iv
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CHAPTER V: RESULTS
Introduction 73
Demographic Diversity and Cognitive Conflict 74
Demographic Diversity and Affective Conflict 75
Cognitive Conflict and Team Performance 76
Affective Conflict and Team Performance 77
Moderator Effects of
Cognitive Conflict Management Practices 78
Moderator Effects of Task Interdependence 80
Mediator Effects of Cognitive Conflict 82
Mediator Effects of Affective Conflict 82
CHAPTER VI: DISCUSSION
Introduction 83
Demographic Diversity and Team Process 83
Team Process and Team Performance 85
Moderator Effects 87
Mediator Effects 89
Study Limitations 90
Managerial Implications 92
BIBLIOGRAPHY 95
APPENDICES
Appendix 1: Information Sheet for Non-Medical Research 123
Appendix 2: Team Member Questionnaire 125
Appendix 3: Manager/Leader Questionnaire 130
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LIST OF TABLES
Table 1: Participating Teams, Their Members,
and Their Response Rates at Each Site 63
Table 2: Profile of Sample 64
Table 3: Results of Confirmatory Factor Analysis
of Conflict and Cognitive Conflict Management Practices Items 71
Table 4: Means and Standard Deviations of Study Variables 73
Table 5: Correlations among Study Variables 74
Table 6: Hierarchical Regression of Cognitive Conflict
on Control and Diversity Variables (N=55) 75
Table 7: Hierarchical Regression of Affective Conflict
on Control and Diversity Variables (N=55) 75
Table 8: Hierarchical Regression of Member-rated Team Performance
on Control and Team Process (Cognitive Conflict) Variables (N=59) 76
Table 9: Hierarchical Regression of Manager-rated Team Performance
on Control and Team Process (Cognitive Conflict) Variables (N=41) 76
Table 10: Hierarchical Regression of Member-rated Team Performance
on Control and Team Process (Affective Conflict) Variables (N=59) 77
Table 11: Hierarchical Regression of Manager-rated Team Performance
on Control and Team Process (Affective Conflict) Variables (N=41) 77
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Table 12: Hierarchical Regression of Member-rated Team Performance
on Control, Team Process (Cognitive Conflict), Moderator (Cognitive Conflict
Management Practices), and Interaction Term (Cognitive Conflict x Cognitive
Conflict Management Practices) Variables (N=59) 79
Table 13: Hierarchical Regression of Manager-rated Team Performance
on Control, Team Process (Cognitive Conflict), Moderator (Cognitive Conflict
Management Practices), and Interaction Term (Cognitive Conflict x Cognitive
Conflict Management Practices) Variables (N=41) 80
Table 14: Hierarchical Regression of Member-rated Team Performance
on Control, Team Process (Affective Conflict), Moderator (Task Interdependence),
and Interaction Term (Affective Conflict x Task Interdependence)
Variables (N=59) 81
Table 15: Hierarchical Regression of Manager-rated Team Performance
on Control, Team Process (Affective Conflict), Moderator (Task Interdependence),
and Interaction Term (Affective Conflict x Task Interdependence)
Variables (N=41) 81
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LIST OF FIGURES
Figure 1: Explaining Demographic Consequences by Presumably Subsuming Team
Process into Diversity 2
Figure 2: Explaining Demographic Consequences through Team Process 3
Figure 3: Explaining Demographic Consequences as a Function of Moderator Effects
on Team Process 5
Figure 4: Cognitive Conflict Management Practices as a Moderator 16
Figure 5: Task Interdependence as a Moderator 17
Figure 6: Moderator Effects of Cognitive Conflict Management Practices 79
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ABSTRACT
Demography scholars suggest including team process in a theoretical
framework to fully understand the effects of demographic diversity on team
performance. However, prior research shows mixed results regarding the association
between team process and performance. Some studies have found effects of team
process on performance, but others have not. A primary objective of this study was
to specify the conditions under which the effects of team process would hold or not.
Race and organizational tenure diversity were measured to examine the
effects of demographic diversity on team performance. Also, cognitive and affective
conflict were used to measure team process, and cognitive conflict management
practices and task interdependence were measured to assess their moderating effects
on the association between team process and performance. To be specific, it was
predicted that diversity measures would have a positive impact on cognitive and
affective conflict. In turn, the positive impact of cognitive conflict and the negative
impact of affective conflict on team performance were predicted. Further, it was
predicted that the positive association between cognitive conflict and team
performance would be stronger when cognitive conflict management practices are
high, and that the negative association between affective conflict and team
performance would be weaker when task interdependence is high.
Fifty-nine team-level responses were used to test these hypotheses. The
sample included team members and managers of different types of teams. The
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results did not support the positive effects of diversity measures on cognitive and
affective conflict. While the positive effects of cognitive conflict on team
performance were not supported, the negative effects of affective conflict were
supported. Moderator effects of cognitive conflict management practices were
partially supported, but those of task interdependence were not. These results imply
to team managers and organizational leaders that they do not have to be very
concerned about diversity effects. However, the effects of cognitive and affective
conflict must be carefully addressed. Especially, appropriate cognitive conflict
management practices should be developed through hiring and training.
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CHAPTER I: INTRODUCTION
Background of the Study
As modern organizations remove the layers of hierarchy that formerly
separated workers and adopt to use teams in response to the increased complexity in
task environments, both management scholars and practitioners are finding that one
of the most challenging human resource issues is the management of
demographically diverse teams (Carrell & Mann, 1995). Since individuals are
designed into a team whose membership is typically stable and well defined, the
dynamics and consequences of their demographic characteristics are particularly
robust (Cohen, 1991). Management scholars have devoted their attention to the full
understanding of demographic diversity within a team and of its fundamental
centrality to the study of team performance (Cohen & Bailey, 1997). Although some
new scholarly attempts to investigate indirect effects of demographic diversity on
team performance may complement existing direct models, they have found mixed
results that cannot serve to guide practitioners to achieve high team performance
(Williams & O’Reilly, 1998).
While a few earlier minor contributions can be found (e.g., Kanter, 1977),
most contemporary research on demography in organizational settings stems from
Pfeffer’s (1983) theoretical essay on the topic. Pfeffer (1983) made an ambitious
argument that an aggregated composition of individuals within the team in terms of
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their attributes, which can be easily accessed and observed by researchers, could
explain its consequences in a number of different contexts in a direct manner that
subsumes team process mediating the relationship between demographic diversity
and its consequences (see Figure 1). Pfeffer’s (1983) research framework derived
more from a strategy of parsimonious explanation than from an attempt to fully
explicate theoretical explanation of the consequences of demographic diversity.
Subsequently, most of management scholars studying diversity effects (e.g.,
Hambrick, Cho, & Chen, 1996; Wagner, Pfeffer, & O’Reilly, 1984; Wiersema &
Bantel, 1992) uncritically have adopted this research framework (Carroll & Harrison,
1998).
Figure 1: Explaining Demographic Consequences by Presumably Subsuming
Team Process into Diversity
Demographic Diversity (=Team Process) => Consequences
One major problem with Pfeffer’s (1983) research framework concerns its
empirical standings. While Pfeffer (1983) argued that his research framework could
explain diversity effects without regard to different contexts, Lawrence’s (1997)
review found that there existed inconsistent levels of variation to explain diversity
effects across demography studies. Further, Lawrence (1997) analyzed prior
research investigating the direct as well as indirect associations between diversity
and its consequences, and found that, contrary to Pfeffer’s (1983) ambitious claim,
diversity measurements have not necessarily subsumed team process measurements,
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thereby suggesting that future studies should investigate the team process that can
mediate the association between demographic diversity and its consequences (see
Figure 2).
Figure 2: Explaining Demographic Consequences through Team Process
Demographic Diversity => Team Process => Consequences
Demography scholars (Cohen & Bailey, 1997; Guzzo & Dickson, 1996;
Lawrence, 1997; Pelled, 1996; Williams & O’Reilly, 1998) now have come to a
consensus that our knowledge of the impacts of demographic diversity can be best
promoted by including the team process into a theoretical model. While some
notable progresses have been made on the conceptualization of how demographic
diversity translates into team performance through team process (Jehn, 1995; 1997;
Jehn, Northcraft, & Neale, 1999; Pelled, 1996; Pelled, Eisenhardt, & Xin, 1999), a
fuller explication has not been made yet. Particularly absent in the literature is the
specification of when certain team process effects may hold or not. It is precisely
from the understanding and analysis of the association between team process and
performance that may change as a function of moderator that our complete
knowledge of diversity effects is likely to emerge.
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Objective of the Study
A primary objective of this study is the fuller theoretical understanding of
team process that mediates the relationship between demographic diversity and team
performance. To be specific, by theoretically distinguishing an emergent state from
its ensuing interactions between individuals within the team process, this study aims
to resolve discrepant findings regarding the association between team process and
performance in the literature. The state of interpersonal dynamics emerges because
of the social presence of other individuals within the team, and then it may be
resolved or not, depending on the nature of ensuing interactions between them. By
making these distinctions, this study seeks to specify the conditions for the presence
of or the lack of translation of an emergent state into team performance. Such an
approach will bring unique, theoretical contributions to the literature. For example,
Hambrick (1994) reviewed the developments in top management team studies and
argued that future scholars should look at behavioral integration by which the team
engages in mutual and collective interaction that enhances the quality of information
exchange. Indeed, with the absence of behavioral integration, a team that has rich
cognitive resources must operate as a loose constellation of individual members. In
a similar vein, Gruenfeld, Mannix, Williams, and Neale (1996) emphasized the
theoretical importance of considering the presence of emergent states and their
effective resolutions independently. More recently, Marks, Mathien, and Zaccaro
(2001) took a detailed look at the concept of team process in team literature and
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posited that to intermingle emergent states and interactional patterns within the team
process may result in serious construct contamination. In fact, as will be shown in
the literature review in the next chapter, recent demography studies have discovered
mixed empirical results regarding the association between team process and
performance. Following Marks et al.’s (2001: 358p) statement, “Emergent states do
not represent team interaction or team actions that lead toward outcomes”, this study
proposes that the association between team process and its performance will be as a
function of moderator effects on the interactions ensuing from an emergent state
within the team process (see Figure 3).
Figure 3: Explaining Demographic Consequences as a Function of Moderator
Effects on Team Process
Demographic Diversity => Team Process => Consequences
(emergent state + ensuing interactions)
It
Moderator Effects
Besides contributing to the fuller theoretical understanding of team process
effects, this research also has practical value for practitioners who supervise teams in
modem organizational settings. Strategic human resource management literature has
advocated that, when the team is composed of demographically different individuals
that can broaden the bases of informational and knowledge resources that are at
themselves rare (Barney, 1991), inimitable (Lippman & Rumlet, 1982), and non-
substitutable (Wright, McMahan, & McWilliams, 1994), the increase of
demographic diversity within the team will lead to an organization’s sustained
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competitive advantage (Peteraf, 1993; Winter, 1987). Nevertheless, empirical
evidence (e.g., Richard, 2000) does not support it. This study will demonstrate that
the increase of demographic diversity within the team does not automatically
translate into better team performance if the team lacks the effective practices to
leverage the positive impact of cognitive conflict and the appropriate task design to
mitigate the negative impact of affective conflict. For team supervisors involved in
the efforts to reap gains and alleviate losses that interpersonal actions cause within
the team (Hackman, 1987), this study’s findings of the conditions in which a team
works best will be crucial in leveraging the successful team (Hackman, 1990;
Williams & O’Reilly, 1998).
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CHAPTER II: THEORETICAL FRAMEWORK
Team
The team is a basic block in contemporary organizational practice. A team is
defined as the composition of individuals who both see themselves and are seen by
others as an intact social entity; because (1) the tasks they perform are
interdependent; (2) they share responsibility for outputs; (3) it is embedded in a
larger organization; and (4) its outputs affect others such as customers and coworkers
outside the team (Cohen & Bailey, 1997; Hackman, 1987). Since the popular
management literature has tended to use the term “team” in order to mean the
composition of individuals that meets these four conditions in organizational setting
(Cohen & Bailey, 1997), this study uses the word “team” rather than the word
“group”. When the word “group” is used, it specifically refers to social groups that
are the divisions of the social world into distinct classes or categories such as race,
gender, religion and the like (Tajfel, 1981).
Three types of teams can be mainly identified in organizational practices
today: (1) work team, (2) project team, and (3) top management team (Cohen &
Bailey, 1997). Each of these types meets the general definition of the team noted
above. Work team corresponds to the production and service team, project team
corresponds to the project and development team, and top management team
corresponds to the strategic direction making team. This study’s theoretical
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framework should be applicable across a variety of these types of teams, because the
interpersonal dynamics at the core of its framework concerns individuals who take
actions in the social presence of others (Edmondson, 1999). This study also will be
able to benefit from previous team demography studies at large. This is so because
the team demography literature has considered that differences in the type of team
have negligible effects on interpersonal actions and team performance (Cohen &
Bailey, 1997; Edmondson, 1999; Williams & O’Reilly, 1998).
Demographic Diversity and Team Performance
Since Pfeffer (1983) had proposed demographic diversity in organizational
settings as a new field of study and had suggested that it could explain a variety of
organizational behaviors and outcomes across different contexts, a variety of
demography research efforts have been made. While a few early studies (e.g.,
McCain et al., 1983) investigated the consequences of demographic diversity within
a social entity (e.g., academic departments) which does not fit into the exact
definition of a team, most studies have examined the consequences of demographic
diversity in terms of members’ attributes within the team, such as tenure in the
organization, education, functional background, age, gender, and race (Williams &
O’Reilly, 1998).
While demographic diversity has different kinds of its consequences, many of
demography studies focused on diversity effects on turnover that Pfeffer (1983)
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emphasized in his research agenda. Many studies (McCain et al., 1983; Pfeffer &
O’Reilly, 1987; Wagner et al., 1984; Wiersema & Bird, 1993) have consistently
found that diversity increased an individual’s turnover. Nevertheless, demography
scholars have paid relatively scant attention to team performance that is another
important consequence of diversity effects (Jackson, 1992). Team performance is a
team-level construct that generally refers to the performance on tasks in terms of
efficiency of team operations and quality of work produced by the team (Jackson,
1992; McGrath, 1984). Effects of demographic diversity on team performance have
found mixed results. Some studies (Bantel & Jackson, 1989; Hambrick et al., 1996;
Murray, 1989) found that demographic diversity within the team had positive
impacts on team performance. On the other hand, other studies (O’Reilly & Flatt,
1989; Zajac, Golden, & Shortell, 1991) found the negative effects of diversity on
team performance.
Team Process
In order to clarify these mixed results regarding the association between
diversity and team performance, some studies have begun to examine the mediator
effects of team process by which diversity influences the outcomes. In general,
mediator effects are said to exist when the inclusion of a mediator between the
predictor and the outcome variables can account for their association more strongly
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than its absence (Baron & Kenny, 1986). Team process as a mediator speaks how
demography effects on team performance occur in this study.
Team process is a team-level construct that is defined as interpersonal actions
taking place among members within the team (Hackman, 1987). Team process
model has an advantage in the theoretical explication of diversity effects because it
can explain cognitive and affective effects (Guzzo & Dickson, 1996) that diversity
causes, and, in turn, affects team performance (Cohen & Bailey, 1997; Lawrence,
1997; Pelled, 1996; Williams & O’Reilly, 1998). Demography scholars now have
come to a consensus that our knowledge of the impacts of demographic diversity is
best promoted by including the team process into a theoretical framework.
Although O’Reilly, Caldwell, and Barnett’s (1989) focus was the
examination of diversity effects on turnover rather than performance, their study is
notable in the sense that they proved the significant role of team process such as
interpersonal attraction (Katz & Kahn, 1978; Shaw, 1981) between individuals
within the team that mediates the association between diversity and its consequences:
diversity is negatively associated with interpersonal attraction, which is in turn
positively related with turnover. Later, Smith, Smith, Olian, Sims, O ’Bannon, and
Scully (1994) examined diversity effects on performance through interpersonal
attraction, however, did not find such mediator effects. With respect to the cognitive
effects of diversity, studies by Ancona and Caldwell (1992), and Glick, Miller, and
Huber (1993) found that diversity increased cognitive resources, however, these
resources did not translate into high team performance.
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While these studies have investigated either cognitive or affective effects of
diversity on team performance separately, recent research (Jehn, 1995; 1997; Jehn et
al., 1999; Pelled, 1996; Pelled et al., 1999) has proposed a unified model in which
both cognitive and affective effects of diversity are included. They used a
multidimensional construct of conflict (Amason, 1996; Amason & Sapienza, 1997;
Amason & Schweiger, 1994; Amason, Thompson, Hochwater, & Harrison, 1995)
that can capture both cognitive and affective aspects of team process. Conflict is
broadly defined as the emergent state that is manifested in incompatibility,
disagreement, or dissonance within or between social entities such as individual,
group and organization (Smith, 1966; Tedeschi, Schlenker, & Bonoma, 1973). More
specifically, cognitive conflict refers to the state of cognitive disagreement among
team members over different aspects of the task, including goals, product and service
domain, resource allocation, and the appropriate procedures to complete the tasks.
Affective conflict is the state of interpersonal incompatibilities characterized by
negative feelings such as frustration, anxiety, dislike, and others forms of negative
affect. Cognitive conflict is directed toward task content, in contrast, affective
conflict is directed toward individuals within the team.
Guetzkow and Gyr (1954) made important distinctions between substantive
and affective conflict: the former occurs when two or more group members disagree
on their task or content issues, and the latter occurs when they have incompatible
feelings and emotions not directly related to team’s tasks. More recently, Jehn’s
(1995) two-factor analysis of eight intragroup conflict items, and Jehn’s (1997)
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qualitative analysis of team members’ experiences of conflict at workplace have
discovered the conceptual distinction between task conflict, which is cognitive
disagreements among team members about the contents of tasks being performed
such as differences in viewpoints, ideas, and opinions, and relationship conflict,
which is interpersonal incompatibilities such as tension, animosity, and annoyance
among members within the team. Consistently with these studies, Pelled et al.’s
(1999) factor analysis has confirmed the same conceptual distinction between task
and emotional conflict. Although these researchers have used different labels in
order to represent the cognitive and affective dimensions of conflict, they have
offered similar definitions for the two dimensions, essentially describing the same
constructs (Pelled, 1996; Pelled et al., 1999).
Cognitive and affective conflict may be seemingly correlated and may shift
from one form to the other over time (Deutsch, 1969). When group members attach
particularly strong feelings to changing task content, they may become emotional
and, subsequently, task conflict may transform into affective conflict. This may
occur because both types of conflict have negative emotionality in common as a
component (Jehn, 1997). However, several studies have shown that cognitive and
affective conflict is distinct and experienced differently by individuals. Amason’s
(1996) assessment, conducting both exploratory and confirmatory factor analyses,
demonstrated that these two dimensions were weakly correlated and that they were
conceptually distinct. Also, Jehn’s (1997) longitudinal study of work teams showed
that transformation of one type of conflict into the other had rarely happened,
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because negative emotion which task conflict contained was often present without
interpersonal animosity. Negative emotion of task conflict was directed toward task
content, hardly to other individuals within teams. Hence, it is conceptualized that
cognitive and affective conflict are distinct dimensions within the multidimensional
construct of conflict.
Prior research suggests that the effects of cognitive and affective conflict on
team performance exist, however, it is not clear when these mediator effects can or
not hold. Put it simply, the effects of team process do not automatically translate
into team performance. For example, it was found that demographic diversity
increased cognitive conflict (Ancona & Caldwell, 1992; Glick et al., 1993; Jehn et
al., 1999; Pelled et al., 1999). In turn, some studies (Amason, 1996; Eisenhardt,
Kahwajy, and Bourgeois; 1997a; 1997b; Jehn et al., 1999; Pelled et al., 1999) found
that the presence of cognitive conflict enhanced team performance, however, other
studies (Ancona and Caldwell, 1992; Glick et al., 1993) did not find such a positive
impact. On the other hand, it was found that demographic diversity increased
affective conflict (Jehn et al., 1999; Pelled et al., 1999). In turn, some studies
(Amason, 1996; Jehn, 1997; Jehn et al., 1999) found that affective conflict was
negatively associated with team performance. However, other studies (Jehn, 1995;
Pelled et al., 1999) found no evidence that affective conflict impairs team
performance.
One possible explanation that can account for the inconsistency of these
mediator effects on team performance is the lack of distinction between the emergent
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state and its ensuing interactions within the team process. After reviewing
accumulated studies on top management team, Hambrick (1994) found that they paid
little attention to behavioral integration by which the team engages in mutual and
collective interaction that enhances the quality of information exchange. Indeed,
with the absence of behavioral integration, the team that has rich cognitive resources
must operate as a loose constellation of individual members. More recently, Marks
et al. (2001) took a detailed look at the concept of team process in a team literature
and posited that to intermingle emergent states and interactional patterns within the
team process may result in serious construct contamination. Indeed, as is noted
above, prior research examining the effects of cognitive and affective conflict has
discovered the mixed results. Following Marks et al.’s (2001: 358p) statement,
“Emergent states do not represent team interaction or team actions that lead toward
outcomes”, this study proposes that the association between team process and its
performance will be as a function of moderator effects on the interactions ensuing
from emergent conflict within the team process
Moderators
Management studies have a tradition of specifying the contingency under
which certain effects hold or not. However, demography studies have rarely paid
attention to “how and when demographic diversity within teams will be associated
with different outcomes” (Williams & O’Reilly, 1998, 117p). Simons, Pelled, and
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Smith (1999) noted that future research must consider the importance of moderator
factors in the effects of diversity on performance. Moderation implies that the causal
association between two variables changes as a function of the moderator variable.
Moderator effects can be represented as the interaction between a focal variable and
a moderator that specifies the appropriate conditions for its operation (Baron &
Kenny, 1986). In this study, moderator effects are supported when the conditions in
which the effects of team process on performance can hold or not are specified.
In addition to these basic considerations, moderators must have two
properties: (a) they are antecedent to team performance, and (b) they strengthen or
weaken the association between team process and performance variables. While
there may plausibly exist some antecedents to team performance, the literature
review identified two important moderators that past researchers have neglected to
consider in conjunction with the effects of cognitive and affective conflict: cognitive
conflict management practices and task interdependence.
Increasingly, team decision-making scholars (Parks & Cowlin, 1995; Stasser
& Stewart, 1992; Stasser & Titus, 1985; 1987; Stasser, Taylor, & Hanna, 1989) have
found that cognitive conflict is an important antecedent to high team performance,
however, their relation may depend on how cognitive conflict is managed within the
team. Cognitive conflict management practices are a team-level construct that refers
to the patterns of verbal behaviors in the exchange of members’ ideas and
information by which the team can elaborate and manage an emergent state of
cognitive disagreements over different aspects of the task (Innami, 1994; Kuhn &
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Poole, 2000). These practices are conceptualized to shape members’ interactions
that ensue from an emergent state of cognitive conflict (see Figure 4). Hence, it is
proposed that team’s unique patterns of these practices will cause differential
impacts on the association between cognitive conflict and team performance.
Figure 4: Cognitive Conflict Management Practices as a Moderator
Demographic Diversity => Team Process => Performance
(cognitive conflict + interactions)
IT
Cognitive Conflict Management Practices
Also, recent research on task interdependence has found that high task
interdependence can shape the patterns of interpersonal actions in a manner that
increases the cooperative behaviors between members and thereby favorable team
performance (Wageman, 1995; Wageman & Baker, 1997). Task interdependence is
a team-level construct that refers to the extent to which members must rely on one
another to complete their tasks (Thompson, 1967; Van de Ven & Ferry, 1980). Since
emotion scholars identified that cooperative behaviors that directly defer self-
interests can enduringly arouse emotional convergence between individuals (Batson,
Shaw, & Oleson, 1992; Batson, Turk, Shaw, & Klein, 1995), it is proposed that task
interdependence will shape emotional dynamics within the team that may affect the
impact of affective conflict on team performance (see Figure 5).
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Figure 5: Task Interdependence as a Moderator
Demographic Diversity => Team Process => Performance
(affective conflict + interactions)
It
Task Interdependence
Demographic Diversity
Management scholars have addressed different features of the team in order
to explain its performance (Gladstein, 1984; Hackman, 1987; McGrath, 1984).
Some scholars have directed their attention to the effects of structural features of
team’s task on team performance. For example, the socio-technical interdependence
(Goodman, 1986; Stewart & Barrick, 2000; Wageman, 1995; Wageman & Baker,
1997) and team autonomy (Campion, Papper, & Medsker, 1993; Manz & Sims,
1987; Stewart & Barrick, 2000) were identified as the important predictors of team
performance.
Another important feature of the team is the demographic diversity among
team members (Pfeffer, 1983). It can occur along several dimensions such as tenure
in the organization, education, functional background, age, gender and race (Pfeffer,
1997). Among these attributes, race and organizational tenure are of this study’s
interests. First, scholars (Cox & Nkomo, 1990; Guzzo & Dickson, 1996; Williams &
O’Reilly, 1998) have pointed out that little research has focused on racial impacts in
comparison with research on other forms of demographic diversity. Race is defined
as an impermeable feature that is related to biological factors, namely skin and
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physical features, and thus cannot be altered by moving from one category to another
(Thompson & Carter, 1997). Though often confused, ethnicity is rather an inclusive
concept of race in the sense that ethnicity is a social boundary that portions a
population with distinctions about membership based on impermeable as well as
permeable features including religion and nationality. Race is a specific instance of
ethnicity, imposed upon person by self and others based on inherited phenotypic
characteristics (Olzak, 1992). Thus, racial diversity within the team refers to the
distribution of individuals across social groups in terms of a nominal parameter.
Although sociologists have restricted the definition of racial minority to include only
subgroups that receive unequal treatment in the larger society (Wirth, 1945), this
study adopts the concept of racial minority used in social psychological literature on
minority influence. Racial minority refers to an individual who has an impermeable
feature of pigmentation and is relatively underrepresented within the team
(Moscovici & Faucheux, 1972; Nemeth, 1981).
Unlike racial diversity, the relationship between organizational tenure and its
consequences has received the most sustained attention among demography scholars
(Sdrensen, 2000; Williams & O’Reilly, 1998). Organizational tenure refers to the
length of service that individuals spend since the time of their entry into the
organization. Interest in the distribution of organizational tenure was stimulated by
Pfeffer’s (1983) seminal essay that suggested that the distribution of organizational
tenure could be an important determinant of team process and performance. While
most studies on tenure diversity have found the positive impacts on turnover, a
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paucity of research investigated the effects of organizational tenure distribution on
team performance (Pelled, 1996; Williams & O’Reilly, 1998). Considering the
magnitude of previous research on organizational tenure, it is compelling to
understand its positive and negative effects on team performance.
Given the importance of racial and organizational tenure compositions in
team demography studies, it is proposed that they will have significant effects on
cognitive and affective conflict. First, as social network theorists have suggested
(Burt, 2000; Gnyawali & Madhavan, 2001; McEvily & Zaheer, 1999), race and
organizational tenure may serve for team members as proxies of or their accesses to
social contacts outside the team and, in turn, may constrain their entrepreneurial
actions in order to take advantage of informational resources from these social
contacts. Secondly, as strategic management scholars has suggested (Hambrick &
Mason, 1984; Rajagopalan, Rasheed, & Datta, 1993), race and organizational tenure
may serve as social categories by which members execute the identification of self
and others and, in turn, may cause emotional frictions and tensions among them.
These complementary roles that race and organizational tenure may play are
proposed to have cognitive and affective impacts on team process and, in turn, team
performance.
In the following chapters, I will theoretically explicate the impacts of
demographic diversity on cognitive and affective conflict and, in turn, their effects
on team performance. Further, I will specify the conditions in which the cognitive
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and affective conflict effects may hold or not in relation to the moderator effects of
cognitive conflict management practices and task interdependence.
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CHAPTER ni: HYPOTHESES
Demographic Diversity and Cognitive Conflict
A central tenet of the social network perspective is that actors vary in the
overall patterns of social relationships that provide access to different sources of
information and opportunities, thus emphasizing actors’ positions in networks and
their social relations as causal explanations of informational benefits (Granovetter,
1973), and both informational and control benefits (Burt, 1992). A network of
relationships that actors build may influence the flow of resources that they can
draw. Because actors vary in the flow of resources and their ability to control such
flows, they have different levels of motivation and ability to undertake the actions or
respond to the actions of others (Gnyawali & Madhavan, 2001). Sociologists have
extended this insight to the explanation of a variety of individual behavior, such as
job-finding (Granovetter, 1973), immigrant enterprise (Portes & Sensenbrenner,
1993), entrepreneurship (Larson, 1992), managerial work (Burt, 1997), gain of
informal support in a nonroutine situation (a hurricane) (Hurlbert, Haines, & Beggs,
2000), and of organization’s performance, such as creation of competitive advantage
(McEvily & Zaheer, 1999; Uzzi, 1997), alliance formation (Gulati, 1999), and
uncertainty reduction in a transitional economy (Peng & Luo, 2000).
While individual can access to various forms of tangible capital resources
through the social relations, the present study’s theoretical interest rests in the team
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member’s immediate circle of discussion partners surrounding the team. They are
defined as a set of individuals who are not coworkers within the team, however, with
whom a given team member may discuss team’s ongoing task concerns. These
individuals have the potential to influence a team member’s recognition of the task,
as well as the quality of his or her contribution to the team’s decision-making and
performance. A key characteristic of such social networks, affecting the type and
quality of information and interpretive framework that a given team member may
obtain, is the relationship heterogeneity with individuals surrounding outside the
team (Powell, 1991).
As the seminal work in the social network perspective, Granovetter (1973)
postulated that new information is obtained through weak ties (diverse sets of
contacts) rather than through strong ties (dense sets of contacts) with individuals
because individuals who are weakly connected to each other are more likely to have
the heterogeneous patterns of social relations and consequently to have less
redundant information. Researchers found that demographic majority and minority
members are embedded in the different types of social networks and pointed out that
network differences tend to lead to their divergent behavioral and economic
consequences (Popielarz, 1999). Team’s demographic mix may affect a member’s
opportunity to form network ties with dissimilar others within the team. For
example, compared with racial minority members, the members of a racial majority
group within the team are likely to have strong ties with each other in a way to
exclude minority members from the exchanges of information (Brass, 1985; Ibarra,
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1995; Larkey, 1996). Consequently, the racial majority members who are connected
through strong ties with each other are able to have better career mobility chances
within the organization than the members of minority groups who could hardly form
strong ties across different races, after taking into account the effects of educational
background (Friedman & Krackhardt, 1997).
Such structural impediments to the formation of strong ties and subsequent
low support provided by the predominantly cross-race ties within the team, in turn,
may direct the members of minority groups to seek supportive relationships with the
same-race individuals surrounding outside the team (Elsass & Graves, 1997; Thomas
& Alderfer, 1989; Thomas & Higgins, 1996) for a wide variety of resource needs
including informational as well as emotional support. These recurrent social
exchanges may enable the minority members to have a relatively high number of
stable social networks with individuals outside the team (Cook, 1991; Ibarra, 1995),
potentially providing the accesses to heterogeneous sources of information that
majority members could not gain. Multiple sources can provide the minority
members with a variety of career enhancement information, as well as different
perspectives to the team’s task (Cox, 1994; Cox & Blake, 1991; Tsui & Gutek,
1999).
Race is not the only proxy for team members to access to social contacts
outside the team. Ancona and Caldwell (1992) noted that the diversity of team
member’s tenure in the organization is positively related with the external
communication beyond the boundary of the team. They argued that the team
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members who have entered the organization at different times know different sets of
people outside the team and thus tend to have different information and perspectives.
These arguments suggest that the individuals who are different from others within
the team in terms of organizational tenure may have more external social contacts
and new information on, and different perspectives to, the team’s task.
While Granovetter (1973) posited that a focal actor who has less redundant
information through weak ties would presumably undertake the entrepreneurial
actions to exploit them (i.e., informational benefits) in any social settings, Burt
(1992) modified this argument by adding that a focal actor may be motivated to do
so only when structural holes exist in the focal actor’s social network. Structural
holes exist in a condition in which a focal actor A has social contacts with both
actors B and C, however, B and C do not have social contacts directly each other, in
other words, B and C can reach each other only through A. Drawn from Burt’s
(1992) work, the structural autonomy is a focal actor-level property that indicates the
extent to which a focal actor has structural holes between the actors it is connected to
but is free of structural holes at its own end. To the extent that a focal actor has
structural holes, he or she is referred to as structurally autonomous and being able to
exploit them. Structurally autonomous A can exploit structural holes that exit
between B and C. In this way, Burt (1992) advanced a social network perspective to
that realizing the value of new information from weak ties with other actors (i.e.,
informational benefits) is contingent on whether a focal actor at the same time can
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have control over these actors who can reach each other only through a focal actor
(i.e., control benefits).
Put it differently, the presence of structural holes in a social network enables
a structurally autonomous actor to make less autonomous actors play against each
other and, by doing so, ensures to enjoy more effective and efficient flow of
informational resources from social contacts. Empirical evidence has shown that a
social network rich in the structural holes can translate a positive informational
resource asymmetry into a focal actor’s competitive advantage (Burt, 2000; McEvily
& Zaheer, 1999).
This framework proposed by Burt (1992) is applicable to the present study.
Individuals who are significantly similar with others within the team in terms of a
certain demographic attribute may implicitly perceive that they have less structural
holes in that demographic attribute-based social network (Burt, 2000). The term
“implicitly” means that, regardless of whether structural holes actually exist between
team members, they tend to infer from the mere presence of others of the same
demographic attribute within the team that there may be less structural holes deriving
from a demography-based social network (Allport, 1954; Burt, 2000). Suggestive
validity of this perception comes from the result of Louch’s (2000) analysis of 1985
General Social Survey data discovering that demo graphically similar individuals
who are coworkers, neighbors, team members, or kin are likely to share their social
contacts with each other elsewhere.
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Taken together, an individual who faces more other individuals of the same
demographic attribute within the team may be afraid to exploit the new information
and perspective deriving from a demographic attribute-based social network (i.e.,
informational benefits) in team’s discussion over various aspects of the task. When
an individual works more with others of the same demographic attribute within the
team who may share the social contacts elsewhere, it implies that he or she has less
structural holes (i.e., no control benefits), in other words, being less structurally
autonomous in a demographic attribute-based social network. The implied presence
of less structural holes in a social network means to an individual that
demographically similar others within the team could easily offer a competitive
frame of references for, and can easily refute the legitimacy of, the information and
perspectives that he or she gains from a demographic attribute-based social network
(Burt, 1997; 2000). Thus, an individual may be afraid to be easily challenged by the
demographically similar others within the team. These arguments are consistent
with prior research. Because the members of a demographic majority group feel the
pressure toward uniformity of the opinions (Festinger, 1954), they are likely to
provide supportive influence, which entails supporting and building on the idea of
another majority member, rather than to define and defend opposing arguments that
challenge the conventional wisdom that majority members share (Dorns & Van
Avermaet, 1985; Laughlin, 1992). In a similar vein, Gnyawali and Madhavan (2001)
noted that social actors with similar resource endowment tend to avoid initiating
direct conflict with each other.
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On the other hand, an individual who faces less other individuals of the same
demographic attribute within the team may undertake deliberate actions to exploit
the new information and perspectives deriving from a demographic attribute-based
social network (i.e., informational benefits). With the implied presence of more
structural holes (i.e., control benefits) in a demographic attribute-based social
network, it is expected that demographically dissimilar others within the team can
hardly offer a competitive frame of references for, or can hardly refute the legitimacy
of, individual’s information and perspectives gained from a demographic attribute-
based social network (Burt, 1997; 2000). Without the fears to be challenged by the
demographically different others, an individual may feel confident to freely express
divergent opinions and perspectives by drawing on a demographic attribute-based
social network. Prior research appears to agree with these arguments. To the extent
that an individual perceives that others have different opinions, he or she tends to
examine his or her own opinions less closely (Festinger, 1954), thus feeling easy to
express them. Also, it was found that a top management team that was composed of
demographically dissimilar members had the potential to generate original
approaches to intellective and decision-making tasks (Bantel & Jackson, 1989;
Murray, 1989).
Hypothesis 1:
Demographic diversity will be positively associated with cognitive conflict within
the team.
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Demographic Diversity and Affective Conflict
Social psychologists have attempted to understand and explain how the
attitudes and behavior of an individual are influenced by the actual, imagined or
implied presence of others (Allport, 1985) through the self (Markus & Wurf, 1987).
Self is a composite view of oneself as an object that is formed through direct
experiences and evaluations adopted from significant others (Bandura, 1986).
Research on self has originated from James (1890), Cooley (1902), and Mead
(1934), all of whom agreed that the society has an important impact on the formation
of self which in turn shapes human attitudes and behavior.
Self-identity or self-concept is made up of individual’s cognitions about
“who I am” (Hogg & Abrams, 1988) that is formed through the ecological processes
of making attributions (Kelley, 1971; Ross, 1977) of others’ reactions relative to
one’s characteristics to the social meanings of these characteristics (Leonard,
Beauvais, & Scholl, 1999). An individual possesses the structurally discontinuous
components of self: personal identity and collective identity (Trafimow, Triandis, &
Goto, 1991). Personal identity is the idiosyncratic part of an individual’s self-
identity that often derives from the experiences of interpersonal competition being
motivated by self-interest. An individual conceives oneself primarily in terms of
individual traits and characteristics, and utilizes comparisons with other individuals
as a frame of reference to establish the personal identity. In contrast, collective
identity is the part of individual’s self-identity that derives from one’s knowledge of
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membership in a social group. Social group refers to the divisions of the social
world into distinct classes or categories such as race, age, gender and religion
(Tajfel, 1981). Collective identity is considered as an enduring, global self-concept
that is carried across situations, thus when it is primed, having fundamental impacts
on human attitudes and behavior (Brockner, 1988; Erez & Earley, 1993; Judge,
Locke, & Durham, 1997; Weiss & Adler, 1984).
Scholars have identified that an individual has a motivation to reduce
subjective uncertainty about one’s perception of self and the surrounding social
settings. Festinger (1954; 1957) found that an individual has a fundamental need for
a consistent state of cognition regarding an evaluation of one’s opinions and abilities
that, in turn, motivates human behavior in a manner that reduces or eliminates
cognitive dissonance. Weick’s (1964) study on the effect of cognitive dissonance
showed that individuals, who had felt more severely deprived of expected rewards
from task, later reevaluated that task more interesting and intrinsically rewarding
than those who had felt less deprived. Adams (1965) argued, on the principle of
human’s retrospectively rational nature (Aronson, 1972; Staw, 1980), that
individuals are motivated to act in such a manner to reduce the inequalities which
they perceive in terms of the ratio of their received rewards to made efforts, when
referring to the members of comparison group that they select (Goodman, 1977).
Staw (1976) showed that individuals are apt to escalate their commitment to a course
of actions, because they seek to appear to others and themselves to be acting
consistently, to make their past decisions appear well, and to avoid the political costs
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of being discovered as having made a mistake. Further, Korman (1970) made an
explicit emphasis on the self-concept and found that individuals are motivated to act
in a manner to consistently maintain the internalized view of self across situations.
Also, research has shown that individuals adopt various strategies when the
self-concept is threatened. Individuals may flatly deny information that is
inconsistent with the self-concept maintained by external environments, and/or seek
to interact with others who provide support for the self-concept that individuals have
held (Markus & Wurf, 1987). Individuals may achieve to maintain a consistent
image of oneself through a more elaborate process in which they selectively evaluate
the information and then attempt to integrate with the existing image of oneself
(Kulik, Sledge, & Mahler, 1986). More importantly, even in the absence of a direct
challenge or threat to self, there exists in the human organism a drive to aggressively
enhance the positive view of self (Tesser & Martin, 1996). The preference to see
oneself in a self-enhancing fashion is one of the most widely documented effects in
social psychology (Pfeffer, Cialdini, Hanna, & Knopoff, 1998). Some data shows
that approximately ninety percent of manager and workers view themselves as
superior to their peers (Headey & Wearing, 1987). Tesser and his colleagues
(Tesser, 1986; Tesser & Campbell, 1983; Tesser & Paulus, 1983; Tesser, Campbell,
& Smith, 1984), for example, demonstrated that individuals tend to choose other
persons as interaction partners in a manner that enhances their self-evaluations,
particularly relative to perceived similar peers. Lewicki (1983) showed that people
prefer to judge others that enhance the probability that oneself is viewed relatively
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superior. As a rule, people assign more intelligence to one who accepts rather than
derogate their persuasive arguments (Cialdini & Mirels, 1976).
Taken together, an individual has two basic psychological needs, that is, to
reduce subjective uncertainty about one’s perception of self-concept, and to enhance
one’s self-concept somehow (Hogg & Terry, 2000). According to social identity
perspective (Tajfel, 1978; 1981; Tajfel & Turner, 1986; Turner, 1982; 1987), the
pursuit of these needs guides an individual to derive the self-concept from one’s
knowledge of a membership in a social group in a manner to attach some value
significance of and emotional commitment with it.
First, in order to reduce perceptual uncertainty, an individual subconsciously
categorizes self and others into social groups, often on the basis of demographic
attributes (Hogg & Terry, 2000). This categorization is more than a mere cognitive
classification in that it carries emotional significance as well (Brewer & Brown,
1998). Next, through the process of social categorization, an individual satisfies
another basic need for self-enhancement by establishing the positive evaluations for
one’s own social group (i.e., in-group) and degrading negative evaluations for other
social groups (i.e., out-groups) (Tajfel, 1978; Turner, 1982). An individual is apt to
attribute positive personality characteristics, such as honesty and trustworthiness, to
the fellow in-group members. On the other hand, he or she may be inclined to form
less favorable impressions of colleagues who are demographically different (Brewer,
1996; Kanter, 1977; Kramer, 1999). Further elaboration of in-group favoritism often
entails the depersonalization of individual self-perception whereby an individual
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perceives oneself as a representative of the in-group category possessing its defining
characteristic that distinguishes the in-group from out-groups. This underlies the
basic collective phenomena, including ethnocentrism, emotional contagion, and
conformity to group norms (Turner, 1987).
Affective conflict, characterized by a state of interpersonal incompatibilities
such as frustration, anxiety, dislike, and other forms of negative affect, is the
consequences of these negative emotions or antipathy directed toward each other
within the team based on the knowledge on social category membership (Abrams,
1996; Brewer & Brown, 1998). Individuals automatically make initial categorization
of other individuals seemingly belonging to different social groups and, without any
interventions, tend to maintain affective conflict against them (Fiske & Neuberg,
1990). Through social categorization, these individuals often feel social distance
away, and social polarization against, the members of out-group (Tajfel & Wilkes,
1963; Brewer & Brown, 1998).
Some forms of negative emotions, such as fear and disgust that imply
avoidance or movement away from the members of out-group (Smith, 1993), often
lead to the formation of a stereotype that monolithically views that the members of
out-group have the same characteristics without considering possible inter-individual
differences between them (Brewer, 1986; Hogg, 1996; Hogg & Abrams, 1988;
Kramer, 1991b; Nelson, 1989). Other forms of negative emotions, such as dislike,
anger and jealously that imply hostility against the members of out-group (Smith,
1993), often result in nonverbal discrimination against them (Hogg & Abrams, 1988;
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Kramer, 1991b; Triandis, 1961; Triandis & Davis, 1965) in a manner of self-
fulfilling prophecy, whereby individuals’ negative emotions induce the members of
out-group to behaviorally confirm those negative emotions (Fiske, 1998). In turn,
the members of out-group who perceive these negative emotions may evoke similar
negative emotions toward these individuals, and hostile interactions erupt between
them (Reardon, 1995). Further, since stereotypes are automatically activated in the
minds of individuals in the presence of a member of different social group, even
individuals’ conscious and intentional attempts to override these impulses may result
in a feeling of discomfort (Devine, 1989; Devine, Monteith, Zuwerink, & Elliot,
1991).
As is noted earlier, demographic attributes often serve as social groups in
terms of which members within the team establish their self-concepts as well as
categorize each other. Demographic attributes that are highly impermeable could
prevent individuals from moving from one social group to another social group
(Pelled, 1996). Social identity that derives from a highly impermeable category is
more likely to become a global self-concept that individuals carry into every
situation (Abrams, 1996; Turner, 1982), and the role it plays is fundamental, central
and wider in scope (Judge et al., 1997), thus enabling scholars to explain the variance
of human attitude and behavior (Brockner, 1988; Weiss & Adler, 1984; Wylie,
1974). Indeed, social identity perspective’s aim and contention is that social
psychology has to provide a supra-individual level of analysis by discrediting
explanations based on individual differences within the same social group (Stryker,
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1987) in order to account for the affective attitudes (e.g., prejudice and
discrimination) it seeks to explain (Abrams, 1996). When self-concepts are activated
under immediate situations, their impacts on the members of the same social group
within the team tend to show the high degree of uniformity (Festinger, 1947; Tajfel
& Turner, 1986; Turner, 1987). For social psychological purposes, the impacts of
self-concept on members’ affective attitudes are presumed equivalent, as well as the
nature of the social identification and social categorization process are presumed
monolithic (Newcomb, 1951).
As the impermeability of demographic attributes that circumscribe social
groups within the team increases, they are likely to serve as the possible bases for
social identity and social category. Race is highly impermeable as a primitive
generic social category (Messick & Mackie, 1989), thereby being proposed to have
significant effects on affective conflict. Also, organizational tenure could serve as a
social category in a manner that prevents individuals from regressing to a lesser
amount of tenure in the organization (Pelled et al., 1999). As there exists more
diversity on these attributes, members will categorize one another and attempt to
establish their social identity in more intensive ways (Stroessner, 1996), leading to
increased affective conflict.
Prior studies suggest that the relative separateness and clarity of a social
group comparison context may affect the extent to which social categorization
occurs. For instance, as religious affiliation became more unambiguous in the
immediate situations, individuals tended to be more conscious of its impermeability
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as a social group, hereby leading to their favorable attitudes between in-group
members, however, being emotionally polarized against out-group members
(Charters & Newcomb, 1952; Festinger, 1947). Other studies showed that the
members of the demographically diverse team have more experiences of negative
affect than those of the demographically homogeneous team (Levine & Moreland,
1990; O’Reilly et al, 1989). High separateness and clarity of a perceived social
group comparison context characterized by race and organizational tenure diversities
will produce more affective conflict through intense categorization of social others
within the team.
Hypothesis 2;
Demographic diversity will be positively associated with affective conflict within the
team.
Cognitive Conflict and Team Performance
Scholars (Wanous & Youtz, 1986) have argued that the presence of cognitive
conflict characterized by the disagreements between individuals can stimulate their
cognitive activities, such as to generate plans or creative ideas, solve problems, or
make informed decisions and, in turn, have a positive impact on their collective
performance. This argument rests on assumption that an exposure to dissent may
encourage individual to search for more information, to delve into issues more
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deeply from multiple perspectives, and to evidence more one’s original thought
(Nemeth & Kwan, 1987; Nemeth & Rogers, 1996; Tjosvold, 1986), hereby enabling
them to detect correct solutions that otherwise would have gone undetected (Mitroff
& Linstone, 1993). It also relies on some evidence of experimental research that
even reading or hearing of counter-attitudinal messages influenced the quantity and
quality of thought (Eagly & Chaiken, 1993; Petty & Cacioppo, 1986).
Janis (1982) posited that, when individuals fail to criticize each other’s
arguments due to strong concerns on maintaining unanimity, they tend to overlook
disagreements critical to a higher quality of decision-making. Similarly, Churchman
(1971) noted that, in ill-structured decision situations confronting modern
organizations, the absence of cognitive conflict in decision-making could be inferior
to dialectical inquiry in which different approaches to problems can foster the debate
over opposing arguments.
To explore the impact of cognitive conflict, decision-making scholars have
employed two types of experimental techniques designed for circumventing the
pressure for social conformity (Janis, 1982) and stimulating the cognitive activities
between individuals (Churchman, 1971). These are dialectical inquiry and devil’s
advocacy. The dialectical inquiry is a method by which, a prevailing plan or
recommended plan is identified, along with the data used to derive it. Then,
individuals attempt to identify the assumptions underlying that plan. Next, a
counter-plan is developed, which is feasible, politically viable, and generally credible
on the basis of different data which rests on assumptions opposite those supporting
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the original plan. From these diametrically opposed positions, individuals rigorously
debate the assumptions until they agree on a set of common assumptions. From
these surviving assumptions, a final plan or recommendation is constructed and
adopted. On the other hand, the devil’s advocacy is a less elaborate method by
which, a prevailing plan or recommended plan is identified and critiqued, however
unlike dialectical inquiry, no explicit counter-plan is offered. Individuals attempt to
discover all that is wrong with the original plan for the sake of denigration, however,
provide neither counter-plan nor counter-evidence to support it.
Mason (1969) argued that the dialectical inquiry should be more effective at
improving a decision-making than the devil’s advocacy. After conducting a meta
analysis of seventeen studies examining the differences in the effects of these
different approaches, Schwenk (1990) found that both the dialectical inquiry and the
devil’s advocacy are more effective than a decision-making without cognitive
conflict in a manner that the dialectical inquiry has a slight advantage over the
devil’s advocacy technique. Individuals that used objective facts and develop a
counter-plan were found to be more effective at stimulating cognitive activities than
those who only critiqued he original plan. To the extent that disagreements from
others are supported by the objective facts and are demonstrable to them, these
disagreements can be perceived as authentic and credible, thus attracting other
individuals’ serious attention (Nemeth, Connell, Rogers, & Brown, 2001) and
enabling them to utilize disagreements effectively in the process of decision-making.
On the other hand, when a superficial critique is offered, it is often discounted as
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useful information on the issue (Maass & Clark, 1984; Moscovici & Nemeth, 1974),
thus is neither sufficiently motivating other individuals to reassess their opinions and
to search for alternative information (Kruglanski, 1989; Taylor, 1981). In a follow
up to this meta-analysis study (Schwenk, 1990), Schwenk and Valacich (1994)
examined the decision-making performance of student teams in the experimental
settings. Their findings, however, did not support the Schwenk’s (1990) claim that
the dialectical inquiry is superior to the devil’s advocacy. They found no significant
differences across the teams using different techniques to decision-making, instead,
that these teams seemed able to make effective use of either technique. In short, it
was concluded that there is no clear pattern for team’s decision-making quality
except that both dialectical inquiry and devil’s advocacy tend to be superior to a
decision-making that does not experience cognitive conflict.
Besides the results of these studies in an experimental setting, several field
studies on intact teams found that the increase of cognitive conflict within the team
has a positive association with its performance. Amason’s (1996) large-scale study
of top management teams found that cognitive conflict within the team is positively
associated with team’s decision quality and performance. In a similar vein,
Eisenhardt et al’s (1997a; 1997b) multiple-case studies found that top management
teams in high-performing firms have higher cognitive conflicts than teams in low-
performing firms. Further, firms with lower cognitive conflict teams did less well.
Other studies of work team by Jehn et al. (1999) and Pelled et al. (1999) supported
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the claim that cognitive conflict within the team is positively associated with team
performance.
Hypothesis 3:
Cognitive conflict within the team will be positively associated with team
performance.
Affective Conflict and Team Performance
Unlike the research on the effects of positive affect (Isen & Baron, 1991), the
experience of negative affect at work settings received relatively little attention from
organization scholars (George, 1992). However, an interest in the study of negative
affect and its consequences is growing as researchers recognize the negative effects
these emotions have on important organizational outcomes such as citizenship
behaviors and withdrawal behaviors (George, 1996). In contrast to the positive
impact of cognitive conflict, the affective conflict between individuals is likely to
have a negative impact on team performance. Scholars have argued that affective
conflict characterized by a state of interpersonal incompatibilities such as frustration,
anxiety, dislike, and other forms of negative emotions would impair team
performance through the lack of cooperation between individuals that can be best
accomplished when they can synchronize their thoughts, feelings, and behavior
(Barnard, 1938; Hackman, 1992).
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When individuals feel antagonistic with one another within the team, they are
unlikely to coordinate their actions effectively and in turn produce suboptimal team
performance (Argyris, 1962). Zajonc (1980) noted that negative emotions have
pervasive impacts on the formation of individuals’ perception of social situations and
its consequent interpersonal behavior. Individuals have a general tendency to
minim ize the efforts to interpret information associated with the attitudes and
behaviors of others in a manner that sustains negative affect (Forgas, 1995; Forgas &
George, 2001; Martin, 1986; Martin, Seta, & Crelia, 1990). Individuals are apt to
selectively activate available memory structures to which the primed negative
emotions are connected (Bower, 1981; Bower & Forgas, 2001), which they may not
even be aware of doing (Bargh & Pietromonaco, 1982). Accordingly, they tend to
persistently make biased information processing of the attitudes and behaviors of
others (Fiske & Taylor, 1991). When the attitudes and behaviors of others are
interpreted in an inaccurate manner that fits negative, stereotypical expectations
individuals already have about them, this confirmed expectations may strengthen
these individuals’ biased information processing tendency (i.e„ self-fulfilling
prophecy) (Fiske & Neuberg, 1990). The consequences of these negative affect are
individuals’ unwillingness to take cooperative actions that potentially enhance the
team’s welfare (Etzioni, 1988).
Through the ecology of inaccurate attribution of each other’s attitudinal and
behavioral intentions in a negative manner, affective conflict is sustained. People in
conversation tend to continuously mimic and synchronize their movements with the
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facial expressions, voices, postures, and behaviors of others (Bavelas, Black,
Lemery, & Mullett, 1987). In a similar vein, the negative affect that individuals have
about others often reciprocates another negative emotions that others have about
these individuals, because people have an innate capacity to catch and mimic others’
emotions by observing their facial and vocal expressions (Hatfield, Cacioppo, &
Rapson, 1994). Weiss and Cropanzano (1996) noted that these primitive emotional
contagions could develop over time into the negative moods characterized by the
relatively long enduring state of affect lacking the specificity of negative emotions
with regard to a particular object or behavioral response.
When there exists affective conflict within the team, individuals may avoid
contact with others with whom they feel uncomfortable. They are less likely to
exchange information nor pay due attention to each other’s potentially useful ideas
that can improve task performance (Argyris, 1993). When people experience intense
frustration and fear associated with affective conflict, they often disengage from
interactions and become disinterested in them (Ross, 1989). As Kramer (1991a)
noted, the expectations of negative experiences of feeling anxiety associated with the
interactions with others can withhold individuals’ interactions with them. Otherwise,
individuals may be excessively concerned to ascertaining the state of others’
feelings, consequently diverting substantial time and energies to it rather than to task
performance (Evan, 1965). When affective conflict exists within the team, it
severely limits team performance in these manners.
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The results of prior research support the proposed association between
affective conflict and team performance. Evan’s (1965) study found that research
and team development teams showing high interpersonal attacks performed less
productively compared with other teams showing low interpersonal attacks. George
(1990) found that negative affective tone was negatively associated with team’s
engagement in prosocial (helping) acts. Jehn’s (1995) interviews and observation of
the work team members revealed that they were psychologically distressed and
became less committed to the task when there were frequent interpersonal crashes
manifesting themselves in intense dislike and frustration. Amason (1996) found that
affective conflict within the top management team diminished decision quality.
Similarly, other studies by Jehn (1997) and Jehn et al. (1999) found that affective
conflict had negative effects on team performance. Recently, Duffy and Shaw
(2000) found that frustration associated with envy between student team members
led to overall diminished team performance. Specifically, they also found that
negative affect led to members’ greater effort reduction in the completion of the
team’s tasks.
Hypothesis 4: Affective conflict within the team will be negatively associated with
team performance.
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Moderator Effects of Cognitive Conflict Management Practices
While some studies (Amasons, 1996; Eisenhardt et al., 1997a; 1997b; Jehn et
al., 1999; Pelled et al., 1999) found that cognitive conflict has a positive impact on
team performance, other studies (Ancona & Caldwell, 1992; Glick et al., 1993) did
not find such a positive association. These discrepant findings suggest that cognitive
conflict may not automatically translate into favorable team performance. For
example, Ancona and Caldwell (1992) noted that, when different perspectives about
the team’s task are provided by members, they may not be utilized effectively unless
the team has appropriate practices to manage cognitive conflict. Likewise, Glick et
al. (1993) concluded that, while demographic diversity affects cognitive conflict, the
positive impact of cognitive conflict is not so pervasive as managerial and academic
literatures often suggest. Scholars agree that, despite the presence of these
discrepant findings, the mechanism by which the benefits of cognitive conflict within
the team can be realized or not is not fully understood yet (Gruenfeld et al., 1996;
Williams & O’Reilly, 1998).
A possible explanation for these mixed findings may be the lack of attention
that has been paid to the practices to manage cognitive conflict between individuals
(Simons et al., 1999; Webber & Donahue, 2001). Gruenfeld et al. (1996)
emphasized the theoretical importance of considering the presence of cognitive
conflict and its effective resolution as well. Kilduff, Angelmar, and Mehra (2000)
found that successful and unsuccessful teams showed quite different patterns of
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practices to resolve cognitive disagreement over the course of the simulation at
experimental decision-making settings. Eisenhardt et al. (1997b) noted that the best
top management teams develop skills toward the management of cognitive conflict
and these skills can distinguish the world-class executive teams from the rest. In the
review of research on top management teams, Hambrick (1994) argued that the key
is behavioral integration by which the team engages in mutual and collective
interaction that enhances the quality of information exchange. Indeed, with the
absence of behavioral integration, a team that has rich cognitive resources must
operate as a loose constellation of individuals. Hence, this study addresses to the
cognitive conflict management practices within the team as a moderator of the
effects of cognitive conflict on team performance.
Cognitive conflict management practices refer to the patterns of verbal
behaviors in the exchange of individuals’ ideas and information by which the team
can elaborate and manage an emergent state of cognitive disagreement over different
aspects of the task (Innami, 1994; Kuhn & Poole, 2000). While most conflict
management practices have been treated as individual characteristics or tendencies
(De Dreu, Evers, Beersma, Kluwer, & Nauta, 2001; Rancer, 1995), it is also possible
to conceptualize them as a team level property of practices that the team enacts when
individuals deal with cognitive disagreement over the aspects of task (Eisenhardt,
1997a; 1997b; Katzenstein, 1996; Woodman, Sawyer, & Griffin, 1993). Indeed,
previous studies (Innami, 1994; Kuhn & Poole, 2000) established the utility and
feasibility of using cognitive conflict management practices as the stable property of
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a team. Innami’s (1994) study is especially important to the purpose of the present
study. He coded the task-related utterances in the context of cognitive disagreement
between individuals over the solution to problems in an experimental setting, and
identified that the reasoning and positional orientations are the major types of
cognitive conflict management practices that can affect the quality of their
interactions and collective performance. This finding was consistent with other
findings on the effects of cognitive conflict management practices at the individual
level of analysis (Falbe & Yukl, 1992; Yukl, Falbe, & Young Youn, 1993).
Accordingly, this study conceptualizes the cognitive conflict management practices
as a team level multidimensional construct that consists of the reasoning and
positional orientations to the resolution of cognitive conflict. These orientations are
proposed to affect individuals’ interactions ensuing from cognitive conflict, and in
turn on team performance.
The reasoning orientations refers to the degree to which team members
exchange facts and reasons that support their ideas in a deliberative process of team’s
decision making (Innami, 1994). Presenting and responding to arguments and
counter-arguments by enumerating examples and clarifying confusion can stimulate
individuals’ cognitive activities more vigorously than criticizing each other’s
arguments peripherally without any substantial facts (Nemeth et al, 2001). These
generally enable the team to make informed decisions (Schwenk, 1990) in manners
that assess different opinions efficiently in comparative ways (Argyres & Mui, 2000)
and sharpen individuals’ viewpoints on the aspects of the task effectively (Eisenhardt
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et al., 1997a; 1997b). It is notable that strategy scholars who develop a knowledge-
based theory of the firm have focused on these deliberative interactions as a source
of sustained competitive advantage (Brown & Duguid, 1991; Nahapiet & Ghoshal,
1998; Nonaka & Takeuchi, 1995).
The positional orientations refers to the degree to which team members stick
to their opinions in defensive ways to avoid demands by others or proactively
persuade others to change their opinions (Ashforth & Lee, 1990; Innami, 1994).
While Porter, Allen, and Angle (1981) viewed these behaviors as discretionary social
influence attempts that are intended to promote or protect the self-interests of
individuals and threaten the self-interests of others, scholars have tended to
operationally focus more on the promotion of self-interests than on their protection
(Ashforth & Lee, 1990). Much of the literature on these behaviors has pertained to
proactive and acquisitive behavior wherein the individual attempted to assert some
control over others at work settings (Kipnis & Schmidt, 1988). As such, previous
studies have neglected the reactive and protective side of these behaviors (Ashforth
& Lee, 1990). Unlike them, the present study treats the positional orientations as
both assertive and defensive tendencies as well that the team enacts in the
management of cognitive conflict.
Research on team decision-making suggests the importance of considering
cognitive conflict management practices in order to understand the effects of
cognitive conflict on team performance. A series of studies (Stasser & Stewart,
1992; Stasser & Titus, 1985; 1987; Stasser et al., 1989) showed that team discussion
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tends to revolve around the information and perspectives that most members share,
and the unique idea known to only one member but necessary to improve the quality
of a final decision is rarely mentioned more than once and thus does not figure into
team’s decision-making process. These studies suggest that, since demographically
similar members usually share certain worldviews (Alderfer & Smith, 1982) and
often have some difficulty in understanding a demographically different member’s
idea (Maznevski, 1994), minority member’s disagreement can be treated with
skepticism by the members of a majority group and is less likely to factor
significantly into team’s discussion. However, when a minority member can
effectively demonstrate one’s own unique idea to the majority members, such
cognitive diversion will not occur. These arguments made by such a minority
member may be perceived as credible (Infante, 1985) and thus accepted into the
enhancement of a final decision-making (Parks & Cowlin, 1996). Put it simply,
unless there exists an exchange of logical arguments between individuals within the
team, the team may make a decision prematurely and have a poor task performance
(Janis, 1982).
Team’s effective management of cognitive conflict takes on additional
significance because the team must respond to ill-structured, judgmental tasks rather
than well-structured, intellective tasks in modern organizations. Judgmental tasks
are those that require a consensual agreement of different perspectives over solution
to collective problems, in contrast, intellective tasks are those that can have a
demonstrably correct answer to them (e.g., math problems) (Laughlin, 1980). Since
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the difficulty to appreciate other’s idea tend to become more distinct in ill-structured,
judgmental tasks, to overcome it is highly important to the success of team’s
discussion (Parks & Cowlin, 1996). When impartial and well-reasoned discussion is
made, individuals can overcome this difficulty and achieve a consensual agreement
of different perspectives by understanding the rationale underlying a final decision.
As a result, they can coordinate their efforts and commitments to it, thereby
enhancing team performance (Amason, 1996; Child, 1972; Quinn, 1980).
When an expressed opinion is disagreed with, an individual may make
inferences about the intention of the opposing individual from the perceptually
salient information that the verbal behavior connotes (Fiske & Taylor, 1991; Heider,
1958). From a social information processing perspective (Griffin, 1983; Salancik &
Pfeffer, 1978), the reasoning and positional orientations will serve as the bases on
which an individual constructs the reality of team events and interpret the intention
of other individual who provides disagreement with his or her opinion (Christiansen,
Villanova, & Mikulay, 1997; Cropanzano, Howes, Grandney, & Toth, 1997; De
Dreu et al., 2001; Ferris, Bhawuk, Fedor, & Judge, 1995). In other words, these
orientations will shape individual’s attribution of other individual’s intention of
disagreement and criticism that may be potentially threatening and embarrassing
nevertheless necessary to the improvement of team performance (Argyris, 1962;
Kelley, 1979). These patterns of attribution may have profound implications for the
successful translation of cognitive conflict into team performance.
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The reasoning orientations may help the team to manage cognitive conflict in
a productive way. First, the reasoning-oriented discussion can induce individual to
attribute the intention of other individual’s criticism to organizational citizenship
(Ferris et al., 1995) and other positive motives (Christiansen et al., 1997) deriving
from the loyalty to the team (Brief & Motowidlo, 1986; Graham, 1991; Organ,
1988). When an individual interprets other’s disagreement as a form of constructive
controversy (Tjosvold, 1986; 1987) and view other’s goal as compatible with one’s
own (Deutsch, 1973; Johnson & Johnson, 1989; Tjosvold, 1985), it elicits
individual’s willingness to listen to other’s opposing views (Leana & Van Buren,
1999; Wood, Lundren, Ouellette, Busceme, & Blackstobe, 1994). Next, the
reasoning orientations can allow other individual to feel safe to provide disagreement
without a fear of retaliation (Edmondson, 1999). These expectations may enable
individuals to mutually reflect one’s argument in a way compatible with other’s
argument (Kilduff et al., 2000; Nahapiet & Ghoshal, 1998; Weick, 1969; 1995).
When these high order interactions are possible, the team can increase the capability
to learn from each other (Ely & Thomas, 2001; Schein & Bennis, 1965), make a
comprehensive understanding on various task issues (Simons et al., 1999), and build
individual’s commitment to team’s resulting decisions (Priem, Harrison, & Muir,
1995),
Also, the reasoning-oriented discussion will have a positive impact on team
member’s perception of the work environments (Jones & James, 1979), especially of
the procedural fairness (Lind & Tyler, 1988) within the team. Procedural fairness
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has two components: a structure of team decision-making process and a quality of
interpersonal treatment in it (Brockner & Siegel, 1996). First, the reasoning-oriented
team discussion contains informal procedural rules on which the conditions and
assumptions underlying different ideas can be rationally analyzed (Mason & Mitroff,
1981; Mitroff, 1974; Toulmin, 1964). The mere presence of these institutionalized
rules may secure team members’ expectations that their performance will be
evaluated by supervisors and peers in a relatively objective and unambiguous way
(Masterson, Lewis, Goldman, & Taylor, 2000; Thibaut & Walker, 1975) and that
their contributions are accordingly rewarded (Adams, 1965; Moorman, 1991;
Mowday, 1991). Secondly, team’s enactment of reasoning principles will make it
possible that a high quality of interpersonal treatment is consistently exchanged
between individuals regardless of their demographic and opinion differences and that
there always exist the opportunities for each individual to correct the team’s decision
(Ely & Thomas, 2001; Leventhal, Karuza, & Fry, 1980). These received treatments
may communicate to all team members, especially to a minority member, that
minority member’s uniqueness is valued and respected (Tyler, 1999). Member’s
experiences of feeling respected and valued can contribute to team’s adaptive
changes to the new task environments and the senses of self- and team-efficacy as
well (Ely & Thomas, 2001; Lind & Tyler, 1988). Further, a high quality of
interpersonal treatment will lead to the identification with team (Smidts, Pruyn, &
Van Riel, 2001) and increase the chances that members will successfully exchange
their ideas and feedbacks (Kogut & Zander, 1996; Nahapiet & Ghoshal, 1998).
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On the other hand, the positional orientations may have a negative impact on
interactions between team members and in turn on team performance. First, when
there exists a relatively high amount of positional-oriented discussion, cognitive
conflict tends to be attributed to other member’s intention of self-serving (Brass &
Burkhardt, 1993; Ferris et al., 1995), such as a cunning way to get one’s way, to buy
time and to impose one’s will on others (De Dreu et al., 2001). When other
member’s criticism provides hidden information selectively (Eisenhardt &
Bourgeois, 1988; Fandt & Ferris, 1990; Pfeffer, 1992) or becomes too assertive
(Tedeschi & Melburg, 1984), the intention of disagreement is interpreted as the
social influence attempts designed to protect the self-interests (Ferris, Russ, & Fandt,
1989; Gray & Ariss, 1985; Madison, Allen, Porter, Renwick, & Mayes, 1980) or to
struggle for power and status (Cropanzano et al., 1997; Innami, 1994; Parker,
Dipboye, & Jackson, 1995). These perceptions often foster more negative
interpersonal attitudes and eventually lead to a stalemate of team discussion wherein
cognitive conflict does not successfully translate into team performance
(Christiansen et al., 1997). When team members divert their efforts to non-task
related issues (Argyres & Mui, 2000; Milgrom & Roberts, 1988; 1990), they do not
pay attention to the success of team decision-making (March & Olsen, 1979) and
feel less responsibility for its outcome (Hackman & Oldham, 1976; Salancik, 1977).
As a result, the team must adopt a final decision or seek a consensus prematurely
(Janis, 1984) in ways that ignore minority member’s valuable and unique inputs into
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the team decision-making, thereby leading to decreased efficiency (Argyres & Mui,
2000) and effectiveness (Eisenhardt & Bourgeois, 1988) in task performance.
Also, the position-oriented discussion may have negative impacts on
worker’s experiences and other outcomes. When there do not exist informal rules to
manage cognitive conflict, it can create ambiguity (Tetlock, 1985) and
unpredictability (Cropanzano et al., 1997) in team members’ expectations that their
performances will not be fairly evaluated (Kipnis & Schmidt, 1988; Parker et al.,
1995; Porter et al., 1981) and that they will be relatively deprived in reference to
other members who are defensive or assertive in discussion (Goodman, 1977).
Perceived positional orientations may lead to a variety of individual outcomes such
as worker’s job dissatisfaction (Ferris & Kacmar, 1992; Gandz & Murray, 1980;
Parker et al., 1995), the feelings of job anxiety (Cropanzano et al., 1997; Kipnis &
Schmidt, 1988), and the withdrawal of efforts and commitment to the task
(Cropanzano et al., 1997; Kidwell & Bennett, 1993), and other team outcomes that
include the decreased amount of cooperation (Cropanzano et al., 1997; Parker et al.,
1995) and innovation (Frost & Egri, 1991). On the other hand, individuals who are
not distracted by the perceived positional orientations (Christiansen et al., 1997) will
aggressively redefine work environments (Cheng, 1983; Weick, 1969; 1995) as the
arena for social influence activities to promote the self-interests and opportunistically
divert resources to them (Fandt & Ferris, 1990; Madison et al., 1980). While these
individuals may feel a certain amount of satisfaction in these acquisitive activities,
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their potentially adverse relationships with coworkers can be detrimental to team
performance (Christiansen et al., 1997).
A high quality of cognitive conflict management practices can be
conceptualized as the proportional composition of reasoning orientations relative to
the combined amount of both orientations, and it is expected to have a positive
impact on the association between cognitive conflict and team performance (De
Dreu, 1997). For example, a high quality of cognitive conflict management practices
that contain more reasoning orientations in relation to positional orientations will
enable the team to successfully translate cognitive conflict into team performance
without experiencing team process losses (Hackman, 1987). On the other hand,
within the team that has a low quality of cognitive conflict management practices
that contain less reasoning orientations in relation to positional orientations,
individuals will not apprehend the accuracy of different perspectives and
consequently they are so divided as unable to learn from each other nor integrate
different them for the sake of improved task performance. Their interactions are
represented as the diversion of team’s resources to peripheral, non-task related
activities.
Hypothesis 5:
The positive association between cognitive conflict and team performance will be
stronger when cognitive conflict management practices are higher rather than lower.
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Moderator Effects of Task Interdependence
While some studies (Amason, 1996; Jehn, 1997; Jehn et al., 1999) found that
affective conflict had a negative impact on team performance, other studies (Jehn,
1995; Pelled et al., 1999) found no evidence that affective conflict impairs team
performance. Pelled et al. (1999) discussed, with respect to their unexpected
findings, that contextual factors would shape the ways in which team members
interact and, in turn, that affective conflict is not necessarily associated with team
performance.
A possible explanation for these discrepant findings is the lack of attention
that has been paid to team’s task design (Williams & O’Reilly, 1998). Macrae and
Bodenhausen (2000) noted that certain type of task design is likely to trigger
stereotype suppression between individuals and its effects need to be empirically
clarified. Relatedly, Jehn (1995) tested the effects of interactions between affective
conflict and task interdependence on team performance and its results, opposing to
her expectations, partially indicated the possibility that task interdependence may
mitigate the effects of affective conflict on team performance.
Interdependence is an important aspect of task design that affects the
association between team process and its performance (Gladstein, 1984). While
prior research (e.g., Johnson, Johnson, & Maruyama, 1984) did not make distinctions
between different types of interdependence, reward and task interdependence are
identified as conceptually and empirically distinct, possible to be designed
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independently with each other (Wageman, 1995; Wageman & Baker, 1997). Reward
interdependence refers to the extent to which the reward that individual receives
depends on the performance of others within team. Reward interdependence is
designed to intensify individual’s economic incentives to cooperate with others. The
least interdependent, or independent, reward is one that exclusively accrues to
individual based on his or her excellence, such as a commission paid to an individual
salesperson. The most interdependent reward is one that is equally given to each
individual, regardless of individual performance, based on collective performance
such as a gain-sharing plan. A hybrid reward that exists between these two extremes
is one in which a significant portion of the reward is given to individual based on
collective performance, and another significant portion is given based on individual
performance. Many organizations adopt a hybrid reward system that is designed to
increase individual’s economic incentives for cooperation as well as individual
excellence (Lawler, 1990).
While a hybrid reward system is seemingly attractive, simply adding reward
measures to address the full spectrum of performance dimensions may not ensure
worker’s optimal attention to all dimensions (Holmstrom & Milgrom, 1991). In a
hybrid system, since workers often perceive that their rewards are neither dependent
on individual nor collective performance, they are confused with the ambiguous
performance-reward link that comes partially from independent rewards for
individual excellence and partially from interdependent rewards for collective
performance (Wageman, 1995). Rosenbaum, Moore, Cotton, Cook, Hieser, Shovar,
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and Gray (1980) found that team performs relatively poor when independent or
hybrid rewards are provided, compared to when interdependent reward is provided.
According them, including even a small portion of independent rewards into task
design can undermine the performance of team because it directs individual’s
attentions to a competitive nature of interpersonal action. In a similar vein, Lazear
(1989) noted that individually based rewards reduce individual’s willingness to
cooperate with other team members. Pfeffer and Langton’s (1993) study found that
the greater reward dispersion is associated with college and university faculty’s
diminished levels of working collaboratively on research with other faculties.
Further, studies by Wageman (1995) and Wageman and Baker (1997)
revealed the insignificant role that reward interdependence can play in order to elicit
individual’s cooperation within the team. They investigated differential effects of
reward and task interdependence on team performance and found that reward system
design alone has no independent effects on cooperative behavior within the team,
regardless of the varying levels of task interdependence. Their findings were that
reward interdependence increases the level of individual’s efforts to execute a task
that is unambiguously assigned to each worker, however, not the level of
individual’s extra efforts to cooperate with coworkers that are not necessarily
prescribed in job description but are crucial to the improvement of task performance
(Katz & Kahn, 1978).
Management scholars emphasize that the team can benefit when members are
willing to expend extra efforts on behalf of the team (Pfefer, 1994). Especially,
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proactively helping behaviors that entail the direct deference of individual’s self-
interests, such as “cross-territory helping” (Wageman, 1995) and “working on
partner’s article” (Wageman & Baker, 1997), has a stronger positive impact on team
performance, relative to other forms of extra-role behaviors such as withholding
complaints and compliance (Podsakoff, Ahearne, & MacKenzie, 1997). While prior
research did not pay much attention to helping behaviors at organizational settings
(Wagner, 1995), they are increasingly considered as the important factor for the team
to learn, to adapt to changes, and to improve task performance in the long term
(Ghoshal & Moran, 1996). Taken together, in order to understand why individual is
willing to help coworkers and expend extra efforts for the improvement of task
performance, researchers should look at task interdependence rather than reward
interdependence (Wageman & Baker, 1997).
Task interdependence is defined as the extent to which individuals must rely
on one another to complete their team’s task (Thompson, 1967; Van de Ven & Ferry,
1980). While task interdependence is partly determined by the requirements and
constraints inherent in task’s technology or design (Goodman, 1986), it is also
shaped by the way that team members with given responsibility and authority choose
to plan, coordinate, and execute their activities in relation to other features of the
task, such as goals, feedback, autonomy, and leadership (Saavedra, Earley, & Van
Dyne, 1993). While individuals are potentially connected to others through a given
form of technology, only active use of connections can engender their social
perceptions of the intact team (Burt, 1982; Monge, Fulk, Kalman, Flanagin,
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Parnassa, & Rumsey, 1998). Since several researchers (Campion et al., 1996; Shea
& Guzzo, 1987; Wageman, 1995) have shown that teams with similar technologies
vary widely in their amount of task interdependence, the present study adopts a
social psychological perspective of task interdependence as the extent to which team
members perceive that cooperation is required to complete the task.
Task interdependence will moderate a negative impact of affective conflict
on team performance. Kiggundu (1981; 1983) found that high task interdependence
increases individual’s perceived responsibility for one’s own and others’ work
outcomes. When individuals see the direct effects of their actions on others, they
come to develop a greater sense of felt responsibility for others’ work outcomes
(Pearce & Gregersen, 1991). Because this felt responsibility implies the importance
of making accurate perception and appraisal of others, individuals attempt to assess
the appropriateness of their emotional reactions to others that emerged as a form of
affective conflict. If individuals find themselves having negative feelings and
thoughts on these significant others as a result of their exposure to others’
demographic dissimilarity, then they attempt to avoid these negative feelings and
thoughts in forming the impression of others. Instead, they partial out the contextual
influences on the formation of negative feelings and thoughts that are consequences
of human’s innate social categorization. Thus, when the team conducts a highly
interdependent task, individual may experience the sense of felt responsibility for
others’ outcomes and formulate less negative impression of others. These processes
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of modifying impression formation are represented as “resetting” (Martin, 1986;
Martin et al., 1990) and “individuation” (Fiske & Neuberg, 1990).
Also, as is noted earlier, high task interdependence may induce individuals’
helping behaviors that are directed toward the goal of relieving others’ needs, not
toward the enhancement of self-interests (Wageman, 1995; Wageman & Baker,
1997). Considering George’s (1990) findings that that affective conflict reduces
team’s engagement in prosocial (helping) acts, the effects of task interdependence on
affective conflict seem significant. Helping acts could facilitate the reduction of
affective conflict and even the emotional convergence between individuals. Lanzetta
and Englis (1989) found that individuals’ emotional responses are partially
determined by their expectancies regarding the nature of social interactions with
others. When individuals can experience others’ helping behaviors, they feel that
their social relationships with others are cooperative, thus causing individuals’
empathic feelings with others. On the other hand, helping behaviors may provide the
helping individuals with supplementing information to infer whether and how much
they value the welfare of others (Batson et al., 1992; 1995). Taken together, high
task interdependence can induce individual’s helping behaviors toward others and, in
turn, arouse his or her emotional dissonance wherein these behaviors are used as
backward information to infer the value of others’ welfare. The results of Batson et
al’s (1995) experimental studies demonstrate that when individuals show helping
behaviors toward others, they come to learn that they value the welfare of others.
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Through these emotional processes, affective conflict may be reduced and even
emotional convergence may occur.
Finally, high task interdependence can provide individual with new,
additional understandings that help to define the social relations with others within
the team (Ashforth & Mael, 1989; Brickson, 2000; White, 1992). High density of
connections and interactions enables individual to realize the interconnectivity with
others (Monge et al., 1998; Robertson, 1999) and to strengthen the perception that
the team is a legitimate social entity (Scott, 1992). These perceptions are often
attached with the positive evaluations with each other and of the team as a whole
(Dovidio, Gaertner, & Kafati, 2000; Gaertner, Rust, Dovodio Bachman, &
Anastasio, 1994; 1996). These new understandings will help to discontirm the
emergent stereotypes that are consequences of social categorization (Chatman &
Flynn, 2001; Islam & Hewstone, 1993) and contribute to emotional attachment with
each other (Bartel & Saavedra, 2000). From these arguments, high task
interdependence is predicted to weaken a negative impact of affective conflict on
team performance.
Hypothesis 6:
The negative association between affective conflict and team performance will be
weaker when task interdependence is higher rather than lower.
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CHAPTER IV: METHODOLOGY
Sample
To test these hypotheses, fifty-nine team-level responses were used.
Although this sample size may be modest by some standards, it compares well with
other field studies published in major management journals and, as a field study,
yields valuable insights that can not be gained from the laboratory studies (Pelled et
al., 1999). This study included three types of teams (twenty-six work teams, thirty-
two project teams, and one top management team) because team literature has
considered that differences in the type of team have negligible effects on
interpersonal actions and team performance (Cohen & Bailey, 1997; Edmondson,
1999; Williams & O’Reilly, 1998).
Research Sites and Survey Procedures
Before the field investigation, I conducted a pretest study to assess the
relevance of this study’s survey instruments to research participants. Nine
individuals (four healthcare and five non-healthcare workers) from different teams
and organizations were asked to complete the questionnaire and to give feedback in
terms of the clarity of instructions and the wording of questionnaire items. Since,
unlike other measures, the reasoning and positional orientations scales were not
standard (had not been used in a published study), a primary objective of the pretest
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was to assess the respondent’s accuracy of understanding these measures. The
verbal and written feedback of respondents was used for the consideration of
modifying the questionnaire items. The responses by individuals participating in this
pretest study were not included in the field investigation’s data.
Following the pretest study, I conducted the cross-sectional field
investigation at a total of eleven research sites all located in the area of southern
California-hereafter referred to as Sites A, B, C, D, E, F, G, H, I, J and K. Sites A
and B were public healthcare organizations. Site C was an automotive
manufacturing firm. Site D was a sales and shipping division within an aerospace
firm. Site E was an engineering division within an electronic products firm. Site F
was an accounting division within a financial service firm. Site G was a customer
services division within an office machine firm. Site H was a liaison division within
a pharmaceutical firm. Site I was an engineering division within an electric wires
and cables firm. Site J was a financial adviser division within a bank branch. Site K
was a nonprofit healthcare organization. I asked the contact person at each site to
identify the teams possibly participating in this study such that they had no less than
three and no more than twenty-five members. Also, a team manager who was
familiar with the team’s work, had an ongoing opportunity to observe team
performance, and was in a position to make such assessments was identified.
Potential participants were informed that their participation was voluntary
and involved the completion of a survey instrument, and that their responses would
be kept confidential (see Appendix 1: Information Sheet for Non-Medical Research).
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The questionnaires (see Appendix 2: Team Member Questionnaire, Appendix 3:
Manager/Leader Questionnaire) were distributed by team managers and after several
weeks collected by the contact person at each site in the sealed envelopes for
confidentiality. Sixty-five teams (545 members) were invited to participate in this
study. 238 members (44 percent) from these teams returned the questionnaires. To
be included in the sample, at least two members from the same team had to complete
the questionnaires (Amason, 1996; Simons et al., 1999). As a result, 232 members
from fifty-nine teams were included in this study’s sample. On average, 46 percent
of the members of a participating team completed the questionnaires. Forty-one
managers’ responses were available for the ratings of these teams’ performance.
Table 1 shows information for each site, the number of participating teams, the total
number of participating members, and the response rates. Table 2 shows descriptive
statistics for the sample as a whole.
Table 1: Participating Teams, Their Members, and Their Response Rates at
Each Site
Site
Participating
Teams
Members
Response
Rates (%)
A 17 84 62
B 8 34 64
C 8 23 40
D 5 17 65
E 3 11 100
F 3 10 100
G 1 6 100
H 1 3 100
I 1 4 100
J 1 4 50
K 11 36 19
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Table 2: Profile of Sample
Age (years) 43.84 (mean) 11.28 (standard deviation)
Gender
Male 34.82 %
Female 65.18 %
Educational background
Not graduated from high school .88 %
Graduated from high school/G.E.D. 1.75 %
Some college or technical training beyond high school (1-3) years 26.32 %
Graduated from college (B.A., B.S., or other bachelor degree) 25.44 %
Some graduate school (but no graduate degree) 5.26 %
Master degree 20.61 %
Doctoral degree 19.74 %
Position (Completed by research participants from Sites A, B and K)
Not included in a survey questionnaire at other sites 34.36 %
Nurse 7.93 %
Nurse attendant 0 %
Physician or surgeon 16.3 %
Therapist 1.76 %
Administrative staff 18.94 %
Technologist or technician 0 %
Secretary or clerk .44 %
Other position 20.26 %
Race
Black/African-American 3.95 %
Asian and Pacific-Islander/Asian-American 23.68 %
American Indian/Alaska Native .44 %
Latino/Hispanic American 7.89 %
White/Caucasian-American 60.09 %
Other (i.e., Multi-Racial) 3.95 %
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Measures
This study included several measures at the team-level of analysis:
demographic diversity (predictor variables), cognitive and affective conflict
(mediator variables), cognitive conflict management practices (moderator variable),
task interdependence (moderating variable), team performance (outcome variable),
and others (control variables).
Predictor variables: demographic diversity. Organizational tenure diversity
within the team was computed as the coefficient of variation (standard deviation
divided by the mean) of organizational tenure between team members (Glick et al.,
1993; Pelled et al., 1999). The higher the organizational tenure’s coefficient of
variation, the greater is the team’s diversity. Following previous research (Ancona
& Caldwell, 1992: Jehn et al., 1999; Pelled et al., 1999), racial diversity within the
team was calculated by the entropy-based index (Teachman, 1980):
I
Diversity = X -P i (InPi).
1=1
This index can take into account categorical diversity among members across the
possible social categories. A total number of categories is expressed by I, and Pi
represents the probability of team members falling into category i. If a certain
category is not represented in the team, its assigned value is zero. Since (InPi)
always takes a negative value, it is formulated to be multiplied by another negative
value.
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This study presumed six racial categories in the team (1=6): 1 corresponds to
Black/African-American, 2 corresponds to Asian- and Pacific-Islander/Asian-
American, 3 corresponds to American Indian/Alaska Native, 4 corresponds to
Latino/Hispanic-American, 5 corresponds to White/Caucasian-American, and 6
corresponds to Other (i.e., multi-racial). For example, if a given team contains ten
members (two Blacks/African-Americans, three Asian- and Pacific-Islanders/Asian-
Americans, two Whites/Caucasian-Americans, and two Latinos/Hispanic-Americans,
and one American Indian/Alaska Native), then Pi equals .20, P2 equals .30, P3 equals
.20, P4 equals .20, P5 equals . 10, and its racial diversity is 1.55. If all members are
Blacks/African-Americans, then Pi equals 1 and team’s racial diversity is 0. Thus,
the higher the categorical diversity index is, the greater the diversity within the team
is.
Mediator variables: cognitive and affective conflict. Cognitive and affective
conflict are different profiles of conflict as a multi-dimensional construct. Because
these dimensions were predicted to have theoretically different impacts on team
performance (Law, Wong, & Mobley, 1998), scholars have treated them as
conceptually distinct. Cognitive and affective conflict scales were adapted from
studies by Jehn (1994) and Pelled et al. (1999). The cognitive conflict scale was
composed of four questionnaire items: (1) ‘T o what extent are there differences of
opinion in your team?”; (2) “How often do the members of your team disagree about
how things should be done?”; (3) “How often do the members of your teams
disagree about which procedures should be used to do your work?”; and (4) ‘T o
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what extent are the arguments in your team task-related?”. The affective conflict
scale was composed of four items: (1) “How much tension is there among the
members of your team?”; (2) “How often do the members of your team get angry
while working in your team?”; (3)”How much jealousy or rivalry is there among the
members of your team?”; and (4) “How much are personality clashes evident in your
team?”. Members rated these items on a five-point Likert scale anchored by l=none
and 5=very much. Team-level measures of cognitive and affective conflict were
formed by averaging each member’s responses to these scales. Higher values
represent greater cognitive and affective conflict. Internal consistency reliability (the
extent to which there is cohesiveness among items) was computed for cognitive (a =
.79) and affective (a = .85) conflict.
Moderator variable: cognitive conflict management practices. The cognitive
conflict management practices scale was composed of the aggregation of the
reasoning and positional orientations that Innami (1992) identified as the two major
types of cognitive conflict management practices. These orientations were identified
as the result of his coding of the task-related utterances that individuals made in the
context of cognitive disagreement over the solution to problems in an experimental
setting. Cognitive conflict management practices were computed as the reasoning
orientations multiplied by the ratio of reasoning orientations to the sum of reasoning
and positional orientations within the team. The reasoning and positional
orientations scales were developed from Innami’s (1992) study. The reasoning
orientations scale was composed of five questionnaire items: (1) “Members often add
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related information or knowledge to the facts and opinions that were initially
introduced by someone in our team”; (2) “Members work to clarify disagreeing
points or confused arguments in discussions”; (3) “In discussions, members often
explore reasons for the team’s conclusions, judgments, or inferences”; (4) ’’Members
clarify the conditions and assumptions behind each other’s arguments”; and (5)
’’Members often provide examples in order to explain their opinions”. The positional
orientations scale was composed of five questionnaire items: (1) “Members often
repeat statements or questions in discussions”; (2) “Members often get defensive in
their arguments”; (3) “Members tend to stick to their opinions in discussions”; (4)
“Members are unnecessarily assertive in discussions”; and (5) “Members do not
really respond to each other’s arguments in discussions”. Respondents rated these
items on a five-point Likert scale anchored by l=strongly disagree and 5=strongly
agree. Team-level measures of reasoning and positional orientations were formed by
averaging each member’s responses to these scales. Higher values of cognitive
conflict management practices represent a high quality of a team’s approach to
cognitive conflict. Internal consistency reliability was computed for reasoning (a =
.82) and positional (a = .64) orientations.
Moderator variable: task interdependence. Since teams with similar
technologies often vary widely in their amount of task interdependence, members’
perception of the level of interdependence that is necessary to complete the task was
assessed. The task interdependence scale was adapted from prior studies (Pearce &
Gregersen, 1991; Bartel & Saavedra, 2000). The task interdependence scale was
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composed of eight questionnaire items: (1) “I work closely with other members in
doing my work”; (2) “I frequently must coordinate my efforts with other members”;
(3) “My own performance is dependent on receiving accurate information from other
members”; (4) ‘The way I perform my job has a significant impact on other
members”; (5) “My work requires me to consult with other members fairly
frequently”; (6) “I work fairly independently of other members in my teams”
(reverse scored); (7) “I can plan my own work with little need to coordinate with
other members” (reverse scored); and (8) “I rarely have to obtain information from
other members to complete my work” (reverse scored). Members rated these items
on a five-point Likert scale anchored by l=very inaccurate and 5=very accurate.
Team-level measures of task interdependence were formed by averaging each
member’s response to this scale. Higher values represent a high level of perceived
interdependence in the team’s task. Internal consistency reliability of this scale was
computed (a = .83).
Outcome variable: team performance. The team performance scale was
assessed in terms of operational efficiency, work and output quality, innovation, and
adherence to schedules. These were considered as the major dimensions of team
performance (Ancona & Caldwell, 1992; Edmondson, 1999; Hackman, 1987; Van de
Ven & Ferry, 1980). The team performance scale was composed of six
questionnaire items: (1) “Our team functions very efficiently”; (2) ‘The quality of
service that our team produces is very high”; (3) “Our team usually meets or exceeds
customers’/clients’/patients’ expectations”; (4) “Critical quality errors occur
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frequently in our team’s work” (reverse scored); (5) “Our team introduces many
innovations or new ideas”; and (6) “Our team usually adheres to schedules”. Team
members rated these items on a five-point Likert scale anchored by l=strongly
disagree and 5=strongly agree. Team-level measures of members’ perceived team
performance were formed by averaging each member’s response to this scale. Also,
team managers’ ratings of the same scale were used as another measure of team
performance when they were available. Higher values represent better team
performance. Internal consistency reliability of this scale was computed for
members’ (a = .81) and manager’s (a = .76) ratings.
Control variables. Since some sites had higher rates of participation from
members than others, site differences were controlled. Team size that represented
the number of team members at each team invited to participate was another control
variable because larger teams have more potential for demographic diversity (Bantel
& Jackson, 1989).
Adequacy of measures. In order to ensure the adequacy of some measures,
the discriminant validity (the extent to which measured constructs are distinct from
each other) was assessed for cognitive and affective conflict, and for reasoning and
positional orientations of cognitive conflict management practices, by conducting
confirmatory factor analysis. Table 3 shows the results of this analysis. The
goodness-of-fit index was .73, and the chi-square test was significant (p < .001).
These figures indicate that there is a good fit between the data observed in the
sample and the theoretical factor structure expected to be observed in the population.
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Table 3: Results of Confirmatory Factor Analysis of Conflict and Cognitive
Conflict Management Practices Items
Loading Factor 1 Factor 2 Factor 3 Factor 4
Cognitive Affective Reasoning Positional
Item Conflict Conflict Orientations Orientations
Cognitive conflict 1 .83
Cognitive conflict 2 .86
Cognitive conflict 3 .83
Cognitive conflict 4 .76
Affective conflict 1 .85
Affective conflict 2 .83
Affective conflict 3 .84
Affective conflict 4 .86
Reasoning orientations 1 .79
Reasoning orientations 2 .83
Reasoning orientations 3 .79
Reasoning orientations 4 .82
Reasoning orientations 5 .82
Positional orientations 1 .71
Positional orientations 2 .82
Positional orientations 3 .72
Positional orientations 4 .82
Positional orientations 5 .77
Also, the intraclass correlation (the extent to which members’ responses from
the same team differ from those of other teams and agree with each other) was
assessed for cognitive and affective conflict, reasoning and positional orientations,
task interdependence, and team performance. First, one-way analysis of variance
(ANOVA) was conducted on the full data set of 232 members’ responses, with team
membership as the independent variable and individual member’s response as the
dependent variable. Cognitive and affective conflict, reasoning and positional
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orientations, and team performance measures were highly significant to p < .01 level,
and task interdependence measure was nearly significant at p = .0557. These results
indicate that members’ responses to these measures were different across teams.
Next, this study assessed the extent to which members’ responses from the same
team agree with each other. Intraclass correlation coefficients were .17 for cognitive
conflict, .47 for affective conflict, .25 for reasoning orientations, .23 for positional
orientations,. 11 for task interdependence, and .24 for team performance. These
positive values indicate that members from the same team are more similar than non
members, whereas negative correlations would indicate greater dissimilarity (Kenny
& La Voie, 1985).
Analysis
In the next chapter, a series of regression analyses will be conducted to
examine the proposed hypotheses. For a hierarchical regression, control and main
variables are entered into the model in the first and second steps, respectively. Next,
moderator and interaction term variables are added in the third and fourth steps,
respectively (Cohen & Cohen, 1983). Also, the mediator effects of cognitive and
affective conflict on team performance will be examined when the results of analysis
can establish the conditions for examining their mediator effects (Baron & Kenny,
1986).
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CHAPTER V: RESULTS
Introduction
Table 4 provides the means and standard deviations of the study variables.
Table 5 provides correlations among these variables. Table 6 to Table 15 show the
results of a series of regression analyses. They report standardized P coefficients
from the final step in their regression models and standard errors in parentheses.
Table 4: Means and Standard Deviations of Study Variables
Variable Mean
Standard
Deviation
Maximum Minimum
Org. Tenure
Diversity
.80 .33 1.68 0.09
Racial Diversity .43 .37 1.32 0
Cognitive
Conflict
2.46 .45 3.33 1.50
Affective
Conflict
1.84 .57 3.63 1.00
Cognitive Conflict
Management
Practices
2.19 .45 3.25 1.30
Task
Interdependence
3.78 .39 4.88 2.96
Member-rated
Team
Performance
3.78 .42 4.75 3.00
Manager-rated
Team
Performance
4.03 .48 5.00 2.83
Team Size 6.59 6.02 25.00 2.00
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Table 5: Correlations among Study Variables
1 2 3 4 5 6 7 8 9
1. Org. Tenure
Diversity
—
2. Racial
Diversity
-. 1 1 —
3. Cognitive
Conflict
-.16 .03 —
4. Affective
Conflict
- .12 .04
72* *
—
5. Cog. Conflict
Mgmt. Practices
.13 -.08 - 41**
_ ^4**
—
6. Task
Interdependenc
e
-.02 .17 .12 .08 .14 —
7.Member-rated
Team
Performance
.11 -.02 - .31* - .58**
69* *
.21 —
8. Manager
rated Team
Performance
.22 -.14 -.34* -.35* .35* - .05 .39* —
9. Team Size .04 -.09 .29* .16 -.07 -.03 -.29* -.17 —
* p < .05
** p < .o i
Demographic Diversity and Cognitive Conflict
Hypothesis 1 stated that organizational tenure and racial diversity would be
positively associated with cognitive conflict within the team. Unexpectedly, Table 6
shows that no positive impact was found on cognitive conflict, instead showing a
modestly negative impact of organizational tenure (P = - .28, p < .10 for
organizational tenure diversity; J 3 = - .01, n.s. for racial diversity).
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Table 6: Hierarchical Regression of Cognitive Conflict on Control and Diversity
Variables (N=55)
Contribution to R2 Independent Variables Cognitive Conflict
Control Variables
A R2 .09 Site Differences .01 (.02)
Team Size .01 (.01)
Diversity Variables
A R2 .05 Org. Tenure Diversity -.2 8 t (.16)
Racial Diversity -.01 (.14)
F 2.18t
Total R2 .14
t p < .10
Demographic Diversity and Affective Conflict
Hypothesis 2 predicted that diversity measures would be positively related to
affective conflict. Surprisingly, the effects of organizational tenure and racial
diversities on affective conflict were not found in Table 7 ((3 = - .22, n.s. for
organizational tenure diversity; (3 = - .04, n.s. for racial diversity).
Table 7: Hierarchical Regression of Affective Conflict on Control and Diversity
Variables (N=55)
Contribution to R2 Independent Variables Affective Conflict
A R2 .17
Control Variables
Site Differences
Team Size
.07** (.02)
- .01 (.01)
A R2 .02
Diversity Variables
Org. Tenure Diversity
Racial Diversity
- .22 (.20)
-.0 4 (.18)
F 3.01*
Total R2 .19
* p < .05
** p < .01
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Cognitive Conflict and Team Performance
Hypothesis 3 predicted that cognitive conflict would be positively associated
with team performance. Contrary to our expectations, Table 8 and Table 9 show that
cognitive conflict has a negative impact on team performance (P = -.21,/? < .10 for
member-rated performance; (3 = -.36, p < .10 for manager-rated performance).
Table 8: Hierarchical Regression of Member-rated Team Performance on
Control and Team Process (Cognitive Conflict) Variables (N=59)
Contribution to R2 Independent Variables
Member-rated Team
Performance
A R2 .16
Control Variables
Site Differences
Team Size
- .04* (.01)
.00 (.01)
A R2 .05
Team Process Variable
Cognitive Conflict - .21+ (.11)
F 4.89**
Total R2 .21
t p < A 0
* p < .05
** p < .01
Table 9: Hierarchical Regression of Manager-rated Team Performance on
Control and Team Process (Cognitive Conflict) Variables (N=41)
Contribution to R2 Independent Variables
Manager-rated Team
Performance
A R2 .07
Control Variables
Site Differences
Team Size
- .02 (.02)
.00 (.01)
A R2 .08
Team Process Variable
Cognitive Conflict - .36t (.19)
F 2.21
Total R2 .15
t p ^ .10
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Affective Conflict and Team Performance
Hypothesis 4 proposed that affective conflict would be negatively related to
team performance. Consistent with Hypothesis 4, TablelO provides a robust support
for this hypothesis ((3 = -.36, p < .01 for member-rated team performance). While
regression of manager-rated team performance did not support H4, its coefficients
were very close to the level of significance (p = - .28, p = .11).
Table 10: Hierarchical Regression of Member-rated Team Performance on
Control and Team Process (Affective Conflict) Variables (N=59)
Contribution to R2 Independent Variables
Member-rated Team
Performance
A R2 .16
Control Variables
Site Differences
Team Size
- .01 (.01)
.00 (.01)
A R2 .22
Team Process Variable
Affective Conflict - .36** (.08)
F 11.50**
Total R2 .38
** p<.0l
Table 11: Hierarchical Regression of Manager-rated Team Performance on
Control and Team Process (Affective Conflict) Variables (N=41)
Contribution to R2 Independent Variables
Manager-rated Team
Performance
A R2 .07
Control Variables
Site Differences
Team Size
- .01 (.02)
.00 (.01)
A R2 .06
Team Process Variable
Affective Conflict - .28 (.17)
F 1.88
Total R2 .13
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Moderator Effects of Cognitive Conflict Management Practices
Hypothesis 5 predicted that the association between cognitive conflict and
team performance would be moderated by cognitive conflict management practices.
Table 12 shows that, after the interaction of cognitive conflict and cognitive conflict
management practices was added, multiple squared correlation coefficients increased
slightly (AR2 = .03). The interaction of cognitive conflict and cognitive conflict
management practices had a modestly significant positive association with member
rated team performance (P = .29, p < .10). The pattern of this interaction was
examined using mean splits (Cohen & Cohen, 1983; Aiken & West, 1991).
Cognitive conflict and cognitive conflict management practices scores were divided
into two groups at one standard deviation above and below their respective means.
Figure 3 shows that when team’s cognitive conflict management practices are high,
the effects of cognitive conflict on team performance are null. However, when the
practices to elaborate and manage cognitive conflict between team members are low,
a high level of cognitive conflict cannot be translated into high team performance.
As a result, these results provide partial support for Hypothesis 5. Regression of
manager-rated team performance (Table 13) found no positive interaction effects
((AR2 = .00, P = .02, n.s.).
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Table 12: Hierarchical Regression of Member-rated Team Performance on
Control, Team Process (Cognitive Conflict), Moderator (Cognitive Conflict
Management Practices), and Interaction Term (Cognitive Conflict x Cognitive
Conflict Management Practices) Variables (N=59)
Contribution to R2 Independent Variables
Member-rated Team
Performance
A R2 .16
Control Variables
Site Differences
Team Size
.00 (.01)
- .01 (.00) t
A R2 .05
Team Process Variable
Cognitive Conflict - .55 (.36)
A R2 .32
Moderator Variable
Cognitive Conflict
Management Practices
- .07 (.43)
A R2 .03
Interaction Term
Cognitive Conflict x
Cognitive Conflict
Management Practices
•29 (.17) t
F 13.58**
Total R2 .56
t p < A 0
** p < .01
Figure 6: Moderator Effects of Cognitive Conflict Management Practices
Member-rated
Team Performance
3.8
3.4
3.3
High Cognitive Conflict Management Practices
Low Cognitive Conflict Management Practices
Low High
Cognitive Conflict
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Table 13: Hierarchical Regression of Manager-rated Team Performance on
Control, Team Process (Cognitive Conflict), Moderator (Cognitive Conflict
Management Practices), and Interaction Term (Cognitive Conflict x Cognitive
Conflict Management Practices) Variables (N=41)
Contribution to R2 Independent Variables
Manager-rated Team
Performance
A R2 .07
Control Variables
Site Differences
Team Size
.00 (.02)
.00 (.01)
A R2 .08
Team Process Variable
Cognitive Conflict - .35 (.92)
A R2 .02
Moderator Variable
Cognitive Conflict
Management Practices
.17(1.02)
A R2 .00
Interaction Term
Cognitive Conflict x
Cognitive Conflict
Management Practices
.02 (.39)
F 1.53
Total R2 .17
Moderator Effects of Task Interdependence
Hypothesis 6 predicted that the association between affective conflict and
team performance would be moderated by task interdependence. Hypothesis 6 was
not supported. Tables 14 and 15show that, after the interaction of affective conflict
and task interdependence was added, multiple squared correlation coefficients did
not change (AR2 = .00). The interaction of affective conflict and task
interdependence was not found to have a positive impact on team performance (3 =
.00, n.s. for member-rated team performance; P = - .26, n.s. for manager-rated team
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performance). Finally, it should be noted that the overall significance of regression
model in Table 14 reflects the intercept effects ((3 = 3.59, s.e. = 1.65, p = .03).
Table 14: Hierarchical Regression of Member-rated Team Performance on
Control, Team Process (Affective Conflict), Moderator (Task Interdependence),
and Interaction Term (Affective Conflict x Task Interdependence) Variables
(N=59)___________________________________________________________________
Contribution to R2 Independent Variables
Member-rated Team
Performance
A R2 .16
Control Variables
Site Differences
Team Size
- .01 (.01)
.00 (.01)
A R2 .22
Team Process Variable
Affective Conflict - .39 (.94)
A R2 .07
Moderator Variable
Task Interdependence
.26 (.43)
A R2 .00
Interaction Term
Affective Conflict x Task
Interdependence
.00 (.24)
F
Total R2
** p<.01
8.70**
.45
Table 15: Hierarchical Regression of Manager-rated Team Performance on
Control, Team Process (Affective Conflict), Moderator (Task Interdependence),
and Interaction Term (Affective Conflict x Task Interdependence) Variables
(N=41)
Contribution to R2 Independent Variables
Manager-rated Team
Performance
A R2 .07
Control Variables
Site Differences
Team Size
- .01 (.02)
.00 (.01)
A R2 .06
Team Process Variable
Affective Conflict .78 (2.01)
A R2 .00
Moderator Variable
Task Interdependence
.41 (.82)
A R2 .00
Interaction Term
Affective Conflict x Task
Interdependence
- .26 (.50)
F
Total R2
1.13
.13
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Mediator Effects of Cognitive Conflict
In general, a given variable can be said to mediate between predictor and
outcome variables when (1) the predictor affects the mediator, (2) the mediator
affects the outcome, and (3) the effects of the mediator on the outcome get reduced
for partial mediation and become insignificant for full mediation when the mediator
is added to the association between predictor and outcome (Baron & Kenny, 1986).
Earlier, neither the effects of diversity measures on cognitive conflict (Hypothesis 1)
nor those of cognitive conflict on team performance (Hypothesis 3) were established.
Since these results did not meet the above conditions, further tests related to the
mediator effects of cognitive conflict were therefore not justified.
Mediator Effects of Affective Conflict
It was found that affective conflict had a significant impact on team
performance (Hypothesis 4). However, the effects of diversity measures on affective
conflict (Hypothesis 2) were not established. While the mediator effects on the
outcome were established, the predictor effects on the mediator were not found.
Hence, this study did not examine the mediator effects of affective conflict.
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CHAPTER VI: DISCUSSION
Introduction
The purpose of this study was to have a better understanding of the effects of
demographic diversity on team process and the effects of team process, in turn, on
team performance. Specifically, this study aimed at understanding how conflict as a
team process may shape team performance, because prior research found discrepant
results regarding its association. The present study proposed to distinguish the
emergent state of conflict between team members from its ensuing interactions
within the team process. Thus, it was predicted that the association between conflict
and team performance would be a function of moderator effects. In this chapter, I
will discuss the results presented in the previous chapter, the limitations of the
present study, and the managerial implications for team managers and organizational
leaders.
Demographic Diversity and Team Process
Drawing on a social network perspective (Burt, 2000; Gnyawali &
Madhavan, 2001; McEvily & Zaheer, 1999), Hypothesis 1 predicted that
demographic diversity would have a positive impact on cognitive conflict within the
team. This hypothesis was not supported. One possible explanation may be that
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there was not so high a level of perceived competition between individuals in the
sample as to motivate them to exploit information asymmetry deriving from their
demographic differences. A social network perspective posits that when structural
holes exist between actors deriving from their dissimilar social contacts, they are
likely to take advantage of these holes for various valued organizational resources,
such as by providing different opinions in team discussions. However, this will not
happen if there does not exist a sufficient amount of intense competition between
actors. While this study did not directly assess the levels of perceived interpersonal
competition across teams, they may have influenced this study’s results. Future
scholars could assess the validity of a social network perspective by clarifying the
impact of perceived competition between actors on their levels of motivation to
exploit structural holes. Also, future research could benefit from an understanding of
what will affect such perceptions between individuals within the team. For example,
personality characteristics could shape the member’s perception of competition with
others that may, in turn, affect the levels of their motivation to exploit information
asymmetry deriving from different social contacts. A team of many individualists
may have more perceived interpersonal competition than that of many collectivists
(Chatman & Barsade, 1995).
Drawing on a social identity perspective (Tajfel, 1978; 1981; Tajfel &
Turner, 1986; Turner, 1982 & 1987), Hypothesis 2 predicted a positive association
between demographic diversity and affective conflict within the team. However, the
result did not support this hypothesis. It will not be so simple that social
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categorization can occur automatically at the team settings, as a social identity
perspective postulates. Although previous research in experimental settings (Devine,
1989; Devine et al., 1991) found a human’s innate tendency to categorize others in
terms of social groups, individuals would not do so in the actual teamwork settings
(Brewer & Brown, 1998). Alternative explanation is that since southern California
where all research site are located has a long history of racial diversity, individuals
working in this area may not experience affective conflict associated with it. Future
research might address the situations under which a variety of social categories
become salient to team members and, in turn, have a positive impact on affective
conflict. For example, these effects may vary in terms of the degree of criticalness
and urgency of the task to team members (Rajagopalan et al, 1993). The more
urgent and critical the task is, the more team members will get frustrated with events
that interfere with its achievement and thus have more interpersonal aggression
(Chen & Spector, 1992) in a manner that social categories can serve to polarize
them. Studying the salience and relative influence of demographic characteristics in
conjunction with team’s events over time will provide a deeper insight on the impact
of social categorization within the team.
Team Process and Team Performance
Drawing on the results of laboratory studies using decision-making
techniques such as dialectical inquiry and devil’s advocacy, this field study predicted
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the positive impact of cognitive conflict on team performance (Hypothesis 3).
Nevertheless, like other studies (Ancona & Caldwell, 1992; Glick et al., 1993), this
study did not find such a positive impact. The results of this study are consistent
with Ancona and Caldwell’s (1992) argument that a high level of cognitive conflict
may lead to a low level of team performance because of the confusion different
perspectives create. In other words, when there exists a variety of cognitive
resources, they may impair team performance unless they are elaborated and
managed effectively by team members. When individuals cannot manage cognitive
conflict effectively by themselves, they will divert their attention from team
discussion (March & Olsen, 1979) and feel less responsible for its resulting decision
(Hackman & Oldham, 1976; Salancik, 1977). In turn, these individuals become less
committed to it (Priem et al., 1995), leading to the lower team performance. These
results provide additional evidence that it is very important to clarify the complex
relationship between cognitive conflict and team performance.
Hypothesis 4 predicted a negative impact of affective conflict on team
performance. Regression of member-rated team performance on affective conflict
provided robust support for this hypothesis. The lack of support from regression of
manager-rated team performance may be that, as Table 4 shows, there was on
average a low level of affective conflict (mean =1.84) relative to a high level of
manager’s rating of team performance (mean = 4.03). Unlike the relationship
between cognitive conflict and team performance where laboratory and field studies
found contradictory results, the association between affective conflict and team
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performance appears much straightforward. When affective conflict exists among
team members, they tend to interpret the attitudes and behaviors of others in a
selective manner to confirm the negative view of them. Through the ecology of
inaccurate attributions of each other’s attitudinal and behavioral intentions in a
negative manner, affective conflict is sustained. Thus, affective conflict induces
team members to avoid contact with others with whom they feel uncomfortable and,
in turn, keeps them from coordinating their actions effectively, thus impairing team
performance.
Moderator Effects
In order to have a clearer picture of the complex relationship between
cognitive conflict and team performance, this study explored the effects on team
performance of cognitive conflict interacting with cognitive conflict management
practices. The effects of this interaction were partially consistent with Hypothesis 5.
It was demonstrated that the impact of cognitive conflict on team performance has to
do with the effectiveness of cognitive conflict management practices. For example,
a divergent view is often treated with skepticism by the individuals who share the
common view. In the absence of cognitive conflict management practices that
contain a higher amount of reasoning orientations relative to positional orientations,
a high level of cognitive conflict can create confusion for team members, leading to
the lower team performance. On the other hand, when the team has appropriate
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cognitive conflict management practices, its members can overcome the team
process losses associated with the emergence of a high level of cognitive conflict
(Hackman, 1987). However, this may not lead to better team performance. Thus,
this study contributes to the literature by resolving the discrepant findings regarding
the association between team process and performance in prior research.
Also, this study showed that the impact of a team’s high level of cognitive
conflict management practices on the association between cognitive conflict and
team performance is null. The impact of high cognitive conflict management
practices may vary across different types of tasks. While this study did not assess
the levels of task complexity across teams, they may influence the moderator effects
of high cognitive conflict management practices on the association between
cognitive conflict and team performance. Teams conducting routine tasks may not
reap performance gains from the combination of a high level of cognitive conflict
and a high level of cognitive conflict management practices as may those teams that
are facing more complex tasks. The level of task complexity warrants greater
attention in future research examining the effects of cognitive conflict management
practices.
Unfortunately, this study did not resolve another discrepant finding regarding
the association between team process and performance in prior research. Hypothesis
6 predicted that task interdependence would moderate the negative impact of
affective conflict on team performance, but this study did not find such evidence.
While Macrae and Bodenhausen (2000) called for management scholars to
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empirically examine different types of task design that can trigger stereotype
suppression between individuals and thus lead to better team performance, the results
of this study provide preliminary evidence that task interdependence does not play
such a role. Exploration of other types of task design that can mitigate the negative
effects of affective conflict on team performance warrants greater attention in future
research. On the other hand, the lack of empirical support for Hypothesis 6 may be
the relatively low level of intraclass correlation in the level of task interdependence
in the sample. While the teams in the sample were nearly significantly different
from each other in the level of task interdependence {p = .0557) and team members’
perceptions of the level of task interdependence converged with each other in an
acceptable manner (r = .11), these numbers were lower compared to those of other
team-level measures used in this study, thus pointing out the possibility that task
interdependence might have suffered from a measurement problem to some extent.
By investigating teams whose intraclass correlation in the level of task
interdependence is higher, future researchers could gain more reliable results
regarding the moderator impact of task interdependence on the association between
affective conflict and team performance.
Mediator Effects
Previously, two studies (Jehn et al., 1999; Pelled et al., 1999) assessed the
mediator effects of cognitive and affective conflict on team performance by
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including conflict as a team process into the theoretical model. While Jehn et al’s
(1999) study supported both of these effects, Pelled et al. (1999) found no evidence
that either cognitive or affective conflict mediates the association between
demographic diversity and team performance. Like Pelled et al.’s (1999) study, the
mediator effects were not present in this study. The lack of these mediator effects
may have stemmed in part from the absence of the direct effects of demographic
diversity on team performance, nevertheless this study could not test it. Although
this study provides additional evidence for the lack of mediator effects of conflict on
team performance, a firm conclusion needs more research.
Study Limitations
The major contribution of this study was to demonstrate that an increased
amount of cognitive conflict does not automatically translate into better team
performance, depending on cognitive conflict management practices. However,
additional research is needed to refine and extend the results of this study. First,
since this study’s sample was not randomly selected but conveniently identified by a
contact person of participating organizations, it may have suffered a biased selection
that in turn affects the results of analysis. Next, this study demonstrated the
important role of cognitive conflict management practices but did not examine any
antecedents associated with it. For example, members’ prior experiences in different
organizations and industries may affect their attitudes toward others in the exchange
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of cognitive disagreements over different aspects of the task. When appropriate
training for these practices are provided in the organization, a team’s ability to
manage cognitive conflict could improve. Also, a longitudinal study could help to
provide deeper insight on the emergence and development of cognitive conflict
management practices over time. Chatman and Flynn (2001) examined how
cooperative norms in work teams developed over time. Likewise, future scholars
might address how and when (in which developmental stage) team’s cognitive
conflict management practices are formed, and whether they have lasting impacts or
can be shaped by the new entry of influential members into the team or by different
managerial styles in leading team discussions (Gersick, 1988).
Due to the lack of an objective measure of team performance that could be
applicable to the variety of participating teams, this study used subjective
performance ratings that may suffer from the tendency of some participants to
always mark categories in the middle of or the extremes of the scale in their ratings
(Pedhazur & Schmelkin, 1991). Managers’ ratings of team performance (mean =
4.03) may have reflected a tendency to rate performance highly. Future researchers
could overcome this problem by conducting a study of the same type of team in a
single organization where the same objective measure of performance would be
applicable to all teams in the sample. On the other hand, such a study may risk
unduly limiting its generalizability across different types of teams and organizations.
Thus, future research must weigh the merits of generalizability deriving from the
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inclusion of various types of teams and organizations, as in this study, against the
weakness due to subjective performance ratings.
Finally, while the sample size of this study is comparable with other field
studies published in major management journals, future investigation of a larger
sample will enable an assessment of the validity of this study’s results. Although the
survey questionnaires included several other measures, they were not included in the
analyses because of the limited size of this study’s sample. Future investigation of a
larger sample will justify the inclusion of these measures into the multivariate
analysis.
Managerial Implications
Despite its limitations, this study extends previous research though its
assessment of moderator effects on team process and has several implications for
team managers and organizational leaders. First, they do not have to be very
concerned about team members’ demographic characteristics such as organizational
tenure and racial diversity because these characteristics do not have a significant
impact on team process.
However, the effects of team process on performance need to be carefully
addressed. Unlike the results of laboratory studies, the presence of disagreements
among team members over various aspects of the task does not automatically
translate into better team performance. On the contrary, its impact can even be
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negative. However, when the team is good at elaborating and managing cognitive
conflict in a well-reasoned manner, its negative effects are mitigated. Regardless of
the amount of cognitive conflict the team is experiencing, it is important that the
organization develops appropriate cognitive conflict management practices though
hir ing and training.
Next, while affective conflict can have a negative impact on team
performance, this study’s findings do not suggest that by changing the task design
into a high level of task interdependence it may possible to mitigate the negative
effects of affective conflict on team performance. As Schneider (1987) noted, if
personality characteristics constitute the basis of affective conflict, team managers
and organizational leaders may reduce its negative impact on team performance by
recruiting the persons of certain personality characteristic. For example, the persons
of high self-monitoring who can anticipate others’ reactions and adjust their feelings
and behaviors accordingly may monitor and control the images of self that they
project to others in social situations (Snyder, Berscheid, & Matwychunk, 1988).
These high self-monitoring persons will be more likely to not only restrain the
expression of their negative affect and but also willing and able to tailor and fashion
of their images while working with others (Snyder and Copeland, 1989). In turn,
high self-monitors will induce coworkers to form more positive impressions of them
(Snyder, 1987), thereby leading to the weakened negative emotions among
coworkers. Consistent with these arguments, Flynn, Chatman, and Spataro (2001)
provided the evidence that self-monitoring moderates the negative effects of negative
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emotions associated with demographic dissimilarity between individuals on
individual performance. The personality characteristics may be another important
dimension to consider when recruiting new members for the successful team.
In sum, this study demonstrates the importance for team managers and
organizational leaders to direct their attention to team process rather than
demographic diversity. While strategic human resource management advocates
increasing demographic diversity among individuals within a team to broaden the
bases of informational and knowledge resources, demographic diversity itself does
not necessarily affect the level of team’s cognitive resources. Instead, while it is still
highly crucial to understand the antecedents to the variety of cognitive resources,
they should pay more attention to how an emergent state of cognitive conflict will
unfold through team members’ interactions.
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Appendix 1: Information Sheet for Non-Medical Research
University of Southern California
School of Policy, Planning, and Development
INFORMATION SHEET FOR NON-MEDICAL RESEARCH
Research Title: Work Team Diversity and its Impacts: Assessing Mediating
Role of Intrateam Process and Moderating Roles of Cognitive Conflict
Management Practices and Task Interdependence
You are asked to participate in a research study conducted by Professors Peter
Robertson, Ph.D. and Robert Myrtle, D.P.A., and doctoral candidate Nobuyuki
Ainoya, M.P.A. from the School of Policy, Planning, and Development at the
University of Southern California. Results of this study will be contributed to a
doctoral dissertation submitted by Nobuyuki Ainoya to School of Policy, Planning,
and Development and the Committee on Graduate Studies of University of Southern
California. You were selected as a possible participant in this study because you are
a member of teams that will vary in terms of measurements in this study. A total of
300-400 subjects will be selected from 50 teams to participate. Your participation is
voluntary.
We are asking you to take part in a research study because we are trying to learn
more about the effects of work team composition on its dynamics and performance.
The results should be useful in determining how the work team can be made more
effective.
Completion and return of the questionnaire or response to the interview
questions will constitute consent to participate in this research project.
You will be asked to fill out a questionnaire that will take approximately 30 minutes.
In each section of the questionnaire, you will be given specific instructions. Some of
the questions will seem repetitive. This is not to test you; rather, it is a method that
researchers use to measure opinions more effectively. Please carefully and honestly
answer each question.
This study assumes no reasonable foreseeable risks, discomforts, and inconveniences
for its participants.
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Results of this study’s analysis and their implications for team management will be
made available to the members of teams, team managers and other organizational
leaders as appropriate. Researchers also will be available to assist in the
interpretation of these results. Further, this study will be contributed to a theoretical
understanding of and practical implications for team management in organizational
settings.
The research participant will not be paid or offered other benefits for participation in
this study.
Any information that is obtained in connection with this study and that can be
identified with you and your team will remain confidential and will be disclosed only
with your and all of you team members’ permissions or as required by law.
When the results of the research are published or discussed in conferences, no
information will be included that would reveal your and your team’s identities.
All responses will be identified by codes linked to research participants’ identity by
separate key code. No one at your organization will have access to responses and
codes as well that are stored in a password-protected computer. Only investigators
will have access to them. All of the processing and analysis of responses will be
done at the University of Southern California.
You can choose whether to be in this study or not. If you volunteer to be in this
study, you may withdraw at any time without consequences of any kind. You may
also refuse to answer any questions you don’t want to answer and still remain in the
study. The investigator may withdraw you from this research if circumstances arise
which warrant doing so.
If you have any questions or concerns about the research, please feel free to contact
Nobuyuki Ainoya at (323) 663-5827, 2031 Dracena Dr. 319, Los Angeles, CA
90027, or Peter Robertson at (213) 740-0353, RGL 222, Los Angeles, CA 90089-
0626.
You may withdraw your consent at any time and discontinue participation without
penalty. You are not waiving any legal claims, rights or remedies because of your
participation in this research study. If you have questions regarding your rights as a
research subject, contact the University Park IRB, Office of the Vice Provost for
Research, Bovard Administration Building, Room 300, Los Angeles, CA 90089-
4019, (213) 740-6709 or upiib@usc.edu.
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Appendix 2: Team Member Questionnaire
Team Member Questionnaire Code Number
Section I
For items 1 thru 8, please circle the number that corresponds to your response to each
statement as it applies to your team.
none
1. To what extent are there differences
of opinion in your team?
2. How much tension is there among
the members of your team?
3. How often do the members of your
team disagree about how things should
be done?
4. How often do people get angry while
working in your team?
5. How often do the members of
your team disagree about which procedure
should be used to do your work?
6. How much jealousy or rivalry is there
among the members of your team?
7. To what extent are the arguments in
your team task-related?
8. How much are personality clashes
evident in your team?
little
2
moderate
3
a lot
4
very much
5
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Code Number
For items 9 thru 18, please circle the number that indicates the extent to which
you agree or disagree with the statement as an accurate description of
your team’s discussion.
strongly disagree neither agree strongly
disagree agree nor agree
disagree
9. Members often add related information 1 2 3 4 5
or knowledge to the facts and opinions
that were initially introduced by someone
in our team.
10. Members often repeat statements
or questions in discussions. 1 2 3 4 5
11. Members work to clarify disagreeing 1 2 3 4 5
points or confused arguments in discussions.
12. Members often get defensive 1 2 3 4 5
in their arguments.
13. In discussions, members often explore 1 2 3 4 5
reasons for the team’s conclusions,
judgments, or inferences.
14. Members tend to stick to 1 2 3 4 5
their opinions in discussions.
15. Members clarify the conditions and 1 2 3 4 5
assumptions behind each other’s arguments.
16. Members are unnecessarily assertive 1 2 3 4 5
in discussions.
17. Members often provide examples 1 2 3 4 5
in order to explain their opinions.
18. Members do not really respond to 1 2 3 4 5
each other’s arguments in discussions.
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Code Number
For items 19 thru 26, please circle the number that corresponds to your response to
each statement as it applies to your work situations.
very moderately accurate moderately very
inaccurate inaccurate accurate accurate
1 9 .1 work closely with other 1 2 3 4 5
members in doing my work.
2 0 .1 frequently must coordinate 1 2 3 4 5
my efforts with other members.
21. My own performance is dependent 1
on receiving accurate information
from other members.
22. The way 1 perform my job has 1
a significant impact on other members.
23. My work requires me to consult 1
with other members fairly frequently.
2 4 .1 work fairly independently of 1
other members in my team.
2 5 .1 can plan my own work with 1
little need to coordinate with
other members.
2 6 .1 rarely have to obtain information 1 2 3 4 5
from other members to complete
my work.
For items 27 thru 29, please circle the number that corresponds to your response to
each statement as it applies to you.
2 7 .1 prefer to work with others in 1
my work team rather than working alone.
28. Given a choice, I would rather do 1
a job where I can work alone than do
a job where I have to work with others.
2 9 .1 like it when members of my 1
work team do things on their own,
rather than working with others all time.
2 3 4 5
2 3 4 5
2 3 4 5
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Code Number
For items 30 thru 35, please circle the number that indicates the extent to which
you agree or disagree with each statement as an accurate description
of your team’s performance.
strongly disagree
disagree
neither agree
agree nor
disagree
strongly
agree
30. Our team functions very efficiently. 1
31. The quality of service that our team 1
produces is very high.
2
2
4
4
32. Our team usually meets or exceeds 1
customers’/clients’/patients’ expectations.
33. Critical quality errors occur
frequently in our team’s work.
1
34. Our team introduces many
innovations or new ideas.
35. Our team usually adheres
to schedules.
Sections II
As is explicitly written in the attached “Information Sheet for Non-Medical
Research”, any information that is obtained in connection with this study and
that can be identified with you and your team will be kept confidential.
1. Are you - (please circle one)?
[1] female
[2] male
2. What is your educational level? (please indicate highest level completed)
[1] did not graduate from high school
[2] graduated from high school or G.E.D.
[3] some college or technical training beyond high school (1-3) years
[4] graduated from college (B.A., B.S., or other bachelor degree)
[5] some graduate school (but no graduate degree)
[6] master degree
[7] doctor degree
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3. When did you first begin work at this organization?
month year
4. When did you first join your present team?
month year
5. If you happen to know, please state approximately when your present team was formed?
month year
6. How often does your present team have a meeting? (please select one and specify)
[1] approximately every___ week
[2] approximately every___month
7. What is the percentage of your attendance at these meetings?
approximately percentage
8. How many different teams other than your present team are you a members of in this
organization?
team(s)
9. The position in my present team is - (please circle one)
[1] nurse
[2] nurse attendant
[3] physician or surgeon
[4] therapist
[5] administrative staff
[6] technologist or technician
[7] secretary or clerk
[8] other (My position i s _______ .)
10. How old are you?
11. Are you - (please circle one)?
[1] Black/African-American
[2] Asian and Pacific-Islander/Asian-American
[3] American Indian/Alaska Native
[4] Latino/Hispanic-American
[5] White/Caucasian-American
[6] Other (i.e., multi-racial)
129
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Appendix 3: Manger/Leader Questionnaire
Manager/Leader Questionnaire Code Number.
For items 1 thru 6, please circle the number that corresponds to your response to
each statement as it applies to your rating of
_______________ team performance.
strongly disagree neither agree
disagree agree nor
disagree
strongly
agree
1. This team functions very efficiently. 1
2. The quality of service that this team 1
produces is very high.
2
2
4
4
3. This team usually meets or exceeds 1
customers’/clients’/patients’ expectations.
4. Critical quality errors occur
frequently in this team’s work.
1
5. This team introduces many
innovations or new ideas.
6. This team usually adheres
to schedules.
130
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

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Asset Metadata

Creator Ainoya, Nobuyuki (author)

Core Title Demographic diversity, team process, and team performance: Assessing moderator effects of cognitive conflict management practices and task interdependence

School Graduate School

Degree Doctor of Philosophy

Degree Program Public Administration

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag business administration, management,OAI-PMH Harvest

Language English

Contributor Digitized by ProQuest (provenance)

Advisor Myrtle, Robert (committee chair), Robertson, Peter J. (committee chair), Salcido, Ramon (committee member)

Permanent Link (DOI) https://doi.org/10.25549/usctheses-c16-503704

Unique identifier UC11335952

Identifier 3140427.pdf (filename),usctheses-c16-503704 (legacy record id)

Legacy Identifier 3140427.pdf

Dmrecord 503704

Document Type Dissertation

Rights Ainoya, Nobuyuki

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA