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Since the meta-analysis by De Dreu and Weingart (2003b) on the effects of intragroup conflict on group outcomes, more than 80 new empirical studies of conflict have been conducted, often investigating more complex, moderated relationships between conflict and group outcomes, as well as new types of intragroup conflict, such as process conflict. To explore the trends in this new body of literature, we conducted a meta-analysis of 116 empirical studies of intragroup conflict (n = 8,880 groups) and its relationship with group outcomes. To address the heterogeneity across the studies included in the meta-analysis, we also investigated a number of moderating variables. Stable negative relationships were found between relationship and process conflict and group outcomes. In contrast to the results of De Dreu and Weingart, we did not find a strong and negative association between task conflict and group performance. Analyses of main effects as well as moderator analyses revealed a more complex picture. Task conflict and group performance were more positively related among studies where the association between task and relationship conflict was relatively weak, in studies conducted among top management teams rather than non-top management teams, and in studies where performance was measured in terms of financial performance or decision quality rather than overall performance.
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The Paradox of Intragroup Conflict: A Meta-Analysis
Frank R. C. de Wit
Leiden University
Lindred L. Greer
University of Amsterdam
Karen A. Jehn
University of Melbourne
Since the meta-analysis by De Dreu and Weingart (2003b) on the effects of intragroup conflict on group
outcomes, more than 80 new empirical studies of conflict have been conducted, often investigating more
complex, moderated relationships between conflict and group outcomes, as well as new types of
intragroup conflict, such as process conflict. To explore the trends in this new body of literature, we
conducted a meta-analysis of 116 empirical studies of intragroup conflict (n8,880 groups) and its
relationship with group outcomes. To address the heterogeneity across the studies included in the
meta-analysis, we also investigated a number of moderating variables. Stable negative relationships were
found between relationship and process conflict and group outcomes. In contrast to the results of De Dreu
and Weingart, we did not find a strong and negative association between task conflict and group
performance. Analyses of main effects as well as moderator analyses revealed a more complex picture.
Task conflict and group performance were more positively related among studies where the association
between task and relationship conflict was relatively weak, in studies conducted among top management
teams rather than non–top management teams, and in studies where performance was measured in terms
of financial performance or decision quality rather than overall performance.
Keywords: task conflict, relationship conflict, process conflict, group performance, group viability
Supplemental materials: http://dx.doi.org/10.1037/a0024844.supp
In response to the broader deployment of groups in organiza-
tions, a large stream of research has emerged on the consequences
of intragroup conflicts for group outcomes. Intragroup conflict can
broadly be defined as the process emerging from perceived incom-
patibilities or differences among group members (De Dreu &
Gelfand, 2008). Past work first distinguished two forms of intra-
group conflict: relationship conflict and task conflict (e.g., Ama-
son, 1996; Guetzkow & Gyr, 1954; Jehn, 1994), and later evidence
has been found for a third type of conflict: process conflict (e.g.,
Jehn, Northcraft, & Neale, 1999). Relationship conflicts involve
disagreements among group members about interpersonal issues,
such as personality differences or differences in norms and values.
Task conflicts entail disagreements among group members about
the content and outcomes of the task being performed, whereas
process conflicts are disagreements among group members about
the logistics of task accomplishment, such as the delegation of
tasks and responsibilities (Jehn & Bendersky, 2003).
Organizational scholars traditionally thought of intragroup
conflicts as a hindrance to effective group functioning (Argyris,
1962; Blake & Mouton, 1984; Pondy, 1967). However, initial
research began to suggest that conflicts between group mem-
bers may not always have to be detrimental for group outcomes
(e.g., Amason, 1996; Eisenhardt & Schoonhoven, 1990; Jehn,
1995, 1997; Van de Vliert & De Dreu, 1994). Task-related
conflicts, for example, may facilitate innovativeness and supe-
rior group decision making because they prevent premature
consensus and stimulate more critical thinking (e.g., Amason,
1996; Jehn, 1995; Pelled, Eisenhardt, & Xin, 1999; Tjosvold,
2008; Van de Vliert & De Dreu, 1994). A meta-analysis by De
Dreu and Weingart (2003b) of 30 empirical studies of intra-
group conflict revealed, however, that both task conflict and
relationship conflict generally have a negative effect on group
outcomes. To reconcile this past meta-analytic finding with past
assumptions of the value of intragroup conflict, a range of
studies have been conducted in recent years to better understand
the circumstances under which intragroup conflicts, and task
conflicts in particular, may either benefit or inhibit group out-
comes (e.g., Bayazit & Mannix, 2003; De Dreu, 2006; Gamero,
Gonza´lez-Roma´, & Peiro´, 2008; Goncalo, Polman, & Maslach,
2010; Langfred, 2007; Mannes, 2009; Mohammed & Angell,
This article was published Online First August 15, 2011.
Frank R. C. de Wit, Institute for Psychological Research, Leiden University,
Leiden, the Netherlands; Lindred L. Greer, Work and Organizational Psychol-
ogy, University of Amsterdam, Amsterdam, the Netherlands; Karen A. Jehn,
Melbourne Business School, University of Melbourne, Melbourne, Victoria,
Australia.
We would like to thank Gerdien de Vries for her assistance with data
collection. We thank Mike Cheung and Conor Dolan for their valuable
assistance with the data analyses and thank Steve Kozlowski, Carsten De
Dreu, Nailah Ayub, Astrid Homan, and Joyce Rupert for their valuable
comments and suggestions on earlier drafts of the manuscript.
Correspondence concerning this article should be addressed to Frank
R. C. de Wit, Leiden University, Institute for Psychological Research, P.O.
Box 9555, 2300 RB Leiden, the Netherlands. E-mail: FWit@fsw
.leidenuniv.nl
Journal of Applied Psychology © 2011 American Psychological Association
2012, Vol. 97, No. 2, 360–390 0021-9010/12/$12.00 DOI: 10.1037/a0024844
360
2004; Olson, Parayitam, & Bao, 2007; Parayitam & Dooley,
2007; Rispens, Greer, & Jehn, 2007; Tekleab, Quigley, &
Tesluk, 2009; Wilkens & London, 2006).
In the current study, we utilize this new wave of studies focusing
on more complex, moderated relationships between conflict and
group outcomes to provide an updated, expanded and yet more
fine-grained meta-analysis of the intragroup conflict literature than
the De Dreu and Weingart (2003b) meta-analysis. The purpose of
the current meta-analysis is to examine the impact of relationship,
task, and process conflict on proximal group outcomes (i.e., emer-
gent states, such as trust, and group viability, such as group
member satisfaction and group member commitment) and distal
group outcomes (i.e., group performance) as moderated by differ-
ences between studies in terms of context (e.g., task type or
cultural context) and methodology (e.g., the way in which perfor-
mance was measured; see also Figure 1).
The current meta-analysis extends earlier assessments of the
intragroup conflict literature in six ways. First, since the July 2001
cutoff for articles included in the meta-analysis by De Dreu and
Weingart (2003b), the number of studies available on intragroup
conflict has tripled. The current study includes 116 studies (484
effect sizes) compared to the 30 studies (78 effect sizes) included
in the De Dreu and Weingart (2003b) meta-analysis. Second, we
expand on earlier reviews and meta-analyses by examining a
broader array of possible moderators. This is line with both meta-
analytic theory (Hunter & Schmidt, 2004) and conflict theory (e.g.,
De Dreu, 2008; De Dreu & Weingart, 2003a; Jehn & Bendersky,
2003), which both suggest that the heterogeneity in research find-
ings demands a contingency approach to better understand the
effects of intragroup conflict on group outcomes. Third, in addition
to examining categorical moderators individually (see also De
Dreu & Weingart, 2003b), we also perform weighted least squares
multiple regression analyses (cf. Lipsey & Wilson, 2001) to gain
better insight into the contribution of specific moderators to effect-
size variability and to test the influence of continuous moderators
(Steel & Kammeyer-Mueller, 2002). Fourth, in addition to task and
relationship conflicts, we also provide a first meta-analysis of the
effects of process conflict on group outcomes. Process conflict was
not included in the initial meta-analysis of De Dreu and Weingart
(2003b) but has generated a substantial body of research in recent
years. Fifth, we use meta-analytic structural equation modeling
(MASEM) to test the incremental relationships between task,
relationship, and process conflict with group outcomes. Finally, to
enable a more general comparison of the effects of conflict on
proximal group outcomes and distal group outcomes (i.e., group
performance), we expand on the work of De Dreu and Weingart
(2003b) by examining the relationships between intragroup con-
flict and a wider array of proximal outcomes (i.e., emergent states,
such as trust and cohesion, and group viability, such as commit-
ment and affect; Hackman & Wageman, 2005; Marks, Mathieu, &
Zaccaro, 2001).
The Effects of Intragroup Conflict on Group
Outcomes
Past research has examined the effects of the three conflict types
(task, relationship, and process) on a variety of group outcomes,
ranging from team cohesion to task performance. The effects of the
three types of intragroup conflict may differ across different out-
come categories. Therefore, when examining the effects of intra-
group conflicts on group outcomes, we distinguish between two
types of outcomes: distal group outcomes and more proximal
group outcomes. In terms of distal group outcomes, we focus on
group performance, which includes outcomes such as innovation,
productivity, and effectiveness (Ancona & Caldwell, 1992; Van
der Vegt & Bunderson, 2005). In terms of more proximal group
outcomes, we focus on group emergent states and group viability.
Group emergent states include the cognitive, motivational, and
affective states of groups, such as intragroup trust or cohesion
(Marks et al., 2001). Group viability is a broad, group-level con-
Figure 1. A conflict– outcome moderated model.
361
INTRAGROUP CONFLICT META-ANALYSIS
struct that reflects group member affect and behavioral intentions
and is represented by group members’ intention to remain working
in the group as well as group member satisfaction and commitment
(Balkundi & Harrison, 2006; Barrick, Stewart, Neubert, & Mount,
1998; Hackman & Wageman, 2005). We suggest that the relationship
between conflict and both types of proximal outcomes (emergent
states and group viability) is equivalent and generally more negative
than that between conflict and distal group outcomes (group perfor-
mance). For instance, a task conflict may have a positive effect on a
more distal group outcome, such as group performance, through
a more critical evaluation of viewpoints and more educated decision
making, yet at the same time, the task conflict may hurt more prox-
imal group outcomes, such as trust within the group and group
member satisfaction. This latter effect is especially likely when group
members interpret their group members’ diverging viewpoints as a
negative assessment of their own abilities and competencies (e.g.,
Swann, Polzer, Seyle, & Ko, 2004). We elaborate in more detail
below on the effects of each of the three types of intragroup conflict
on both proximal and distal group outcomes.
Task Conflict
Past theory and research often suggested that task conflict has
the potential to benefit a broad variety of group outcomes (e.g.,
Amason, 1996; Jehn, 1995). However, much research has found
task conflict to impair both proximal and distal group outcomes
(De Dreu & Weingart, 2003b; Hinds & Mortensen, 2005; Lau &
Murnighan, 2005; Raver & Gelfand, 2005). The negative effects of
task conflict on proximal outcomes, such as satisfaction, can be
explained by self-verification theory (Swann et al., 2004), which
suggests that group members become dissatisfied when they in-
terpret challenges of their viewpoints by other group members as
a negative assessment of their own abilities and competencies.
This, for instance, can cause people to ruminate and experience
stress as a result of task conflict (cf. Dijkstra, Van Dierendonck, &
Evers, 2005; Yang & Mossholder, 2004). The findings of the
negative effects of task conflict on more distal group outcomes,
such as group performance, support the information-processing
perspective (e.g., Carnevale & Probst, 1998), which suggests that
task conflicts are a distraction and require resources that cannot be
directly invested into task performance. As task conflict increases
cognitive load, it also interferes with effective cognitive processes
(e.g., Carnevale & Probst, 1998) and may result in narrow, black-
and-white thinking and, thereby, obstruct distal group outcomes,
such as group effectiveness, creativity, and decision making (De
Dreu, 2008).
On the positive side, task conflicts often have been suggested to
potentially benefit group outcomes and distal group outcomes,
such as group performance, in particular (e.g., Amason, 1996;
Jehn, 1995; Olson et al., 2007). A main benefit of task conflict for
groups and their members is thought to be an increased under-
standing of the task at hand and a more critical evaluation of each
other’s ideas (Amason, Thompson, Hochwater, & Harrison, 1995;
Nemeth, 1995). In this way, task conflict may benefit distal group
outcomes, such as by overcoming confirmatory biases in group
decision making (e.g., Schulz-Hardt, Brodbeck, Mojzisch, Kersch-
reiter, & Frey, 2006; Schweiger, Sandberg, & Rechner, 1989;
Schwenk, 1990) and enhancing innovation (e.g., De Dreu, 2006;
De Dreu & West, 2001). Additionally, task conflict may benefit
proximal group outcomes. As a task conflict facilitates group
members to voice their own perspective of the task at hand (e.g.,
Simons & Peterson, 2000), task conflict may be positive for task
commitment and member satisfaction (Behfar, Mannix, Peterson,
& Trochim, 2011).
Relationship Conflict
Relationship conflicts have generally been found to have large
negative effects on both proximal and distal group outcomes (cf.
Amason, 1996; Jehn, 1995). Disagreements about personal issues
heighten member anxiety (Dijkstra et al., 2005) and often represent
ego threats because the issues central to these conflicts are strongly
intertwined with the self-concept. This ego threat (Baumeister,
1998) often increases hostility among group members, which, in
turn, makes these conflicts more difficult to manage (De Dreu &
Van Knippenberg, 2005) and more likely to negatively affect
proximal group outcomes, such as identification or trust (e.g.,
Jehn, Greer, Levine, & Szulanski, 2008; Polzer, Milton, & Swann,
2002; Rispens, Greer, & Jehn, 2007) and member commitment or
turnover intentions (e.g., Bayazit & Mannix, 2003; Conlon & Jehn,
2007; Elron, 1997; Raver & Gelfand, 2005). Relationship conflicts
also tend to impair more distal group outcomes. Specifically,
relationship conflicts can harm group performance because they
reduce collaborative problem solving (De Dreu, 2006) and because
the time group members spend responding to non-task-related
issues could be spent more efficiently on task accomplishment
(Evan, 1965). In support of this, relationship conflicts have often
been found to harm distal group outcomes, such as group creativity
(e.g., Farh, Lee, & Farh, 2010) and group performance (e.g., Brief
& Weiss, 2002; Carnevale & Probst, 1998; De Dreu & Weingart,
2003b; Jehn, 1997; Staw, Sandelands, & Dutton, 1981).
However, research has suggested that the negative effects of
these conflicts on both proximal and distal group outcomes can be
reduced under certain conditions (e.g., Rispens, Greer, Jehn, &
Thatcher, in press). For example, recent research has begun to
identify the conditions under which relationship conflict may be less
likely to negatively affect both proximal and distal group outcomes,
such as when members employ effective conflict management strat-
egies (e.g., De Dreu & Van Vianen, 2001; Jehn, 1997; Murnighan &
Conlon, 1991; Tekleab et al., 2009) or have low emotionality sur-
rounding relationship conflicts (e.g., Jehn et al., 2008).
Process Conflict
A growing line of research has demonstrated a predominantly
negative association between process conflict and both proximal
and distal group outcomes (e.g., Behfar, Mannix, Peterson, &
Trochim, 2002; Greer & Jehn, 2007; Jehn et al., 2008; Matsuo,
2006; Passos & Caetano, 2005; Vodosek, 2007). The negative
effects of process conflict on group outcomes are thought to occur
because the issues at the heart of process conflicts, such as task
delegation or role assignment, often carry personal connotations in
terms of implied capabilities or respect within the group (cf. Jehn
& Bendersky, 2003). For example, when a process conflict arises
over the delegation of tasks, members who disagree with their task
assignments may feel the task is below them and feel that being
assigned the task is a personal insult. In this way, process conflicts
may become highly personal (cf. Greer & Jehn, 2007) and may
362 DE WIT, GREER, AND JEHN
have long-term negative effects on group functioning (Greer, Jehn,
& Mannix, 2008). Process conflicts, for instance, may harm the
quality of emergent states and group viability (e.g., Jehn et al.,
1999; Thatcher, Jehn, & Zanutto, 2003; Vodosek, 2007) and
distract members from task accomplishment (Jehn, 1995), thereby
negatively impacting both proximal and distal group outcomes.
However, there is reason to believe that under certain circum-
stances, process conflicts might be less likely to hinder group
performance (e.g., Behfar et al., 2011). For example, disagree-
ments about who is responsible for what and how things should
proceed might facilitate crucial reevaluations of processes, stan-
dards, and task and resource assignments, which may even im-
prove group outcomes (e.g., Jehn & Mannix, 2001) and distal
group outcomes, such as group performance, in particular. Recent
research has begun to examine potential moderating effects of
process conflict and has found that the negative effects of process
conflict on more proximal group outcomes, such as trust or neg-
ative affect, may be reduced when members can effectively resolve
their process conflicts (Jehn et al., 2008) or when members per-
ceive the process conflict as being about actual process improve-
ments and not other members trying to obstruct them (Greer &
Jehn, 2007). Additionally, process conflict may be more advanta-
geous at the start of group project, when the group is still in the
preparation stage and can still benefit from the examination of
different alternatives to complete the task (Goncalo et al., 2010).
Differences Among Conflict Types and Group
Outcomes
Taken together, past theory and research suggest that all forms
of conflict may have a negative effect on group outcomes (De
Dreu & Weingart, 2003b) and proximal outcomes in particular but
that this negative effect can be reduced and even reversed under
certain conditions. Additionally, differences may exist between the
different conflict types in the magnitude of these effects. Specifi-
cally, past research suggests that the effect of task conflict on both
proximal and distal group outcomes may be less negative than that
of relationship or process conflict. Task conflicts are less closely
associated with negative emotions than the other conflict types
(Jehn et al., 2008) and tend to carry fewer personal connotations
(cf. Greer & Jehn, 2007). Compared to relationship and process
conflicts, task conflicts have been to found to be less negatively
related to more proximal group outcomes, such as groups’ affec-
tive climate (i.e., as moods shared by team members; Gamero et
al., 2008) and group members’ satisfaction and intentions to re-
main working in a group (Bayazit & Mannix, 2003; De Dreu &
Weingart, 2003b). For example, Thatcher, Jehn, and Chadwick
(2007) found that with respect to group member morale (i.e., the
degree to which individuals felt satisfied and committed about the
group interactions), task conflict did not appear to have the ex-
pected negative relationship, whereas both process and relation-
ship conflict did. This suggests that the bivariate relationship
between task conflict and proximal group outcomes may not be as
negative as that between relationship or process conflicts and
proximal group outcomes.
Similarly, task conflicts, compared to process and relationship
conflicts, are the least likely to negatively affect more distal group
outcomes. This is because task conflicts, as compared to process
and relationship conflicts, are the conflicts most directly related to
the task at hand. Task conflicts are therefore the most likely to
facilitate a crucial reevaluation of initial viewpoints, which can
result in improved distal group outcomes, such as group perfor-
mance (e.g., Amason, 1996). This implies that the potential for
conflicts to be less negative and even positive for distal group
outcomes is stronger for task conflicts than for process and rela-
tionship conflicts (see also Figure 1).
A Contingency Approach in Understanding the Effects
of Intragroup Conflict
To address potential differences between different types of
conflict and group outcomes, we apply a contingency framework
in this meta-analysis in which the effects of conflict are proposed
to depend on the type of conflict, the type of outcomes, and the
presence of critical moderating variables (cf. Jehn & Bendersky,
2003; see also Figure 1). On the basis of past theory and research,
we have identified two categories of critical moderating variables:
contextual characteristics and methodological characteristics. We
discuss in the following section the theoretical rationale underlying
the role of study contextual characteristics in determining the
effects of conflict on both proximal and distal group outcomes and
discuss in our Method section the methodological characteristics
that may have also influenced the effects of conflict on proximal
and distal group outcomes in past research.
Co-Occurrence of Conflict Types
The first critical contextual moderating variable we focus on is
the co-occurrence of conflict types across different studies. Task
conflict, for example, is suggested to be more positively related to
group outcomes when it does not co-occur with relationship con-
flicts (e.g., Eisenhardt, Kahwajy, & Bourgeois, 1997; Gamero et
al., 2008; Mooney, Holahan, & Amason, 2007). In contrast, when
task conflicts are paired with relationship conflicts, the hostilities
that characterize relationship conflicts (cf. Jehn, 1995; Jehn &
Bendersky, 2003) may prevent any positive effects of task conflict
from emerging (e.g., Amason & Sapienza, 1997; Mooney et al.,
2007; Pelled, 1996; Simons & Peterson, 2000; Yang & Mossh-
older, 2004). Eisenhardt et al. (1997), for example, found that
firms with top management teams that had high task conflict
without interpersonal hostilities outperformed firms that either
lacked conflict completely or were characterized by high levels of
relationship conflict. Similarly, De Dreu and Weingart (2003b)
found that task conflict and group performance were less nega-
tively associated among studies where task and relationship con-
flict were weakly rather than strongly correlated.
We also expect task conflict to be more negatively related to
group outcomes when it co-occurs with process conflicts. The
additional time that is lost in resolving process-related issues may
facilitate more negative effects of task conflicts on both proximal
and distal group outcomes. In addition, due to reduced conflict
resolution efficacy, the negative effects of process conflicts are
likely to become augmented when group members simultaneously
experience task conflicts and/or, especially, relationship conflicts
(e.g., Jehn et al., 2008). Behfar et al. (2011), for example, found
that people-related process conflicts tended to significantly reduce
group viability through lower group member satisfaction.
363
INTRAGROUP CONFLICT META-ANALYSIS
Task Type
The second moderating variable we investigate is task type. We
propose that structural aspects of the group context, such as the
specific task at hand, may determine the extent to which intragroup
conflict and task conflict in particular will be disruptive for group
outcomes (e.g., Jehn et al., 1999; McGrath, 1984). In line with De
Dreu and Weingart (2003b), we build on McGrath’s (1984) task
circumplex to distinguish four types of tasks: (a) creativity tasks,
which require idea generation, innovation, research, and/or devel-
opment of new ideas, services, or products; (b) decision-making
tasks, which involve tasks where group members need to reach
consensus about a certain solution but where there is no demon-
strable right answer; (c) production tasks, which involve routine
tasks that require overt physical and/or intellectual task execution
and where individuals strive to meet certain standards; and (d)
project tasks, which involve tasks that are concerned with problem
solving and generating plans.
Theories of requisite variety (Ashby, 1956) and information
processing (Galbraith, 1973; Tushman & Nadler, 1978) suggest
that the amount of disagreement should match the type of the task.
When the group task is to generate new ideas or to find solutions
to a problem without a demonstrable best solution, groups need to
derive multifaceted solutions that may be best found through
disagreement and opinion variety (e.g., Jehn, 1995). In contrast,
routine tasks and other simple tasks (together labeled as production
tasks; McGrath, 1984) demand simple solutions found without
disagreement. Hence, when a task is well understood and relatively
straightforward, debates about the task or specific process will be
counterproductive and interfere with group functioning (e.g., Glad-
stein, 1984; Jehn et al., 1999) and, thereby, distal group outcomes.
Thus, production tasks such as assembly line work may not benefit
as much from the exchange of information or ideas, as the task is
clearly known and understood and task conflicts may be an un-
necessary waste of time (Jehn, 1995). Hence, compared to cre-
ative, decision-making, and project tasks, we suggest that groups
are less likely to benefit from task conflicts when they are working
on production tasks.
The moderating effect of task type may not be limited to group
performance but translate to proximal outcomes as well. Jehn
(1995), for example, found that on more routine tasks, task conflict
had a more negative effect on group member satisfaction and
intentions to remain working in the group than among less routine
tasks. Therefore, we also expect that compared to production tasks,
task conflict is less negatively related to proximal outcomes during
creative, decision-making, and project tasks. Finally, we propose
that the moderating effect of task type on group outcomes is
restricted to task conflict. Whereas for creative, decision-making,
and project tasks, task conflict may facilitate an exchange of
information and ideas that is crucial for superior group outcomes,
debates about relationship and process issues remain counterpro-
ductive. Hence, irrespective of the task at hand, we expect rela-
tionship and process conflict to interfere with group functioning
and to be negatively related to both proximal and distal group
outcomes (e.g., Jehn, 1995).
Organizational Level
The third critical moderating variable we investigate is the
organizational level of the groups studied. Organizational level
refers to the position of a group in the context of the broader
organizational hierarchy (Greer, Caruso, & Jehn, in press; Greer &
van Kleef, 2010). Research has suggested that groups that differ in
organizational level (such as service teams in branch offices vs.
management teams in the head office) may differ in their conflict
dynamics (Greer et al., in press; Greer & van Kleef, 2010). This is
because members of teams higher up in the organization, such as
management teams, are likely to be more politically savvy and
better able to handle complex interpersonal situations, such as
conflicts (Lazear & Rosen, 1981). Therefore, studies where groups
were located generally higher up in the organizational hierarchy
should show less negative effects of all forms of conflict on
proximal group outcomes and potentially even positive effects of
task conflict on distal group outcomes.
Cultural Context
The fourth group contextual moderating variable we investigate
is cultural context. In line with theories of psychological stress and
emotion (e.g., Frijda, 1993; Lazarus & Folkman, 1984), culturally
shaped beliefs and expectations regarding conflict situations have
been proposed and found to modify reactions and behaviors to-
ward conflict (Fu et al., 2007; Gelfand et al., 2001; Markus &
Kitayama, 1991; Tjosvold, Law, & Sun, 2006). Cultural context
has been found to play an important role during negotiations (e.g.,
Brett et al., 1998). Japanese and American negotiators, for in-
stance, differ in the extent to which they focus on winning or
compromising during a negotiation (Gelfand et al., 2001), as well
as whether they exchange information in a direct or indirect
manner (Adair, Okumura, & Brett, 2001). Similar differences have
been found with respect to negotiators’ tendencies to stress rela-
tionships and social roles instead of logic and reasoning (Drake,
1995). Likewise, a culture’s values and norms for power have been
found to determine whether power strategies may help or hinder
joint gains (Adair et al., 2004).
Although culture may play an important role in shaping the
conflict– outcome relationship, research has mainly focused on
(intergroup) negotiations, and relatively little attention has been
directed at the impact of cultural context on intragroup conflict.
We propose that the relationship between task conflict, relation-
ship conflict, process conflict, and both proximal and distal group
outcomes will depend on the cultural context. More specifically,
differences in the way group members respond to conflicts and
therefore in the way in which intragroup conflicts impact group
outcomes might reflect differences in cultural dimensions such as
power distance, uncertainty avoidance, individualism versus col-
lectivism, long-term versus short-term orientation, and masculinity
versus femininity (e.g., Hofstede, 2001; see also Cai & Fink, 2002;
Fu et al., 2007; Gabrielidis, Stephan, Ybarra, Pearson, & Villareal,
1997; Sanchez-Burks et al., 2008). For instance, the extent to
which process conflicts about roles and responsibilities hurt group
outcomes might differ across cultures high and low on power
distance as a greater acceptance of the unequal distribution of
power might prevent process conflicts from escalating. Similarly,
intragroup conflicts may be less negatively related to distal group
outcomes among uncertainty-accepting (compared to uncertainty-
avoiding) cultures as they generally are more tolerant of opinions
different from their own (e.g., Hofstede, 2001). Similar effects
may be found with respect to the collectivistic versus individual-
364 DE WIT, GREER, AND JEHN
istic nature of the cultural context. European Americans, for ex-
ample, have a greater preference for addressing conflict with a
competing style (Fu et al., 2007) and hold more positive beliefs
about relationship conflicts compared to Korean and Chinese
participants, who generally score significantly higher on collectiv-
ism (Sanchez-Burks et al., 2008). Likewise, among cultures char-
acterized by a long-term orientation, group members may have a
greater preference for preserving good relationships for obtaining
future rewards and therefore may be more willing to compromise
and find a mutually beneficial solution than to win the conflict.
Finally, when the dominant values in a certain cultural context are
relatively masculine, individuals may be more assertive, more
rigid, and less caring for others during conflicts than among more
feminine cultural contexts, in which individuals generally will
be more cooperative in addressing conflicts (e.g., Leung, Bond,
Carment, Krishnan, & Liebrand, 1990), and this may facilitate
more negative effects of conflict in masculine, rather than femi-
nine, cultures. Therefore, cultural context may have an important
influence on the effects of the three conflict types on both proximal
and distal group outcomes.
Method
Literature Search
The first step in developing the database for the present meta-
analysis was a keyword search in several electronic databases and
search engines for journal articles dated between 1990 and Sep-
tember 2010 (e.g., ABI/Inform, Google Scholar, PsycINFO, Web
of Science, and proceedings of the Academy of Management
conferences). To find published and unpublished articles on intra-
group conflict, we used the keyword team or group in combination
with conflict or disagreement and other keywords such as task,
relationship, process, cognitive, affective, and emotional. We also
searched using combinations of these words with indicators of
proximal group outcomes, such as viability (e.g., satisfaction and
commitment) and emergent states (e.g., trust and cohesion), and
indicators of more distal group outcomes, such as performance.
The second step was to closely examine the reference lists of past
(meta-analytic) reviews of the conflict literature (e.g., De Dreu &
Weingart, 2003b; Jehn & Bendersky, 2003) to make sure we
included all articles they included. Third, using the cited reference
search offered by Web of Science, we searched among publica-
tions that had cited important articles in the field (e.g., De Dreu &
Weingart, 2003b; Jehn, 1995; Jehn et al., 1999; Pelled et al., 1999).
Fourth, we examined the table of contents of the last 5 years of the
relevant journals in social psychology and organizational behavior
(e.g., Academy of Management Journal, Administrative Science
Quarterly, International Journal of Conflict Management, Journal
of Applied Psychology, Journal of Management, Journal of Orga-
nizational Behavior, Journal of Occupational and Organizational
Psychology, Journal of Personality and Social Psychology, Jour-
nal of Vocational Behavior, and Strategic Management Journal).
Fifth, to address publication bias (e.g., Rothstein, Sutton, & Bo-
renstein, 2005), we sent queries via Listservs and newsletters to
members of, for example, the Academy of Management, the Eu-
ropean Association of Experimental Social Psychology, the Euro-
pean Association of Work and Organizational Psychology, and the
International Academy of Conflict Management for working pa-
pers or publications in this area. Finally, we contacted authors who
in the past had published on conflict to ask if they would send us
any (yet) unpublished work that could be included in our data set.
Inclusion Criteria
We used inclusion criteria that were equivalent to those of De
Dreu and Weingart (2003b). Hence, studies were included if they
(a) measured relationship conflict, task conflict, and/or process
conflict; (b) included a measure of proximal and/or distal group
outcomes; and (c) gave sufficient statistical information to com-
pute effect sizes. Given that our research question is concerned
with intragroup conflict, studies had to include groups; we there-
fore excluded studies on buyer–seller relationships, studies on
dyads, and studies using only individual- or organizational-level
measurements. As they did not report data at the group level of
analysis, we decided not to include five studies that De Dreu and
Weingart did include (i.e., Bradford, 1999; Duffy, Shaw, & Stark,
2000; Gardner, 1998; Pelled, 1996; Winters, 1997). Additionally,
we were not able to locate two other studies included by De Dreu
and Weingart (Nauta & Molleman, 2001; Nijdam, 1998). An
explicit comparison of our sample and findings with those of the
meta-analysis by De Dreu and Weingart (including, as well as
excluding, these seven studies) is available upon request from
Frank R. C. de Wit. Furthermore, to avoid using the results of one
data set twice, in case two articles used an identical data set, we
included only the most elaborate article or the one including the most
variables of interest. Similarly, studies that collapsed task, relation-
ship, and process conflict together into one variable were also ex-
cluded as our goal was to distinguish the effects of each type of
conflict separately. Finally, besides intragroup conflict, the study had
to include one or more group outcomes. We included decision quality,
effectiveness, financial performance, innovativeness, and overall per-
formance as indicators of group performance. As proximal group
outcomes, we included two emergent states (intragroup trust and
group cohesion) and six indicators of group viability (group member
satisfaction, commitment, identification with the group, organiza-
tional citizenship behavior, counterproductive workplace behavior,
and positive affect; Balkundi & Harrison, 2006).
Data Set and Coding of Studies
Our literature search resulted in an initial collection of around
300 articles. Using the above inclusion criteria, the number of
studies finally included in the present meta-analysis was 116
studies. The references considered but excluded from the meta-
analyses are available online as supplemental materials. All arti-
cles (including those excluded) were examined twice, once by a
trained research assistant and once by either Frank R. C. de Wit or
Lindred L. Greer. Interrater agreement was high; similar codings
were obtained for 96.7% of the coded effect sizes and moderator
variables. Discrepancies were resolved by reaching consensus via
discussion. Together, the 116 studies represent 484 effect sizes.
The coders collected information on sample size and statistical
artifact information, such as the reliability of the scales used to
measure conflict and group outcomes. The coders also collected
information on the four theoretical moderators: (a) the association
between task, relationship, and process conflict (correlation of
task, relationship, and process conflicts), to test whether the effect
365
INTRAGROUP CONFLICT META-ANALYSIS
sizes depend on the extent to which the three types of conflict
accompany each other (e.g., Gamero et al., 2008; Mooney et al.,
2007); (b) group task, to test whether the effect sizes depend on the
type of the task being performed (we used McGrath’s, 1984, group
task circumplex to distinguish five different tasks: creativity tasks,
decision-making tasks, production-planning tasks, project tasks, and
mixed tasks; in the mixed-tasks category, we included studies in
which groups worked on a variety of tasks); (c) organizational level
(top management teams vs. non–top management teams), to test for
differences between groups at the top of the organizational hierarchy
versus groups at lower levels of the organizational hierarchy (e.g.,
Greer et al., in press); and (d) cultural context, to test whether the
effect sizes differ across cultures (e.g., Tjosvold et al., 2006): We first
determined the geographical location where a study was conducted
and then assigned to the study the associated values of Hofstede’s
(2001) five cultural dimensions: power distance, individualism–
collectivism, masculinity–femininity, uncertainty avoidance, and
long-term versus short-term orientation. To avoid potential problems
with multicollinearity, all scores were mean-centered.
In addition to the theoretical moderators included in this study,
we also collected information about methodological aspects that
may have had an influence on whether conflict was positively or
negatively related to group outcomes. We examined the following
methodological moderators: (a) average level of intragroup con-
flict, to test whether studies among groups with relatively high
levels of conflict differ from studies among groups with relatively
low levels of conflict (we adjusted and controlled for the number
of answer categories that were used to measure conflict); (b)
setting (field and nonfield), to assess whether results differ for
studies conducted within organizations or within laboratories or
classrooms; (c) subjects (professionals, undergraduates, and post-
graduates), to test whether the effect sizes vary when group mem-
bers were professionals instead of students; (d) conflict scale (Jehn
and non-Jehn), to test whether the effect sizes vary across different
scales used to measure conflict (e.g., Korsgaard, Jeong, Mahony,
& Pitariu, 2008); (e) operationalization of group performance,
1
to
test whether results differ across five different operationalizations
of group performance (e.g., De Dreu, 2008): decision quality,
effectiveness, financial performance, innovativeness, and overall
performance (in which multiple performance dimensions were
combined into one measure, such as in overall course grades or
measures that combined efficiency, output quality, and adherence
to budget into one measure); (f) measurement of performance
(objective and subjective), to test whether there is a difference in
effect sizes when performance is measured via more objective, for
instance, financial, measures or via more subjective ratings of
performance (Arvey & Murphy, 1998); and (g) publication status
(unpublished and published), to test whether the effect sizes are
affected by publication selection bias. Descriptive statistics of the
continuous moderators (e.g., cultural context and co-occurrence of
conflict types) can be found in Table 1. Moreover, all the effect
sizes, as well as reliability and moderator information, can be
found in Appendixes A, B, and C.
Meta-Analytic Procedures
All the effect sizes were first corrected for sampling error. Next,
we corrected for the measurement error in the independent and
dependent variables. This was done according to the approach
developed by Hunter and Schmidt (1990, 2004); we divided indi-
vidual effect sizes by the square root of the reliability estimates of
the two correlated variables. We used internal consistency coeffi-
cients reported in the respective study as the reliability estimates.
In case the authors did not report internal consistency coefficients,
the internal consistency coefficient for each variable across all
studies included in the meta-analysis was used. We assigned a
reliability coefficient of 1.00 to objective performance indicators
for which no reliability coefficient was reported (for similar pro-
cedures, see, e.g., Riketta, 2008). In case a study provided multiple
estimates of a correlation between a predictor (X) and a criterion
(Y), we used the formula for composites (Hunter & Schmidt,
2004) to derive a linear composite of the effect sizes to ensure the
independence of effects sizes in the final data set. The analyses
were conducted using the Schmidt-Le program (Version 1.1;
Schmidt & Le, 2004). The precision of the effect sizes was
examined by calculating the 95% confidence interval (CI) around
the effect size. Finally, we used the procedures described by
Viechtbauer and Cheung (2010) to derive outlier and influence
diagnostics, using the Metafor meta-analysis package for R (Ver-
sion 1.4-0; Viechtbauer, 2010a, 2010b).
Moderator Analyses
Heterogeneity among the effect sizes of the relationship be-
tween intragroup conflict and group outcomes was examined by
calculating 90% credibility intervals (Hunter & Schmidt, 2004).
Subsequently, we assessed the significance of the categorical mod-
erator variables by comparing the 95% CIs of the associated
moderator categories. We interpreted nonoverlapping CIs as sig-
nifying reliable differences among categories (Hunter & Schmidt,
2004). We also performed meta-analytic weighted least squares
(WLS) regression analyses to examine (a) the impact of continu-
ous moderator variables and (b) the influence of multiple moder-
ator effects simultaneously (Steel & Kammeyer-Mueller, 2002;
Viechtbauer, 2007; Viswesvaran & Sanchez, 1998). In the WLS
regression analyses, studies were given inverse variance weights
based on their sample size (see Hedges & Olkin, 1985). These are
weights that are inversely proportional to the variance of the study
so that studies with a larger sample size, which are assumed to
offer more precise estimations of an effect size than studies with a
smaller sample size, are given larger weight in the analyses (see
Heugens & Lander, 2009; Lipsey & Wilson, 2001). We used
Wilson’s (2005) SPSS macros for meta-analytic WLS regression
analyses to derive fixed- and mixed-effects models. In fixed-
effects models, the studies being analyzed are assumed to be
homogeneous at the level of study population effect sizes, and
differences between studies are attributed to sampling error and
other study artifacts (Hunter & Schmidt, 2000). In mixed-effects
models, this assumption is not made, and variance in effect sizes is
attributed to sampling error, other study artifacts, and a remaining
unmeasured random component (Lipsey & Wilson, 2001). Mixed-
effects models, therefore, are more conservative, allowing for the
1
It is important to note that there was little overlap between task type and
what aspect of performance was measured. For example, whereas top man-
agement teams can be classified as decision-making teams, often their perfor-
mance was not measured directly by assessing the quality of their decisions but
more indirectly via financial indicators such as profitability of the organization.
366 DE WIT, GREER, AND JEHN
possibility that the population parameter values can vary between
studies (Hunter & Schmidt, 2000).
Results
Intragroup Conflict and Proximal Group Outcomes
Table 2 presents the overall mean corrected correlations be-
tween intragroup conflict and proximal group outcomes. In the
case of task conflict and its relationship with trust and commit-
ment, the study by Parayitam and Dooley (2007) was identified as
a positive outlier and was not included in the analyses. The results
show that task, relationship, and process conflicts are reliably
negatively related to trust (ˆ⫽⫺.45, ˆ⫽⫺.53, ˆ⫽⫺.59,
respectively) and group member commitment (ˆ⫽⫺.31, ˆ
.47, and ˆ⫽⫺.54, respectively). With respect to trust, for all
three types of conflict, the credibility intervals do not contain zero,
Table 1
Descriptive Statistics for the Continuous Moderators
Moderator MSDMinimum Maximum
Uncorrected correlations
Task conflict–relationship conflict 0.52 0.32 0.69 0.93
Task conflict–process conflict 0.66 0.28 0.50 0.93
Relationship conflict–process conflict 0.67 0.15 0.24 0.90
Cultural dimension
Power distance 43.32 11.15 13.00 80.00
Masculinity (vs. femininity) 53.27 17.57 14.00 70.00
Individualism (vs. collectivism) 79.25 22.17 17.00 91.00
Uncertainty avoidance 49.81 12.69 8.00 104.00
Long-/short-term orientation 37.67 22.59 19.00 118.00
Average level of task conflict 3.54 0.85 1.63 6.30
Average level of relationship conflict 2.72 0.70 1.36 5.35
Average level of process conflict 2.54 0.46 1.86 3.66
Table 2
Meta-Analysis Results for Intragroup Conflict and Proximal Group Outcomes
Predictor kNMean rMean ˆSD ˆ 90% credibility interval SE ˆ 95% confidence interval
Trust
Task conflict 16 1,205 .37 .45 .20 0.78, 0.12 .06 0.56, 0.33
Relationship conflict 16 1,302 .45 .53 .29 1.00, 0.05 .08 0.68, 0.38
Process conflict 7 492 .51 .59 .16 0.85, 0.32 .07 0.73, 0.45
Cohesion
Task conflict 16 1,326 .01 .00 .50 0.83, 0.83 .13 0.26, 0.25
Relationship conflict 14 1,175 .37 .44 .19 0.75, 0.13 .06 0.55, 0.33
Process conflict 3 205 .45 .48 .20 0.81, 0.16 .13 0.74, 0.23
Satisfaction
Task conflict 26 1,979 .22 .24 .38 0.87, 0.38 .08 0.40, 0.09
Relationship conflict 26 1,901 .47 .54 .17 0.82, 0.27 .04 0.62, 0.47
Process conflict 10 643 .52 .61 .05 0.70, 0.52 .04 0.68, 0.53
Commitment
Task conflict 13 1,044 .25 .31 .19 0.62, 0.01 .06 0.43, 0.18
Relationship conflict 12 772 .41 .47 .28 0.93, 0.02 .09 0.64, 0.30
Process conflict 8 538 .45 .54 .17 0.82, 0.26 .07 0.68, 0.40
Identification
Task conflict 5 229 .26 .30 .01 0.32, 0.28 .07 0.44, 0.15
Relationship conflict 5 229 .43 .49 .12 0.69, 0.29 .08 0.65, 0.33
Process conflict 1 38 .05 .05
Organizational citizenship behavior
Task conflict 7 427 .19 .23 .22 0.59, 0.12 .10 0.43, 0.04
Relationship conflict 7 436 .32 .38 .20 0.72, 0.04 .09 0.56, 0.20
Process conflict 1 121 .24 .27
Counterproductive workplace behavior
Task conflict 4 296 .42 .53 .00 0.53, 0.53 .04 0.46, 0.60
Relationship conflict 4 296 .43 .54 .39 0.10, 1.17 .20 0.14, 0.94
Positive affect
Task conflict 5 623 .05 .05 .57 0.89, 0.99 .26 0.46, 0.56
Relationship conflict 4 387 .40 .48 .38 1.11, 0.15 .17 0.87, 0.09
Note. k number of effect sizes; Ntotal sample size; rmean estimate of uncorrected correlations; SE ˆmean estimate of corrected population
correlation; SD ˆestimated standard deviation of mean ˆ;SE ˆestimated standard error of mean ˆ.
367
INTRAGROUP CONFLICT META-ANALYSIS
indicating that the negative relationships with trust are generaliz-
able across different settings. Table 2 further shows that both task
and relationship conflicts are negatively related to group member
identification (ˆ⫽⫺.30 and ˆ⫽⫺.49, respectively), organiza-
tional citizenship behaviors (OCB; ˆ⫽⫺.23 and ˆ⫽⫺.38,
respectively) and positively related to counterproductive work
behaviors (CWB; ˆ.53 and ˆ.54, respectively).
With respect to group member satisfaction, group cohesion, and
positive affect, the results indicate a significant difference between
the conflict types. First, the associated CIs indicate that process
and relationship conflicts are more negatively related to group
member satisfaction (ˆ⫽⫺.54 and ˆ⫽⫺.61, respectively) than
task conflict (ˆ⫽⫺.24). These results replicate the findings of De
Dreu and Weingart (2003b), who also found a less negative rela-
tionship between task conflict and group member satisfaction (ˆ
.27) than between relationship conflict and group member sat-
isfaction (ˆ⫽⫺.48). Second, whereas there is a strong negative
association between relationship conflict and cohesion (ˆ⫽⫺.44),
there is not between task conflict and cohesion (ˆ.00). Third,
whereas relationship conflict is reliably negatively associated with
positive affect (ˆ⫽⫺.48), task conflict is not (ˆ.05). More-
over, the credibility intervals indicate that for the relationships
between task conflict and cohesion, group member satisfaction,
and positive affect, the presence of subpopulations (moderators) is
likely.
Intragroup Conflict and Distal Group Outcomes
Table 3 summarizes the overall mean corrected correlations
between the three types of intragroup conflict and the primary
distal group outcome we investigated: group performance. The
results show that relationship conflict (ˆ⫽⫺.16) and process
conflict (ˆ⫽⫺.15) are negatively related to group performance
but that, overall, neither a positive nor a negative relationship
exists between task conflict and group performance (ˆ⫽⫺.01).
As the associated CIs for both process and relationship conflict do
not include zero, the results suggest that the negative relationship
between both process and relationship conflict and group perfor-
mance is reliable (Whitener, 1990). Moreover, as the CIs of
process conflict and relationship conflict do not overlap with the
CI of task conflict, the results indicate that process and relationship
conflicts are significantly more negatively related to group perfor-
mance than task conflict.
The results for relationship conflict replicate those of De Dreu
and Weingart (2003b), who found a similar negative association
between relationship conflict and group performance (ˆ⫽⫺.22).
The results for task conflict are notably different. De Dreu and
Weingart found a more negative relationship between task conflict
and group performance (ˆ⫽⫺.23) than we did (ˆ⫽⫺.01).
Similar to the findings of De Dreu and Weingart, for all three
conflict types, the 90% credibility intervals reported in Table 3
were relatively wide and included zero. This indicates that there
are restrictions to the generalizability of the estimated correlations
and that there is a sufficient amount of heterogeneity in the
observed results to justify an investigation of potential moderators
of these effects.
Moderator Analyses
We performed subgroup analyses to test categorical moderators
(e.g., Hunter & Schmidt, 2004) and WLS regression analyses to
test continuous moderators (e.g., Lipsey & Wilson, 2001) and to
test multiple moderators simultaneously (e.g., Steel & Kammeyer-
Mueller, 2002). We tested multiple moderators simultaneously
only when the total sample size for a specific effect size was larger
than 50 studies as testing multiple moderators simultaneously may
lead to misestimating moderator effects when the data set is too
small (see Steel & Kammeyer-Mueller, 2002). More than 50
studies were available for group performance and its association
with task conflict and relationship conflict but not for group
performance and process conflict or for any of the proximal group
outcomes. Hence, for the association between process conflict and
group performance, as well as the proximal group outcomes, we
tested the moderators only individually.
Moderators of the association between intragroup conflict
and proximal group outcomes. The overall effect sizes re-
ported in Table 2 indicate that, for process conflict, the negative
relationships with proximal group outcomes are generalizable
across different settings. With respect to relationship conflict,
heterogeneity existed in the relationships with CWB and positive
affect, and with respect to task conflict, heterogeneity existed in
the relationships with cohesion, satisfaction, OCB, and positive
affect. In the case of OCB (k7), CWB (k4), and positive
affect (k5), the sample size was too small to conduct meaning-
ful moderator analyses. Therefore, we examined the effects of
group contextual and methodological moderators only for the
relationships between task conflict and group cohesion and be-
tween task conflict and group member satisfaction. With respect to
group member satisfaction, one study (Oliver, Poling, & Woehr,
2008) was identified as an outlier and excluded from the analyses.
We found one moderator (the co-occurrence of task and relation-
ship conflict) to moderate the association between task conflict and
group member satisfaction. The results presented in Table 4 show
that the stronger the association between task and relationship
conflict, the more negative the association between task conflict
and group member satisfaction (p.001). Table 4 further shows
Table 3
Meta-Analysis Results for Group Performance
Predictor kNMean rMean ˆSD ˆ 90% credibility interval SE ˆ 95% confidence interval
Task conflict 95 7,201 .01 .01 .23 0.38, 0.36 .03 0.06, 0.04
Relationship conflict 80 5,369 .15 .16 .16 0.43, 0.10 .02 0.21, 0.12
Process conflict 24 1,752 .13 .15 .20 0.47, 0.17 .05 0.25, 0.06
Note. k number of effect sizes; Ntotal sample size; rmean estimate of uncorrected correlations; ˆmean estimate of corrected population
correlation; SD ˆestimated standard deviation of mean ˆ; SE ˆestimated standard error of mean ˆ.
368 DE WIT, GREER, AND JEHN
that the relationship between task conflict and group member
satisfaction is not moderated by the association between task
conflict and process conflict. Finally, similar to group member
satisfaction, we found that the stronger the association between
task and relationship conflict, the more negative the association
between task conflict and group member cohesion (p.001).
Moderators of the association between intragroup conflict
and distal group outcomes.
Task conflict and group performance. Two moderators were
tested individually (the co-occurrence of task and process conflict
and organizational level) as they could not be included in the
regression analyses due to the limited number of studies that
provided information on these two variables. More specifically,
only a limited number of studies on task conflict also measured
process conflict (N22). Similarly, in case of organizational
level, only 60 studies were conducted in a field setting, whereas 35
were conducted in the lab or in the classroom. Of the 60 field
studies, only 41 reported sufficient data on the organizational
level. We tested the moderating effect of the co-occurrence of task
and process conflict using WLS regression analyses. The study by
Wan and Ong (2005) was identified as an outlier and therefore
excluded from these analyses. As shown Table 4, we found no
effect of the co-occurrence of task and process conflict (also if we
controlled for the co-occurrence of task and relationship conflict).
The moderating effect of organizational level was analyzed using
subgroup analyses, and as shown in Table 5, we found a reliable
difference between studies conducted among top management
teams and studies conducted among teams lower in the organiza-
tional hierarchy. Compared to non–top management teams (ˆ
.21, CI [0.34, 0.09]), the relationship between task conflict
and performance was distinctly more positive for top management
teams (ˆ.09, CI [0.01, 0.18]).
The remaining moderators were tested simultaneously using
WLS regression analyses. The residual component Q
residual
of the
fixed-effects model was significant, and as this violates the as-
sumptions of fixed-effects analysis (see Lipsey & Wilson, 2001),
in Table 6, we report only the more conservative mixed-effects
model. The mixed-effects model fitted the data well and showed
support for several of the hypothesized moderating effects.
First, the results confirm that the relationship between task
conflict and group performance becomes more negative when
the association between task and relationship conflict among
the groups within a study is higher (p.01). This result is also
depicted in Figure 2, showing the association between task
conflict and group performance varies as a function of the
association between task conflict and relationship conflict. This
Table 4
WLS Regression Analyses With the Association Between Conflict Types as Predictor Variables
Predictor BSEBZp90% confidence interval R
2
k
Task conflict and group member satisfaction
Constant .16 .17 .00 0.97 .33 0.17, 0.50 .36 21
Association between task and relationship conflict .84 .25 .60 3.32 .00 1.34, 0.35
Task conflict and group member satisfaction
Constant .19 .30 .00 0.63 .53 0.76, 0.39 .09 10
Association between task and process conflict .31 .35 .29 0.87 .38 1.00, 0.38
Task conflict and group performance
Constant .14 .34 .00 0.41 .68 0.81, 0.53 .00 21
Association between task and process conflict .03 .40 .02 0.09 .93 0.76, 0.83
Relationship conflict and group performance
Constant .38 .25 .00 1.52 .13 0.11, 0.88 .22 21
Association between relationship and process conflict .66 .30 .47 2.17 .03 1.26, 0.07
Process conflict and group performance
Constant .01 .43 .00 0.02 .98 0.84, 0.82 .04 19
Association between task and process conflict .05 .56 .03 0.09 .93 1.05, 1.15
Association between relationship and process conflict .32 .50 .21 0.65 .52 1.31, 0.66
Table 5
Results for Categorical Moderator Analyses of Organizational Level
Predictor kN rˆSD ˆ 90% credibility interval SE ˆ 95% confidence interval
Task conflict–group performance
Non–top management 22 1,007 .17 .21 .23 0.60, 0.17 .06 0.34, 0.09
Top management 19 2,464 .07 .09 .18 0.21, 0.39 .05 0.01, 0.18
Relationship conflict–group performance
Non–top management 18 871 .21 .25 .09 0.40, 0.11 .04 0.34, 0.16
Top management 12 1,344 .17 .18 .16 0.45, 0.08 .06 0.29, 0.07
Process conflict–group performance
Non–top management 7 366 .28 .32 .00 0.32, 0.32 .06 0.44, 0.21
Top management 2 259 .07 .08 .11 0.26, 0.11 .11 0.29, 0.13
Note. k number of effect sizes; Ntotal sample size; rmean estimate of uncorrected correlations; ˆmean estimate of corrected population
correlation; SD ˆestimated standard deviation of mean ˆ; SE ˆestimated standard error of mean ˆ.
369
INTRAGROUP CONFLICT META-ANALYSIS
replicates the findings by De Dreu and Weingart (2003b), who
found a more negative relationship between task conflict and
group performance (ˆ⫽⫺.35 vs. ˆ⫽⫺.10) in studies that
reported a relatively high (vs. low) correlation between task and
relationship conflict. The results further indicate that compared
to when performance was measured in terms of overall perfor-
mance (i.e., the reference category), the relationship between
task conflict and group performance was more positive when it
was measured in terms of decision-making quality (p.01) or
financial performance (p.01). In addition, two moderators
had a marginally significant effect on the relationship between
task conflict and group performance. The relationship between
task conflict and group performance was more negative when
the average level of task conflict among teams within a study
was relatively high (p.096). Additionally, compared to when
the study was conducted in a classroom or laboratory setting,
Table 6
WLS Regression Analysis Results for Group Performance
Variable
Task
conflict–performance
Relationship
conflict–performance
Group contextual moderators
(1) Association task and relationship conflict 0.34 (0.11)
ⴱⴱ
0.05 (0.10)
(2) Group task: project 0.06 (0.12) 0.10 (0.11)
(2) Group task: creativity 0.13 (0.19) 0.17 (0.18)
(2) Group task: decision making 0.10 (0.13) 0.02 (0.12)
(2) Group task: production planning 0.15 (0.16) 0.20 (0.15)
(3) Cultural dimension: power distance 0.86 (1.35) 1.35 (1.26)
(3) Cultural dimension: masculinity (vs. femininity) 0.32 (0.30) 0.35 (0.28)
(3) Cultural dimension: individualism (vs. collectivism) 0.23 (0.64) 0.69 (0.59)
(3) Cultural dimension: uncertainty avoidance 0.37 (0.38) 0.15 (0.35)
(3) Cultural dimension: long-/short-term orientation 0.49 (0.40) 0.19 (0.37)
Methodological moderators
(5a) Average level of relationship conflict 0.03 (0.07) 0.09 (0.06)
(5b) Average level of task conflict 0.12 (0.07)
0.04 (0.07)
(6) Field setting 0.21 (0.12)
0.08 (0.11)
(7) Non-Jehn conflict scale 0.09 (0.15) 0.01 (0.14)
(8) Performance indicator: decision quality 0.44 (0.14)
ⴱⴱ
0.14 (0.13)
(8) Performance indicator: innovativeness 0.37 (0.35) 0.01 (0.32)
(8) Performance indicator: effectiveness 0.18 (0.16) 0.14 (0.15)
(8) Performance indicator: financial performance 0.47 (0.17)
ⴱⴱ
0.20 (0.16)
(9) Objective 0.08 (0.12) 0.04 (0.12)
(10) Published 0.09 (0.10) 0.13 (0.09)
Constant 0.55 (0.27)
0.28 (0.25)
R
2
0.60 0.47
K55 55
Q
model
(p)45.88 (.001) 27.29 (.127)
Q
Residual
(p)30.18 (.656) 31.40 (.596)
V0.04 0.03
Note. Unstandardized regression coefficients are presented with standard errors in parentheses. kis the total
number of effect sizes; Qis the homogeneity statistic with its probability in parentheses; vis the random-effects
variance component.
p.10.
p.05.
ⴱⴱ
p.01.
Figure 2. The association between task conflict and group performance (n61) as a function of the
association between task conflict and relationship conflict. Only positive correlations are included in this figure.
370 DE WIT, GREER, AND JEHN
task conflict were more negatively related to performance in
studies conducted in the field (p.073).
The results presented in Table 6 show no support for the
hypothesized effect of task type. Hence, the relationship between
task conflict and group performance does not appear to differ
across studies investigating mixed, project, creativity, decision-
making, or production-planning tasks when controlling for other
moderating effects. This is in contrast to the meta-analysis of De
Dreu and Weingart (2003b), who found that studies that investi-
gated production teams (ˆ.04) reported weaker negative cor-
relations than studies that investigated decision-making teams
(ˆ⫽⫺.20), project teams (ˆ⫽⫺.26), or mixed teams (ˆ⫽⫺.43).
Similarly, no support was found for a moderating effect of cultural
context, the average level of relationship conflict, the scales used
to measure intragroup conflict, whether performance was mea-
sured objectively versus subjectively, or whether the study was
published or not.
Relationship conflict and group performance. Two moder-
ators were again tested individually: the co-occurrence of rela-
tionship and process conflict and the organizational level. The
results reported in Table 4 indicate that the association between
relationship conflict and group performance becomes more
negative when the association between process and relationship
conflict within a study is stronger (p.05). This effect was not
found for the association between relationship conflict and task
conflict, as can also be seen in Table 4. As shown in Table 5,
we did not find a difference between studies conducted among
top management teams and studies conducted among teams
lower in the organizational hierarchy. The remaining modera-
tors were investigated using WLS regression analyses. The
residual component of the fixed-effects model was significant.
Therefore, in Table 6, we again report only the more conser-
vative mixed-effects model. The results indicate that when
controlling for the presence of other moderators, none of the
moderators affected the association between relationship con-
flict and group performance.
Process conflict and group performance. As the number of
studies available on process conflict was too small to test moder-
ators simultaneously, we tested the moderators individually for the
relationship between process conflict and group performance. In-
terestingly, none of our group contextual and methodological
moderators affected the association between process conflict and
group performance. For example, as shown in Table 4, neither the
moderating effect of the co-occurrence of relationship and process
conflict nor the co-occurrence of task conflict and process conflict
was significant (the study by Brauckmann, 2007, was identified as
an outlier and therefore excluded from these analyses). Likewise,
as shown in Table 5, only for studies conducted among teams
lower in the organizational hierarchy was the negative association
between process conflict and group performance reliable and gen-
eralizable, yet the difference between studies conducted among top
management teams and studies conducted among teams lower in
the organizational hierarchy was not significant.
Supplementary Analysis
The results reported above are consistent with our hypotheses
that relationship conflict and process conflict are more negatively
related to both proximal and distal group outcomes than task
conflict. In addition, the findings show that the relationships be-
tween task and relationship conflict and group outcomes are mod-
erated by several characteristics, such as the type of performance
measure and the co-occurrence of conflict types. Yet, so far, we
have not looked at the unique contribution of the three types of
intragroup conflict on group outcomes. To develop a clearer pic-
ture of the incremental relationships between process conflict,
relationship conflict, task conflict, and proximal and distal group
outcomes, we therefore conducted supplemental path analyses
using MASEM (e.g., Viswesvaran & Ones, 1995). Given the
heterogeneity in our data set, we used two-stage structural equation
modeling (TSSEM) in which correlation matrices are first tested
for homogeneity and then pooled and used in a MASEM (Cheung
& Chan, 2005). We used Cheung’s metaSEM package for R to
conduct these analyses (Version 0.5-1; Cheung, 2010).
With respect to conflict and proximal group outcomes, we
restrict ourselves to the results for satisfaction. Similar results were
obtained for the other proximal outcome (i.e., group cohesion) and
are available on request from Frank R. C. de Wit. The first stage
of the MASEM indicated heterogeneity among the correlation
matrices,
2
(91, N2,257) 528.61, root-mean-square error of
approximation (RMSEA) .25, comparative fit index (CFI)
.76. This is in line with the results reported above that suggested
that the relationship between task conflict and group satisfaction is
moderated by the association between relationship conflict and
task conflict. To address the heterogeneity in the correlation ma-
trices, we therefore used a random-effects model to average the
correlation matrices (see Becker, 1992) as suggested by Cheung
and Chan (2005). Yet, as the associated weighted covariance
matrix was nonpositive definite, we could not proceed to the
second stage of the structural equation modeling (i.e., Cheung &
Chan, 2005). This problem resulted from missing values in the
many studies that did not measure process conflict in combination
with pairwise deletion when synthesizing the correlation matrices.
We therefore performed structural equation modeling without pro-
cess conflict. The resulting pooled correlation matrix of task con-
flict, relationship conflict, and group member satisfaction is found
in Table 7. On the basis of the pooled correlation matrix, we
proceeded to the second step of the TSSEM and performed struc-
tural equation modeling to calculate the incremental relationships
between the task and relationship conflicts and group satisfaction.
Given that the model was fully saturated, the fit indices could not
be used to test the fit of the model, and therefore, we restrict
ourselves to describing the path coefficients. The results of the
structural equation modeling showed that both the standardized
path coefficient of task conflict (␤⫽⫺.13, SE 0.06, CI [0.24,
0.02], p.05) and that of relationship conflict were significant
and negative (␤⫽⫺.39, SE 0.05, CI [0.48, 0.30], p
.001).
For group performance, the results of the first stage of the
MASEM again indicated heterogeneity among the correlation ma-
trices,
2
(295, N7,905) 1,553.25, RMSEA .24, CFI
.70.
2
We therefore used a random-effects model to average the
correlation matrices (see Becker, 1992). The pooled correlation
matrix is reported in Table 7. The results of the second step of the
2
The studies by Wan and Ong (2005) and Brauckmann (2007) were
again identified as outliers and excluded from the analyses.
371
INTRAGROUP CONFLICT META-ANALYSIS
TSSEM showed that the standardized path coefficients character-
izing the effect of task conflict were significant and positive (␤⫽
.15, SE 0.07, CI [0.00, 0.29], p.05), while those of relation-
ship conflict (␤⫽⫺.10, SE 0.05, CI [0.20, 0.00], p.059)
and process conflict (␤⫽⫺.21, SE 0.11, CI [0.43, 0.00], p
.055) were negative but only marginally significant. The results
suggest that, controlling for the other two types of conflict, task
conflict is positively related to group performance, while process
conflict and relationship conflict are negatively related to group
performance. Again, these results should be taken with caution
because considerable heterogeneity existed among the correlation
matrices.
Discussion
In this meta-analysis of 116 studies on intragroup conflict, we
examined the relationship of three types of intragroup conflict (i.e.,
task, relationship, and process conflict) with proximal group out-
comes (i.e., group viability and emergent states) and distal group
outcomes (i.e., group performance). Overall, we found that the
three types of conflict are more negatively related to proximal
group outcomes than to distal group outcomes (i.e. group perfor-
mance). For several proximal outcomes, such as group member
satisfaction and cohesion, we found that the relationships are less
negative for task conflict as compared to process and relationship
conflict. Similarly, we found that for task conflict, the overall
association with group performance is neither negative nor posi-
tive, whereas the overall association of relationship and process
conflict with group performance is more uniformly negative.
Among the studies included in the meta analysis, considerable
heterogeneity existed for each of the three types of intragroup conflict
and their relationship with group performance. Further exploration of
this heterogeneity revealed that the relationship between task conflict
and group performance depends heavily on the presence of different
moderating factors. We also found this to be true for the relationship
between task conflict and proximal group outcomes such as group
member satisfaction. Below, we address these moderating factors in
more detail as well as the theoretical and methodological implications
of this meta-analysis.
Theoretical Implications
Our meta-analysis suggests that the effects of conflict are better
understood by a contingency approach. This offers an important
extension to the meta-analysis of De Dreu and Weingart (2003b) as
we have shown across 116 studies (86 studies more than the 30
studies included in their meta-analysis) that the effects of conflict are
dependent on the type of conflict, the context studied, and the methods
used. Factors such as the type of conflict, type of outcome, correlation
between task and relationship conflict, organizational level, and how
variables are operationalized and measured may explain when conflict
is more negatively or positively related to group outcomes.
Extension of De Dreu and Weingart (2003b)
Whereas some of the findings of the current meta-analysis are
consistent with the findings of the De Dreu and Weingart (2003b)
meta-analysis, such as the negative association between relation-
ship conflict and group outcomes and the moderating effect of the
association between task conflict and relationship conflict, other
findings extend or refine the insights gained from their meta-
analysis. First, we have expanded their review by examining a
broader array of possible moderators and group outcomes and have
provided a first meta-analysis of the effects of process conflict on
group outcomes. Second, in contrast to their finding that task and
relationship conflict are equally disruptive for group outcomes, we
have found that task conflict has a less negative (and under certain
conditions, a positive) relationship with group outcomes than
process and relationship conflict. Indeed, when entering all three
conflict types into a path analysis together, task conflict actually
became positive for group performance, whereas relationship and
process conflict affected performance negatively. Third, De Dreu and
Weingart found that task conflict had the least negative correlation
with task performance in studies on production teams and more
negative relations with performance in studies on decision-making
and project teams. They concluded that “conflict interferes with
information processing capacity and therefore impedes task perfor-
mance, especially when tasks are complex and demand high levels of
cognitive activity” (De Dreu & Weingart, 2003b, p. 747). We did not
find support for this conclusion, however, as we did not find a
difference between task types when testing all moderators simultane-
ously. Importantly, when testing the moderating effect of group task
type in isolation (using subgroup analyses), we found a small and
positive correlation among studies on decision-making tasks.
3
Simi-
larly, we also found that in studies in which performance was mea-
sured specifically in terms of decision-making quality or financial
performance (instead of more global overall performance), task con-
flict and performance were more positively related. To test whether
3
The results of the subgroup analyses are available upon request from
Frank R. C. de Wit.
Table 7
Corrected Meta-Analytic Intercorrelations Among Study Variables
Variable 1. Process conflict 2. Relationship conflict 3. Task conflict 4. Satisfaction
1. Process conflict
2. Relationship conflict .73 (k18, N1,157) .58 (k21, N1,491) .47 (k25, N1,765)
3. Task conflict .72 (k19, N1,353) .54 (k73, N4,845) — .36 (k25, N1,843)
4. Performance .18 (k21, N1,428) .18 (k77, N5,045) .07 (k92, N6,877) —
Note. Values above the diagonal are the pooled correlation coefficients based on the correlation matrices including group member satisfaction. Values
below the diagonal are the pooled correlation coefficients based on the correlation matrices including group performance. knumber of effect sizes; N
total sample size.
372 DE WIT, GREER, AND JEHN
the differences between the results of De Dreu and Weingart and the
current meta-analysis were due to coding decisions, we ran a separate
analysis in which we restricted the analyses to the studies that existed
when they performed their meta-analysis. The results of these analy-
ses exhibited the same general pattern as De Dreu and Weingart, and
thus, the difference between the two meta-analyses is not due to
divergent coding decisions. Instead, the primary explanation for the
difference in the two findings is the greater breadth of studies that we
have included in the current meta-analysis. For example, at the time
of De Dreu and Weingart’s meta-analysis, only five of the available
studies were qualified as decision-making teams. In contrast, in the
current study, 23 studies of decision-making teams were included.
Theoretical moderators of the conflict– outcomes relation-
ship.
Co-occurrence of conflict types. One important moderator of
the relationship between task conflict and both proximal and distal
group outcomes (i.e., group performance and group member sat-
isfaction) was the association between task conflict and relation-
ship conflict. The moderator analyses revealed that task conflict
was more negatively related to group performance and group
member satisfaction among studies where task conflict and rela-
tionship conflict were highly associated. These findings are in line
with theory and research suggesting that if task conflicts can occur
without relationship conflicts also occurring, task conflicts are less
likely to be emotional (Yang & Mossholder, 2004), escalate (Greer
et al., 2008), and impair group performance (Peterson & Behfar,
2003; Shaw et al., 2011; Simons & Peterson, 2000). Interestingly,
the association between relationship conflict and group perfor-
mance was not altered when controlling for the association be-
tween task conflict and relationship conflict within a study. We did
find that the association between relationship conflict and group
performance was moderated by the co-occurrence of process con-
flict and relationship conflict; the stronger the association between
process and relationship conflict reported by a study, the more
negative the association between relationship conflict and group
performance in that study. These findings suggest that if relation-
ship conflicts can occur without process conflicts, they will have a
less negative effect on group performance. Interestingly, the asso-
ciation between process conflict and group performance was not
affected when controlling for the association between process
conflict and relationship conflict or task conflict. Process conflicts
seem to be negatively related to group performance irrespective of
the extent to which they co-occur with relationship conflict or task
conflict. The results of our two-stage meta-analytic path analyses
provided additional support for these findings. When investigating
the incremental effects of task, relationship, and process conflict,
task conflict was positively related to performance, while relation-
ship conflict and process conflict were negatively related to group
performance. Moreover, instead of relationship conflict, process
conflict appeared to be the most negative form of conflict for
group performance. Given the heterogeneity among the correla-
tions and the correlation matrices and the influence of the other
moderating processes, this conclusion should, however, be taken
cautiously.
Organizational level. We also found that the association
between task conflict and performance was distinctly more posi-
tive among studies on top management teams than among studies
on teams operating at lower levels of the organizational hierarchy.
The same result was not found for relationship or process conflict
or for other group outcomes. Interestingly, a closer inspection of
the data revealed that the average correlation of task conflict with
relationship conflict among studies on top management teams was
significantly lower than among the studies on non–top manage-
ment teams. Since a weaker correlation between task and relation-
ship conflicts is related to a more positive relationship between
task conflict and group performance, an alternative explanation for
why task conflicts in top management teams are more positively
related to group performance is that members of top management
teams are better able to prevent task conflict from turning into
relationship conflict. It will be interesting for future research to
investigate why, in top management teams, task and relationship
are more weakly correlated than in non–top management teams. It
might be that members of top management teams are under greater
time constraints and therefore have a greater need to remain task
focused or, alternatively, that members of top management teams
are more politically savvy (Lazear & Rosen, 1981) and therefore
better able to prevent task conflicts from escalating into relation-
ship conflicts.
Task type. In contrast to the findings of De Dreu and Wein-
gart (2003b), task type was not found to moderate the association
between task conflict and group outcomes (even though we made
the same coding decisions). Similarly, we did not find support for
task type moderating the stable negative effect of process conflict
on group outcomes. Although the WLS regression analyses
showed that when controlling for other moderators, task type did
not moderate the association between relationship conflict and
group outcomes, a replication of the subgroup analyses by De Dreu
and Weingart showed that, compared to studies in which groups
worked on mixed tasks, relationship conflict was less negatively
related to group performance among studies in which groups
worked on project tasks. One possible explanation might be that
during project tasks, group members are together for a short and
limited period of time and work relatively independently through-
out the project. This might prevent relationship conflicts from
escalating or persisting over longer time periods and, therefore,
could make relationship conflict less detrimental for group perfor-
mance (Jehn, 1995). Future research should therefore investigate
which specific factors cause outcomes of project tasks to be less
affected by relationship conflicts and how this interacts with other
potential moderating effects.
Cultural context. Finally, controlling for the effects of the
other moderators, we did not find that cultural context affects the
associations between intragroup conflict and group outcomes. In
contrast to our expectations, the relationships between intragroup
conflict and group outcomes, therefore, seem to be stable and
generalizable across different cultural contexts.
Methodological Implications
We also found that differences in the methods employed in past
studies of intragroup conflict may play a role in determining
whether or not the effects of conflict were positively or negatively
related to group outcomes. We found that the association between
conflict and performance depended on the way in which perfor-
mance was operationalized. Compared to overall performance, the
relationship between task conflict and performance was more
positive in studies where performance was operationalized in
terms of financial performance. Additionally, the moderator anal-
373
INTRAGROUP CONFLICT META-ANALYSIS
yses showed that, compared to overall performance, the relation-
ship between task conflict and performance was more positive in
studies where performance was operationalized in terms of deci-
sion quality. Since overall performance measures often include
more subjective evaluations of performance than, for instance,
objective financial performance indicators, these findings suggest
that subjective evaluations of performance might be more suscep-
tible to the negative affect that is triggered by conflict and that may
cause more unfavorable and pessimistic overall performance eval-
uations (e.g., Ferris, Judge, Rowland, & Fitzgibbons, 1994; Mayer,
Gaschke, Braverman, & Evans, 1992). Research has shown that
those who experience negative affect have a more pessimistic
outlook and easily link their negative affect to a certain target
(Isen, Shalker, Clark, & Karp, 1978; Schwarz & Bohner, 1996).
Since financial performance and decision quality are generally
more objective indicators of performance, they are less affected by
these negative biases and result in more positive performance
evaluations, thereby showing a more positive association between
conflict and performance. When controlling for the effects of the
other moderators, we also found that the relationship between task
conflict and group performance was more negative among studies
conducted in the field than among studies conducted in the labo-
ratory or the classroom. Although this effect was only marginally
significant, it suggests that as groups in laboratory settings nor-
mally have a clear common group goal (e.g., finish a student
project) and as group members are only together for a relatively
short period of time, task conflicts may be less likely to escalate
and easier to resolve as members realize their collaboration is
temporary and focus on the accomplishment of the immediate
common goal.
With respect to relationship conflict and process conflict, the
above effects were not found, reflecting their stable negative
relationships with all types of group outcomes. For example, with
respect to relationship conflict, we did not find that the different
measures used to measure relationship conflict or performance
affected the association between relationship conflict and group
performance. Similar and exemplary of the stable negative rela-
tionship of process conflict with group outcomes is the finding that
none of the studies on process conflict that were included in the
current meta-analysis reported a positive association of process
conflict with emergent states and group viability, despite the
different methods used to measure process conflict and group
outcomes. Moreover, 19 of the 24 studies reported a negative
relationship of process conflict with group performance. Not sur-
prisingly, therefore, none of the moderators that we included in
this study affected the direction or the strength of the association
between process conflict and group performance, emergent states,
and group viability. In sum, process conflicts seem to be uniformly
negative for group outcomes.
Limitations and Future Research
Our meta-analysis yields important insights into the effects of
conflict on group outcomes, as well as potential boundary
conditions of these effects. However, there are several limita-
tions to our findings. First and perhaps most important, our
meta-analysis was conducted at the study, and not group, level
of analysis. As such, interpretation of our findings to the group
level of interaction and analysis should be made cautiously to
prevent committing the ecological fallacy of making inferences
at a level of analysis different from the level at which the
meta-analytic results exist (Robinson, 1950). For instance, we
can only conclude that in studies where task conflict and
relationship conflict are highly correlated, task conflict is more
negatively related to team performance. We are unfortunately
unable to conclude whether, in groups in which relationship
conflict and task conflict are both high, team performance will
suffer. Therefore, future research should test this finding on the
group level directly, to allow between-group, rather than
between-study, conclusions to be drawn. Relatedly, because we
could only investigate between-study differences, we were lim-
ited in the moderators we could examine in this article, as, for
many theoretically relevant moderators, such as trust, conflict
management style, and group demography, only a limited num-
ber of studies exist that have examined these moderators.
Therefore, future research would also benefit from further in-
vestigation of theoretically relevant moderators of the conflict–
outcomes relationship.
Another limitation of our study is that the effect sizes for the
relationships with group performance are relatively small.
However, they are comparable to other meta-analyses of the
intragroup conflict literature (e.g., De Dreu & Weingart,
2003b). Furthermore, common method variance may potentially
underlie the relatively strong relationship between intragroup
conflict and proximal outcomes, such as intragroup trust. Future
research, therefore, would benefit from (quasi-)experimental
investigations that examine the relationship between intragroup
conflict and proximal group outcomes more directly. Addition-
ally, we did not find cultural context to moderate the association
between intragroup conflict and group outcomes. Given that we
could examine the moderating effect of cultural context only
indirectly, conflict research would benefit from a more direct
and systematic examination of the effect of cultural context to
investigate whether the findings are truly generalizable across
different cultural contexts. Finally, since the results from mod-
erator analyses do not provide any evidence of a causal rela-
tionship between moderators and outcomes (Cooper, 1998;
Viechtbauer, 2007), future research should aim to better under-
stand exactly how the causal relationships between intragroup
conflict and group outcomes are affected by the moderators
identified in this study (Cooper, 1998).
Future research on conflict would benefit from taking a more
multilevel, process-oriented view of intragroup conflict, including
focusing on, for example, within-group, rather than between-
group, studies of the development and dynamics of intragroup
conflicts over time. Understanding more precisely what happens
within a team when intragroup conflicts occur (who perceives
what issues, who in the group engages in what conflict behaviors,
etc.) and how these dynamics evolve within the team over time
may help provide further insights into how intragroup conflicts
occur and how exactly they may eventually come to positively or
negatively affect group outcomes.
Several promising research directions exist in this area. One
research direction is that of asymmetric conflict perceptions (Jehn,
Rispens, & Thatcher, 2010). By recognizing and better investigat-
ing how members within the same team may come to view the
same conflict in different manners, researchers may be able to
better understand the nuances and dynamics of intragroup con-
374 DE WIT, GREER, AND JEHN
flicts. Another related and interesting future pathway is that of the
dynamics underlying intragroup conflict involvement, or the num-
ber of people involved in the intragroup conflict (Greer, Jehn, &
Lytle, 2009). By understanding the team-level and individual-level
factors that may differentially lead individuals within teams to join
intragroup conflicts, researchers and practitioners may be able to
better understand and manage team conflicts. Last, another inter-
esting research direction would be to focus on the temporal pat-
terns within groups over time in terms of conflict types and
performance (e.g., Gersick, 1988; Jehn & Mannix, 2001). For
example, it could be insightful to look at whether periods of time
in a group when task and relationship co-occur versus do not occur
simultaneously are more or less productive periods. Relatedly,
identifying the tipping points in groups in which task and relation-
ship conflicts start to co-occur would also be interesting (the arise
of asymmetric perceptions, emotional interpretations of conflict
situations, etc.).
Future research should identify factors that determine whether
groups are able to separate task from relationship conflicts. More
generally, future research may examine moderators of the relation-
ships between the three types of conflict. One possible factor may
be the level of behavioral integration within the group: the extent
to which group members meet regularly, exchange a significant
amount of information, and are collaborative (Hambrick, 1994).
Behavioral integration seems to go hand in hand with collaborative
communication styles in which group members communicate their
disagreement in a helpful, problem-solving, and nonpunitive man-
ner (e.g., De Dreu & West, 2001; Lovelace, Shapiro, & Weingart,
2001). Moreover, behavioral integration appears to increase trust
among group members (e.g., Polzer, Crisp, Jarvenpaa, & Kim,
2006) as well as a greater understanding of each other’s emotions
during conflict (Yang & Mossholder, 2004). As such, behavioral
integration may reduce misattributions of task conflict and thus
weaken the relation between task and relationship conflict
(Gamero et al., 2008; Mooney et al., 2007; Simons & Peterson,
2000).
Conclusion
The findings of the current meta-analysis offer hope for a less
negative view of intragroup conflict. Whereas groups should be
better off without relationship or process conflicts, we have found
that task conflicts are not necessarily disruptive for group out-
comes. Instead, conditions exist under which task conflict is pos-
itively related to group performance. For example, task conflict is
more positively related to team performance when task conflict
and relationship conflict are weakly correlated, when the conflict
occurs among top management teams rather than teams at lower
levels of the organizational hierarchy, and when performance is
operationalized in terms of financial performance or decision qual-
ity (rather than overall performance). Hereby, the current results
reemphasize the need for future research to adopt a contingency
approach to understand the relationships between intragroup con-
flict and group outcomes.
References
References marked with an asterisk indicate studies included in the
meta-analysis.
*Acun˜ a, S. T., Go´ mez, M., & Juristo, N. (2009). How do personality, team
processes and task characteristics relate to job satisfaction and software
quality? Information and Software Technology, 51, 627– 639. doi:
10.1016/j.infsof.2008.08.006
Adair, W., Brett, J., Lempereur, A., Okumura, T., Shikhirev, P., Tinsley,
C., & Lytle, A. (2004). Culture and negotiation strategy. Negotiation
Journal, 20, 87–111. doi:10.1111/j.1571-9979.2004.00008.x
Adair, W. L., Okumura, T., & Brett, J. M. (2001). Negotiation behavior
when cultures collide: The United States and Japan. Journal of Applied
Psychology, 86, 371–385. doi:10.1037/0021-9010.86.3.371
*Amason, A. C. (1996). Distinguishing the effects of functional and
dysfunctional conflict on strategic decision making: Resolving a paradox
for top management teams. Academy of Management Journal, 39, 123–
148. doi:10.2307/256633
*Amason, A. C., & Mooney, A. C. (1999). The effects of past performance
on top management team conflict in strategic decision making. Interna-
tional Journal of Conflict Management, 10, 340 –359. doi:10.1108/
eb022829
Amason, A. C., & Sapienza, H. J. (1997). The effects of top management
team size and interaction norms on cognitive and affective conflict.
Journal of Management, 23, 495–516.
Amason, A. C., Thompson, K. R., Hochwater, W. A., & Harrison, A. W.
(1995). Conflict: An important dimension in successful management
teams. Organizational Dynamics, 24, 20 –35. doi:10.1016/0090-
2616(95)90069-1
Ancona, D. G., & Caldwell, D. F. (1992). Demography and design:
Predictors of new product team performance. Organization Science, 3,
321–341. doi:10.1287/orsc.3.3.321
Argyris, C. (1962). Interpersonal competence and organizational effective-
ness. Homewood, IL: Dorsey.
Arvey, R. D., & Murphy, K. R. (1998). Performance evaluation in work
settings. Annual Review of Psychology, 49, 141–168. doi:10.1146/
annurev.psych.49.1.141
Ashby, W. R. (1956). An introduction to cybernetics. London, England:
Methuen.
*Ayoko, O. B., Callen, V. J., & Ha¨ rtel, C. E. J. (2008). The influence of
emotional climate on conflict and team members’ reactions to climate.
Small Group Research, 39, 121–149. doi:10.1177/1046496407304921
Balkundi, P., & Harrison, D. A. (2006). Ties, leaders, and time in teams:
Strong inference about network structure’s effects on team viability and
performance. Academy of Management Journal, 49, 49 – 68. doi:
10.5465/AMJ.2006.20785500
*Barrick, M., Stewart, G., Neubert, M., & Mount, M. (1998). Relating
member ability and personality to work-team processes and team effec-
tiveness. Journal of Applied Psychology, 83, 377–391. doi:10.1037/
0021-9010.83.3.377
*Barsade, S. G., Ward, A. J., Turner, J. D. F., & Sonnenfeld, J. A. (2000).
To your heart’s content: A model of affective diversity in top manage-
ment teams. Administrative Science Quarterly, 45, 802– 836. doi:
10.2307/2667020
Baumeister, R. (1998). The self. In D. T. Gilbert, S. T. Fiske, & G. Lindzey
(Eds.), The handbook of social psychology (4th ed., Vol. 1, pp. 680
740). Boston, MA: McGraw-Hill.
*Bayazit, M., & Mannix, E. A. (2003). Should I stay or should I go?
Predicting team members’ intent to remain in the team. Small Group
Research, 34, 290 –321. doi:10.1177/1046496403034003002
Becker, B. J. (1992). Using results from replicated studies to estimate
linear models. Journal of Educational Statistics, 17, 341–362. doi:
10.2307/1165128
*Beersma, B., Hollenbeck, J. R., Conlon, D. E., Humphrey, S. E., Moon,
H., & Ilgen, D. R. (2009). Cutthroat cooperation: The effects of team
role decisions on adaptation to alternative reward structures. Organiza-
tional Behavior and Human Decision Processes, 108, 131–142. doi:
10.1016/j.obhdp.2008.07.002
375
INTRAGROUP CONFLICT META-ANALYSIS
Behfar, K. J., Mannix, E. A., Peterson, R. S., & Trochim, W. M. K. (2002,
June). A multi-faceted approach to intragroup conflict issues of theory
and measurement. Paper presented at the 15th Annual Conference of the
International Association for Conflict Management, Salt Lake City, UT.
Behfar, K. J., Mannix, E. A., Peterson, R. S., & Trochim, W. M. K. (2011).
Conflict in small groups: The meaning and consequences of process
conflict. Small Group Research, 42, 127–146. doi:10.1177/
1046496410389194
*Bendersky, C., & Hays, N. (in press). Status conflict in groups. Organi-
zation Science.
*Bierly, P. E., III, Stark, E. M., & Kessler, E. H. (2009). The moderating
effects of virtuality on the antecedents and outcome of NPD team trust.
Journal of Product Innovation Management, 26, 551–565. doi:10.1111/
j.1540-5885.2009.00680.x
Blake, R. R., & Mouton, J. S. (1984). Solving costly organizational
conflicts. San Francisco, CA: Jossey-Bass.
Bradford, K. (1999). Conflict management in buyer-seller relationships (Un-
published doctoral dissertation). University of Florida, Gainesville, FL.
*Bradford, K. D., Stringfellow, A., & Weitz, B. (2007). The effect of
conflict and knowledge distribution on knowledge work team perfor-
mance. Unpublished manuscript, Department of Marketing, University
of Notre Dame, Notre Dame, IN.
*Bradford, K. D., Stringfellow, A., & Weitz, B. A. (2004). Managing
conflict to improve the effectiveness of retail networks. Journal of
Retailing, 80, 181–195. doi:10.1016/j.jretai.2003.12.002
*Brauckmann, C. M. B. (2007). Some kind of monster: A multilevel
analysis of the moderating effect of commitment, on the relationship
between conflict and individual outcomes (Unpublished master’s thesis).
Leiden University, Leiden, the Netherlands.
Brett, J. M., Adair, W., Lempereur, A., Okumura, T., Shikhiru, P., Tinsley,
C., & Lytle, A. (1998). Culture and joint gains in negotiation. Negoti-
ation Journal, 14, 61– 86. doi:10.1111/j.1571-9979.1998.tb00148.x
Brief, A. P., & Weiss, H. M. (2002). Organizational behavior: Affect in the
workplace. Annual Review of Psychology, 53, 279 –307. doi:10.1146/
annurev.psych.53.100901.135156
Cai, D. A., & Fink, E. L. (2002). Conflict style differences between
individualists and collectivists. Communication Monographs, 69, 67–
87. doi:10.1080/03637750216536
Carnevale, P. J., & Probst, T. M. (1998). Social values and social conflict
in creative problem solving and categorization. Journal of Personality
and Social Psychology, 74, 1300 –1309. doi:10.1037/0022-
3514.74.5.1300
*Chatman, J. A., Polzer, J. T., Barsade, S. G., & Neale, M. A. (1998).
Being different yet feeling similar: The influence of demographic com-
position and organizational culture on work processes and outcomes.
Administrative Science Quarterly, 43, 749 –780. doi:10.2307/2393615
Cheung, M. W. L. (2010). metaSEM: Meta-analysis—A structural equa-
tion modeling approach, R package Version 0.5-1 [Computer software].
Retrieved from http://courses.nus.edu.sg/course/psycwlm/Internet/
Cheung, M. W. L., & Chan, W. (2005). Meta-analytic structural equation
modeling: A two-stage approach. Psychological Methods, 10, 40 – 64.
doi:10.1037/1082-989X.10.1.40
*Choi, J. N., & Sy, T. (2010). Group-level organizational citizenship
behavior: Effects of demographic faultlines and conflict in small groups.
Journal of Organizational Behavior, 31, 1032–1054.
*Conlon, D. E., & Jehn, K. A. (2007). Behind the music: Conflict, perfor-
mance effectiveness, and behavioral outcomes in punk and new wave
rock bands. Unpublished manuscript.
Cooper, H. M. (1998). Synthesizing research: A guide for literature re-
views (3rd ed.). Thousand Oaks, CA: Sage.
*Cunningham, G. B., & Waltemyer, D. S. (2007). The moderating effect of
outcome interdependence on the relationship between task conflict and
group performance. Unpublished manuscript, Department of Health and
Kinesiology, Texas A&M University, College Station, TX.
*Curs¸ue, P. L., & Schruijer, S. G. L. (2010). Does conflict shatter trust or
does trust obliterate conflict? Revisiting the relationships between team
diversity, conflict, and trust. Group Dynamics: Theory, Research, and
Practice, 14, 66 –79. doi:10.1037/a0017104
*DeChurch, L. A., & Marks, M. A. (2001). Maximizing the benefits of task
conflict: The role of conflict management. International Journal of
Conflict Management, 12, 4 –22. doi:10.1108/eb022847
*De Dreu, C. K. W. (2006). When too little or too much hurts: Evidence
for a curvilinear relationship between task conflict and innovation in
teams. Journal of Management, 32, 83–107. doi:10.1177/
0149206305277795
De Dreu, C. K. W. (2008). The virtue and vice of workplace conflict: Food
for (pessimistic) thought. Journal of Organizational Behavior, 29, 5–18.
doi:10.1002/job.474
De Dreu, C. K. W., & Gelfand, M. J. (2008). Conflict in the workplace:
Sources, functions, and dynamics across multiple levels of analysis. In
C. K. W. De Dreu & M. J. Gelfand (Eds.), The psychology of conflict
and conflict management in organizations (pp. 3–54). New York, NY:
Erlbaum.
De Dreu, C. K. W., & Van Knippenberg, D. (2005). The possessive self as
a barrier to conflict resolution: Effects of mere ownership, process
accountability, and self-concept clarity on competitive cognitions and
behavior. Journal of Personality and Social Psychology, 89, 345–357.
doi:10.1037/0022-3514.89.3.345
*De Dreu, C. K. W., & Van Vianen, A. E. M. (2001). Managing relation-
ship conflict and the effectiveness of organizational teams. Journal of
Organizational Behavior, 22, 309 –328. doi:10.1002/job.71
De Dreu, C. K. W., & Weingart, L. R. (2003a). A contingency theory of
task conflict and performance in groups and organizational teams. In M.
West, D. Tjosvold, & K. G. Smith (Eds.), International handbook of
organizational teamwork and cooperative working (pp. 151–166).
Chichester, England: Wiley.
De Dreu, C. K. W., & Weingart, L. R. (2003b). Task versus relationship
conflict, team effectiveness, and team member satisfaction: A meta-
analysis. Journal of Applied Psychology, 88, 741–749. doi:10.1037/
0021-9010.88.4.741
*De Dreu, C. K. W., & West, M. A. (2001). Minority dissent and team
innovation: The importance of participation in decision making. Journal
of Applied Psychology, 86, 1191–1201. doi:10.1037/0021-
9010.86.6.1191
*Desivilya, H. S., & Yagil, D. (2005). The role of emotions in conflict
management: The case of work teams. International Journal of Conflict
Management, 16, 55– 69. doi:10.1108/eb022923
*De Vries, B. (1998). Interdependentie en conflict: Het belang voor interne
commuicatie en teamproductiviteit [Interdependence and conflict: The
relevance for internal communication and team productivity] (Unpub-
lished master’s thesis). University of Amsterdam, Amsterdam, the Neth-
erlands.
Dijkstra, M. T. M., Van Dierendonck, D., & Evers, A. (2005). Responding
to conflict at work and individual well-being: The mediating role of
flight behaviour and feelings of helplessness. European Journal of Work
and Organizational Psychology, 14, 119 –135. doi:10.1080/
13594320444000254
Drake, L. (1995). Negotiation styles in intercultural communication. Inter-
national Journal of Conflict Management, 6, 72–90. doi:10.1108/
eb022756
Duffy, M. K., Shaw, J. D., & Stark, E. M. (2000). Performance and
satisfaction in conflicted interdependent groups: When and how does
self-esteem make a difference? Academy of Management Journal, 43,
772–782. doi:10.2307/1556367
Eisenhardt, K. M., Kahwajy, J. L., & Bourgeois, L. J. (1997). How
management teams can have a good fight. Harvard Business Review, 75,
77– 85.
Eisenhardt, K. M., & Schoonhoven, C. B. (1990). Organizational growth:
376 DE WIT, GREER, AND JEHN
Linking founding team, strategy, environment, and growth among US
semiconductor ventures, 1978 –1988. Administrative Science Quarterly,
35, 504 –529. doi:10.2307/2393315
*Elron, E. (1997). Top management teams within multinational corpora-
tions: Effects of cultural heterogeneity. Leadership Quarterly, 8, 393–
412. doi:10.1016/S1048-9843(97)90021-7
*Ensley, M. (2006). Family businesses can out-compete: As long as they
are willing to question the chosen path. Entrepreneurship Theory and
Practice, 30, 747–754. doi:10.1111/j.1540-6520.2006.00148.x
*Ensley, M. D., & Hmieleski, K. A. (2005). A comparative study of new
venture top management team composition, dynamics and performance
between university-based and independent start-ups. Research Policy,
34, 1091–1105. doi:10.1016/j.respol.2005.05.008
*Ensley, M. D., Pearson, A. W., & Amason, A. C. (2002). Understanding
the dynamics of new venture top management teams: Cohesion, conflict
and new venture performance. Journal of Business Venturing, 17, 365–
386. doi:10.1016/S0883-9026(00)00065-3
*Ensley, M. D., Pearson, A. W., & Sardeshmukh, S. R. (2007). The
negative consequences of pay dispersion in family and non-family top
management teams: An exploratory analysis of new venture, high-
growth firms. Journal of Business Research, 60, 1039 –1047. doi:
10.1016/j.jbusres.2006.12.012
Evan, W. (1965). Conflict and performance in R&D organizations. Indus-
trial Management Review, 7, 37– 46.
*Farh, J. L., Lee, C., & Farh, C. I. C. (2010). Task conflict and team
creativity: A question of how much and when. Journal of Applied
Psychology, 95, 1173–1180. doi:10.1037/a0020015
Ferris, G. R., Judge, T. A., Rowland, K. M., & Fitzgibbons, D. E. (1994).
Subordinate influence and the performance evaluation process: Test of a
model. Organizational Behavior and Human Decision Processes, 58,
101–135. doi:10.1006/obhd.1994.1030
Frijda, N. H. (1993). The place of appraisal in emotion. Cognition and
Emotion, 7, 357–387. doi:10.1080/02699939308409193
Fu, J. H. Y., Morris, M. W., Lee, S. L., Chao, M., Chiu, C. Y., & Hong,
Y. Y. (2007). Epistemic motives and cultural conformity: Need for
closure, culture, and context as determinants of conflict judgments.
Journal of Personality and Social Psychology, 92, 191–207. doi:
10.1037/0022-3514.92.2.191
Gabrielidis, C., Stephan, W. G., Ybarra, O., Pearson, V. M. D., & Villareal,
L. (1997). Preferred styles of conflict resolution: Mexico and the United
States. Journal of Cross-Cultural Psychology, 28, 661– 677. doi:
10.1177/0022022197286002
Galbraith, J. R. (1973). Designing complex organizations. Reading, MA:
Addison-Wesley.
*Gamero, N., Gonza´ lez-Roma´ , V., & Peiro´ , J. M. (2008). The influence of
intra-team conflict on work teams’ affective climate: A longitudinal
study. Journal of Occupational and Organizational Psychology, 81,
47– 69.
Gardner, D. B. (1998). Effects of conflict types and power style use among
health professionals in interdisciplinary team collaboration (Unpub-
lished doctoral dissertation). George Mason University, Fairfax, VA.
Gelfand, M. J., Nishii, L. H., Holcombe, K., Dyer, N., Ohbuchi, K., &
Fukumo, M. (2001). Cultural influences on cognitive representations of
conflict: Interpretations of conflict episodes in the United States and
Japan. Journal of Applied Psychology, 86, 1059 –1074.
Gersick, C. J. G. (1988). Time and transition in work teams: Toward a new
model of group development. Academy of Management Journal, 31,
9 – 41.
Gladstein, D. L. (1984). A model of task group effectiveness. Administra-
tive Science Quarterly, 29, 499 –517.
*Goncalo, J. A., Polman, E., & Maslach, C. (2010). Can confidence come
too soon? Collective efficacy, conflict and group performance over time.
Organizational Behavior and Human Decision Processes, 113, 13–24.
Greer, L. L., Caruso, H. M., & Jehn, K. A. (in press). The bigger they are,
the harder they fall: Linking team power, conflict, congruence, and team
performance. Organizational Behavior and Human Decision Processes.
Greer, L. L., & Jehn, K. A. (2007). The pivotal role of emotion in
intragroup process conflict: An examination of the nature, causes, and
effects of process conflict. Research on Managing Groups and Teams,
10, 23– 45.
*Greer, L. L., Jehn, K. A., & Lytle, A. (2009, August). Who’s fighting?
The effects of intragroup conflict involvement on team outcomes.
Paper presented at the conference of the Academy of Management,
Chicago, IL.
Greer, L. L., Jehn, K. A., & Mannix, E. A. (2008). Conflict transformation:
An exploration of the inter-relationships between task, relationship, and
process conflict. Small Group Research, 39, 278 –302.
*Greer, L. L., Jehn, K. A., & Thatcher, S. M. B. (2011). Faultline
token-splits: Effects on conflict and performance. Unpublished manu-
script, Work and Organizational Psychology, University of Amsterdam,
Amsterdam, the Netherlands.
*Greer, L. L., Jehn, K. A., Thatcher, S. M. B., & Mannix, E. A. (2011). The
effect of trust on conflict and performance in groups split by demo-
graphic faultlines. Unpublished manuscript, Work and Organizational
Psychology, University of Amsterdam, Amsterdam, the Netherlands.
Greer, L. L., & van Kleef, G. A. (2010). Equality versus differentiation:
The effects of power dispersion on social interaction. Journal of Applied
Psychology, 95, 1032–1044.
Guetzkow, H., & Gyr, J. (1954). An analysis of conflict in decision-making
groups. Human Relations, 7, 367–381.
Hackman, J. R., & Wageman, R. (2005). A theory of team coaching.
Academy of Management Review, 30, 269 –287.
Hambrick, D. C. (1994). Top management groups: A conceptual integra-
tion and reconsideration of the “team” label. In L. L. Cummings & B. M.
Staw (Eds.), Research in organizational behavior (Vol. 16, pp. 171–
213). Greenwich, CT: JAI Press.
Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis.
San Diego, CA: Academic Press.
Heugens, P. P. M. A. R., & Lander, M. W. (2009). Structure! Agency! (and
other quarrels): A meta-analysis of institutional theories of organization.
Academy of Management Journal, 52, 61– 85.
*Hinds, P. J., & Mortensen, M. (2005). Understanding conflict in geo-
graphically distributed teams: The moderating effects of shared identity,
shared context, and spontaneous communication. Organization Science,
16, 290 –307.
Hofstede, G. (2001). Culture’s consequences: Comparing, values, behav-
iors, institutions, and organizations across nations (2nd ed.). Thousand
Oaks, CA: Sage.
*Homan, A. C., Van Knippenberg, D., Van Kleef, G. A., & De Dreu,
C. K. W. (2007). Interacting dimensions of diversity: Cross-
categorization and the functioning of diverse work groups. Group Dy-
namics: Theory, Research, and Practice, 11, 79 –94.
*Hsu, J.-L., Chou, H.-W., Hwang, W.-Y., & Chou, S.-B. (2008). A
two-dimension process in explaining learners’ collaborative behaviors in
CSCL. Educational Technology & Society, 11, 4, 66– 80.
Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis: Cor-
recting error and bias in research findings. Beverly Hills, CA: Sage.
Hunter, J. E., & Schmidt, F. L. (2000). Fixed effects vs. random effects
meta-analysis models: Implications for cumulative knowledge in psy-
chology. International Journal of Selection Assessment, 8, 275–292.
Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Cor-
recting error and bias in research findings (2nd ed.). Thousand Oaks,
CA: Sage.
Isen, A. M., Shalker, T. E., Clark, M. S., & Karp, L. (1978). Affect,
accessibility of material in memory, and behavior: A cognitive loop?
Journal of Personality and Social Psychology, 36, 1–12.
*Janssen, O., Van de Vliert, E., & Veenstra, C. (1999). How task and
377
INTRAGROUP CONFLICT META-ANALYSIS
person conflict shape the role of positive interdependence in manage-
ment groups. Journal of Management, 25, 117–141.
*Jehn, K. A. (1994). Enhancing effectiveness: An investigation of advan-
tages and disadvantages of value-based intragroup conflict. International
Journal of Conflict Management, 5, 223–238.
Jehn, K. A. (1995). A multimethod examination of the benefits and
detriments of intragroup conflict. Administrative Science Quarterly, 40,
256 –282.
Jehn, K. A. (1997). Qualitative analysis of conflict types and dimensions in
organizational groups. Administrative Science Quarterly, 42, 530 –557.
Jehn, K. A., & Bendersky, C. (2003). Intragroup conflict in organizations:
A contingency perspective. Research in Organizational Behavior, 25,
189 –244.
*Jehn, K. A., & Bezrukova, K. (2007). The effects of faultline activation on
coalition formation, conflict, and group outcomes. Unpublished manu-
script, Institute for Psychological Research, Leiden University, Leiden,
the Netherlands.
*Jehn, K. A., Chadwick, C., & Thatcher, S. M. B. (1997). To agree or not
agree: The effects of value congruence, member diversity, and conflict
on workgroup outcomes. International Journal of Conflict Management,
8, 287–305.
*Jehn, K. A., Greer, L. L., Levine, S., & Szulanski, G. (2008). The effects
of conflict types, dimensions, and emergent states on group outcomes.
Group Decision and Negotiation, 17, 465– 495.
*Jehn, K. A., & Mannix, E. A. (2001). The dynamic nature of conflict: A
longitudinal study of intragroup conflict and group performance. Acad-
emy of Management Journal, 44, 238 –251.
*Jehn, K. A., Northcraft, G., & Neale, M. A. (1999). Why differences make
a difference: A field study of diversity, conflict, and performance in
workgroups. Administrative Science Quarterly, 44, 741–763.
Jehn, K. A., Rispens, S., & Thatcher, S. (2010). The effects of conflict
asymmetry on workgroup and individual outcomes. Academy of Man-
agement Journal, 53, 596 – 616.
*Jordan, P. J., & Troth, A. C. (2004). Managing emotions during team
problem solving: Emotional intelligence and conflict resolution. Human
Performance, 17, 195–218.
*Jules, C. (2007). Diversity of member composition and team learning in
organizations (Unpublished doctoral dissertation). Case Western Re-
serve University, Cleveland, OH.
*Konradt, U., Andreßen, P., & Ellwart, T. (2009). Self leadership in
organizational teams: A multilevel analysis of moderators and media-
tors. European Journal of Work and Organizational Psychology, 18,
322–346.
Korsgaard, A. M., Jeong, S. S., Mahony, D. M., & Pitariu, A. H. (2008).
A multilevel view of intragroup conflict. Journal of Management, 34,
1222–1252.
*Kurtzberg, T. R. (2000). Creative styles and teamwork: Effects of coor-
dination and conflict on group outcomes (Unpublished doctoral disser-
tation). Northwestern University, Evanston, IL.
*Langfred, C. W. (2007). The downside of self-management: A longitu-
dinal study of the effects of conflict on trust, autonomy, and task
interdependence. Academy of Management Journal, 50, 1217–1234.
*Lau, D., & Murnighan, J. K. (2005). Interaction within teams and sub-
groups: The effects of demographic faultlines. Academy of Management
Journal, 48, 645– 659.
Lazarus, R. S., & Folkman, S. (1984). Stress, appraisal and coping. New
York, NY: Springer.
Lazear, E. P., & Rosen, S. (1981). Rank-order tournaments as optimum
labor contracts. Journal of Political Economy, 89, 841– 864.
*Leslie, L. M. (2007). Putting differences in context: Incorporating the
role of status and cooperation into work unit ethnic composition re-
search (Unpublished doctoral dissertation). University of Maryland,
College Park, MD.
Leung, K., Bond, M. H., Carment, D. W., Krishnan, L., & Liebrand,
W. B. G. (1990). Effects of cultural femininity on preference for meth-
ods of conflict processing: A cross-cultural study. Journal of Experi-
mental Social Psychology, 26, 373–388.
*Li, J. T., & Hambrick, D. C. (2005). Factional groups: A new vantage on
demographic faultlines, conflict, and disintegration in work teams. Acad-
emy of Management Journal, 485, 794 – 813.
*Liang, T. P., Liu, C. C., Lin, T. M., & Lin, B. (2007). Effect of team
diversity on software project performance. Industrial Management &
Data Systems, 107, 636 – 653.
Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis. Thousand
Oaks, CA: Sage.
*Lira, E. M., Ripoll, P., Peiro´ , J. M., & Gonza´ lez, P. (2007). The roles of
group potency and information and communication technologies in the
relationship between task conflict and team effectiveness: A longitudinal
study. Computers in Human Behavior, 23, 2888 –2903.
*Liu, J., Fu, P., & Liu, S. (2009). Conflict in top management teams and
team/firm outcomes: The moderating effect of conflict-handling ap-
proaches. International Journal of Conflict Management, 20, 228 –250.
*Lovelace, K., Shapiro, D. L., & Weingart, L. R. (2001). Maximizing
cross-functional new product teams’ innovativeness and constraint ad-
herence: A conflict communications perspective. Academy of Manage-
ment Journal, 44, 779 –783.
*Mannes, A. E. (2009). An integrative solution to the conflict over conflict
(Unpublished doctoral dissertation). Duke University, Durham, NC.
Marks, M. A., Mathieu, J. E., & Zaccaro, S. J. (2001). A temporally based
framework and taxonomy of team processes. Academy of Management
Review, 26, 356 –376.
Markus, H. R., & Kitayama, S. (1991). Culture and the self: Implications
for cognition, emotions and motivation. Psychological Review, 98, 224 –
253.
*Martinez-Moreno, E., Gonza´ lez-Navarro, P., Zornoza, A., & Ripoll, P.
(2009). Relationship, task and process conflicts on team performance:
The moderating role of communication media. International Journal of
Conflict Management, 20, 251–268.
Matsuo, M. (2006). Customer orientation, conflict, and innovativeness in
Japanese sales departments. Journal of Business Research, 59, 242–250.
Mayer, J. D., Gaschke, Y. N., Braverman, D. L., & Evans, T. W. (1992).
Mood-congruent judgment is a general effect. Journal of Personality
and Social Psychology, 63, 119 –132.
McGrath, J. E. (1984). Groups: Interaction and performance. Englewood
Cliffs, NJ: Prentice-Hall.
*Menon, A., Bharadwaj, S. G., & Howell, R. (1996). The quality and
effectiveness of marketing strategy: Effects of functional and dysfunc-
tional conflict in intraorganizational relationships. Journal of the Acad-
emy of Marketing Science, 244, 299 –313.
*Minichilli, A., Zattoni, A., & Zona, F. (2008). Making boards effective:
An empirical examination of board task performance. British Journal of
Management, 20, 55–74.
*Mohammed, S., & Angell, L. C. (2004). Surface- and deep-level diversity
in workgroups: Examining the moderating effects of team orientation
and team process on relationship conflict. Journal of Organizational
Behavior, 25, 1015–1039.
Mooney, A. C., Holahan, P. J., & Amason, A. C. (2007). Don’t take it
personally: Exploring cognitive conflict as a mediator of affective con-
flict. Journal of Management Studies, 44, 733–758.
*Mortensen, M. (2004). Antecedents and consequences of team boundary
disagreement. Unpublished manuscript, Faculty of Management, McGill
University, Montreal, Quebec, Canada.
*Mortensen, M., & Hinds, P. J. (2001). Conflict and shared identity in
geographically distributed teams. International Journal of Conflict Man-
agement, 123, 212–238.
*Moye, N. A., & Langfred, C. W. (2004). Information sharing and group
conflict: Going beyond decision making to understand the effects of
378 DE WIT, GREER, AND JEHN
information sharing on group performance. International Journal of
Conflict Management, 154, 381– 410.
Murnighan, J. K., & Conlon, D. J. (1991). The dynamics of intense work
groups: A study of British string quartets. Administrative Science Quar-
terly, 36, 165–186.
Nauta, A., & Molleman, E. (2001). [Team conflict and team performance].
Unpublished raw data.
Nemeth, C. (1995). Dissent as driving cognition, attitudes and judgments.
Social Cognition, 13, 273–291.
*Nguyen, R. V. (2007). Conflict in functionally diverse teams (Unpub-
lished doctoral dissertation). Claremont Graduate University, Clare-
mont, CA.
*Nibler, R., & Harris, K. L. (2003). The effects of culture and cohesiveness
on intragroup conflict and effectiveness. Journal of Social Psychology,
143, 613– 631.
Nijdam, N. E. (1998). The functioning of work teams (Unpublished mas-
ter’s thesis). University of Amsterdam, Amsterdam, the Netherlands.
*Okhuysen, G. A., & Jehn, K. (2000, August). The interplay of conflict
types, group process, and group task: An examination of the temporal
effects of intra-group conflict. Paper presented at the conference of the
Academy of Management, Washington, DC.
*Oliver, J., Poling, T. L., & Woehr, D. J. (2008, August). A multilevel
examination of the relationship of intra-team conflict with team viability.
Paper presented at the conference of the Academy of Management,
Anaheim, CA.
Olson, B. J., Parayitam, S., & Bao, Y. (2007). Strategic decision making:
The effects of cognitive diversity, conflict, and trust on decision out-
comes. Journal of Management, 33, 196 –222.
*Papenhausen, C. (2006). Half full or half empty: The effects of top
managers’ dispositional optimism on strategic decision-making and firm
performance. Journal of Behavioral and Applied Management, 7, 103–
115.
*Parayitam, S., & Dooley, R. S. (2007). The relationship between conflict
and decision outcomes: Moderating effects of cognitive- and affect-
based trust in strategic decision-making teams. International Journal of
Conflict Management, 18, 42–73.
*Parayitam, S., Olson, B. J., & Bao, Y. (2010). Task conflict, relationship
conflict and agreement seeking behavior in Chinese top management
teams. International Journal of Conflict Management, 21, 94 –116.
*Parry, M. E., Song, M., & Spekman, R. E. (2008). Task conflict, inte-
grative potential, and conflict management strategies in joint ventures.
IEEE Transactions on Engineering Management, 55, 201–218.
*Passos, A., & Caetano, A. (2005). Exploring the effects of intragroup
conflict and past performance feedback on team effectiveness. Journal
of Managerial Psychology, 20, 231–244.
*Patrick, R. R. (1997). Teams and conflict management style: The moderating
effect of conflict management style on the relationship between the type of
conflict and team effectiveness in continuous work teams (Unpublished
doctoral dissertation). University of Nebraska, Lincoln, NE.
Pelled, L. H. (1996). Demographic diversity, conflict, and work team
outcomes: An intervening process theory. Organization Science, 7,
615– 631.
*Pelled, L. H., Eisenhardt, K. M., & Xin, K. R. (1999). Exploring the black
box: An analysis of work team diversity, conflict, and performance.
Administrative Science Quarterly, 44, 1–28.
*Peterson, R. S., & Behfar, K. J. (2003). The dynamic relationship between
performance feedback, trust, and conflict in groups: A longitudinal
study. Organizational Behavior and Human Decision Processes, 92,
102–112.
*Polzer, J. T., Crisp, C. B., Jarvenpaa, S. L., & Kim, J. W. (2006).
Extending the faultline model to geographically dispersed teams: How
co-located subgroups can impair group functioning. Academy of Man-
agement Journal, 49, 679 – 692.
*Polzer, J. T., Milton, L. P., & Swann, W. B. (2002). Capitalizing on
diversity: Interpersonal congruence in small work groups. Administra-
tive Science Quarterly, 47, 296 –324.
Pondy, L. R. (1967). Organizational conflict: Concepts and models. Ad-
ministrative Science Quarterly, 12, 296 –320.
*Porter, T. W., & Lilly, B. S. (1996). The effects of conflict, trust, and task
commitment on project team performance. International Journal of
Conflict Management, 7, 361–376.
*Quigley, N. R., Tekleab, A. G., & Tesluk, P. E. (2007). Comparing
consensus- and aggregation-based methods of measuring team-level
variables: The role of relationship conflict and conflict management
processes. Organizational Research Methods, 10, 589 – 608.
*Raver, J. L., & Gelfand, M. J. (2005). Beyond the individual victim:
Linking sexual harassment, team processes, and team performance.
Academy of Management Journal, 48, 387– 400.
*Raver, J. L., & van Knippenberg, D. (2007, April). Openness to diversity
and the informational benefits of gender diversity. In J. L. Raver & D.
van Knippenberg (Chairs), Work group diversity: Sophisticated concep-
tualizations, task-relevant characteristics, and multilevel perspectives.
Symposium conducted at the annual conference of the Society for
Industrial and Organizational Psychology, New York, NY.
Riketta, M. (2008). The causal relation between job attitudes and perfor-
mance: A meta-analysis of panel studies. Journal of Applied Psychology,
93, 472– 481.
*Rispens, S., Greer, L. L., & Jehn, K. A. (2007). It could be worse: A study
on the alleviating roles of trust and connectedness in intragroup con-
flicts. International Journal of Conflict Management, 18, 325–344.
*Rispens, S., Greer, L. L., Jehn, K. A., & Thatcher, S. M. B. (2007). Bring
it on! The positive influence of liking and understanding in relationship
conflicts. Unpublished manuscript, Institute for Psychological Research,
Leiden University, Leiden, the Netherlands.
Rispens, S., Greer, L. L., Jehn, K. A., & Thatcher, S. M. B. (in press). How
relational closeness buffers the effect of relationship conflict on helpful
and deviant group behaviors. Negotiation and Conflict Management
Research.
Robinson, W. (1950). Ecological correlations and the behavior of individ-
uals. American Sociological Review, 15, 351–357.
Rothstein, H. R., Sutton, A. J., & Borenstein, M. (Eds.). (2005). Publica-
tion bias in meta-analysis: Prevention, assessment and adjustments.
Sussex, England: Wiley.
*Rupert, J., & Jehn, K. A. (2009a, August). Subgroup perceptions, conflict,
and team learning. Paper presented at the conference of the International
Association of Conflict Management, Chicago, IL.
*Rupert, J., & Jehn, K. A. (2009b). When subgroups fuse and divide:
Effects of faultlines on team learning and performance. Unpublished
manuscript, Institute for Psychological Research, Leiden University,
Leiden, the Netherlands.
*Rupert, J., & Meurs, B. (2007). Is het geheel meer dan de som der delen?
De invloed van sociaal categorische en informationele breuklijnen op de
prestatie van professionele voetbalteams [Is the whole more than the
sum of the parts? The influence of social category and informational
faultlines on the performance of professional soccer teams] (Unpub-
lished master’s thesis). Leiden University, Leiden, the Netherlands.
Sanchez-Burks, J., Neuman, E. J., Ybarra, O., Kopelman, S., Park, H., &
Goh, K. (2008). Folk wisdom about the effects of relationship conflict.
Negotiation and Conflict Management Research, 1, 53–76.
Schmidt, F. L., & Le, H. (2004). Software for the Hunter–Schmidt meta-
analysis methods. Iowa City: Department of Management and Organi-
zation, University of Iowa.
Schulz-Hardt, S., Brodbeck, F. C., Mojzisch, A., Kerschreiter, R., & Frey,
D. (2006). Group decision making in hidden profile situations: Dissent
as a facilitator for decision quality. Journal of Personality and Social
Psychology, 91, 1080 –1093.
Schwarz, N., & Bohner, G. (1996). Feelings and their motivational impli-
cations: Moods and the action sequence. In P. M. Gollwitzer & J. A.
379
INTRAGROUP CONFLICT META-ANALYSIS
Bargh (Eds.), The psychology of action: Linking cognition and motiva-
tion to behavior (pp. 119 –145). New York, NY: Guilford Press.
Schweiger, D. M., Sandberg, W. R., & Rechner, P. L. (1989). Experiential
effects of dialectical inquiry, devil’s advocacy, and consensus ap-
proaches to strategic decision making. Academy of Management Jour-
nal, 32, 745–772.
Schwenk, C. R. (1990). Effects of devil’s advocacy and dialectical inquiry
on decision making: A meta-analysis. Organizational Behavior and
Human Decision Processes, 47, 161–176.
*Sempere, J., Gonza´ lez-Roma´ , V., & Peiro´ , J. M. (2007, May). Diversity
and performance in work teams: Testing some hypotheses from the
categorization-elaboration. Poster session presented at the 13th Euro-
pean Congress of Work and Organizational Psychology, Stockholm,
Sweden.
*Sessa, V. I. (1993). Conflict within small decision-making and problem
solving teams: A process model (Unpublished doctoral dissertation).
New York University, New York, NY.
Shaw, J. D., Zhu, J., Duffy, M. K., Scott, K. L., Shih, H. A., & Susanto, E.
(2011). A contingency model of conflict and team effectiveness. Journal
of Applied Psychology, 96, 391– 400.
*Simons, T., Pelled, L. H., & Smith, K. A. (1999). Making use of
difference: Diversity, debate, and decision comprehensiveness in top
management teams. Academy of Management Journal, 42, 662– 673.
*Simons, T. L., & Peterson, R. S. (2000). Task conflict and relationship
conflict in top management teams: The pivotal role of intragroup trust.
Journal of Applied Psychology, 85, 102–111.
*Stalmeijer, R. E., Gijselaers, W. H., Wolfhagen, I. H. A. P., Harendza, S.,
& Scherpbier, A. J. J. A. (2007). How interdisciplinary teams can create
multi-disciplinary education: The interplay between team processes and
educational quality. Medical Education, 41, 1059 –1066.
*Stark, E. M., & Bierly, P. E., III. (2009). An analysis of predictors of team
satisfaction in product development teams with differing levels of vir-
tualness. R&D Management, 39, 461– 472.
Staw, B. M., Sandelands, L. E., & Dutton, J. E. (1981). Threat-rigidity
effects in organizational behavior: A multilevel analysis. Administrative
Science Quarterly, 26, 501–524.
Steel, P. D., & Kammeyer-Mueller, J. D. (2002). Comparing meta analytic
moderator estimation techniques under realistic conditions. Journal of
Applied Psychology, 87, 96 –111.
Swann, W. B., Jr., Polzer, J. T., Seyle, D. C., & Ko, S. J. (2004). Finding
value in diversity: Verification of personal and social self-views in
diverse groups. Academy of Management Review, 29, 9 –27.
*Talaulicar, T., Grundei, J., & van Werder, A. (2005). Strategic decision
making in start-ups: The effect of top management team organization
and processes on speed and comprehensiveness. Journal of Business
Venturing, 20, 519 –541.
Tekleab, A. G., Quigley, N. R., & Tesluk, P. E. (2009). A longitudinal
study of team conflict, conflict management, cohesion, and team effec-
tiveness. Group & Organizational Management, 34, 170 –205.
*Thatcher, S. M. B., Jehn, K. A., & Chadwick, C. (2007). What makes a
difference? The impact of individual demographic differences, group
diversity, and conflict on individual performance. Unpublished manu-
script, Management Information Systems Department, University of
Arizona, Tucson, AZ.
*Thatcher, S. M. B., Jehn, K. A., & Zanutto, E. (2003). Cracks in diversity
research: The effects of diversity faultlines on conflict and performance.
Group Decision and Negotiation, 12, 217–241.
Tjosvold, D. (2008). The conflict-positive organization: It depends upon
us. Journal of Organizational Behavior, 29, 19 –28.
*Tjosvold, D., Law, K. S., & Sun, H. (2006). Conflict in Chinese teams:
Conflict types and conflict management approaches. Management and
Organization Review, 2, 231–252.
Tushman, M. L., & Nadler, D. A. (1978). Information processing as an
integrating concept in organizational design. Academy of Management
Review, 3, 613– 624.
Van der Vegt, G. S., & Bunderson, J. S. (2005). Learning and performance
in multidisciplinary teams: The importance of collective team identifi-
cation. Academy of Management Journal, 48, 532–547.
Van de Vliert, E., & De Dreu, C. K. W. (1994). Optimizing performance
by conflict simulation. International Journal of Conflict Management, 5,
211–222.
*Van Woerkom, M., & Van Engen, M. L. (2009). Learning from conflicts?
The relations between task and relationship conflicts, team learning, and
team performance. European Journal of Work and Organizational Psy-
chology, 18, 381– 404.
*Vermeul, L. (1996). Het functioneren van werkteams in organisaties: Een
onderzoek naar de relatie tussen groepscohesie, conflict, prestatie en
satisfactie [The functioning of workteams in organizations: A study into
the relations between group cohesion, conflict, performance, and satis-
faction] (Unpublished master’s thesis). University of Amsterdam, Am-
sterdam, the Netherlands.
Viechtbauer, W. (2007). Accounting for heterogeneity via random-effects
models and moderator analyses in meta-analysis. Journal of Psychology,
215, 104 –121.
Viechtbauer, W. (2010a). Conducting meta-analyses in R with the metafor
package. Journal of Statistical Software, 36, 1– 48.
Viechtbauer, W. (2010b). Metafor meta-analysis package for R, Version
1.4-0 [Computer software]. Retrieved from http://CRAN.R-project.org/
packagemetafor.
Viechtbauer, W., & Cheung, M. (2010). Outlier and influence diagnostics
for meta-analysis. Research Synthesis Methods, 1, 112–125.
Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psy-
chometric meta-analysis and structural equations modeling. Personnel
Psychology, 48, 865– 885.
Viswesvaran, C., & Sanchez, J. I. (1998). Moderator search in meta-
analysis: A review and cautionary note on existing approaches. Educa-
tional and Psychological Measurement, 58, 77– 87.
*Vodosek, M. (2007). Intragroup conflict as a mediator between cultural
diversity and work group outcomes. International Journal of Conflict
Management, 18, 345–375.
*Wakefield, R. L., Leidner, D. E., & Garrison, G. (2008). A model of
conflict, leadership, and performance in virtual teams. Information Sys-
tems Research, 19, 434 – 455.
*Wan, D., & Ong, C. H. (2005). Board structure, process and performance:
Evidence from public-listed companies in Singapore. Corporate Gover-
nance: An International Review, 13, 277–290.
*Watson, W., Cooper, D., Torres, M. A. J. L. N., & Boyd, N. G. (2008).
Team processes, team conflict, team outcomes, and gender: An exami-
nation of U.S. and Mexican learning teams. International Journal of
Intercultural Relations, 32, 524 –537.
*Weingart, L. R., Todorova, G., & Cronin, M. A. (2008, August). Repre-
sentational gaps, team integration, and team creativity. Paper presented
at the conference of the Academy of Management, Anaheim, CA.
Whitener, E. M. (1990). Confusion of confidence intervals and credi-
bility intervals in meta-analysis. Journal of Applied Psychology, 75,
315–321.
*Wilkens, R., & London, M. (2006). Relationships between climate, pro-
cess, and performance in continuous quality improvement groups. Jour-
nal of Vocational Behavior, 69, 510 –523.
Wilson, D. B. (2005). Meta-analysis macros for SAS, SPSS, and Stata
[Computer software]. Retrieved from http://mason.gmu.edu/dwilsonb/
ma.html
Winters, N. (1997). Conflict, information sharing, and goal-setting in
teams (Unpublished master’s thesis). University of Amsterdam, Amster-
dam, the Netherlands.
*Wolfe, C. J., & Murthy, U. S. (2005). Negotiation support systems in
380 DE WIT, GREER, AND JEHN
budget negotiations: An experimental analysis. Journal of Management
Information Systems, 22, 351–381.
Yang, J., & Mossholder, K. W. (2004). Decoupling task and relationship
conflict: The role of intragroup emotional processing. Journal of Orga-
nizational Behavior, 25, 589 – 605.
*Yeh, Y. J., & Chou, H. W. (2005). Team composition and learning
behaviors in cross-functional teams. Social Behavior and Personality,
33, 391– 402.
*Zhang, Z. X., Hempel, P. S., & Han, Y. L. (2008, August). Can innova-
tion strategy and decentralization guarantee team performance? Type of
conflict matters. Paper presented at the conference of the Academy of
Management, Anaheim, CA.
*Zhu, J., Shaw, J. D., & Scott, K. L. (2008, August). A contingency model
of conflict and team effectiveness. Paper presented at the conference of
the Academy of Management, Anaheim, CA.
*Zona, F., & Zattoni, A. (2007). Beyond the black box of demography:
Board processes and task effectiveness within Italian firms. Corporate
Governance, 15, 852– 864.
(Appendices follow)
381
INTRAGROUP CONFLICT META-ANALYSIS
Appendix A
Effect Sizes Regarding Group Performance, as Well as Reliability and Moderator Information
Study
Sample
size
Moderator
Effect size Reliability 1
23 4
5
67
a
8910
b
TC RC PC TC RC PC Perf TC–RC TC–PC RC–PC
Mean
TC
Mean
RC
Scale
TC
Scale
RC
Acun˜a, Go´mez, & Juristo
(2009) 35 .19 .14 n.a. n.a. 1.00 .64 C Spain n.a. n.a. n.a. 1–5 1–5 NF 0 E S 1
Amason (1996) 48 .09 .38 .79 .86 .91 .38 DM USA TMT 2.51 1.93 1–5 1–5 F 0 DQ S 1
Amason & Mooney (1999) 44 .21 .37 .73 .88 1.00 .42 DM USA TMT 2.97 1.99 1–5 1–5 F 0 FFP Ob 1
Ayoko, Callen, & Ha¨ rtel
(2008) 97 .86 .87 .67 Mix Australia n.a. n.a. n.a. 1–5 1–5 F 0 1
Barrick, Stewart, Neubert,
& Mount (1998) 51 .39 .83 .83 P&S USA Non-TMT 2.75 1–5 F 1 GP S 1
Barsade, Ward, Turner, &
Sonnenfeld (2000) 62 .01 .07 .73 .93 1.00 .84 DM USA TMT 3.54 3.42 1–7 1–7 F 0 FFP Ob 1
Bayazit & Mannix (2003) 28 .15 .04 .77 .79 .85 .56 O USA n.a. 1.87 1.31 1–5 1–5 NF 0 GP S 1
Beersma et al. (2009) 75 .29 .86 1.00 Mix USA n.a. 1.23 1–5 NF 0 DQ Ob 1
Bendersky & Hays (in
press) 44 .10 .08 .04 .74 .79 .74 .78 .59 .64 .69 n.a. USA n.a. 1–7 1–7 NF 0 GP S 1
Bierly, Stark, & Kessler
(2009) 116 .71 .83 .60 C USA & UK n.a. 2.14 1–5 F 1 1
Bradford, Stringfellow, &
Weitz (2004) 81 .81 .94 .61 DM USA n.a. 4.21 2.32 1–7 1–7 NF 1 1
Bradford, Stringfellow, &
Weitz (2007) 196 .05 .06 .84 .91 1.00 .62 C USA n.a. 1.88 1–7 F 1 GP Ob 0
Brauckmann (2007) 33 .28 .02 .37 .85 .74 .92 n.a. .30 .88 .24 C Netherlands n.a. 2.18 1.29 1–5 1–5 F 0 FFP S 0
Chatman, Polzer, Barsade,
& Neale (1998) 14 .05 1.00 1.00 C USA n.a. 2.5 1–7 NF 1 GP Ob 1
Choi & Sy (2010) 62 .44 .40 .85 .94 .89 .58 Mix USA n.a. 2.83 2.97 1–7 1–7 F 0 GP S 1
Conlon & Jehn (2007) 84 .27 .08 .87 .83 1.00 .36 C USA n.a. 1.63 1.78 1–7 1–7 F 1 FFP Ob 0
Cunningham & Waltemyer
(2007) 45 .43 .94 .64 O USA n.a. 3.43 1–7 F 0 GP S 1
Curs¸ue & Schruijer (2010) 174 .01 .20 .76 .80 1.00 .59 P Netherlands n.a. 2.75 1.67 1–5 1–5 NF 0 GP S 1
DeChurch & Marks (2001) 96 .17 .87 1.00 P USA n.a. 1.86 1–5 NF 0 GP S 1
De Dreu (2006)
Study 1 21 .01 .76 1.00 P&S Netherlands Non-TMT 2.64 1–5 F 0 I S 1
Study 2 29 .18 .15 .78 .81 .82 .66 n.a. Netherlands n.a. 2.65 2.17 1–5 1–5 F 0 I S 1
De Dreu & Van Vianen
(2001) 27 .06 .91 .82 n.a. Netherlands n.a. 2.24 1–5 F 0 E S 1
De Dreu & West (2001) 21 .20 .79 1.00 P&S Netherlands Non-TMT 2.86 1–5 F 0 I S 1
(Appendices continue)
382 DE WIT, GREER, AND JEHN
Appendix A (continued)
Study
Sample
size
Moderator
Effect size Reliability 1
23 4
5
67
a
8910
b
TC RC PC TC RC PC Perf TC–RC TC–PC RC–PC
Mean
TC
Mean
RC
Scale
TC
Scale
RC
Desivilya & Yagil (2005) 69 .74 .84 .66 O Israel Non-TMT 2.91 2.89 1–5 1–5 F 1 1
De Vries (1998) 32 .42 .35 .85 .76 .77 .68 Mix Netherlands Mixed 2.68 2.22 1–5 1–5 F 1 GP S 1
Elron (1997) 109 .24 .72 .85 DM USA TMT 3.70 1–5 F 1 GP S 1
Ensley (2006) 108 .07 .79 DM USA TMT 2.65 1–5 1–5 F 0 O S 1
Ensley & Hmieleski
(2005) 256 .19 .21 .79 .85 1.00 .41 DM USA TMT 1.94 2.26 1–5 1–5 F 0 FFP Ob 1
Ensley, Pearson, &
Amason (2002) 70 .27 .10 .79 .85 1.00 .56 DM USA TMT 2.78 2.37 1–5 1–5 F 0 FFP Ob 1
Ensley, Pearson, &
Sardeshmukh (2007) 200 .19 .12 .82 .87 1.00 .58 DM USA TMT 3.01 2.38 1–5 1–5 F 0 FFP Ob 1
Farh, Lee, & Farh (2010) 71 .19 .08 .76 .82 .85 .43 P China Non-TMT 2.61 2.08 1–5 1–5 F 1 I S 1
Gamero, Gonza´ lez-Roma´,
& Peiro´ (2008)
Time 1 156 .89 .89 .78 P&S Spain Non-TMT 2.22 1.77 1–5 1–5 F 0 1
Time 2 156 .92 .91 .81 P&S Spain Non-TMT 2.22 1.79 1–5 1–5 F 0 1
Aggregated 156 .91 .90 .80 P&S Spain Non-TMT 2.22 1.78 1–5 1–5 F 0 1
Goncalo, Polman, &
Maslach (2010)
Study 1, Time 1 42 .15 .80 P USA n.a. NF 0 GP S 1
Study 1, Time 2 42 .34 .70 P USA n.a. NF 0 GP S 1
Study 1 aggregated 42 .10 .75 P USA n.a. NF 0 GP S 1
Study 2, Time 1 72 .15 .11 .02 .85 .82 .81 1.00 .47 .41 .39 P USA n.a. 1.96 1.39 1–5 1–5 NF 0 GP S 1
Study 2, Time 2 72 .07 .23 .30 .82 .82 .86 1.00 .66 .42 .58 P USA n.a. 1.89 1.31 1–5 1–5 NF 0 GP S 1
Study 2, Time 3 72 .07 .14 .07 .83 .81 .84 1.00 .42 .65 .61 P USA n.a. 1.8 1.39 1–5 1–5 NF 0 GP S 1
Study 2, Time 4 72 .04 .12 .01 .88 .86 .90 1.00 .69 .65 .73 P USA n.a. 1.86 1.4 1–5 1–5 NF 0 GP S 1
Study 2, Time 5 72 .03 .23 .11 .86 .84 .93 1.00 .68 .70 .74 P USA n.a. 1.94 1.51 1–5 1–5 NF 0 GP S 1
Study 2 aggregated 72 .02 .07 .02 .85 .83 .88 1.00 .60 .58 .62 P USA n.a. 1.87 1.40 1–5 1–5 NF 0 GP S 1
Greer, Jehn, & Lytle
(2009) 36 .22 .01 .78 .85 1.00 .44 n.a. Australia n.a. 4.49 2.87 1–7 1–7 NF 0 GP S 0
Greer, Jehn, & Thatcher
(2011) 68 .23 .23 .12 .84 .79 .90 1.00 .58 .74 .63 DM USA n.a. 2.44 1.61 1–7 1–7 F 0 DQ Ob 0
Greer, Jehn, Thatcher, &
Mannix (2011)
Study 1 60 .84 .79 .90 1.00 .58 .75 .62 DM USA n.a. 2.43 1.6 1–7 1–7 F 0 DQ Ob 0
Study 2, Time 1 28 .07 .17 .16 .75 .94 .81 1.00 .81 .83 .88 Mix USA n.a. 2.71 1.91 1–7 1–7 NF 0 GP S 0
Study 2, Time 2 28 .01 .24 .21 .83 .89 .91 1.00 .79 .83 .91 Mix USA n.a. 2.68 1.84 1–7 1–7 NF 0 GP S 0
Study 2 aggregated 28 .04 .21 .19 .79 .92 .87 1.00 .80 .83 .90 Mix USA n.a. 2.70 1.88 1–7 1–7 NF 0 GP S 0
Hinds & Mortensen (2005) 35 .23 .12 .82 .89 .84 .75 C Mixed Non-TMT 2.51 2.03 1–5 1–5 F 0 GP S 1
(Appendices continue)
383
INTRAGROUP CONFLICT META-ANALYSIS
Appendix A (continued)
Study
Sample
size
Moderator
Effect size Reliability 1
23 4
5
67
a
8910
b
TC RC PC TC RC PC Perf TC–RC TC–PC RC–PC
Mean
TC
Mean
RC
Scale
TC
Scale
RC
Homan, Van Knippenberg,
Van Kleef, & De
Dreu (2007) 66 1.00 1.00 .46 DM Netherlands n.a. 9.19 0.19 n.a. n.a. NF 0 1
Hsu, Chou, Hwang, &
Chou (2008) 18 .81 P Taiwan n.a. 2.9 1–5 NF 0 1
Janssen, Van de Vliert, &
Veenstra (1999) 102 .27 .51 .80 .87 .80 .46 DM Netherlands TMT 3.48 2.74 1–5 1–5 F 0 DQ S 1
Jehn (1994) 88 .38 .40 .79 .83 1.00 .26 P USA n.a. 2.39 3.02 1–5 1–5 NF 0 GP S 1
Jehn & Bezrukova (2007) 38 .32 .46 .43 .92 .83 .91 1.00 .42 .801 .774 P&S USA n.a. 2.51 1.59 1–5 1–5 NF 0 E Ob 0
Jehn, Chadwick, &
Thatcher (1997) 88 .11 .15 .86 .81 .94 .48 P USA n.a. 4.45 5.35 1–7 1–7 NF 0 GP S 1
Jehn, Greer, Levine, &
Szulanski (2008) 53 .06 .22 .13 .90 .89 .83 1.00 .49 .69 .40 P USA n.a. 3.47 1.48 1–7 1–7 NF 0 E Ob 1
Jehn & Mannix (2001) 51 .16 .10 .12 .94 .94 .93 .93 .55 .48 .63 P USA n.a. 1.87 1.31 1–5 1–5 NF 0 GP S 1
Jehn, Northcraft, & Neale
(1999) 92 .29 .29 .36 .88 .90 .78 1.00 .55 .55 .63 Mix USA Mixed 2.64 2.22 1–5 1–5 F 0 GP Ob 1
Jordan & Troth (2004) 108 .08 .13 .82 .85 1.00 .82 DM Canada n.a. 2.36 1.64 1–5 1–5 NF 0 DQ Ob 1
Jules (2007) 33 .45 .73 .80 n.a. USA Non-TMT F 0 GP S 0
Konradt, Andreßen, &
Ellwart (2009) 40 .39 .25 .90 .89 1.00 .64 P&S Germany Non-TMT 2.67 2.11 1–5 1–5 F 1 GP S 1
Kurtzberg (2000)
Study 1 26 .11 .01 .77 P USA n.a. n.a. n.a. n.a. n.a. F n.a. n.a. n.a. 0
Study 2 119 .03 .01 .18 P USA n.a. n.a. n.a. n.a. n.a. NF n.a. n.a. n.a. 0
Langfred (2007)
Time 1 31 .31 .41 .89 .86 n.a. .82 Mix USA n.a. 3.6 2.99 1–7 1–7 NF 0 GP S 1
Time 2 31 .42 .39 .89 .86 n.a. .91 Mix USA n.a. 3.53 3.22 1–7 1–7 NF 0 GP S 1
Aggregated 31 .37 .40 .89 .86 n.a. .87 Mix USA n.a. 3.57 3.11 1–7 1–7 NF 0 GP S 1
Lau & Murnighan (2005) 79 .22 .29 .80 .87 n.a. .77 P Canada n.a. 2.71 2.03 1–5 1–5 NF 0 GP S 1
Leslie (2007) 121 .11 .01 .02 .85 .90 .93 1.00 .78 .81 .78 Mix USA Mixed 2 2.17 1–5 1–5 F 0 FFP Ob 0
Li & Hambrick (2005) 71 .31 .42 .71 .76 .94 .6 DM China TMT 2.28 2.14 1–4 1–4 F 0 GP S 1
Liang, Liu, Lin, & Lin
(2007) 16 .60 .19 1.00 1.00 .68 .596 C Taiwan Non-TMT n.a. n.a. 1–5 1–5 F 0 GP S 1
Lira, Ripoll, Peiro´, &
Gonza´ lez (2007) 44 .18 .83 n.a. Mix USA n.a. 3.3 1–5 NF 0 E S 1
Liu, Fu, & Liu (2009) 123 .14 .20 .88 .81 .92 .35 DM China TMT 4.01 2.51 1–6 1–6 F 0 E S 1
Lovelace, Shapiro, &
Weingart (2001) 43 .41 .81 .86 C USA Non-TMT 3.15 1–7 F 1 I S 1
Mannes (2009)
Study 1 73 .03 .11 .80 .77 1.00 .67 DM USA n.a. 4.28 1.82 1–7 1–7 NF 0 DQ Ob 0
Study 2 60 .44 .16 .74 .72 1.00 .54 P USA n.a. 0.89 0.17 0–4 0–4 NF 0 DQ Ob 0
(Appendices continue)
384 DE WIT, GREER, AND JEHN
Appendix A (continued)
Study
Sample
size
Moderator
Effect size Reliability 1
23 4
5
67
a
8910
b
TC RC PC TC RC PC Perf TC–RC TC–PC RC–PC
Mean
TC
Mean
RC
Scale
TC
Scale
RC
Martinez-Moreno,
Gonza´ lez-Navarro,
Zornoza, & Ripoll
(2009)
Time 1 66 .12 .06 .11 .77 .69 .70 .90 .68 .46 .54 Mix Spain n.a. 2.13 1.35 1–5 1–5 NF 0 GP S 1
Time 2 66 .18 .34 .34 .83 .85 .79 1.00 .65 .74 .61 Mix Spain n.a. 3.30 1.97 1–5 1–5 NF 0 GP S 1
Aggregated 66 .03 .15 .23 .80 .78 .75 .95 .67 .62 .58 Mix Spain n.a. 2.59 1.00 1–5 1–5 NF 0 GP S 1
Menon, Bharadwaj, &
Howell (1996) 236 .36 .91 .87 DM USA n.a. 5.63 1–7 F 1 GP S 1
Minichilli, Zattoni, & Zona
(2008) 301 .05 .91 .80 DM Italy TMT 2.06 1–5 F 1 GP S 1
Mohammed & Angell
(2004)
Time 1 45 .12 .90 P USA n.a. 1.84 1–5 NF 0 GP S 1
Time 2 45 .20 .92 P USA n.a. 1.9 1–5 NF 0 GP S 1
Aggregated 45 .16 .91 P USA n.a. 1.87 1–5 NF 0 GP S 1
Mortensen (2004) 43 .48 .52 .79 .86 .85 .72 C USA Non-TMT 2.41 2.04 1–5 1–5 F 0 GP S 0
Mortensen & Hinds (2001) 24 .41 .43 .87 .96 .79 .85 C Mixed Non-TMT 2.46 1.89 1–5 1–5 F 0 GP S 1
Moye & Langfred (2004) 38 .40 .40 .87 .93 1.00 .81 P USA n.a. 4.00 3.45 1–9 1–9 NF 0 GP S 1
Nguyen (2007) 41 .49 .50 .80 .90 n.a. .75 Mix USA Mixed 2.72 1.85 1–5 1–5 F 0 GP S 0
Nibler & Harris (2003) 50 .11 .20 .89 .86 1.00 .67 DM Mixed n.a. 3.84 2.84 1–7 1–7 NF 0 DQ Ob 1
Okhuysen & Jehn (2000) 21 .13 .38 .19 P USA n.a. n.a. n.a. n.a. n.a. NF 1 n.a. n.a. 0
Oliver, Poling, & Woehr
(2008) 136 .16 .01 .94 .89 1.00 .43 DM USA n.a. 5.75 1.82 1–7 1–5 NF 0 GP Ob 0
Papenhausen (2006) 35 .24 .29 n.a. n.a. 1.00 .93 DM USA n.a. 3.48 2.76 1–5 1–5 NF 0 E Ob 1
Parayitam & Dooley
(2007) 109 .58 .15 .85 .92 .85 .40 DM USA TMT 2.34 2.05 1–7 1–7 F 0 DQ S 1
Parayitam, Olson, & Bao
(2010) 252 .85 .83 .61 DM China n.a. 3.47 2.90 1–7 1–7 F 0 1
Parry, Song, & Spekman
(2008) 196 .20 .87 1.00 DM USA TMT 2.91 1–10 F 1 FFP Ob 1
Passos & Caetano (2005) 47 .08 .15 .34 .79 .84 .62 1.00 .26 .68 .54 DM Portugal TMT 3.68 1.36 1–7 1–7 F 0 FFP Ob 1
Patrick (1997) 57 .18 .06 .70 P&S USA n.a. n.a. n.a. n.a. n.a. F n.a. E S 0
Pelled, Eisenhardt, & Xin
(1999) 45 .05 .07 .78 .83 .61 .48 C USA Non-TMT n.a. n.a. 1–5 1–5 F 0 GP S 1
Peterson & Behfar (2003)
Time 1 67 .03 .03 .91 .97 .75 P USA n.a. 4.50 2.90 1–9 1–9 NF 0 GP S 1
Time 2 67 .12 .04 .87 .96 .73 P USA n.a. 4.90 3.60 1–9 1–9 NF 0 GP S 1
Aggregated 67 .05 .04 .89 .97 .74 P USA n.a. 4.70 3.25 1–9 1–9 NF 0 GP S 1
Polzer, Crisp, Jarvenpaa,
& Kim (2006) 45 n.a. n.a. .74 P Mixed n.a. 2.51 2.64 1–5 1–5 NF 0 1
(Appendices continue)
385
INTRAGROUP CONFLICT META-ANALYSIS
Appendix A (continued)
Study
Sample
size
Moderator
Effect size Reliability 1
23 4
5
67
a
8910
b
TC RC PC TC RC PC Perf TC–RC TC–PC RC–PC
Mean
TC
Mean
RC
Scale
TC
Scale
RC
Polzer, Milton, & Swann
(2002) 83 .01 .13 .81 .92 1.00 .72 Mix USA n.a. 2.78 2.37 1–5 1–5 NF 0 GP S 1
Porter & Lilly (1996) 80 .35 .82 DM USA n.a. 2.80 1–7 NF 1 DQ S 1
Quigley, Tekleab, &
Tesluk (2007) 53 .24 .94 1.00 Mix USA n.a. 1.82 1–7 NF 0 GP S 1
Raver & Gelfand (2005) 27 .35 .52 .86 .85 1.00 .74 P&S USA Non-TMT 2.63 2.36 1–5 1–5 F 1 FFP Ob 1
Raver & Van Knippenberg
(2007) 38 .23 .06 n.a. n.a. .61 DM Canada n.a. 2.61 1.61 1–5 1–5 NF GP S 0
Rispens, Greer, & Jehn
(2007) Study 2 27 .71 .92 .57 Mix USA n.a. 3.09 2.39 1–7 1–7 F 0 1
Rispens, Greer, Jehn, &
Thatcher (2007) 27 .68 .59 .90 .76 .87 .71 P&S Netherlands Non-TMT 3.33 2.17 1–7 1–7 F 0 GP S 1
Rupert & Jehn (2009a) 67 .30 .26 .15 .91 .88 .86 .88 .69 .78 .78 P&S Netherlands Non-TMT 3.35 2.70 1–7 1–7 F 0 GP S 0
Rupert & Jehn (2009b) 49 .20 .17 .22 .77 .78 .78 .91 .49 .66 .69 DM Netherlands Non-TMT 3.32 2.85 1–7 1–7 F 0 GP S 0
Rupert & Meurs (2007) 17 .38 .29 .36 .80 .85 .82 1.00 .87 .93 .81 O Netherlands Non-TMT 3.85 3.75 1–7 1–7 F 0 GP Ob 0
Sempere, Gonza´ lez-Roma´,
& Peiro´ (2007) 65 .39 .91 .95 P&S Spain n.a. 2.03 1–6 F 0 GP S 0
Sessa (1993) 30 .00 .09 .61 .61 .87 .23 DM USA n.a. 2.70 2.10 1–5 1–5 F 1 DQ S 0
Simons, Pelled, & Smith
(1999) 57 .07 .75 1.00 DM USA TMT 2.90 n.a. F 1 FFP Ob 1
Simons & Peterson (2000) 70 .78 .87 .57 DM USA TMT 2.56 1.85 1–5 1–5 F 0 1
Stalmeijer, Gijselaers,
Wolfhagen, Harendza,
& Scherpbier, (2007) 21 .18 .30 .75 .84 .69 P Netherlands n.a. n.a. n.a. n.a. n.a. F 1 GP S 1
Stark & Bierly (2009) 178 .79 C USA & UK n.a. 2.09 1–5 F 1 0
Talaulicar, Grundei, & van
Werder (2005) 48 .08 .77 .56 DM Germany TMT 4.50 1–5 F 1 O S 1
Thatcher, Jehn, &
Chadwick (2007)
Time 1 144 .70 .92 .83 1.00 .61 .58 .65 Mix USA n.a. 3.47 2.67 1–7 1–7 NF 0 GP S 1
Time 2 144 .09 .13 .06 n.a. n.a. n.a. 1.00 .58 .67 .73 Mix USA n.a. 3.00 2.57 1–7 1–7 NF 0 GP S 1
Aggregated 144 .09 .13 .06 .70 .92 .83 1.00 .60 .63 .69 Mix USA n.a. 3.24 2.62 1–7 1–7 NF 0 GP S 1
Thatcher, Jehn, & Zanutto
(2003) 79 .29 .64 .66 .70 .92 .83 1.00 .56 .66 .81 Mix USA n.a. 2.90 2.54 1–7 1–7 NF 0 GP S 1
Tjosvold, Law, & Sun
(2006) 186 .09 .06 .73 .82 .80 .62 P&S China Non-TMT 3.46 3.01 1–7 1–7 F 0 E S 1
Van Woerkom & Van
Engen (2009) 84 .25 .32 .74 .80 .68 .55 Mix Netherlands n.a. 2.80 2.29 1–5 1–5 F 0 GP S 1
Vermeul (1996) 16 .21 .21 .77 .77 Mix Netherlands Non-TMT 2.33 2.07 1–5 1–5 F 1 E S 1
Vodosek (2007) 76 .41 .42 .45 .76 .93 .87 .84 .75 .84 .83 C USA Non-TMT n.a. n.a. 1–7 1–7 F 0 GP S 1
(Appendices continue)
386 DE WIT, GREER, AND JEHN
Appendix A (continued)
Study
Sample
size
Moderator
Effect size Reliability 1
23 4
5
67
a
8910
b
TC RC PC TC RC PC Perf TC–RC TC–PC RC–PC
Mean
TC
Mean
RC
Scale
TC
Scale
RC
Wakefield, Leidner, &
Garrison (2008)
23 .30 .22 .34 .91 .92 .89 .88 .80 .85 .76 Mix USA &
Korea
Non-TMT 2.84 2.72 1–7 1–7 F 0 GP S 1
Wan & Ong (2005) 212 .01 .06 .01 .77 .80 .73 1.00 .58 .50 .66 DM Singapore TMT 3.91 2.19 1–5 1–5 F 0 FFP Ob 1
Watson, Cooper, Torres, &
Boyd (2008)
142 .83 .81 .64 n.a. USA &
Mexico
n.a. 2.35 1.70 1–5 1–5 NF 0 1
Weingart, Todorova, &
Cronin (2008) 21 .44 .14 .83 .87 .82 .25 C USA n.a. n.a. n.a. n.a. n.a. NF 0 I S 0
Wilkens & London (2006) 8 .17 .00 .95 .91 .63 .50 Mix USA Non-TMT 4.22 2.51 1–7 1–7 F 0 E S 1
Wolfe & Murthy (2005) 87 .79 .78 .33 O USA n.a. NF 1 1
Yeh & Chou (2005) 88 .02 .20 .84 .93 .88 .64 P&S Taiwan n.a. 3.14 2.36 1–5 1–5 F 0 E S 1
Zhang, Hempel, & Hahn
(2008) 101 .12 .11 .17 .84 .90 .84 .82 .70 .66 .74 C China Non-TMT 2.42 2.08 1–5 1–5 F 0 E S 0
Zhu, Shaw, & Scott (2008) 103 .10 .06 .76 .78 1.00 .51 n.a. USA n.a. 1.55 2.11 1–5 1–5 NF 0 GP S 0
Zona & Zattoni (2007) 301 0.00 .86 .75 O Italy TMT 1.73 1–5 F 0 GP S 1
Note. Moderators: 1 association between conflict types; 2 task type; 3 country where study was conducted; 4 organizational level; 5 mean level of task and relationship conflict; 6
field setting versus nonfield setting; 7 conflict scale; 8 performance indicator; 9 objective versus subjective performance indicator; 10 publication status. Abbreviations: C creativity; DM
decision making; DQ decision quality; E effectiveness; F field setting; FFP financial (firm) performance; GP general performance; I innovativeness; Mix mixed set of tasks; n.a.
not applicable; NF nonfield setting; O other; Ob objective; P project; PC process conflict; Perf performance; P&S production and service; RC relationship conflict; S subjective;
TC task conflict; TMT top management team.
a
0Jehn scale, 1 non-Jehn scale.
b
0not published, 1 published.
(Appendices continue)
387
INTRAGROUP CONFLICT META-ANALYSIS
Appendix B
Effect Sizes Between Intragroup Conflict and Trust, Cohesion, Satisfaction, and Commitment
Study
Trust Cohesion Satisfaction Commitment
TC RC PC TC RC PC TC RC PC TC RC PC
Acun˜a, Go´mez, & Juristo (2009) .41 .48 n.a. .53 .35 n.a.
Barrick, Stewart, Neubert, & Mount (1998) .90 .87
Bayazit & Mannix (2003) .16 .55 .83
Bierly, Stark, & Kessler (2009) .64 .47 .89
Bradford, Stringfellow, & Weitz (2004) .59 .60 .89 .41 .54 .84
Brauckmann (2007) .27 .62 .20 .38 .51 .21 .75
Curs¸ue & Schruijer (2010) .32 .39 .75
DeChurch & Marks (2001) .47 .94
De Dreu & Van Vianen (2001) .30 .78
Elron (1997) .56 .77
Ensley & Hmieleski (2005) .37 .21 .84
Ensley, Pearson, & Amason (2002) .12 .24 .83
Ensley, Pearson, & Sardeshmukh (2007) .46 .41 .88
Greer, Jehn, Thatcher, & Mannix (2011)
Study 1 .45 .21 .46 .85 .37 .30 .50 .89 .30 .18 .34 .77
Study 2, Time 1 .45 .45 .60 .94
Study 2, Time 2 .45 .50 .51 .93
Study 2 aggregated .45 .48 .56 .94
Homan, Van Knippenberg, Van Kleef, & De Dreu (2007) .24 .46 .96
Jehn (1994) .12 .60 .88
Jehn & Bezrukova (2007) .50 .53 .52 .91
Jehn, Chadwick, & Thatcher (1997) .19 .50 .92
Jehn, Greer, Levine, & Szulanski (2008) .28 .38 .38 .82
Jehn & Mannix (2001) .22 .17 .19 .82 .24 .19 .19 .94
Jehn, Northcraft, & Neale (1999) .41 .50 .39 .85 .31 .41 .30 .85
Langfred (2007)
Time 1 .52 .60
Time 2 .84 .88
Aggregated .72 .78 .89
Lau & Murnighan (2005) .50 .65 .88
Leslie (2007) .60 .79 .64 .95 .58 .73 .62 .92
Lira, Ripoll, Peiro´ , & Gonza´ lez (2007) .49 .85 .60 .90
Liu, Fu, & Liu (2009) .10 .20 .78
Mannes (2009)
Study 1 .53 .71 .76
Study 2 .23 .14 .87
(Appendices continue)
388 DE WIT, GREER, AND JEHN
Appendix B (continued)
Study
Trust Cohesion Satisfaction Commitment
TC RC PC TC RC PC TC RC PC TC RC PC
Minichilli, Zattoni, & Zona (2008) .00 .76
Oliver, Poling, & Woehr (2008) .69 .57 .96
Papenhausen (2006) .47 .60 n.a.
Parayitam & Dooley (2007) .30 .10 .90 .69 .12 .88
Parayitam, Olson, & Bao (2010) .12 .29 .89
Parry, Song, & Spekman (2008) .18 n.a.
Passos & Caetano (2005) .18 .41 .50 .86
Peterson & Behfar (2003) Time 1 .57 .70 .89
Polzer, Crisp, Jarvenpaa, & Kim (2006) .56 .54 .82
Porter & Lilly (1996) .46 .84 .29 .84
Quigley, Tekleab, & Tesluk (2007) .38 .94 .38 .96
Raver & Gelfand (2005) .48 .56 .77
Rispens, Greer, & Jehn (2007) Study 2 .18 .48 .73
Rispens, Greer, Jehn, & Thatcher (2007) .67 .74 .89
Rupert & Jehn (2009a) .67 .78 .76 .72 .50 .58 .55 .91 .57 .58 .58 .91
Rupert & Jehn (2009b) .24 .34 .30 .71 .13 .50 .32 n.a. .12 .30 .13 .88
Rupert & Meurs (2007) .69 .69 .77 n.a. .59 .58 .59 .82
Simons & Peterson (2000) .36 .62 .89
Stalmeijer, Gijselaers, Wolfhagen, Harendza, &
Scherpbier (2007) .61 .55
Stark & Bierly (2009) .50 1.00
Talaulicar, Grundei, & van Werder (2005) .03 .84
Thatcher, Jehn, & Chadwick (2007)
Time 1 .43 .67 .64 n.a. .41 .66 .61 n.a.
Time 2 .31 .58 .63 n.a. .32 .60 .61 n.a.
Aggregated .37 .63 .63 n.a. .37 .63 .61 n.a.
Vermeul (1996) .30 .37 .75 .39 .23 .74 .30 .11 .82
Vodosek (2007) .47 .61 .60 .92 .44 .60 .57 .78
Watson, Cooper, Torres, & Boyd (2008) .31 .48 .83
Wolfe & Murthy (2005) .11 .10 .73
Yeh & Chou (2005) .25 .42 .93
Zhu, Shaw, & Scott (2008) .31 .35 .73
Note. n.a. not applicable; PC process conflict; RC relationship conflict; TC task conflict.
389
INTRAGROUP CONFLICT META-ANALYSIS
Appendix C
Effect Sizes Between Intragroup Conflict and Identification, Organizational Citizenship
Behavior, Counterproductive Workplace Behavior, and Positive Affect
Study
Identification
Organizational citizenship
behavior
Counterproductive
workplace behavior Positive affect
TC RC PC TC RC PC TC RC TC RC
Ayoko, Callen, & Ha¨ rtel (2008) .49 .63 .71
Choi & Sy (2010) .01 .27 .94
De Dreu & Van Vianen (2001) .22 .83
Desivilya & Yagil (2005) .02 .03 .77
Gamero, Gonza´ lez-Roma´ , & Peiro´
(2008)
Time 1 .59 .63 .92
Time 2 .59 .57 .92
Aggregated .59 .60 .92
Hsu, Chou, Hwang, & Chou (2008) .69 .84
Janssen, Van de Vliert, & Veenstra
(1999) .35 .74 .91
Jehn & Bezrukova (2007) .07 .19 .05 .88
Leslie (2007) .25 .33 .24 .86
Mannes (2009) Study 2 .27 .19 .90
Menon, Bharadwaj, Howell (1996) .61 .84
Mortensen (2004) .45 .62 .80
Mortensen & Hinds (2001) .44 .47 .93
Nguyen (2007) .15 .21 .76
Polzer, Milton, & Swann (2002) .24 .53 .92
Raver & Gelfand (2005) .00 .14 .88
Rispens, Greer, & Jehn (2007)
Study 2 .30 .29 n.a. .36 .43 n.a.
Sessa (1993) .42 .31 .29 .00
Vermeul (1996) .86
Watson, Cooper, Torres, & Boyd
(2008)
.31 .54 .85 .41 .55 .84
Note. n.a. not applicable; PC process conflict; RC relationship conflict; TC task conflict.
Received March 29, 2010
Revision received June 9, 2011
Accepted June 20, 2011
390 DE WIT, GREER, AND JEHN
... Research is needed to integrate both streams to provide information about the interconnection between both concepts and to better understand and manage workplace conflict. Conflict type research is about the content of the conflict (Jehn et al., 2012), whereas conflict management research is about the style of managing the conflict (Tjosvold, 2008). While conflict type research examines the source and level of conflict, conflict management research examines how the disputants interact to manage conflict (DeChurch et al., 2013). ...
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Purpose-Rising expectations for exceptional customer experiences demand strategic amalgamation of cross-functional, customer-focused teams (marketing/sales/service departments). However, the long history of interface conflicts between functional teams continues to attract research attention. Past research has given more attention to conflicts between marketing and sales teams than to triadic interface conflict between custom-focused teams and their sub-conflicts in a business-to-business (B2B) sales process. The purpose of this research paper is to quantify the triadic interface conflicts and associated sub-conflicts between customer-focused teams, discuss conflict resolution strategies and perform a sensitivity analysis (SA) to give a fuller account of functional team conflict. Design/methodology/approach-Multi-criteria decision-making (MCDM) based in the analytic hierarchy process (AHP) is proposed for identifying and resolving conflicts in customer-focused team interfaces. A group of 30 managers of a large electronics company participated in this research. The authors collected the data from customer-focused team managers during training sessions on interface conflicts and conflict management/ resolution strategies. The authors perform SA to test the robustness of conflict resolution strategy rankings. Findings-The findings reveal that managers adjudge task as the most crucial conflict attribute driving teams apart, followed by lack of communication. For the sub-conflicts, managers considered how to do the task as the most important conflict attribute, followed by lack of regular meetings. For conflict resolution strategies, managers regarded collaboration or integration as the overall best strategy, followed by compromise. Leveraging the AHP-based MCDM to resolve customer-focused team interface conflicts provides managers with the confidence in the consistency and the robustness of these solutions. By testing the SA, it is also discovered that the final outcome stayed robust (stable) regardless when the priorities of the main criteria influencing the decision are increased and decreased by 5% in every combinations. Research limitations/implications-This study examined only a large B2B company in the electronics industry in African and Middle East settings, focusing on interface conflicts among customer-focused departments. Future research could address these limitations. Practical implications-This paper advances our understanding of customer-focused team interface conflicts in a B2B sales process. It also provides valuable insights on effective management of major and sub-interface conflicts. This paper provides a framework for and practical insights into how interface conflicts that are prevalent in marketing, sales and service sectors can be resolved to improve customer experience and business performance. Originality/value-This study contributes to the literature by developing an AHP-based MCDM, which not only extends our conceptual understanding of the interface conflicts between customer-focused teams by emphasizing their triadic nature but also provides valuable strategies and insights into the practical resolution of such conflicts in a B2B firm's sales process. Methodologically, SA is valuable to ensuring the robustness of the conflict resolution strategies' rankings that will influence relevant pragmatic decision-making.
... Since poor handling of team conflict can lead to disharmony between teams within the workplace (de Wit et al., 2012;Bradley et al., 2015), Lee et al. (2018) note that it behooves managers to understand how team conflict impacts team dynamics, team conflict and performance. Nesterkin and Porterfield (2016) define conflict resolution as the degree to which team members behave to reduce tensions and anxiety. ...
Article
Purpose Rising expectations for exceptional customer experiences demand strategic amalgamation of cross-functional, customer-focused teams (marketing/sales/service departments). However, the long history of interface conflicts between functional teams continues to attract research attention. Past research has given more attention to conflicts between marketing and sales teams than to triadic interface conflict between custom-focused teams and their sub-conflicts in a business-to-business (B2B) sales process. The purpose of this research paper is to quantify the triadic interface conflicts and associated sub-conflicts between customer-focused teams, discuss conflict resolution strategies and perform a sensitivity analysis (SA) to give a fuller account of functional team conflict. Design/methodology/approach Multi-criteria decision-making (MCDM) based in the analytic hierarchy process (AHP) is proposed for identifying and resolving conflicts in customer-focused team interfaces. A group of 30 managers of a large electronics company participated in this research. The authors collected the data from customer-focused team managers during training sessions on interface conflicts and conflict management/resolution strategies. The authors perform SA to test the robustness of conflict resolution strategy rankings. Findings The findings reveal that managers adjudge task as the most crucial conflict attribute driving teams apart, followed by lack of communication. For the sub-conflicts, managers considered how to do the task as the most important conflict attribute, followed by lack of regular meetings. For conflict resolution strategies, managers regarded collaboration or integration as the overall best strategy, followed by compromise. Leveraging the AHP-based MCDM to resolve customer-focused team interface conflicts provides managers with the confidence in the consistency and the robustness of these solutions. By testing the SA, it is also discovered that the final outcome stayed robust (stable) regardless when the priorities of the main criteria influencing the decision are increased and decreased by 5% in every combinations. Research limitations/implications This study examined only a large B2B company in the electronics industry in African and Middle East settings, focusing on interface conflicts among customer-focused departments. Future research could address these limitations. Practical implications This paper advances our understanding of customer-focused team interface conflicts in a B2B sales process. It also provides valuable insights on effective management of major and sub-interface conflicts. This paper provides a framework for and practical insights into how interface conflicts that are prevalent in marketing, sales and service sectors can be resolved to improve customer experience and business performance. Originality/value This study contributes to the literature by developing an AHP-based MCDM, which not only extends our conceptual understanding of the interface conflicts between customer-focused teams by emphasizing their triadic nature but also provides valuable strategies and insights into the practical resolution of such conflicts in a B2B firm’s sales process. Methodologically, SA is valuable to ensuring the robustness of the conflict resolution strategies’ rankings that will influence relevant pragmatic decision-making.
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