LIT REVIEW

INSTRUCTIONS FOR PAPER ATTACHED AND ARTICLES

INSTUCTIONS FOR LIT. REVIEW PAPER

Your literature review will be a 6- to 8-page Microsoft Word

7 scholarly sources ATTACHED PDF FILES

Access a minimum of seven appropriate peer-reviewed articles in the online library resources. Read the articles to analyze the major themes of team leadership and conflict-competent teams.

Your selected articles should discuss some aspects of team conflict, conflict resolution, and the leader’s role in resolving conflict; team development and team conflict dynamics; development of an ethical and diverse culture; as well as other relevant theoretical and practical approaches discussed in the course. Ensure that your selected articles reflect a blend of research that has contributed to the generation of applicable theories as well as a critique and affirmation of the specific theories.

1. Develop an introduction on the background of the conflict management approaches and strategies that leaders can use to resolve team conflict.

2. Analyze all articles and describe the key themes that emerge across the selected articles.

3. Synthesize the material and summarize the patterns of similarities and differences regarding how each of the authors has presented each theme.

4. On the basis of your analysis of the literature, conclude by evaluating the impact of leadership approaches and the development of conflict-competent teams.

The purpose of this literature review is for you to practice:

· Critically reading and understanding the articles and how to tie the concepts together

· Synthesizing the various concepts and results of the review

· Writing a collective analysis of the articles that will help you address the topic of the final assignment

Remember, a literature review is not simply a summary of the articles but a synthesis of the many ideas and concepts presented in the various articles.

Your literature review will be a 6- to 8-page Microsoft Word document written in APA format and utilize at least seven scholarly sources.

Your paper should be written in a clear, concise, and organized manner; demonstrate ethical scholarship in accurate representation and attribution of sources; and display accurate spelling, grammar, and punctuation.

GRADING CRITERIA THAT NEEDS TO BE MET

Grading Criteria

Maximum Points

Access a minimum of seven appropriate peer-reviewed articles in the Argosy University online library resources. Read the articles to analyze the major themes of team leadership and conflict-competent teams.

Develop an introduction on the background of the team leadership approaches and the development and dynamics of teams that support conflict-competent teams.

Analyze all articles and describe the key themes that emerge across the selected articles.

Synthesize the material and summarize the patterns of similarities and differences regarding how each of the authors has presented each theme.

On the basis of your analysis of the literature, conclude by evaluating the impact of leadership approaches and the development of conflict-competent teams.

Write in a clear, concise, and organized manner; demonstrate ethical scholarship in accurate representation and attribution of sources (i.e., APA); and display accurate spelling, grammar, and punctuation.

Total:

200

Diversity in team

composition

,
relationship conflict and team

leader support on globally
distributed virtual software

development team performance
Vathsala Wickramasinghe and Sahan Nandula

Department of Management of Technology, University of Moratuwa,
Moratuwa, Sri Lanka

Abstract
Purpose – This study aims to investigate whether diversity in team composition leads to relationship
conflict, and, consequently, relationship conflict leads to team performance, and whether team leader
support moderates the negative effects of relationship conflict on team performance.
Design/methodology/approach – For the study, 216 team members working in globally distributed
virtual software development projects responded. To examine the hypothesized relationships,
structural equation modeling with maximum likelihood estimation was performed.
Findings – It was found that diversity in team composition leads to relationship conflict, relationship
conflict leads to team performance and team leader support moderates the latter relationship.
Practical implications – The findings suggest the role of team leaders in reducing the harmful effect
of relationship conflict on team performance. The findings imply the need of providing training to team
leaders to create cohesive teams that deliver on project goals.
Originality/value – Empirical studies on globally distributed virtual teams could provide new
insights into challenges and issues associated with team composition, relationship conflict and team
leader support in achieving higher levels of team performance.

Keywords Knowledge-based systems, Emerging markets, Virtual teams,
Economic and social systems, Global outsourcing

Paper type Research paper

Introduction
Owing to competitive pressures, organizations are forced to find more flexible and
versatile business structures (Bell and Kozlowski, 2002; Peters and Karren, 2009).
Team-based virtual work structures are identified as one of the best means to achieve
this flexibility and versatility (Mishra and Mahanty, 2014; Peters and Karren, 2009;
Saxena and Burmann, 2014). According to Curşeu and Wessel (2005, p. 271), “a virtual
team is a collection of individuals who are geographically, organizationally or otherwise
dispersed and who collaborate, using varying degrees of communication and
information technologies in order to accomplish a specific goal”. Innovations in
information and communication technologies (ICT) have accelerated the growth of
globally distributed virtual software development (GDVSD) or offshore outsourcing of

The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1753-8297.htm

SO
8,2/3

138

Received 8 February 2015
Revised 1 April 2015
15 May 2015
Accepted 27 May 2015

Strategic Outsourcing: An
International Journal
Vol. 8 No. 2/3, 2015
pp. 138-

155

http://dx.doi.org/10.1108/SO-02-2015-0007

software development during the past two decades (Kotlarsky et al., 2007; Mishra and
Mahanty, 2014).

A GDVSD project team is a network of dispersed group of people who work together
toward a common goal and who share together resources, know-how, services and
by-products (Bourgault et al., 2008; Reed and Knight, 2010). For the success of project
teams, organizations expect a higher level of team performance that leads to increased
team effectiveness (such as work quality and ability to meet project goals) and efficiency
(such as adherence to time schedules and budget) as well as psychosocial outcomes
(such as the degree of experienced friendliness and support) (Faraj and Sproull, 2000;
Pinto and Pinto, 1990; Saxena and Burmann, 2014). However, there are several factors in
virtual team environment that operate as barriers for effective team performance.
Temporarily assigned members of globally distributed virtual teams (GDVTs) typically
come from different national, ethnic, functional and educational backgrounds; reside in
different countries or continents with different time zones; and rarely or never see each
other in-person (Cusumano, 2008; Kankanhalli et al., 2006; Kotlarsky and Oshri, 2005;
Reed and Knight, 2010). Yet, they work together interdependently and use ICT to
communicate and coordinate their time-constrained project tasks (Bourgault et al., 2008;
Peters and Karren, 2009). In general, team diversity and space–time dispersion in
GDVSD project teams are celebrated for stimulating creativity and allowing a variety of
skills to be brought to bear on problems at hand (Kankanhalli et al., 2006). Yet, such
characteristics may also cause problems in achieving successful collaboration by
reducing team cohesion and increasing team conflict (Furumo, 2009; Kotlarsky et al.,
2007; Pazos, 2012). The present study is confined to investigate causes and
consequences of relationship conflict.

The relationship conflict arises due to disagreements between team members that are
characterized by feelings of anger, hostility, frustration and distrust among team
members (Furumo, 2009; Hinds and Bailey, 2003; Jehn and Mannix, 2001). The majority
of previous studies provided evidence that relationship conflict decrease team
performance and the intent of team members to remain in the team, while some others
provided less conclusive evidence (Furumo, 2009; Jehn and Mannix, 2001). Hence, on the
one hand, factors influencing virtual team performance are not well-understood. On the
other hand, the dynamics of team leader support are not well-researched and understood
(Thomas and Bostrom, 2010; Wakefield et al., 2008; Zakaria et al., 2004). Although team
leader support is vital in alleviating team conflict and enhancing team performance,
little empirical research has specifically examined the role of team leader support in
GDVTs (Hertel et al., 2005; Thomas and Bostrom, 2010; Wakefield et al., 2008). Further,
the majority of previous empirical studies were conducted on student project teams
(Kankanhalli et al., 2006; Van Dick et al., 2008; Zhang and Wang, 2011) compared to the
number of studies conducted on actual virtual teams (Peters and Karren, 2009; Saxena
and Burmann, 2014; Thomas and Bostrom, 2010; Wakefield et al., 2008). Therefore,
empirical studies examining team composition, relationship conflict and team leader
support in achieving higher levels of team performance in virtual teams could make a
significant contribution to the literature.

In the above context, the purpose of the study was to investigate whether diversity in
team composition leads to relationship conflict, and, consequently, relationship conflict
leads to team performance, and whether team leader support reduces (moderates) the
negative effects of relationship conflict on team performance. For the present study, 216

139

Diversity in
team

composition

team members working in GDVSD projects responded by revealing their actual project
experiences. Consistent with the objectives, the rest of the article reviews, briefly, the
theoretical background of the study. This is followed by the methodology adopted.
Thereafter, the main findings are presented and discussed. The article concludes with a
discussion on managerial implications of the findings and research areas for further
inquiry and understanding.

Theoretical background and hypotheses
Team composition
Temporary, geographically and organizationally dispersed and electronically
communicating work teams have been brought about to get projects completed in a
minimum time while incorporating a wide range of cross-functional knowledge and
expertise possessed by individual members into a collective body for effective
problem-solving (Andres, 2002; Garrison et al., 2010; Van Knippenberg et al., 2004).
Therefore, it is expected that the very nature of GDVT would bring different and
complementary knowledge and expertise enhancing creativity among team members
(Zakaria et al., 2004).

However, many GDVTs fail to meet expected project results (Zakaria et al., 2004).
The literature suggests that although team composition offers potential benefits, it also
presents major challenges in GDVTs (Peters and Karren, 2009; Saxena and Burmann,
2014; Zakaria et al., 2004). First, the temporary nature of virtual teams suggests that
team membership is fluid, as it evolves according to changing project requirements
influencing how they work – members do not share past history and they may not work
together in the future (Kanawattanachai and Yoo, 2007). When team members have a
short history together, it may negatively influence how they work together in a team
(Gibson and Gibbs, 2006). Therefore, traditional coordination and control mechanisms
are less effective in GDVTs due to the complexity of team dynamics.

Second, geographical dispersion implies that team members rarely, if ever, meet in a
face-to-face setting (Kanawattanachai and Yoo, 2007; Saxena and Burmann, 2014;
Schiller and Mandviwalla, 2007). Although they may rely on a combination of ICT, these
may reduce non-verbal cues about interpersonal affections such as tone, warmth and
attentiveness that could in turn reduce message clarity, delay in feedback and the
interpretation of feedback (Kanawattanachai and Yoo, 2007; Kotlarsky and Oshri, 2005).
In addition, when team members are residing in different time zones in various parts of
the world, it may reduce opportunities for real-time collaboration (Pauleen and Yoong,
2001; Sarker and Sahay, 2004; Zhou et al., 2014). Therefore, time and distance are
important boundaries that GDVT should cross in building rapport and developing
long-term relationships.

Third, national and linguistic diversity also create challenges for effective GDVT
collaboration (Kankanhalli et al., 2006; Kotlarsky and Oshri, 2005; Pauleen and Yoong,
2001; Zhou et al., 2014). Virtual teams often comprise members from a wide range of
organizations, countries and continents, and may impact on identification in virtual
teams, leading to unhealthy racial and national stereotypes (Au and Marks, 2012). When
team members are situated across national and organizational boundaries, they may
have differing attitudes toward hierarchy and authority which may influence how they
operate as a team (Kanawattanachai and Yoo, 2007; Zhou et al., 2014). Further, national
diversity can be identified as a barrier if team members of one nationality have negative

SO
8,2/3

140

feelings toward other nationalities believing that one’s own nationality is superior to
others (Kankanhalli et al., 2006). Furthermore, distributed team work is also a
linguistically bounded concept (Au and Marks, 2012; Zakaria et al., 2004; Zhou et al.,
2014). Language will become a barrier if misunderstanding and frustration occur due to
accents or lack of fluency (Duckworth, 2008). Such situations impact on daily
communication and coordination between team members (Au and Marks, 2012). Au and
Marks (2012, p. 282) conclude “linguistic differences can lead to the loss of information
and communication problems as team members attempt to decipher their colleagues’
communications through their own cultural perspectives”. Therefore, team diversity
presents enormous challenges to team members, team processes and, ultimately, team
outcomes, although ICT makes it easier than ever to form GDVT consisting of members
from different countries with varying time zones and cultures (Malhotra et al., 2007;
Pauleen and Yoong, 2001; Zhou et al., 2014). Fourth, the literature identifies team
member differences in terms of sex, age or tenure as demographic diversity, which could
act as a barrier for effective GDVT (Kankanhalli et al., 2006). Demographic differences
are, in general, found to encompass negative consequences for team processes such as
communication and social integration (Homan et al., 2008).

Overall, GDVT can typically be conceived as a team of people working toward a
common goal but separated by a number of boundaries, such as those of distance, time,
organizational affiliation, nationality and language. Hence, team composition of GDVT
could provide numerous implications for academics and practitioners.

Relationship conflict
According to De Dreu and Weingart (2003), conflicts emerge from team members’
tension for real or perceived differences. Intra-team conflict is commonly defined by Jehn
and Mannix (2001, p. 238) as “an awareness on the part of the parties involved of
discrepancies, incompatible wishes, or irreconcilable desires”. The literature identifies
three types of intra-team conflict, namely, relationship conflict, task conflict and process
conflict (De Dreu and Weingart, 2003; Jehn and Mannix, 2001). Relationship conflict
relates to interpersonal frictions and disagreements among team members on personal
issues; task conflict relates to disagreements among team members about the team task
at hand; process conflict relates to disagreements among team members on the way in
which the task should be achieved (Jehn and Mannix, 2001). The three types of conflict
have differential impact on team performance (De Jong et al., 2008). Relationship conflict
distracts team members from the task; task conflict might increase team performance if
it leads to better understanding of task issues; process conflict might increase time spent
on deciding how to achieve the task (Martínez-Moreno et al., 2009). As mentioned in the
Introduction, the present study is confined to investigate relationship conflict.

Relationship conflict (also known as affective, personalized or emotional conflict)
may evoke due to interpersonal incompatibilities and frictions between team members
resulting in tension, annoyance and animosity (Furumo, 2009; Hinds and Bailey, 2003;
Jehn and Mannix, 2001) and interpersonal disagreements between team members on
matters that are not directly related to project tasks (Thomas and Bostrom, 2010;
Wakefield et al., 2008). For instance, interpersonal misunderstandings, attitude
problems and damaged relations between team members could lead to relationship
inadequacies (Lim and Suh, 2014; Thomas and Bostrom, 2010). In other words,
relationship conflict is characterized by interpersonal issues involving mutual dislike,

141

Diversity in
team
composition

personality clashes, the feelings of anger and frustration and distrust between team
members (Hinds and Bailey, 2003; Jehn and Mannix, 2001; Thomas and Bostrom, 2010;
Wakefield et al., 2008).

Scholars used similarity attraction theory and social identity theory to explain
relationship conflict in GDVT (Kankanhalli et al., 2006). Similarity attraction theory
suggests that people prefer to interact with similar rather than dissimilar people; social
identity theory suggests that people like to be affiliated with others belonging to their
own social category with some emotional and value significance (Kankanhalli et al.,
2006). By using these theories, previous studies found that relationship conflict could
occur when people belonging to diverse groups work together (Hong, 2010; Kankanhalli
et al., 2006; Williams and O’Reilly, 1998). For instance, Hong (2010) states that
individuals feel comfortable in interacting with those who are similar to them; cultural
differences among team members may influence how they attach to and identify with
one another within the virtual team. Williams and O’Reilly (1998) found that diverse
teams are more likely to be less integrated and less communicated and have more
conflict. Hence, as mentioned in the section on Team composition, relationship conflict
could occur in GDVT when members work across cultural, national, linguistic,
geographical and time boundaries.

According to the available literature, the effect of team composition on relationship
conflict is not well-understood (Kankanhalli et al., 2006; Van Knippenberg et al., 2004;
Williams and O’Reilly, 1998). Some previous studies provide evidence that teams
composed with individuals from diverse backgrounds could be a liability to team
performance (Kankanhalli et al., 2006; Van Knippenberg et al., 2004), while some other
studies failed to provide conclusive evidence (Mortensen and Hinds, 2001). Therefore,
empirical evidence for the effect of team composition on relationship conflict in GDVSD
is not very clear, and this demands further investigations. Based on the literature
reviewed above, it is proposed for the study that diversity in team composition leads to
relationship conflict. Therefore, it is hypothesized:

H1. Teams composed with members from diverse backgrounds experience higher
levels of relationship conflict.

Team performance
Previous researchers conceptualized the dimensions of team performance under several
broad areas. For instance, Faraj and Sproull (2000) classified team performance into two
broad areas of team effectiveness (e.g. work quality and ability to meet project goals)
and efficiency (e.g. adherence to time schedules and budgets). Pinto and Pinto (1990)
classified team performance into two broad areas of task outcomes (e.g. adherence to the
estimated schedule and budget) and psychosocial outcomes (e.g. degree of experienced
friendliness and support).

In operatinalizing team performance, some researchers such as Huckman et al. (200

and Henderson and Lee (1992) proposed objective measures (e.g. delivered source code
instructions per man-hour and number of defects in acceptance testing), while some
others such as Bourgault et al. (2008) and Staples and Webster (2007) proposed
subjective measures (e.g. team autonomy and ability to cope). In this regard, Faraj and
Sproull (2000) state that either objective measures are often unavailable or they are
subject to manipulation and may reflect the specific accounting practices of a particular
project. Therefore, Faraj and Sproull (2000) suggest that relying on subjective measures

SO
8,2/3

142

is a better source for team performance data. However, there are no agreed-upon
measures to evaluate team performance in the literature. Table I summarizes some of the
frequently used objective and subjective dimensions of team performance. It is apparent
from Table I that some of the frequently used dimensions to evaluate team performance
include multiple parameters such as adherence to time schedules (Huckman et al., 2007),
adherence to budget (Faraj and Sproull 2000) and positive work experiences for team
members (Staples and Webster, 2007). Of the previous research shown in Table I, the
studies of Saxena and Burmann (2014), Huckman et al. (2007), Faraj and Sproull (2000)
and Henderson and Lee (1992) addressed virtual software development setting.

Previous studies provide evidence for the negative effect of relationship conflict on
team performance (Au and Marks, 2012; De Dreu and Weingart, 2003; Gibson and
Gibbs, 2006; Wakefield et al., 2008). For instance, Au and Marks (2012) argued that
language barriers due to cultural diversity coupled with poor communication via
technology could reduce cooperative behavior of team members, which in turn reduce
performance. Further, when relationship conflict is perceived to increase in a team,
members wish to distance themselves from each other and cooperate with one another
only to deal with just the task at hand (Au and Marks, 2012; Stark et al., 2014). Overall,
the findings of these studies suggest that teams with unresolved relationship conflict
lower cohesion, the effectiveness of information exchange and the intention of members
to remain in the team and increase the time and energy consumption of team members
associated with emotional disagreements. As a consequence, relationship conflict is
detrimental to team performance. Therefore it is hypothesized:

H2. Relationship conflict lowers team performance.

Team leader support
In GDVSD teams, members are located in various countries, participating in a project
where their contributions are independent of each other, but the parts contributed by
each member make a complete project (Ahuja, 2002). In this regard, Lacity and
Willcocks (2014) provide evidence for assigning right leadership in the context of
business process outsourcing for dynamic innovation. Previous studies provide
evidence that team leaders play a crucial role in effective GDVT management by
coordinating tasks, motivating team members, monitoring and/or facilitating
collaboration and resolving conflict (Anh et al., 2012; Zakaria et al., 2004; Zhang and
Wang, 2011). Further, some previous studies emphasize the importance of team leaders
in social facilitation in the virtual team context to increase team unity and to create a
cohesive work unit (Duckworth, 2008; Kargar and An, 2011; Zakaria et al., 2004).
Furthermore, Wakefield et al. (2008) found a negative relationship between facilitating
role of team leader and the level of relational conflict perceived by team members.

Therefore, literature suggests the importance of relational coordination or horizontal
coordination for virtual teams (Anh et al., 2012; Duckworth, 2008; Kargar and An, 2011;
Zakaria et al., 2004; Zhang and Wang, 2011). In this regard, Gittell (2000) states that
work processes in distributed workplaces require reciprocal, iterative interactions
among team members rather than sequential hand-offs performed by operators on a
production line. According to Gittell (2000), relational coordination is characterized by
frequent and timely problem-solving communication, helpfulness, shared goals, shared
knowledge and mutual respect. Gittell (2000) found that supervisors, or in the case of
GDVSD, team leaders, can support this relational coordination. In a similar vein, Barge

143

Diversity in
team
composition

Table I.
Team performance
measures

A
ut

ho
rs

M
ea

su
re

H
en

de
rs

on
an

d
le

e
(1

99
2)

F
ar

aj
an

d
sp

ro
ul

l
(2

00
0)

H
in

ds
an

d
ba

ile
y

(2
00

H
in
ds
an

d
m

or
te

ns
en

(2
00

H
er

te
l

et
al

.
(2

00
5)

H
uc

m
an

et
al
.
(2

00
7)

St
ap

le
s

an
d

w
eb

st
er

(2
00
7)

B
ou

rg
au

lt
et

al
.

(2
00

Sa
xe

na
an

d
bu

rm
an

n
(2

01
4)

A
bi

it
y

to
co

pe
(b

y
te

am
m

em
be

rs
)

✓

bi
lit

y
to

m
ee

t
pr

oj
ec

t
go

al
s

✓
A

dh
er

en
ce

to
ti

m
e

sc
he

du
le

s
✓

✓
✓

A
dh

er
en

ce
to

bu
dg

et
s

✓
✓
✓
✓
✓
A
dh
er
en
ce

to
en

d-
us

er
sp

ec
ifi

ca
ti

on
s

D
el

iv
er

ed
so

ur
ce

co
de

in
st

ru
ct

io
ns

pe
r

m
an

-h
ou

r
✓

✓
E

xt
en

t
of

m
ee

ti
ng

de
si

gn
ob

je
ct

iv
es

✓
F

or
m

al
iz

at
io

n
of

de
ci

si
on

pr
oc

es
se

s
✓

In
it

ia
ti

ve
of

th
e

te
am

✓
In

te
nt

io
n

to
re

m
ai

n
on

th
e
te
am

✓
N

um
be

r
of

de
fe

ct
s

in
ac

ce
pt

an
ce

te
st

in
g

✓
P

er
ce

iv
ed

in
di

vi
du

al
pe

rf
or

m
an

e
✓

P
os

it
iv

e
w

or
k

ex
pe

ri
en

ce
s

fo
r

te
am

m
em

be
rs

/s
at

is
fa

ct
io

n
w

it
h

th
e
te
am

✓
Q

ua
lit

y
of

de
ci
si
on

-m
ak

in
g
pr
oc

es
s

✓
✓

R
ep

ut
at

io
n

of
w

or
k

ex
ce

lle
nc

e/
w

or
k
ex
ce
lle
nc
e
✓

✓
T

ea
m

au
to

no
m

y
✓

T
ea

m
op

er
at

io
ns

/t
ea

m
ef

fe
ct

iv
en

es
s

in
pe

rf
or

m
in

g
ta

sk
s/

pe
rc

ei
ve

d
te

am
pe

rf
or
m
an

ce
✓

✓
✓
✓
T
ea
m

ef
fi

ca
cy

T
ea
m
ef

fi
ci

en
cy

in
pe
rf
or
m
in
g
ta

sk
s

✓
✓
✓
T

ec
hn

ic
al

in
no

va
ti

on
✓

U
se

r
fr

ie
nd

lin
es

s
W

or
k

qu
al

it
y/

qu
al
it
y

of
th

e
te

am
w

or
k

re
su

lt
s

✓
✓
✓

N
o
te

:
T

ab
le

de
ve

lo
pe

d
by

th
e

au
th

or
s

SO
8,2/3

144

(1996) emphasized the importance of relational management, to which Barge (1996)
refers to as the ability of leaders to develop interpersonal relations that foster a workable
balance of cohesion and unity in the team. Therefore, team leaders in virtual
environments are expected to project a wider degree of behavioral repertoires such as
facilitating, mentoring, understanding, empathy and relationship building (Anh et al.,
2012; Duckworth, 2008; Wakefield et al., 2008).

Therefore, some previous studies suggest that the managerial purpose of team leader
changes from one of direct supervision to one of enabler or relationship moderator in
GDVTs (Anh et al., 2012; Wakefield et al., 2008). In other words, diversity has potential
value for teams because diverse teams may enhance team performance, while diversity
may disrupt team processes and performance. Therefore, it is very difficult to
apprehend the effect of diversity without taking moderators into account. In this regard,
Ehrlich and Cataldo (2014) state that although team leaders are important for the smooth
functioning of teams, their effect on team performance is not well-established. Wakefield
et al. (2008) found that team leader’s ability to assume leadership roles to manage
conflict before the conflict negatively impacts team outcomes is not statistically
significant. In our study, we propose that the effect of relationship conflict on team
performance will be reduced (moderated) by team leader support. Therefore, it is
hypothesized:

H3. The negative effect of relationship conflict on team performance is moderated
by team leader support.

The framework developed for the study is shown in Figure 1.

Methodology
Sample and method of data collection
A random sample of employees working in GDVSD project teams were selected from
software development firms operating in Sri Lanka. In doing so, a contact person was
identified at each firm. The contact persons together with one of the authors of this paper
randomly selected software development project team members who have had
completed a work assignment in a GDVSD project during the past 12-month period.
Further, not more than three people were identified from the same development project.
The contact persons distributed the link to on-line self-administered survey
questionnaire via e-mail. A total of 216 usable responses resulted in 54 per cent response
rate. Respondents were involved in software development work for client firms located
in the USA, the EU and the Asia-Pacific region. Some of the broad job categories of
respondents are software architect, principal software engineer, senior software
engineer, software engineer, quality assurance engineer and business system analyst.
The demographics of the sample are shown in

Table II.

Diversity in team
composition

Relationship
conflict

Team
performance

Team leader
support

Figure 1.
Research model

145

Diversity in
team
composition

Table II.
Sample
characteristics

About respondents (%)

Gender
Male 71
Female 29

Marital statues
Single 49
Married 51

Age (in years)
Mean 28.72
SD 3.43

Team size
Mean 12.13
SD 3.94

Tenure in virtual teams (in years)
Mean 4.17
SD 2.64

Highest level of education
Degree or equivalent 79
Postgraduate degree 21
About other team members

Countries of other team membersa

Sweden 51
Norway 28
England 18
USA 17
India 14
Denmark 11
Bangladesh 8
China 8
The Netherlands 8
Pakistan 7
Austria 7
Germany 7
Arabic countries (various) 7
Canada 6
Indonesia 6
Japan 6
Thailand 5
Singapore 5
Spain 5
Finland 3
Australia 2
Mexico 2
African countries (various) 2
Russia 1

(continued)

SO
8,2/3

146

Measures
Team composition was measured using a four-item scale developed based on the
literature reviewed earlier. Relationship conflict was measured using a four-item scale
adopted from Kankanhalli et al. (2006). Team leader support was measured using a
three-item scale developed based on the literature reviewed earlier. Building on previous
studies (Bourgault et al., 2008), team performance was conceptualized as team members’
perception of their own performance. A five-item scale was developed based on the
literature reviewed earlier. Responses for team composition and relationship conflict
were on a five-point Likert scale ranging from (1) never to (5) always. Responses for team
leader support and team performance were on a five-point Likert scale ranging from (1)
strongly disagree to (5) strongly agree.

Methods of data analysis
Self-administered survey questionnaire was used for the data collection. The
questionnaire was pre-tested with a random sample that fitted with the intended sample
of the study prior to the distribution. When self-report measures from a single source are
used to evaluate variables, the literature highlights the problem of common method bias
(Podsakoff et al., 2003; Spector, 1994). However, Spector (1994) suggests that despite the
weaknesses of the cross-sectional self-report methodology, this design can be quite
useful in providing a picture of and inter-correlations among people’s job environment
and their reactions to jobs, which can be useful for deriving hypotheses about how
people react to jobs. Therefore, procedural and statistical measures were taken to reduce
common method bias in the present study. The anonymity of respondents was ensured
to reduce evaluation apprehension. Factor analysis was used to conduct Harman’s
single-factor test; neither single factor emerged from this analysis nor was there a
general factor that could account for the majority of variance fulfilling the recommended
guidelines of Podsakoff et al. (2003). Data were tested for appropriate:

• internal consistency reliability;
• factor structure;
• convergent validity; and
• construct reliability to identify any issues with multicollinearity and response

bias.

Table II.
About respondents (%)

Religions of other team membersa

Catholic 63
Christian 59
Islam 33
Hindu 32
Buddhist 27
Other 4

Note: a Does not add up to 100 due to multiple answers

147

Diversity in
team
composition

With regard to the procedure used for the analysis of data, mean and standard deviation
were used to describe the data. Correlation analysis was used to understand the nature
of relationship between variables. To examine the hypothesized relationships,
structural equation modeling (SEM) with maximum likelihood estimation was
performed using AMOS 16. In this regard, Kremelberg (2011, p. 360) states that SEM is
a very new and more powerful method than methods such as regression. As we used
already available item measures from the literature to measure our latent variables, the
full model was tested with SEM (Kremelberg, 2011). Fit measures relating to absolute fit
(CMIN/df, GFI), relative fit (CFI) and parsimonious fit (PRATIO) and fit measures based
on the non-central chi-square distribution (RMSEA, PCLOSE) were used to evaluate the
model– data fit.

Results and discussion
The items, factor loadings and reliability statistics of the four measures are shown in
Table III. Specifically, the measure on diversity in team composition had Cronbach’s
alpha reliability of 0.734; principal component factor analysis yielded one factor. The
measure on relationship conflict had Cronbach’s alpha reliability of 0.793; principal
component factor analysis yielded one factor. The measure on team leader support had
Cronbach’s alpha reliability of 0.811; principal component factor analysis yielded one
factor. The measure on team performance had Cronbach’s alpha reliability of 0.789;
principal component factor analysis yielded one factor.

Table IV shows means, standard deviations and zero-order correlations between the
variables. As can be seen in Table IV, a significant positive correlation (Pearson
r � 0.356, p � 0.01) between diversity in team composition and relationship conflict
supports the arguments made in H1. A significant negative correlation (Pearson r �
�0.

148

, p � 0.05) between relationship conflict and team performance supports the
arguments made in H2. A significant positive correlation (Pearson r � 0.273, p � 0.01)
between team leader support and team performance together with a significant negative
correlation (Pearson r � �0.165, p � 0.05) between team leader support and relationship
conflict support the arguments made in H3. However, correlation and its associated
significance does not imply causality; therefore, relationships should be assessed using
the coefficient of determination (Hole, 2015) in SEM. Overall, correlations between
variables of interest suggest a better prediction in SEM.

The structural model achieved a good level of fit having CMIN/df � 2.583, GFI �
0.871, CFI � 0.914 and RMSEA � 0.068. The model satisfies the requirements of
goodness-of-fit criteria (Byrne, 2001). The summary of analysis is provided in Table V.
Standardized regression coefficient of 0.433 (p � 0.001) reveals that diversity in team
composition significantly positively predicts relationship conflict. This supports H1.
Standardized regression coefficient of �0.406 (p � 0.001) reveals that relationship
conflict significantly negatively predicts team performance. This supports H2. As
predicted in H3, the negative regression coefficient between relationship conflict and
team performance (�0.406, p � 0.001) is reduced by the interaction term (�0.305,
p � 0.001), suggesting team leader support as a moderator in the above relationship.
This supports H3. Further, when the full structural model is taken into account, the
coefficient of determination of 0.312 suggests that the variables of interest account for 31
per cent of the variation of team performance.

SO
8,2/3
148

Overall, the results of the study support the arguments made by us where diversity in
team composition operates as an antecedent to relationship conflict, which in turn
affects team performance; team leader support operates as a moderator on the latter
relationship.

Table III.
Summarized results:

validity and
reliability

Items Estimate
Cronbach’s
alpha AVE

Construct
reliability

Diversity in team composition 0.734 0.704 0.904
I collaborate with team members whose nationality
is different to mine 0.872
I collaborate with team members whose native
language is different to mine 0.866
I collaborate with team members who are located in
different geographical regions with different time
zones 0.811
I collaborate with team members who belong to
different age groups than mine 0.805
Relationship conflict 0.793 0.682 0.896
My team members confronted each other on
personal matters 0.862
My team members made negative remarks about
each other 0.829
Some of my team members tended to ridicule others 0.820
The differences experienced by my team were
interpersonal-related 0.791
Team leader support 0.811 0.732 0.891
My team leader had ability to communicate details
about team members 0.867
My team leader had knowledge and understanding
about the globally distributed project work
environment 0.893
My team leader had ability to influence team
members 0.805
Team performance 0.789 0.715 0.926
My team adhered to time schedules 0.872
My team adhered to budget 0.882
My team was able to meet project goals 0.807
My team was able to meet design objectives 0.861
My team has had reputation for work excellence 0.803

Table IV.
Correlations

No. Variables Mean SD 1 2 3

1 Diversity in team composition 3.90 0.50 1
2 Relationship conflict 3.67 0.59 0.356** 1
3 Team leader support 2.17 0.69 0.132 �0.165* 1
4 Team performance 3.43 0.66 �0.180** �0.148* 0.273**

Notes: * Significant at the 0.05 level; ** significant at the 0.01 level

149

Diversity in
team
composition

Conclusions and implications
The available literature provides little empirical evidence on the relationship between
team diversity, relationship conflict, team leader support and team performance as
manifested in the attitudes and expectations of knowledge workers. Drawing upon a
random sample of software developers engaged in globally distributed project teams in
Sri Lanka, we empirically tested whether diversity in team composition positively
related to relationship conflict, relationship conflict negatively related to team
performance and team leader support moderates the harmful effects of relationship
conflict on team performance. The novel character of this research is that it brought
together and analyzed, in parallel, several factors which until recently had been
analyzed separately.

It was found that respondents work in virtual teams that comprised diverse set of
team members. With regard to relationship conflict, a mean value of 3.67 suggests a
considerably high level of conflict between team members. Further, a positive
correlation was found between diversity in team composition and relationship conflict.
This supports the findings of previous studies such as Peters and Karren (2009) and
Zakaria et al. (2004). With regard to team leader support, a mean value of 2.17 suggests
a low level of team leader support in terms of communicating details of team members,
team leader’s knowledge and understanding about the project work environment
and team leader’s ability to influence team members in creating a sense of shared space
when team members are located apart. With regard to team performance, a mean value
of 3.43 suggests a moderate level of team performance in terms of time schedules,
budget, project goals, design objectives and teams’ reputation for work excellence. It
was also found that diversity in team composition leads to relationship conflict, which in
turn negatively impacts on their performance. This supports the findings of previous
studies such as Hinds and Bailey (2003) and Kankanhalli et al. (2006). The findings also
supported our prediction that team leader support moderates the link between
relationship conflict and team performance. Specifically, team leader support could
reduce the negative effect of relationship conflict on team performance.

The findings of the study have both theoretical and practical implications. First, both
academics and practitioners need valid information to better understand the influence of
team leader support on relationship conflict and team performance in the context of
GDVSD. This becomes important because the popularity of GDVSD is relatively recent
and knowledge workers engaged in GDVT are growing, while scholarly research in this
area is presently lacking. In this context, our research investigated relationships
between diversity in team composition, relationship conflict, team leader support and
team performance. By doing so, the study produced new insight beyond prior studies to
the literature. Such extended investigations become important, as the role of team leader

Table V.
Summary of the
results–structural
model coefficients

Path
Standardized regression
estimate (significance)

Coefficient of
determination

Diversity in team composition ¡ Relationship conflict 0.433 (p�0.001) 0.187
Relationship conflict ¡ Team performance �0.406 (p�0.001) 0.312
Team leader support ¡ Team performance 0.144 (p�0.001)
Team leader support � Relationship conflict ¡ Team
performance

�0.305 (p�0.001)

SO
8,2/3

150

support has not been investigated so far in relation to GDVT with the other three
variables (relationship conflict, diversity in team composition and team performance).
We have not come across previous survey-based studies that investigated the links
proposed in this study to make straightforward comparisons. Therefore, there is a lack
of research investigating these four essential elements in totality within an extended
framework. However, considerable future research is necessary to validate the links
suggested in this study. The present study represents a step in that direction. Second,
the findings of our study imply the importance of relationship building between virtual
team members to reduce relationship conflict; findings could help academics and
practitioners to design interventions to manage causes and consequences of relationship
conflict. Third, the findings imply that when selecting virtual team members, the
demands of globally distributed work context itself should be acknowledged. For
instance, in the GDVT context, most of the team communication may occur in written
form. This excludes most of the body language, vocal inflection and pacing and other
social cues available in face-to-face interactions. Further, for some team members,
communications will also be occurring in a language other than their native tongue.
Furthermore, to reduce occurrences of relationship conflict in globally distributed
teams, members’ prior experience in working across borders and their cross-cultural
competencies could be taken into granted.

Fourth, the findings also imply the role of team leaders in reducing the harmful
effects of relationship conflict on team performance. Therefore, the role of team leader in
identifying conflict situations and in reducing its effect on team performance is vital.
The findings also imply the need of providing training to team leaders to create a
cohesive team that delivers on project goals.

Limitations of the study and areas for future research
The data were collected from a considerably large homogeneous sample of individuals
engaged as team members in GDVSD project teams in Sri Lanka. The study relied on
self-reported data. However, as mentioned in the section on Methods of data collection, a
considerable attempt has been made to overcome problems that may occur due to
common method variance. With regard to areas for future research, the validity of a
measure cannot be truly established on the basis of a single cross-sectional study. The
validation of a measure requires the assessment of measurement properties over a
variety of samples in similar and different contexts. Hence, future research, in different
samples and longitudinal studies, is necessary that complements questionnaire surveys
with interviews. The study relied on experiences of respondents working in Sri Lanka
on GDVSD projects. As a result, they revealed their experiences of their immediate
project leaders in Sri Lanka. Future research could overcome this limitation by
expanding the research to include global virtual team members in other locations.
Future research could incorporate other variables of interest such as how global virtual
team leaders exercise power to resolve relationship conflict, what role communication
media plays in supporting team leaders and what skills and resources virtual team
leaders need to moderate the link between relationship conflict and team performance.
Our study was confined to investigating the relationship conflict, which is detrimental
to team performance. Future studies could investigate other types of conflict such as
task-related. Unlike relationship conflict, task conflict may have positive results by
influencing internal competition leading to innovation.

151

Diversity in
team
composition

References
Ahuja, S. (2002), “Distributed teams in e-work organisations: the new issues”, Journal of Services

Research, Vol. 2 No. 2, pp. 79-95.

Andres, H.P. (2002), “A comparison of face-to-face and virtual software development teams”,
Team Performance Management: An International Journal, Vol. 8 Nos 1/2, pp. 39-48.

Anh, N.D., Cruzes, D.S. and Conradi, R. (2012), “Dispersion, coordination and performance in
global software teams: a systematic review”, ESEM’12, 19-20 September, Lund,
pp. 129-139.

Au, Y. and Marks, A. (2012), “Virtual teams are literally and metaphorically invisible”, Employee
Relations, Vol. 34 No. 3, pp. 271-287.

Barge, J.K. (1996), “Leadership skills and the dialectics of leadership in group decision making”, in
Hirokawa, R.Y. and Poole, M.S. (Eds), Communication and Group Decision Making, Sage,
Thousand Oaks, CA, pp. 301-342.

Bell, S.B. and Kozlowski, S.W. (2002), “A typology of virtual teams: implications for effective
leadership”, Group & Organization Management, Vol. 27, pp. 14-49.

Bourgault, M., Drouin, N. and Hamel, E. (2008), “Decision making within distributed project
teams: an exploration of formalization and autonomy as determinants of success”, Project
Management Journal, Vol. 39, pp. S97-S110.

Byrne, B.M. (2001), Structural Equation Modelling with AMOS: Basic Concepts, Applications and
Programming, Lawrence Erlbaum, London.

Curşeu, P.L. and Wessel, I. (2005), “Information processing in virtual teams: implications for
virtual team effectiveness”, in Curşeu, P.L. (Ed.), Complexity within Organizations, Pearson
Education, Harlow.

Cusumano, M.A. (2008), “Managing software development in globally distributed teams”,
Communications of the ACM, Vol. 51 No. 2, pp. 15-17.

De Dreu, C.K.W. and Weingart, L.R. (2003), “Task versus relationship conflict, team performance,
and team member satisfaction: a meta-analysis”, Journal of Applied Psychology, Vol. 88
No. 4, pp. 741-749.

De Jong, R., Schalk, R. and Curşeu, P.L. (2008), “Virtual communicating, conflicts and performance
in teams”, Team Performance Management: An International Journal, Vol. 14 Nos 7/8,
pp. 364-380.

Duckworth, H. (2008), “How TRW automotive helps global virtual teams perform at the top of
their game”, Global Business and Organizational Excellence, November/December, pp. 6-16.
doi: 10.1002/joe.20237.

Ehrlich, K. and Cataldo, M. (2014), “The communication patterns of technical leaders: impact on
product development team performance”, CSCW’14, 15-19 February, Baltimore, MD,
pp. 733-744.

Faraj, S. and Sproull, L. (2000), “Coordinating expertise in software development teams”,
Management Science, Vol. 46, pp. 1554-1568.

Furumo, K. (2009), “The impact of conflict and conflict management style on deadbeats and
deserters in virtual teams”, Journal of Computer Information Systems, Vol. 49 No. 4,
pp. 66-73.

Garrison, G., Wakefield, R.L., Xu, X. and Kim, S.H. (2010), “Globally distributed teams: the effect
of diversity on trust, cohesion and individual performance”, The DATA BASE for
Advances in Information Systems, Vol. 41 No. 3, pp. 27-48.

SO
8,2/3

152

http://dx.doi.org/10.1002/joe.20237

Gibson, C.B. and Gibbs, J.L. (2006), “Unpacking the concept of virtuality: the effects of geographic
dispersion, electronic dependence, dynamic structure, and national diversity on team
innovation”, Administrative Science Quarterly, Vol. 51 No. 3, pp. 451-495.

Gittell, J.H. (2000), “Organizing work to support relational coordination”, International Journal of
Human Resource Management, Vol. 11 No. 3, pp. 517-539.

Henderson, J.C. and Lee, S. (1992), “Managing I/S design teams: a control theories perspective”,
Management Science, Vol. 18 No. 6, pp. 757-777.

Hertel, G., Geister, S. and Konradt, U. (2005), “Managing virtual teams: a review of current
empirical research”, Human Resource Management Review, Vol. 15, pp. 69-95.

Hinds, P.J. and Bailey, D.E. (2003), “Out of sight, out of sync: understanding conflict in distributed
teams”, Organization Science, Vol. 14 No. 6, pp. 615-632.

Hinds, P.J. and Mortensen, M. (2005), “Understanding conflict in geographically distributed teams:
the moderating effects of shared identity, shared context, and spontaneous
communication”, Organization Science, Vol. 16 No. 3, pp. 290-307.

Hole, G. (2015), Research Skills One, Correlation Interpretation, University of Sussex, available at:
www.sussex.ac.uk/Users/grahamh/RM1web/Eight%20things%20you%20need%20to%
20know%20about%20interpreting%20correlations (accessed 10 March 2015).

Homan, A.C., Hollenbeck, J.R., Humphrey, S.E., Van Knippenberg, D., Ilgen, D.R. and
Van Kleef, G.A. (2008), “Facing differences with an open mind: openness to experience,
salience of intragroup differences, and performance of diverse work groups”, Academy of
Management Journal, Vol. 51 No. 6, pp. 1204-1222.

Hong, H. (2010), “Bicultural competence and its impact on team effectiveness”, International
Journal of Cross Cultural Management, Vol. 10 No. 1, pp. 93-120.

Huckman, R.S., Staats, B.R. and Upton, D.M. (2007), “Team familiarity, role experience, and
performance: evidence from Indian software services”, Working Paper, available at: www.
hbs.edu/research/pdf/08-019 (accessed 26 September 2011).

Jehn, K.A. and Mannix, E.A. (2001), “The dynamic nature of conflict: a longitudinal study of
intragroup conflict and group performance”, Academy of Management Journal, Vol. 44,
pp. 238-251.

Kanawattanachai, P. and Yoo, Y. (2007), “The impact of knowledge coordination on virtual team
performance over time”, MIS Quarterly, Vol. 31 No. 4, pp. 783-808.

Kankanhalli, A., Tan, B.C.Y. and Wei, K.-K. (2006), “Conflict and performance in global virtual
teams”, Journal of Management Information Systems, Vol. 23 No. 3, pp. 237-274.

Kargar, M. and An, A. (2011), “Discovering Top-k teams of experts with/without a leader in social
networks”, CIKM’11, 24-28 October, Glasgow, pp. 985-994.

Kotlarsky, J. and Oshri, I. (2005), “Social ties, knowledge sharing and successful collaboration in
globally distributed system development projects”, European Journal of Information
Systems, Vol. 14, pp. 37-48.

Kotlarsky, J., Oshri, I., Kumar, K. and Van Hillegersberg, J. (2007), “Globally distributed
component-based software development: an exploratory study of knowledge management
and work division”, Journal of Information Technology, Vol. 22 No. 2, pp. 161-173.

Kremelberg, D. (2011), Practical Statistics – A Quick and Easy Guide to IBM SPSS Statistics,
STATA, and Other Statistical Software, Sage Publications, Thousand Oaks, CA.

Lacity, M. and Willcocks, L. (2014), “Business process outsourcing and dynamic innovation”,
Strategic Outsourcing: An International Journal, Vol. 7 No. 1, pp. 66-92.

153

Diversity in
team
composition

http://www.sussex.ac.uk/Users/grahamh/RM1web/Eight%20things%20you%20need%20to%20know%20about%20interpreting%20correlations

http://www.hbs.edu/research/pdf/08-019

Lim, H. and Suh, B. (2014), “Now here or nowhere: conflict resolution strategies for intimate
relationship in diverse geographical contexts”, CSCW’14 Companion, 15-19 February,
Baltimore, MD, pp. 197-200.

Malhotra, A., Majchrzak, A. and Rosen, B. (2007), “Leading virtual teams”, Academy of
Management Perspectives, Vol. 21 No. 1, pp. 60-70.

Martínez-Moreno, E., González-Navarro, P., Zornoza, A. and Ripoll, P. (2009), “Relationship, task
and process conflicts on team performance”, International Journal of Conflict Management,
Vol. 20 No. 3, pp. 251-268.

Mishra, D. and Mahanty, B. (2014), “The effect of onsite-offshore work division on project cost,
schedule, and quality for re-engineering projects in Indian outsourcing software industry”,
Strategic Outsourcing: An International Journal, Vol. 7 No. 3, pp. 198-225.

Mortensen, M. and Hinds, P.J. (2001), “Conflict and shared identity in geographically distributed
teams”, International Journal of Conflict Management, Vol. 12 No. 3, pp. 212-238.

Pauleen, D.J. and Yoong, P. (2001), “Relationship building and the use of ICT in boundary-crossing
virtual teams: a facilitator’s perspective”, Journal of Information Technology, Vol. 16,
pp. 205-220.

Pazos, P. (2012), “Conflict management and effectiveness in virtual teams”, Team Performance
Management: An International Journal, Vol. 18 Nos 7/8, pp. 401-417.

Peters, L. and Karren, R.J. (2009), “An examination of the roles of trust and functional diversity on
virtual team performance ratings”, Group & Organization Management, Vol. 34 No. 4,
pp. 479-504.

Pinto, J.K. and Pinto, M.B. (1990), “Project team communication and cross-functional cooperation
in new program development”, Journal of Product Innovation and Management, Vol. 7
No. 3, pp. 200-212.

Podsakoff, P., Mackenzie, S., Lee, J.-Y. and Podsakoff, N. (2003), “Common method biases in
behavioral research: a critical review of the literature and recommended remedies”, Journal
of Applied Psychology, Vol. 88 No. 5, pp. 879-903.

Reed, A.H. and Knight, L.V. (2010), “Project risk differences between virtual and co-located
teams”, Journal of Computer Information Systems, pp. 19-30.

Sarker, S. and Sahay, S. (2004), “Implications of space and time for distributed work: an
interpretive study of US-Norwegian system development teams”, European Journal of
Information Systems, Vol. 13 No. 1, pp. 3-20.

Saxena, A. and Burmann, J. (2014), “Factors affecting team performance in globally distributed
setting”, SIGMIS-CPR’14, 29-31 May, Singapore, pp. 25-33.

Schiller, S.Z. and Mandviwalla, M. (2007), “Virtual team research – an analysis of theory use and
a framework for theory appropriation”, Small Group Research, Vol. 38 No. 1, pp. 12-59.

Spector, P.E. (1994), “Using self-report questionnaires in OB research: a comment on the use of a
controversial method”, Journal of Organizational Behavior, Vol. 15 No. 5, pp. 385-392.

Staples, D.S. and Webster, J. (2007), “Exploring traditional and virtual team members’ ‘best
practices’ – a social cognitive theory perspective”, Small Group Research, Vol. 38 No. 1,
pp. 60-97.

Stark, E., Bierly, P. and Harper, S.R. (2014), “The interactive influences of conflict, task
interdependence and cooperation on perceptions of virtualness in co-located teams”, Team
Performance Management, Vol. 20 Nos 5/6, pp. 221-241.

Thomas, D.M. and Bostrom, R.P. (2010), “Vital signs for virtual teams: an empirically developed
trigger model for technology adaptation interventions”, MIS Quarterly, Vol. 34 No. 1,
pp. 115-142.

SO
8,2/3

154

Van Dick, R., Van Knippenberg, D., Hägele, S., Guillaume, Y.R.F. and Brodbeck, F.C. (2008),
“Group diversity and group identification: the moderating role of diversity beliefs”, Human
Relations, Vol. 61 No. 10, pp. 1463-1492.

Van Knippenberg, D., De Dreu, C.K.W. and Homan, A.C. (2004), “Work group diversity and group
performance: an integrative model and research agenda”, Journal of Applied Psychology,
Vol. 89, pp. 1008-1022.

Wakefield, R.L., Leidner, D.E. and Garrison, G. (2008), “A model of conflict, leadership, and
performance in virtual teams”, Information Systems Research, Vol. 19 No. 4, pp. 434-455.

Williams, K.Y. and O’reilly, C.A. (1998), “Demography and diversity in organizations: a review of
40 years of research”, in Staw, B.M. and Cummings, L.L. (Eds), Research in Organizational
Behavior, Vol. 20, JAI Press, Greenwich, CT, pp. 77-140.

Zakaria, N., Amelinckx, A. and Wilemon, D. (2004), “Working together apart? Building a
knowledge-sharing culture for global virtual teams”, Creativity and Innovation
Management, Vol. 13 No. 1, pp. 15-29.

Zhang, C. and Wang, J.A. (2011), “Effects of communication, leadership, and team performance on
successful it capstone projects: a case study”, SIGITE’11, 20-22 October, West Point, NY,
pp. 281-286.

Zhou, N., Gifford, W.M., Ratakonda, K., Westerwick, G.H. and Engel, C. (2014), “On the
quantification of global team performance and profitability”, SCC’14 Proceedings of the
2014 IEEE International Conference on Services Computing, IEEE Computer Society
Washington, DC, pp. 378-385. doi. 10.1109/SCC.2014.57.

Further reading
Scholarios, D. and Marks, A. (2004), “Work-life balance and the software worker”, Human

Resource Management Journal, Vol. 14 No. 2, pp. 54-74.

Corresponding author
Vathsala Wickramasinghe can be contacted at: vathsala@mot.mrt.ac.lk

For instructions on how to order reprints of this article, please visit our website:
www.emeraldgrouppublishing.com/licensing/reprints.htm
Or contact us for further details: permissions@emeraldinsight.com

155
Diversity in
team
composition

http://dx.doi.org/10.1109/SCC.2014.57

mailto:vathsala@mot.mrt.ac.lk

mailto:permissions@emeraldinsight.com

Reproduced with permission of the copyright owner. Further reproduction prohibited without
permission.

Diversity in team composition, relationship conflict and team leader support on globally distrib …

Introduction
Theoretical background and hypotheses
Relationship conflict
Team performance
Team leader support
Methodology
Results and discussion
Conclusions and implications
Limitations of the study and areas for future research
References

Conflict management and
performance of information

technology development teams
Dmitriy Nesterkin

D# Media, Baltimore, Maryland, USA, and

Tobin Porterfield
Department of eBusiness and Technology Mgmt,

Towson University, College of Business and Economics, Towson,
Maryland, USA

Abstract
Purpose – This research aims to investigate how team support and cohesion channel the effects of
relationship conflict and its management on team productivity.
Design/methodology/approach – Questionnaire data were sampled from students working in
groups to design software systems for companies. Structural equation methodology was used to
estimate the proposed model.
Findings – The results indicate that the mediators (team support and cohesion) positively affect each
other and team performance. The results support that the effects of conflict and conflict management on
team performance are mediated by team support first and then indirectly through team cohesion.
Research limitations/implications – This paper empirically establishes the mechanisms through
which conflict and its management affect team performance. The following limitations should be
considered when generalizing the results of the study: team-level phenomena were assessed using
perceived measures of individual team members and an academic setting was used for data collection.
Practical implications – The findings indicate that team support plays an important role in
protecting the team from the negative effects of conflict and that team support contributes to the
development of team cohesion.
Originality/value – This work is one of the first to evaluate the mechanisms of team support and
cohesion through which team conflict and its management affect team performance.

Keywords Relationship conflict, Team performance, Team management, Conflict management,
Team cohesion

Paper type Research paper

1. Introduction
The extensive use of teams in the workplace has stimulated great interest from
researchers and practitioners (Hempel et al., 2009; Kirchmeyer and Cohen, 1992; Tekleab
et al., 2009; Tjosvold et al., 2003). The interactions of individuals within teams have
brought relational conflict and task conflict to the forefront as the focus of several
studies (De Dreu and Weingart, 2003; Huang, 2010; Simons and Peterson, 2000).
Relationship conflict results from differences in individuals and how they interact with
other team members (Choi and Sy, 2010; Jehn et al., 1999). Task conflict emerges from
disagreements on how the team completes its work (Ward et al., 2007; De Dreu and
Weingart, 2003). While the literature consistently identifies relational conflict as being

The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/1352-7592.htm

TPM
22,5/6

242

Received 2 May 2016
Revised 8 June 2016
Accepted 8 June 2016

Team Performance Management
Vol. 22 No. 5/6, 2016
pp. 242-

256

http://dx.doi.org/10.1108/TPM-05-2016-0018

detrimental to team performance (Behfar et al., 2008; Somech et al., 2009; Tekleab et al.,
2009; Tjosvold et al., 2003), task conflict varies in how it affects performance depending
on contextual factors.

The management of conflict, generally defined as the extent to which team members
engage in actions aimed at diffusing team strife, is distinct from the conflict itself.
Effective conflict management has been shown to enhance team performance (Behfar
et al., 2008; Somech et al., 2009; Tekleab et al., 2009; Tjosvold et al., 2003).

While extant research has addressed how relationship conflict and conflict
management affect team performance, minimal research addresses the mechanisms
through which they operate. Even the more established individual-level conflict
literature has only recently begun examining how relationship conflict affects
performance (Lau and Cobb, 2010). This study focuses on the relationship conflict and
seeks to evaluate two of those mechanisms applied in the less-studied context of IT
development teams (Lee et al., 2014). This study addresses the research gap by
theoretically establishing and empirically testing the mediating role that team support
and team cohesion play in mediating the effect of relationship conflict and conflict
management on IT team performance.

2. Background and research model
Teams are formed to achieve a level of performance that is often impossible for
individuals. Team productivity is thus a coordinated and cumulative combination of
team members’ actions toward a common goal. Successful teamwork requires that team
members develop and hold a common identity and function as a unit (Van Der Vegt and
Bunderson, 2005). Establishing a social identity with a team means recognizing oneself
as an inseparable part of the collective and deriving certain emotions of value and
importance because of that membership (Tajfel, 1972). By seeing self as part of a group,
the individual starts to see themselves containing the prominent attributes of a focal
team (Hogg and Terry, 2000). One’s motivations and goals then become closely
intertwined with the motivations and goals of the group and team’s achievements and
missteps are seen as personal successes and failures (Ashforth and Mael, 1989). Because
doing well by a team is seen as doing well by oneself, teams with an established identity
are more likely to build efficient productivity-supporting intra-team processes such as
task coordination, communication and information exchange (Stewart and Barrick,
2000). Members of such teams are also likely to possess a generally positive attitude
toward their peers. Thus, the main premise of this study is that the attainment and
sustainment of team productivity depends on both facilitating and attitudinal factors. In
this work, the factors are represented by the constructs of team support and team
cohesion.

The focus on these concepts is deliberate. Team support represents the availability of
general helping behaviors of team members toward one another. The construct is
conceptualized as a synergistic interaction process (Drach-Zahavy, 2004), without
which group productivity is likely to be reduced or undermined completely. Team
cohesion is a complementary affect-based construct that represents team members’
feelings of belongingness or attraction to the group and indicates team members’
attitudes toward the team and toward one another (Bollen and Hoyle, 1990). Essentially,
one may view a group as embodying multidirectional assembly line-like processes
which require both the supportive behaviors (as the exchange of resources and

243

Information
technology

development
teams

information) and cohesion (to “grease” the assembly line wheels) to attain the best
performance (LePine et al., 2008). The optimal manifestations of team support and
cohesion, and, subsequently, team performance are posited here as reflective of the
extent to which team members see and characterize themselves as deeply congruent
with their group.

2.1 Team relationship conflict, identity and performance
The main claim of this research is that relationship conflict – defined as strife such as
differences over values, norms and attitudes (Lau and Cobb, 2010, p. 900) – reduces or
eliminates identification an individual has or could have with his or her group. The
undermining of the individuals’ sense of oneness with a team is likely to diminish the
intra-team-enabling supportive processes (i.e. team support) and is also likely to
diminish a generally benevolent attitude that team-identified members feel toward each
other (i.e. team cohesion). The reduction in team support and cohesion destabilizes team
performance.

According to social identity theory, groups emerge and exist because of individuals’
cornerstone needs of self-esteem enhancement and uncertainty avoidance (Hogg, 2001).
One feels high self-esteem when a team to which an individual belongs acquires and
keeps a positive differentiation when compared with other teams. That is, being part of
a seemingly successful team makes an individual feel good. So long as that group’s
differentiation is maintained and is supportive of one’s esteem, an individual is likely to
remain a part of the collective. On the other hand, when a group’s positive differentiation
is reduced, a group member may physically and/or psychologically dissolve his or her
membership in that group (Hogg and Terry, 2000).

Identity with a group is also driven by a need to reduce one’s uncertainty about one’s
self-concept and belonging in chaotic social surroundings (Hogg and Terry, 2000). Social
structures reduce awareness of uncertainty by allowing individuals to access a common
pool of information and understanding shared by the social structure. This shared
mental model is called a prototype (Hogg et al., 1995). The prototype holds all chief
attributes (e.g. feelings, beliefs and actions) that characterize a group and differentiate it
from other collectives. Subjective uncertainty is thus diminished because perceptions,
feelings and behaviors are based upon knowledge and understanding that is
consensually supported by the entire group. Put differently, by being a part of a social
structure, a person reduces the mental and affective burdens of adaptation to an
uncertain environment by using already-prescribed and cumulatively validated
attitudes and actions (Hogg and Terry, 2000).

When relationship conflict occurs, it is likely to reduce team identity, thereby disrupting
supportive processes and generally favorable attitudes (supported by that identification) via
a reduction of team members’ self-esteem and amplification of the environmental
uncertainty that group members may sense. A key characteristic of relationship conflict is
negative feelings manifested as insults, avoidance of commitment and negative evaluation
of the actions of others (Bodtker and Jameson, 2001; Simons and Peterson, 2000).
Relationship conflict, by raising tensions and negative differences, thus impairs the
perception of the team’s positive differentiation, and thus vitiates the esteem one feels from
being a team member. As a group member’s self-esteem falters, the individual is likely to
withdraw from the team, thereby disengaging from supportive intra-team processes and
short-circuiting the feelings of belongingness and being in cohesion with the team.

TPM
22,5/6

244

Additionally, when relationship conflict enhances negative differences within a team, the
conflict is likely to compromise the shared collective knowledge and understanding, thus
amplifying uncertainty that each member may sense. Persons are generally risk- and
loss-averse (Thaler and Sunstein, 2008). Social structures with higher levels of perceived
chaos are likely to be avoided. Therefore, relationship conflict, by increasing the subjective
tumult that team members perceive in their environment, may cause team members to
withdraw from their group and from productivity-central processes of team support and to
withdraw their feelings of being cohesive with their peers:

H1. Team relationship conflict is negatively related to team support.

H2. Team relationship conflict is negatively related to team cohesion.

Relationship conflict disrupts productivity by undermining a group’s assembly line by
short-circuiting supporting processes and causing team members to lose feelings of
belonging with their peers. Successful team support and cohesion are thus prerequisite
to the timely and distributed amalgamation of each of the group member’s contributions
to the final product. The question is whether conflict can influence productivity directly
beyond its effects on support and cohesion. Relationship conflict is seen here as distal,
and is important to the study of group performance insofar as it is an undermining
influence – a disruptor – that can impact team performance by producing stress,
negativity and lack of unity (De Dreu and Weingart, 2003). This deflates the team’s
identity and promotes alienation among group peers, thereby slowing down the
production processes by which individual contributions are combined. From a different
perspective, as relationship conflict burns time and energy, the time and energy
available for supportive and cohesive actions decrease. Complete withdrawal of support
and complete lack of cohesion would lead to zero individual productivity, thereby
precluding any gains in team performance (LePine et al., 2008). This suggests that any
level of relationship conflict on performance would have to be first fully carried by team
support and cohesion. Therefore, the effect of relationship conflict on team productivity
is likely to be fully mediated through team support and cohesion:

H3. The effect of team relationship conflict on team performance is fully channeled
through team support and cohesion.

2.2 Team conflict management, identity and performance
Conflict management is a principal driver of team performance (Alper et al., 2000; Jehn
and Bendersky, 2003; Montoya-Weiss et al., 2001). The existing literature has clearly
established that the processes of conflict management buffer the detrimental effect of all
types of conflict by supporting work effectiveness, resource usage efficiency and
procedural justice (Behfar et al., 2008). Conflict management research primarily studies
behavioral interventions such as compromising, avoiding, accommodating, competing,
problem-solving and cooperating actions and their impact in defusing conflict (Behfar
et al., 2008; Cropanzano et al., 1999; Folger et al., 2001). This work does not strive to
differentiate between various conflict management behavioral patterns and their
impacts. Instead, conflict management is defined generally as the extent to which group
peers act to reduce tensions.

The goal of this study is to understand how broad conflict management actions
influence team performance. Drawing on social identity theory (Ashforth and Mael,

245

Information
technology
development
teams

1989), conflict management practices are likely to fix conflict-undermined identity by
pulling group members into interactions that block conflict and once again restore the
positive differentiation of the team, thereby inflating the esteem that individuals obtain
through group membership (Stets and Burke, 2000). This enhances the perception of
oneness with the team and the division between group peers is likely to disappear. When a
person resumes seeing others in the same light as himself or herself, the number of actions
done on behalf of others (i.e. group) is likely to rise. Subsequently, the conflict-damaged team
support and cohesion are likely to become restored. Conflict management may also repair
the team prototype. In the process of actively addressing a conflict, a team is likely to amplify
the sameness within and attenuate any conflict-arisen distinctions. This is likely to
strengthen the shared mental models that the group individuals can then use to conduct
themselves with more certainty in a chaotic social context. By repairing the team’s prototype,
conflict management is likely to increase the importance of team membership that brings
with it a collection of heuristics that reduce mental and affective work, thereby reducing
perceived environmental complexity. In an environment with lower perceived chaos, the
team productivity increases through the freeing of time and energy to be supportive and
well-meaning toward other team members:

H4. Team conflict management is positively related to team support.

H5. Team conflict management is positively related to team cohesion.

How would the effect of conflict management on productivity be channeled? Would it be
direct, beyond its effects through team support and cohesion? Or, would the effect of
conflict management be fully transferred through the mediators? Conflict management
comes into play in repairing relational team dynamics when conflict occurs. Conflict
management, similar to relationship conflict, is thus a remote influence and is connected
to team productivity in restoring team interactions and positive attitudes by repairing
team identification. Therefore, the effect of conflict management on team performance is
expected to be fully directed through team support and cohesion:

H6. The effect of team conflict management on team performance is fully channeled
through team support and cohesion.

2.3 Team support, cohesion and performance
The direct positive effects of team support and cohesion on performance are well
documented (Beal et al., 2003; Tekleab et al., 2009; Drach-Zahavy and Somech, 2002).
However, little is known about the influences that support and cohesion may exert on
each other. The connection between team support and cohesion can be enlightened via
Tuckman’s (1965) developmental model. That is, team cohesion, as a structural
attribute, begins to emerge in the latter stages of group development and is preceded by
team members’ commitment to working together (Guzzo, 1995; Yukelson et al., 1984).
Therefore, the expectation here is for team support – a collaborative process that is likely
to emerge first – to directly and positively influence team cohesion. On the other hand,
team cohesion, once established or beginning to be established, as a unifying force, is
likely to positively influence the propensity of team members to behave in the interests
of one another. Therefore, both team support and cohesion are expected to positively
influence each other. However, because support is viewed as a more salient factor, its
effect on cohesion is expected to be stronger than the effect of cohesion on team support.

TPM
22,5/6

246

Because support and cohesion are expected to directly affect each other and team
performance, the effect of support on performance is also expected to be partially
mediated through team cohesion. The resulting effect of cohesion on performance is also
expected to be partially mediated through team support:

H7. Team support is positively related to team cohesion.

H8. Team cohesion is positively related to team support.

H9. Team support will have a stronger impact on team cohesion than team
cohesion will have on team support.

H10. The effect of team support on team performance is partially mediated through
team cohesion.

H11. The effect of team cohesion on team performance is partially mediated
through team support.

2.4 Complete model
The previous theoretical development implies a multi-stage mediation from the antecedents
to the dependent variable. The effect of relationship conflict on performance, channeled
through team support and cohesion, is expected to be partially mediated with the effect team
support has on cohesion and through the effect cohesion has on team support. Likewise, the
effect of conflict management on performance, channeled through team support and
cohesion, is also expected to be partially mediated through the effect team support has on
cohesion and the effect cohesion has on team support:

H12. The effect of team relationship conflict on team performance, through team
support, is partially mediated through the effect of team support on team
cohesion.

H13. The effect of team relationship conflict on team performance, through team
cohesion, is partially mediated through the effect of team cohesion on team
support.

H14. The effect of team conflict management on team performance, through team
support, is partially mediated through the effect of team support on team
cohesion.

H15. The effect of team conflict management on team performance, through team
cohesion, is partially mediated through the effect of team cohesion on team
support.

3. Methodology
3.1 Sample and survey procedures
Study participants were undergraduate students from all business academic majors
enrolled in the core technology course at a major university in the northeast USA. The
average team size was four and teams remained intact throughout the 15-week semester.
The teams collaborated on computer system design projects for industry clients which
allowed them to use similar procedures and face challenges similar to teams in a
professional environment. The use of an academic setting is consistent with similar
team research where the environment can be controlled (Piccoli et al., 2004).

247

Information
technology
development
teams

Questionnaires were administered at the end of the course as part of the team project
assessment and were collected from 100 per cent of the students (n � 352). Further, 23
observations were removed because of missing values and 5 were removed because of
multivariate outliers resulting in a final sample size of 324.

3.2 Measures
Relationship conflict was operationalized using four items adapted from Jehn (1995).
Conflict management was operationalized using three items developed for this study
based on the extent to which team members engaged in activities aimed at diffusing
team strife. Team support was operationalized as the extent to which team members
helped, supported and encouraged each other and was assessed using three items
adapted from Drach-Zahavy and Somech (2002). Team cohesion was operationalized
as the extent to which the focal team completed tasks better than prior teams and was
assessed using three items developed for this study. Performance was operationalized
as the extent to which a team was effective and was assessed using three items adapted
from Jehn et al. (1999). Responses used seven-point Likert scales anchored by strongly
disagree (1) and strongly agree (7). The face validity and the content validity of the
conflict management and cohesion items were assessed by several subject-matter
experts to ensure items completeness, accuracy and clarity.

4. Results
4.1 Measurement model
Using PROC CALIS of SAS, confirmatory factor analysis was performed to assess the
five-factor measurement model (Table I). The model fit the data well: �2(68) � 136.84,
�2/df � 2.01, Tucker–Lewis fit index (TLI; also called the non-normed fit index, or NNFI) �
0.9806, comparative fit index (CFI) � 0.9855, root mean square error of approximation
(RMSEA) � 0.0585, probability of close fit (PCLOSE) � 0.1562 and goodness-of-fit index
(GFI) � 0.9398.

Cronbach’s coefficient alpha (Cronbach, 1951), composite reliability and average variance
extracted (AVE) indices (Fornell and Larcker, 1981) were computed for all constructs. All
coefficient alpha measures were above the recommended threshold of 0.8 (Nunnally, 1993).
Composite reliability measures were above the recommended threshold of 0.7 (Hair et al.,
1998). Additionally, all AVE measures were above the recommended threshold of 0.5
(Bagozzi, 1991) (Table II). Convergent validity was demonstrated with all standardized item
loadings being greater than 0.7 and the squared multiple correlation between each item and
its respective latent variable exceeding 0.5.

Chi-square difference and AVE tests were used to establish discriminant validity
(Anderson and Gerbing, 1988; Hatcher, 1994). The chi-square difference tests fully
support discriminant validity of all constructs, discriminant validity is demonstrated if
the chi-square value is significantly lower for the model where the factors are
unconstrained. The more stringent AVE approach affirmed discriminate validity for all
constructs except team support and team performance (Table II). Specifically, the
squared correlation between team support and team performance of 0.757 exceeded the
AVE of 0.71 for team support. However, this squared correlation was less than the AVE
of 0.78 for team performance and given the stringency of the AVE test the discriminant
validity for team support and team performance was deemed marginally satisfied.

TPM
22,5/6

248

To determine whether a common method variance is a significant influence, all
indicators, in the context of confirmatory factor analysis, were loaded on a single factor
(Podsakoff et al., 2003; Podsakoff and Organ, 1986; for example, see Mossholder et al.,
1998). The model did not fit the data well: �2(77) � 3,448.4816, �2/df � 44.7855,

Table I.
Confirmatory factor

analysis results

Item Loadings

Relationship conflict
There was a lot of tension in our team 0.94
The majority of team members seemed upset working
in our team 0.98
There was a great deal of emotional conflict in our team 0.98

Conflict management
When we had disagreements, we tried to resolve them 0.85
My team managed conflicts effectively 0.94
Most of our team conflicts were successfully resolved 0.88

Team support
Members in my team often supported each other in
tasks 0.95
Members of my team often encouraged each other in
the face of difficulties 0.97
Members in my team helped keep each other motivated 0.90

Team cohesion
My team worked together better than most teams on
which I have worked 0.96
My teammates and I helped each other better than most
other teams on which I have worked 0.95

Team performance
I think my team did great on the project 0.98
I think my team was very effective 0.93
My team got things done quickly 0.84

Notes: �2(68) � 136.84; �2/df � 2.01; NNFI � 0.9806; CFI � 0.9855; RMSEA � 0.0585; PCLOSE �
0.1562; GFI � 0.9398

Table II.
Descriptive statistics,
reliability indices and

correlations

Construct M SD � CR 1 2 3 4 5

1. Relationship conflict 1.63 1.00 0.98 0.97 (0.93) –0.05 –0.23*** –0.19*** –0.21***
2. Conflict management 5.27 1.27 0.92 0.86 –0.04 (0.67) 0.62*** 0.40*** 0.54***
3. Team support 5.64 1.08 0.91 0.88 –0.24*** 0.68*** (0.71) 0.74*** 0.77***
4. Team cohesion 5.28 1.36 0.95 0.92 –0.20*** 0.44*** 0.83*** (0.85)*** 0.69***
5. Team performance 5.89 1.14 0.94 0.92 –0.24*** 0.58*** 0.87*** 0.75*** (0.78)

Notes: Average variance extracted (AVE) values are in parentheses on the diagonal; correlation
coefficients below the diagonal were computed using factors scores; correlation coefficients above the
diagonal were computed using raw data; M�mean; SD�standard deviation; ��Cronbach’s coefficient
alpha; CR�composite reliability; *** p � 0.001 (two-tailed)

249

Information
technology
development
teams

NNFI � 0.162, CFI � 0.291, RMSEA � 0.3846, PCLOSE � 0.0000 and GFI � 0.2475,
suggesting a negligible effect of a common method variance.

4.2 Hypothesized structural model
The hypothesized model was tested using the PROC CALIS structural equation
modeling module of SAS. The estimated model explained 71.24 per cent of the variance
in performance, 68.43 per cent of the variance in team support and 59.88 per cent of the
variance in team cohesion. The model fit the data well: �2(67) � 136.84, �2/df � 2.04,
NNFI � 0.9801, CFI � 0.9853, RMSEA � 0.0593, PCLOSE � 0.1348 and GFI � 0.9398.
According to Bagozzi (1980), standardized path coefficients are stable in comparing
relative contributions of factors to explained variance and are therefore reported in
Figure 1.

4.3 Direct effects
Supporting H1, relationship conflict was negatively related to team support (� � �0.154,
p � 0.001). Supporting H4, conflict management was positively related to team support
(� � 0.509, p � 0.001). Team support (� � 0.613, p � 0.001) was positively related to team
cohesion and team cohesion was positively related to team support (� � 0.24, p � 0.001),
supporting H7 and H8. H9 was also supported, with the results showing a stronger
influence of support on team cohesion than vice versa. H2 and H5 were not supported with
relationship conflict and conflict management having no direct effect on team cohesion
(� � �0.049, p � 0.225 and � � 0.019, p � 0.613, respectively).

4.4 Indirect effects
Indirect standardized path coefficients were computed by multiplying the respective
standardized direct path coefficients, and significance testing was performed using the
Sobel (1987) test. H3 proposes that the effect of relationship conflict on performance is
fully mediated through team support and team cohesion.

A non-significant direct effect between relationship conflict and team cohesion (see
H2) precludes support for full mediation through team support and team cohesion.

0.067

– 0.047

R2 =0.7124

R2 =0.5988

R2 =0.6843

0.316***

0.172*

0.648***

0.613***

0.019

0.509***

– 0.049

– 0.154***

Team Relationship Conflict

Team Conflict Management

Team Support

Team Cohesion

Team Performance

Notes: * p < 0.05; *** p < 0.001; dashed paths are non-significant; fit indices = χ2(67) = 136.84; χ2/df = 2.04; NNFI = 0.9801; CFI = 0.9853; RMSEA = 0.0593; PCLOSE = 0.1348; GFI = 0.9398

Figure 1.
Theoretical model
with standardized
path coefficients

TPM
22,5/6

250

Instead, given a non-significant direct path between relationship conflict and
performance (� � �0.047, p � 0.202), the only fully mediated effect of relationship
conflict on performance was through team support (� � �0.10, p � 0.001), partially
supporting H3. H6 proposes that the effect of conflict management on performance is
fully mediated through team support and team cohesion. A non-significant direct effect
between conflict management and team cohesion (see H5) precludes support for full
mediation through team support and team cohesion. Instead, given a non-significant
direct path between conflict management and performance (� � 0.067, p � 0.209), the
only fully mediated effect of conflict management on performance was through team
support (� � 0.33, p � 0.001), partially supporting H6.

H10 posits that the effect of team support on performance is partially mediated
through team cohesion. A significant direct effect of team support on performance
(see H7) and a significant indirect path between team support and performance, through
team cohesion (� � 0.105, p � 0.05), lend support to H10. H11 proposes that the effect
of team cohesion on performance is partially mediated through team support. A
significant direct effect of team cohesion on performance (see H8) and a significant
indirect path between team cohesion and performance, through team support (� � 0.205,
p � 0.001), demonstrate support for H11.

H12 through H15 posit the effects of relationship conflict and conflict management on
performance are partially mediated through the effect of team support on team cohesion and
through the effect of team cohesion on team support. Support for H12 is identified by the
significant indirect path between relationship conflict and performance, through the effect of
team support on team cohesion (� � �0.016, p � 0.05). A significant indirect path between
conflict management and performance, through the effect of team support on team cohesion
(� � 0.054, p � 0.05), provides support for H14. Neither relationship conflict nor conflict
management had significant direct effects on team cohesion (see H2 and H5), precluding
support for H13 and H15 (Table III).

5. Discussion
5.1 Contributions to theory
This study is one of the first that examines how relationship conflict and its
management affect performance (Tekleab et al., 2009). The study confirmed (as already
established in the literature) a direct positive effect of team support and team cohesion
on performance. The effects of relationship conflict and conflict management on team
support, previously unexplored in the literature, were also examined. As expected,
relationship conflict undermined team support and conflict management enhanced team
support. The relationship between the two mediators, team support and team cohesion,
was unexplored in the literature. This study purports and empirically establishes the
positive and stronger effect of team support on team cohesion and the positive but
weaker effect of team cohesion on team support. The results are intuitive, in that
intra-team supportive behaviors are prerequisite to the establishment of team cohesion.
Yet, team cohesion, once emerged or emerging, as a force of unity, positively influences
the propensity of team members to help one another.

The unexpected findings in the study are the non-significant effects of
relationship conflict and conflict management on team cohesion. These results are
surprising given the existing literature that established a direct negative
relationship between relationship conflict and team cohesion and a direct positive

251

Information
technology
development
teams

relationship between conflict management and team cohesion (Tekleab et al., 2009).
This “anomaly” is likely because of contextual factors and, surprisingly, it appears
to support the theorizing presented in the previous sections. Specifically, the
position of this study is that team work is a necessary condition for the emergence
of team cohesion. When team members are committed to working with each other it
creates a foundation for the formation of unity. Team cohesion, however, as a
structural property of a team, takes time to develop.

This study focused on teams that worked together for about three months. Hence,
there is a strong effect of relationship conflict and conflict management on team support
and no effect on team cohesion. Additionally, the effect of team support on team
cohesion is much stronger than the effect of team cohesion on team support. This
suggests that early in a team’s development, team support processes are the drivers of
team cohesion formation. Hence, when conflict occurs, it undermines team cohesion by
slowing or shutting down the very mechanisms necessary to bring cohesion to
“maturity”. The expectation, then, is for the links between relationship conflict and team

Table III.
Research hypotheses

Hypothesis Description Supported

1 Team relationship conflict is negatively related to team support

Yes

2 Team relationship conflict is negatively related to team

cohesion

3 The effect of team relationship conflict on team performance is
fully mediated through team support and team cohesion

4 Team conflict management is positively related to team
support

Yes

5 Team conflict management is positively related to team
cohesion

6 The effect of team conflict management on team performance is
fully mediated through team support and team cohesion

7 Team support is positively related to team cohesion Yes
8 Team cohesion is positively related to team support Yes
9 Team support will have a stronger impact on team cohesion

than team cohesion will have on team support
Yes

10 The effect of team support on team performance is partially
mediated through team cohesion

Yes

11 The effect of team cohesion on team performance is partially
mediated through team support

Yes

12 The effect of team relationship conflict on team performance,
through team support, is partially mediated through the effect
of team support on team cohesion

Yes

13 The effect of team relationship conflict on team performance,
through team cohesion, is partially mediated through the effect
of team cohesion on team support

14 The effect of team conflict management on team performance,
through team support, is partially mediated through the effect
of team support on team cohesion

Yes

15 The effect of team conflict management on team performance,
through team cohesion, is partially mediated through the effect
of team cohesion on team support

No
TPM
22,5/6

252

cohesion and conflict management and team cohesion to become more salient in more
established teams. Of course, it is possible, even in mature teams, for the effects of
relationship conflict and conflict management on team cohesion to still be fully mediated
through team support and other processes. That is, team cohesion as a positive
team-level attribute emerges from and is likely to be sustained by the ongoing
functioning of synergistic intra-team processes such as team support. As such, even in
mature teams, when the synergistic processes are shut down, the cohesion may also
diminish.

Lastly, the primary focus of this study was identifying mechanisms which
connect relationship conflict and conflict management to team performance. The
results demonstrate strong support for the full mediation model where the total
effects of relationship conflict and conflict management on performance were
mediated through team support first and then indirectly through team cohesion.
These findings are intuitive, in that helping behaviors within a team and the
cohesion that they nurture are proximal and necessary conditions for team
performance. When conflict or its management is activated their operation is either
disruption or repair of the team mechanisms and, consequently, team attributes that
drive team performance.

5.2 Limitations
Three limitations of this study should be considered before generalizing the results.
First, this study uses the perceptions of individual team members to assess team-level
phenomena. To ensure that the results were applicable to team-level theory, all
team-level constructs’ items were framed with team as the referent.

Second, constructs in structural equation models with only two indicators are often
associated with problems in identification and convergence. The models in this study
did not exhibit any problems with identification nor convergence.

Third, the sample was gathered in an academic setting. While the demographics
of undergraduates may differ from a traditional work setting, the academic context
afforded advantages that aid generalizability of the results. Data were collected
from several sections of a course taken by all business majors, the sample equally
represented males and females, students worked on an industry project rather than
an academic case and the 15-week semester provided time for team dynamics to be
experienced.

6. Conclusion
This study examined the mediating role of two specific team mechanisms, team support
and team cohesion. These intra-team mechanisms are shown to mediate the effect of
relationship conflict and conflict management on team performance. The results
support a full mediation model in which relationship conflict and conflict management
are mediated first through team support and then from team support indirectly through
team cohesion before affecting performance. Additionally, the mediators, team support
and team cohesion, are found to interact with each other, whereby team members who
support each other create a more cohesive team and team members who are unified offer
more support to one another.

253

Information
technology
development
teams

References
Alper, S., Tjosvold, D. and Law, K.S. (2000), “Conflict management, efficacy, and performance in

organizational teams”, Personnel Psychology, Vol. 53 No. 3, pp. 625-642.
Anderson, R.E. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and

recommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-423.
Ashforth, B.E. and Mael, F. (1989), “Social identity theory and the organization”, Academy of

Management Review, Vol. 14 No. 1, pp. 20-39.
Bagozzi, R.P. (1980), Causal Modeling in Marketing, Wiley, New York, NY.
Bagozzi, R.P. (1991), “Further thoughts on the validity of measures of elation, gladness and joy”,

Journal of Personality and Social Psychology, Vol. 61 No. 1, pp. 98-104.
Beal, D.J., Cohen, R.R., Burke, M.J. and McLendon, C.L. (2003), “Cohesion and performance in

groups: a meta-analytic clarification of construction relations”, Journal of Applied
Psychology, Vol. 88 No. 6, pp. 989-1004.

Behfar, K.J., Peterson, R.S., Mannix, E.A. and Trochim, W.M.K. (2008), “The critical role of conflict
resolution in teams: a close look at the links between conflict type, conflict management
strategies and team outcomes”, Journal of Applied Psychology, Vol. 93 No. 1, pp. 170-188.

Bodtker, A.M. and Jameson, J.K. (2001), “Emotion in conflict formation and its transformation:
application to organizational conflict management”, International Journal of Conflict
Management, Vol. 12 No. 3, pp. 259-275.

Bollen, K.A. and Hoyle, R.H. (1990), “Perceived cohesion: a conceptual and empirical
examination”, Social Forces, Vol. 69 No. 2, pp. 479-504.

Choi, J.N. and Sy, T. (2010), “Group-level organizational citizenship behavior: effects of
demographic faultlines and conflict in small work groups”, Journal of Organizational
Behavior, Vol. 31 No. 7, pp. 1032-1054.

Cronbach, L.J. (1951), “Coefficient alpha and the internal structure of tests”, Psychometrika, Vol. 16
No. 3, pp. 297-334.

Cropanzano, R., Aguinis, H., Schminke, M. and Denham, D.L. (1999), “Disputant reactions to
managerial conflict resolution tactics – a comparison among Argentina, the Dominican
Republic, Mexico, and the United States”, Group & Organization Management, Vol. 24
No. 2, pp. 124-154.

Drach-Zahavy, A. (2004), “Exploring team support: the role of team’s design, values, and leader’s
support”, Group Dynamics – Theory Research and Practice, Vol. 8 No. 4, pp. 235-252.

Drach-Zahavy, A. and Somech, A. (2002), “Team heterogeneity and its relationship with team
support and team effectiveness”, Journal of Educational Administration, Vol. 40 No. 1,
pp. 44-66.

Folger, J., Poole, M. and Stutman, R. (2001), Working through Conflict: Strategies for Relationships,
Groups and Organizations, 5th ed., Longman, New York, NY.

Fornell, C. and Larcker, D.F. (1981), “Evaluating structural equation models with unobserved
variables and measurement error”, Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.

Guzzo, R.A. (1995), “At the intersection of team effectiveness and decision making”, in Guzzo, R.A.
and Salas, E. (Eds), Team Effectiveness and Decision Making in Organizations, Jossey-Bass,
San Francisco, CA, pp. 1-8.

TPM
22,5/6

254

Hair, J.F. Jr, Anderson, R.E., Tatham, R.L. and Black, W.C. (1998), Multivariate Data Analysis, 5th
ed., Prentice Hall, Upper Saddle River, NJ.

Hatcher, L. (1994), A Step-by-Step Approach to Using the SAS System for Factor Analysis and
Structural Equation Modeling, SAS Institute Inc, Cary, NC.

Hempel, P.S., Zhang, Z.X., and Tjosvold, D. (2009), “Conflict management between and within
teams for trusting relationships and performance in China”, Journal of Organizational
Behavior, Vol. 30 No. 1, pp. 41-65.

Hogg, M.A. (2001), “A social identity theory of leadership”, Personality and Social Psychology
Review, Vol. 5 No. 3, pp. 184-200.

Hogg, M.A. and Terry, D.J. (2000), “Social Identity and self-categorization processes in
organizational contexts”, Academy of Management Review, Vol. 25 No. 1, pp. 121-140.

Hogg, M.A., Terry, D.J. and White, K.M. (1995), “A tale of two theories: a critical comparison of
identity theory with social identity theory”, Social Psychology Quarterly, Vol. 58 No. 4,
pp. 255-269.

Huang, J. (2010), “Unbundling task conflict and relationship conflict – the moderating role of team
goal orientation and conflict management”, Information Technology & People, Vol. 21 No. 3,
pp. 334-355.

Jehn, K.A. (1995), “A multimethod examination of the benefits and detriments of intragroup
conflict”, Administrative Science Quarterly, Vol. 40 No. 2, pp. 256-282.

Jehn, K.A. and Bendersky, C. (2003), “Intragroup conflict in organizations: a contingency
perspective on the conflict-outcome relationship”, Research and Organizational Behavior,
Vol. 24 No. 1, pp. 187-242.

Jehn, K.A., Northcraft, G.B. and Neale, M.A. (1999), “Why differences make a difference: a field
study of diversity, conflict, and performance in workgroups”, Administrative Science
Quarterly, Vol. 44 No. 4, pp. 741-763.

Kirchmeyer, C., and Cohen, A. (1992), “Multicultural groups – their performance and reactions
with constructive conflict”, Group & Organization Management, Vol. 17 No. 2, pp. 153-170.

Lau, R.S. and Cobb, A.T. (2010), “Understanding the connections between relationship conflict and
performance: the intervening roles of trust and exchange”, Journal of Organizational
Behavior, Vol. 31 No. 6, pp. 898-917.

Lee, J., Lee, H. and Park, J. (2014), “Exploring the impact of empowering leadership on knowledge
sharing, absorptive capacity and team performance in IT services”, Information
Technology & People, Vol. 27 No. 3, pp. 366-386.

LePine, J.A., Piccolo, R.F., Jackson, C.L., Mathieu, J.E. and Saul, J.R. (2008), “A meta-analysis of
teamwork processes: tests of a multidimensional model and relationships with team
effectiveness criteria”, Personnel Psychology, Vol. 61 No. 2, pp. 273-307.

Montoya-Weiss, M.M., Massey, A.P. and Song, M. (2001), “Getting it together: temporal
coordination and conflict management in global virtual teams”, Academy of Management
Journal, Vol. 44 No. 6, pp. 1251-1262.

Mossholder, K.W., Bennett, N., Kemery, E.R. and Wesolowski, M.A. (1998), “Relationships
between bases of power and work reactions: the mediational role of procedural justice”,
Journal of Management, Vol. 24 No. 4, pp. 533-552.

Nunnally, J.C. (1993), Psychometric Theory, McGraw-Hill, New York, NY.

Piccoli, G., Powell, A. and Ives, B. (2004), “Virtual teams: team control structure, work processes,
and team effectiveness”, Information Technology & People, Vol. 17 No. 4, pp. 359-379.

255

Information
technology
development
teams

Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in organizational research: problems and
prospects” Journal of Management, Vol. 12 No. 4, pp. 531-544.

Podsakoff, P.M., MacKenzie, S.B., Podsakoff, N.P. and Lee, J.Y. (2003), “Common method biases in
behavioral research: a critical review of the literature and recommended remedies”, Journal
of Applied Psychology, Vol. 88 No. 5, pp. 879-903.

Simons, T.L. and Peterson, R.S. (2000), “Task conflict and relationship conflict in top management
teams: the pivotal role of intragroup trust”, Journal of Applied Psychology, Vol. 85 No. 1,
pp. 102-111.

Sobel, M.E. (1987), “Direct and indirect effects in linear structural equation models”, Sociological
Methods & Research, Vol. 16 No. 1, pp. 155-176.

Somech, A., Desivilya, H.S. and Lidogoster, H. (2009), “Team conflict management and team
effectiveness: the effects of task interdependence and team identification”, Journal of
Organizational Behavior, Vol. 30 No. 3, pp. 359-378.

Stets, J.E. and Burke, P.J. (2000), “Identity theory and social identity theory”, Social Psychology
Quarterly, Vol. 63 No. 3, pp. 224-237.

Stewart, G.L. and Barrick, M.R. (2000), “Team structure and performance: assessing the mediating
role of intrateam process and the moderating role of task type”, Academy of Management
Journal, Vol. 43 No. 2, pp. 135-148.

Tajfel, H. (1972), “La catégorisation sociale”, in Moscovici, S. (Ed.), Introduction à la Psychologie
Sociale (Vol. 1), Larousse, Paris.

Tekleab, A.G., Quigley, N.R. and Tesluk, P.E. (2009), “A longitudinal study of team conflict,
conflict management, cohesion, and team effectiveness”, Group & Organizational
Management, Vol. 34 No. 2, pp. 170-205.

Thaler, R.H. and Sunstein, C.R. (2008), Nudge: Improving Decisions about Health, Wealth, and
Happiness, Yale University Press, New Haven, CT.

Tjosvold, D., Hui, C., and Yu, Z.Y. (2003), “Conflict management and task reflexivity for team
in-role and extra-role performance in China”, International Journal of Conflict Management,
Vol. 14 No. 2, pp. 141-163.

Tuckman, B.W. (1965), “Developmental sequence in small groups”, Psychological Bulletin, Vol. 63
No. 6, pp. 384-399.

Van Der Vegt, G.S. and Bunderson, J.S. (2005), “Learning and performance in multidisciplinary
teams: the importance of collective team identification”, Academy of Management Journal,
Vol. 48 No. 3, pp. 532-547.

Ward, A.J., Lankau, M.J., Amason, A.C., Sonnenfeld, J.A. and Agle, B.R. (2007), “Improving the
performance of top management teams”, MIT Sloan Management Review, Vol. 48 No. 3,
pp. 85-90.

Yukelson, D., Weinberg, R. and Jackson, A. (1984), “A multi-dimensional group cohesion
instrument for intercollegiate basketball teams”, Journal of Applied Psychology, Vol. 6 No. 1,
pp. 103-117.

Corresponding author
Tobin Porterfield can be contacted at: tporterfield@towson.edu

TPM
22,5/6
256

mailto:tporterfield@towson.edu

mailto:permissions@emeraldinsight.com

Reproduced with permission of the copyright owner. Further reproduction prohibited without
permission.

Conflict management and performance of information technology development teams

1. Introduction
2. Background and research model
3. Methodology
4. Results
5. Discussion
6. Conclusion
References

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

A Model of Conflict, Leadership, and Performance in Virtual Teams
Wakefield, Robin L;Leidner, Dorothy E;Garrison, Gary
Information Systems Research; Dec 2008; 19, 4; ABI/INFORM Collection
pg. 434

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

A review of factors affecting individual performance in team …
O’Connor, Matthew
Library Management; 2006; 27, 3; ABI/INFORM Collection
pg. 135

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

A review of factors affecting individual performance in team …
O’Connor, Matthew
Library Management; 2006; 27, 3; ABI/INFORM Collection
pg. 135

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Exploring the Effects of Value Diversity on

Team Effectivenes

David J. Woehr • Luis M. Arciniega •

Taylor L. Poling

Published online: 2 June 201

� Springer Science+Business Media, LLC 2012

Abstract

Purpose The goal of the present study was to explore the

potential impact of within-team value diversity with

respect to both team processes and task performance.

Design/Methodology/Approach We explored value

diversity within a comprehensive framework such that all

components of basic human values were examined. A

sample of 306 participants randomly assigned to 60 teams,

performed a complex hands-on task, demanding high

interdependence among team members, and completed

different measures of values and team processes.

Findings Results indicated that value diversity among

team members had no significant impact on task perfor-

mance. However, diversity with respect to several value

dimensions had a significant unique effect on team process

criteria. Results were consistent with respect to the nature

of the impact of value diversity on team process outcomes.

Specifically, the impact of team value diversity was such

that less diversity was positively related to process out-

comes (i.e., more similarity resulted in more team cohesio

and efficacy and less conflict).

Implications The results indicated that disparity among

teammates in many of these values may have important

implications on subsequent team-level phenomena. We

suggest team leaders and facilitators of teambuilding

efforts could consider adding to their agendas a session

with team members to analyze and discuss the combined

value profiles of their team.

Originality/Value This is the first study to highlight the

unique impact of many unexamined, specific components

of team diversity with respect to values on team effec-

tiveness criteria.

Keywords Value diversity � Team diversity �
Team processes � Team effectiveness � Team cohesion �
Team conflict

Work force diversity has become an increasingly promi-

nent concern in recent years. Many organizations have

moved to incorporate diversity into their business structure

and strategy, hoping for both societal approval and positive

performance dividends (Horwitz 2005). The focus on

workforce diversity taken together with the increased

emphasis on team-based work groups (Applebaum and Batt

1994; Ilgen 1999) has resulted in a surge of interest in the

relationship between team member diversity and overall

team effectiveness (e.g., Bell 2007; Horwitz 2005; Kle

et al. 2011; Mannix and Neale 2005; Mohammed and

Angell 2004; Webber and Donahue 2001; Harrison et al.

1998; Jackson and Rudermann 1997; Milliken and Martins

1996). Although the majority of past research has focused

on demographic, surface-level diversity (e.g., age, race,

gender) (Harrison et al. 1998), the impact of diversity with

respect to deeper, psychological variables (e.g., values,

personality, attitudes, etc.) is likely of greater concern. As

stated by Hollenbeck et al. (2004), ‘‘demographic diversity

is actually less important to team performance than

D. J. Woehr

Management Department, University of North Carolina,

Charlotte, NC, USA

L. M. Arciniega (&

)

Management Department, Instituto Tecnológico Autónomo de

México (ITAM) School of Business, Rı́o Hondo 1, Mexico,

D.F. 01080, Mexico

e-mail: larciniega@itam.mx

T. L. Poling

Joint Advertising Market Research and Studies (JAMRS),

Alexandria, VA, USA

123

J Bus Psychol (2013) 28:107–12

DOI 10.1007/s10869-012-9267-4

psychological diversity, especially over time’’ (p. 357).

Thus, the goal of the present study is to explore the

potential impact of within team diversity with respect to a

specific set of psychological characteristics, namely values,

on both team processes and task outcomes. It is important

to highlight the lack of studies in this specific line of

research, and more over, the inexistence of a study utilizing

a comprehensive taxonomy of basic values to examine

these relations. This study focuses on filling this gap.

Defining Diversity

Mannix and Neale (2005) note that diversity is a complex

and multifaceted term. It encompasses a variety of differ-

ences among people (e.g., demographic variables, job-

related characteristics, attitudes, values, personality traits,

etc.), and the positive or negative effects of diversity may

be contingent on the variables under investigation as well

as the performance criteria. In a review of the team com-

position literature, Bell (2007) contends that discussing

‘‘diversity’’ without reference to a particular attribute or

variable is meaningless; thus, the specific variable or

family of variables on which team members differ must be

identified before the relationship with team effectiveness

can be examined. In order to provide some conceptual

organization to this multifaceted phenomenon, recent the-

oretical discussions have classified dimensions of diversity

into two general categories: attributes that are demographic

and non-psychological versus attributes that are non-visi-

ble, underlying, and psychological in nature.

Attributes that are non-psychological and easily detect-

able fall under Harrison et al.’s (1998) surface-level

categorization. Typical attributes associated with this cat-

egorization include age, gender, race, and physical dis-

abilities (Mannix and Neale 2005). In contrast, non-

apparent, psychological differences (e.g., cognitive ability,

personality traits, values, beliefs, and attitudes) fall under

the deep-level diversity category (Harrison et al. 1998).

Information on deep-level attributes is acquired via

observation of verbal and non-verbal behavioral patterns

(Harrison et al. 1998). The deep-level label is analogous to

similar descriptors such as ‘‘underlying’’ (Milliken and

Martins 1996), ‘‘less observable’’ (Jackson et al. 1995), and

‘‘psychological’’ (Jackson and Rudermann 1997) used by

other researchers. General values are prominent examples

of Harrison’s deep-level diversity category.

Team diversity in surface-level characteristics has been

the focus of ample research, which taken as a whole has

yielded equivocal results (e.g., Webber and Donahue

2001). However, deep-level diversity may operate dif-

ferently than surface-level diversity. In fact, research

has demonstrated that surface-level diversity does not

necessarily relate to deep-level diversity (Harrison et al.

2002; Horwitz and Horwitz 2007). These findings highlight

the need for the direct investigation of deep-level diversity.

Yet, the research on deep-level diversity to date is under-

developed. Specifically, Bell (2007) demonstrated that of

studies examining deep-level team composition, those

focusing on diversity are few, fragmented, and inconsis-

tent. Bell (2007) also highlighted the dearth of studies on

team member value composition despite the role of values

as behavioral and attitudinal determinants. Tentative find-

ings for only two specific value dimensions (i.e., collec-

tivism and preference for teamwork) were reported, which

were based on data from three and two studies, respec-

tively. Bell (2007) commented that further research is

necessary to assess the impact of other value dimensions on

team performance. We propose that these other dimensions

should include basic human values such as those related to

independent thought and action, stability of self and rela-

tionships, and the welfare of others with whom one is in

constant interaction. Basic values such as these have sig-

nificant implications for interpersonal behavior.

Theoretical Underpinnings of Potential Diversity

Effects

Research on deep-level team diversity in general and value

diversity in particular, has only recently begun to emerge

and is relatively limited (Harrison et al. 2002). However, the

theoretical foundations of this research are longstanding.

There are two primary classes of theories underpinning this

area of study. On the surface, these theories appear to be in

direct opposition, as one advocates a ‘‘pessimistic’’ view of

diversity and the other an ‘‘optimistic’’ view (Mannix and

Neale 2005). In general, the pessimistic view focuses on the

affective and interactional problems caused by diversity;

whereas, the optimistic view posits enhanced creativity,

quality, and innovative task performance that results from

increased access to a variety of perspectives and resources

(Kravitz 2005). Respectively, these views are grounded in

the similarity-attraction/social identity paradigms, and the

information processing/cognitive resource paradigms.

The Pessimistic Perspective

In general, negative expectations regarding the impact of

diversity in team composition stem from the similarity-

attraction paradigm (Byrne 1971; Tziner 1985) and social

identity theory (Tajfel 1978). Social attraction theory posits

that similarity in values, beliefs, and attitudes increases

interpersonal attraction, and when individuals like each

other, their values, beliefs, and attitudes become more

aligned. Together, attraction and similarity reciprocally

108 J Bus Psychol (2013) 28:107–121

build on one another, facilitating a pull toward symmetry

and an avoidance of the strain produced by dissimilarity

(Rosenbaum 1986; Mannix and Neale 2005). Furthermore,

people tend to categorize themselves relative to similar

others and in an effort to maintain their social identities,

they will demonstrate a bias toward those whom they

believe share similar characteristics (Tajfel and Turner

1986; Turner and Haslam 2001). Byrne’s (1971) early

attraction-similarity research supports the perspective that

individuals are drawn toward others who they think share

similar attitudes to themselves and report that these indi-

viduals are smarter and more well-adjusted than others.

These propositions also underlie Schneider’s (1987) well-

known attraction, selection, attrition (ASA) theory, which

supports the notion that this similarity-attraction process

naturally produces increasingly homogenous work envi-

ronments (Giberson et al. 2005).

Overall, these theories posit that teams with members

who have homogeneous values will more readily identify

with each other. As a result, they will be more cohesive,

facilitating both interaction and subsequent performance.

Teams with heterogeneous values are predicted to be less

cohesive and thus less productive because of the conflicts

and stress that result from the differences in members’

beliefs.

The Optimistic Perspective

Alternately, cognitive resource theory posits the ‘‘value in

diversity’’ hypothesis, which advocates the benefits of the

unique resources that members with diverse attributes

bring to the team (Cox and Blake 1991; Easley 2001). The

underlying assumption here is that diversity in members’

attributes will result in more informed decisions by pro-

moting creativity, innovation, and alternative problem

solving. This information processing perspective suggests

that differences create an opportunity for team members to

share different perspectives and thus examine issues at a

deeper level of analysis (Mannix and Neale 2005). More-

over, different perspectives are predicted to interact syn-

ergistically to create a ‘‘process gain’’ for the group to the

extent that they are able to overcome potential social-

integration problems that may result from their differing

perspectives (Steiner 1972).

Overall, cognitive resource theory posits that diverse

values among teammates will contribute to better team

performance. Members will share information from a

greater variety of perspectives, a practice that leads to

higher quality analysis of tasks, which in turn fosters higher

quality results. Although these two perspectives are often

pitted against one another, they are not necessarily mutu-

ally exclusive. For example, a team with a diverse set of

perspectives may produce high quality task results (e.g.,

more creative solutions), but in the process experience

interpersonal conflict and low cohesion. Moreover, even

supporters of the ‘‘value in diversity’’ hypothesis have

noted that diversity may offer benefits for team outcomes

even as it creates barriers for team interaction processes

(Mannix and Neale 2005). In sum, while these theoretical

perspectives posit different expectations with respect to

value diversity, it is feasible for both perspectives to

operate simultaneously contingent on the value and type of

criterion in question. Even when this approach is theoret-

ically feasible, a recent meta-analysis highlights the lack of

studies combining both perspectives at the same time (Van

Knippenberg and Schippers 2007).

As noted above, the primary goal of the present study is

to explore team member value diversity with respect to an

encompassing taxonomy of basic human values. Our

objective is to dig into the impact of team value diversity

on task performance, and on the following aspects of team

effectiveness: relationship and task conflict, cohesion, and

team efficacy. Below, we begin by presenting a brief

review of previous findings pertaining to value diversity.

Next, we discuss the concept of basic values and present

Schwartz comprehensive model of values. We then briefly

highlight the key team process variables that reflect team

effectiveness and that are likely to be influenced by team

member value diversity. Finally, we consider several

research questions addressed in this study.

Previous Findings on Value Diversity

As noted by Harrison et al. (2002), and more recently by

Bell (2007), relatively little research has examined the

impact of diversity among team members in terms of basic

values on effectiveness (c.f., Fisher et al. 1996; Jehn et al.

1997; Jehn and Mannix 2001; Klein et al. 2011). Among

the few relevant existing studies, there is substantial vari-

ability with respect to both the conceptual and operational

definitions of values as well as the outcomes examined.

One approach has been to measure basic values at the

individual-level using the classic Rokeach Value Survey

(RVS; Rokeach 1979), and then either aggregate members

responses to represent the team level (Rodriguez 1998) or

compute their concordance (Fisher et al. 1996). Regarding

this measure, Rokeach never suggested any a priori struc-

ture for the RVS, and further studies suggest that it does not

cover the full domain of the values construct (e.g., Sch-

wartz 1992). Nonetheless, Fisher and collaborators indi-

cated that teams with more agreement in their ratings

across the set of nine personal value scales, demonstrated

better task performance than those with less concordance.

Though the study presented promising results, it had a

serious limitation: after collecting data from 22 teams of

J Bus Psychol (2013) 28:107–121 109

123

undergraduate students, 12 teams were dropped due to

inadequate levels of concordance between the members’

values ratings. As a result, the analyses were based on only

ten teams. The other study employing this approach

(Rodriguez 1998), also used a very small sample – 11

teams.

Recently, Klein et al. (2011) demonstrated that team

leader style moderates the relationship between team val-

ues diversity and team conflict. They propose that leaders

who are task-focused, create a strong team setting, with

clear rules and roles, constraining the influence of team

members’ values. Even when the results are relevant, they

analyzed value diversity from a simple framework of two

values: Protestant work ethic (individual tendency to work

hard even in the absence of material rewards) and tradi-

tionalism (commitment and acceptance of the customs and

ideas of traditional cultures or religions). This framework

does not cover relevant aspects of the values domain such

as: power, achievement, altruism, etc.

Another approach used previously has been to measure

organizational values preferences at the individual-level,

and then compare the profiles of team members to assess

value congruence (Jehn 1994). Using this approximation,

Jehn and Mannix (2001) found that team member simi-

larity with respect to work-related values (i.e., similarity

across a set of 54 items related to innovativeness, stability,

detail orientation, outcome orientation, aggressiveness,

supportiveness, reward orientation, team orientation, and

decisiveness) was positively related to task performance.

However, Jehn and collaborators (1997) examined team

member value congruence (defined in terms of a median

split of team consistency scores derived from ratings of the

same work-related values discussed previously) and found

that value congruence was related to perceived perfor-

mance via a negative correlation with relationship conflict;

however, value congruence did not relate to subjective

expert ratings of task performance. Both studies employed

an adapted version of the Organizational Culture Profile

(OCP; O’Reilly et al. 1991). The OCP was developed to

obtain profiles of the cultures of organizations, and to

assess individual preferences for organizational cultures

(O’Reilly et al. 1991, p. 496), but not to measure individual

values.

Finally, there are various studies using cultural-level

values measured at the individual-level (e.g., Eby and

Dobbins 1997; Vodosek 2007). These studies rest on the

assumption that research on cultural diversity can be con-

ducted using individual-level representations of cultural-

level constructs (e.g., Maznevski et al. 2002), since some

aspects of culture are internalized by individuals. For

instance, Kirkman and Shapiro (2001) reported on the

impact of collectivism, power distance, doing orientation,

and determinism on the performance of self-managed work

teams, utilizing an instrument that operationalized two

different models of cultural values (i.e., Hofstede 1991;

Kluckhohn 1951). According to Smith and Schwartz

(1997), this approach is inappropriate. These cross-cultural

scholars argue that the relations between values at the

cultural level reflect the dynamic conflicts of the societies

that exist as a result of the way their institutions pursue

their goals, adding that these relations are not necessarily

the same at the individual-level.

Schwartz Model of

Values

Values have generally been referred to as needs, beliefs, or

norms. Values can be best understood as cognitive repre-

sentations of universal needs (Rokeach 1979; Schwartz

1992). These needs are expressed through over-arching

goals that direct behavior across situations, and are ordered

by importance as guiding principles in life (Schwartz et al.

2001). Schwartz (1992) posits that the essence of a value is

the motivational goal it expresses. From this premise,

Schwartz derived ten value types that form a circumplex

structure (see Fig. 1) such that value types that share a

similar general motivational goal are arranged closer

together. Alternately, types representing divergent goals

are arranged more distantly around the circumference of

the model. For instance, power (PO) and achievement (AC)

are two compatible value types sharing the general

Fig. 1 Example value profiles of the members of a team. SD self-
direction, UN universalism, BE benevolence, CO conformity,
TR tradition, SE security, PO power, AC achievement, HE hedonism,
ST stimulation

110 J Bus Psychol (2013) 28:107–121

123

motivational goal of enhancing personal status, even at the

expenses of others. Conversely, power (PO) and univer-

salism (UN) are two conflicting values; the motivational

goal of power is enhancing personal interests, whereas the

motivational goal of universalism is promoting the welfare

of others. The pattern of compatibilities and incompati-

bilities between value types is based on the premise that

actions taken in the pursuit of each type have both psy-

chological and behavioral consequences, which may be

compatible or in conflict with the goals derived from other

values. The Appendix provides a brief description of the

ten value types (for a full description of these values see

Schwartz 1992). It is important to highlight that a recent

meta-analysis has validated this circumplex structure in

more than seventy countries (Steinmetz et al. 2012)

Team member diversity in values is represented by the

disparity in the importance assigned by each team member

to each value type. The more the variability in the impor-

tance assigned by the members of the team to each value

type, the greater the level of diversity across team mem-

bers. Figure 1 shows this idea schematically. Each radius

represents one of ten value types, and each irregular

decagon, the profile of a team member. The lower the

importance a team member assigns to a specific value, the

closer the point associated with that individual’s profile

will be to the center on the respective value radius. The

degree of spread among the points on a given value radius

represents the degree of team diversity on that value. For

instance, in the case of the radius of benevolence (BE), the

variance among the four value profiles is low compared to

the variance on the radius for achievement (AC). Given the

contradictory nature across the motivational goals under-

lying opposing values, it is inappropriate to compute an

overall ‘‘values’’ score. Moreover, the configuration

approach (Moynihan and Peterson 2001) argues that whe-

ther homogeneity or heterogeneity regarding deep-level

attributes is preferable depends on the specific value or trait

in question. Consistent with these propositions, diversity

should be examined separately with respect to each of the

ten values. Given the predominant role of values with

respect to attitudes and subsequent behavior, team member

value diversity is likely to be a key factor for both process

and outcome measures of team effectiveness.

Team Effectiveness

The evaluation of teams encompasses a variety of com-

ponents. Many theories have addressed the multifaceted

nature of team effectiveness (e.g., Shea and Guzzo 1987;

Gladstein 1984; Hackman 1987). According to Hackman

(1987), group effectiveness can be defined in terms of three

criteria. First, the final outputs produced by the team must

meet or exceed the standards set by key constituents within

the organization. Second, the internal social processes

operating as the team interacts should enhance, or at least

maintain, the group’s ability to work together in the future.

Finally, the experience of working in the team environment

should act to satisfy rather than aggravate the personal

needs of team members. In order to address these criteria,

team effectiveness evaluation should include both a mea-

sure of the teams’ final task performance as well as criteria

with which to assess intragroup process. The current paper

explores task performance and prominent team process

criteria. The three major intragroup process constructs

examined are: intra-group conflict, team cohesion, and

team-efficacy.

Intra-group conflict has emerged as an integral team

process variable. Previous research has differentiated two

components of intra-group conflict: relationship conflict and

task conflict. Jehn (1994) describes relationship conflict as

interpersonal incompatibilities between team members such

as annoyance and animosity. Task conflict occurs when

members convey divergent ideas and opinions about specific

aspects related to task accomplishment (Jehn 1994).

Research to date indicates that relationship conflict is largely

detrimental to team performance (e.g., Evan 1965; Baron

1991; van Woerkom and van Engen 2009; Vodosek 2007).

The impact of task conflict is less clear. While it has been

argued that task conflict facilitates enhanced performance

via thorough task analysis (e.g., Amason and Schweiger

1994), empirical evidence is equivocal. Some research has

found positive relationships between task conflict and novel

idea generation and strategic planning (Baron 1991; Amason

1996), but others have shown task conflict may hinder goal

accomplishment and implementation (Amason 1996;

Vodosek 2007). In a direct investigation of task conflict,

Jehn (1994) found only a small amount of task conflict was

beneficial, after which team performance began to deterio-

rate, and a meta-analysis demonstrated a negative relation-

ship between task conflict and team satisfaction and

performance (De Dreu and Weingart 2003). Nonetheless,

both types of conflict have proven to be significant correlates

of a variety of team effectiveness criteria.

Team cohesion is another important process variable

(Chiocchio and Essiembre 2009; Swezey and Salas 1992).

While a multitude of definitions and measures have been

offered (Mullen and Copper 1994), basically, cohesion is

viewed as ‘‘a general indicator of synergistic group

interaction—or process’’ (Barrick et al. 1998, p. 382).

Meta-analyses have revealed significant team cohesion-

performance effects (Beal et al. 2003; Mullen and Copper

1994). Furthermore, cohesion has been linked to greater

coordination during team-tasks (Morgan and Lassiter 1992)

as well as improved satisfaction, productivity, and group

interactions (Bettenhausen 1991).

J Bus Psychol (2013) 28:107–121 111

123

Finally, team efficacy is another important team process

construct. Team efficacy refers to team members’ percep-

tions of task-specific team competence (Gibson 1999). This

construct is thought to create a sense of confidence within

the team that enables the group to persevere when faced

with hardship (Gully et al. 2002). Several researchers have

related team efficacy to aspects of team effectiveness (e.g.,

Campion et al. 1993; Gibson 1999; Gibson et al. 2000),

and a meta-analysis demonstrated that the relationship

between team efficacy and performance was greater than

that between cohesion and performance (Gully et al. 2002).

Present Study

Our review of both the extant research as well as the

theoretical underpinnings highlights several limitations in

the literature to date. Specifically, the few studies exam-

ining diversity with respect to team member values has

largely focused on congruence across a set of context

specific values as opposed to a comprehensive set of more

broadly defined values such as that posited by Schwartz.

To date, no study has examined team member diversity

with respect to the full domain of values on both process

and performance criteria. Moreover, the literature offers

little guidance as to whether value diversity will lead to

positive or negative effects with respect to team processes

and outcomes, or to what extent these effects will be

contingent on the specific value dimensions examined.

Finally, while the literature examining the impact of sur-

face-level diversity has capitalized on the fact that these

characteristics are readily observable and therefore likely

to have immediate effects on team outcomes. It has been

argued, however, that diversity with respect to deep-level

characteristics such as values may take longer to manifest

itself with respect to team outcomes (e.g., Harrison et al.

1998). Therefore, it is not at all clear as to whether there

will be effects of value diversity in short-term novel

teams.

Thus, our goal in the present study is to explore the

relationship between values diversity and team effective-

ness. We provide a preliminary investigation of the impact

of basic values, on both process and task performance

aspects of team effectiveness. Toward this end, we seek to

address two research questions. Specifically:

(1) To what extent does diversity across team members

with respect to basic values impact team process and

outcome variables in a short-term team task with

novel teams?

(2) Will the impact of team member value diversity be

consistent with the optimistic or pessimistic views of

team diversity?

Method

Participants

Three hundred and six undergraduate college students at a

large U.S. southeastern university participated in the

present study. Participants were randomly assigned to

mixed gender teams of 4–6 (M = 4.6; mode = 5) resulting

in 60 teams. Participants were 43 % (134) male, and 78 %

(237) white. The mean age of participants was 22 years,

and the ages ranged from 19 to 38 years (SD = 2.32).

Task

The task was a complex team-based exercise called the

Chinese Bridge (Arciniega and Castañón 2002). The task is

a relatively difficult one requiring both the design and

building of a complex structure. Specifically, the task

requires each team to design and build a replica of a real

bridge, using 33 plastic pipes of three different sizes and 20

rubber bands (with instructions that all of the materials

must be used in the bridge). The task is designed such that,

given the material available, there is one optimal solution.

In addition, the task is designed so that even if a team were

given specific plans for the bridge, multiple people working

together are required to actually build the structure (e.g.,

one must hold pieces while another connects them, etc.).

Thus, successful completion requires team members to

work interdependently. This type of simulation could be

categorized as a high interdependence task, since team

members collectively work together to complete the task

while sharing information and resources (Horwitz and

Horwitz 2007). Based on a recent review of the literature

(Joshi and Roh 2008), these contextual factors combining

task interdependence and complexity, promote a scenario

where deep-level team diversity variables really emerge.

The simulation consists of four phases: (a) a multimedia

presentation describing the task and presenting a picture of

the real bridge; (b) a 20-min period for team members to

familiarize themselves with the materials; (c) a 30-min

period to sketch a proposed design of the bridge; and

(d) the building phase lasting approximately 60 min.

Measures

Values

Values were assessed using the Portrait Values Question-

naire (PVQ; Schwartz et al. 2001). The 40-item PVQ

measures the ten value types proposed by Schwartz (1992).

These values as measured by the PVQ are defined in the

Appendix. The scale includes short verbal portraits of

hypothetical individuals (e.g., Thinking up new ideas and

112 J Bus Psychol (2013) 28:107–121

123

being creative is important to him. He likes to do things in his

own original way). Respondents are asked to rate the extent

to which they agreed with each item on a scale from 1 (not

like me at all) to 6 (very much like me). The PVQ has been

used in several studies, in more than 60 countries, and has

been shown to be a reliable and valid measure of personal

values (Schwartz 1992; Schwartz et al. 2001). The average

alpha across these ten dimensions was .68 (SD = .08).

Here, it is important to note that previous studies utilizing

the PVQ during the last decade have tended to report rel-

atively low reliability estimates (particularly estimates of

internal consistency) for many of the value dimensions

(e.g., Aitken-Schermer et al. 2008; Fotopoulos et al. 2011;

Liem et al. 2011; Schwartz et al. 2001). Schwartz justifies

the low reliability of some of the value scales based on the

fact that many of these, have conceptually broad defini-

tions, assessing multiple components, rather than narrowly

defined constructs (Schwartz et al. 2001, pp. 531–532).

Consistent with this perspective, previous studies have

found clear effects between the value types and a plethora

of psychological variables under study despite relatively

low reliability estimates. Nonetheless, the tradition scale

demonstrated a particularly low alpha (.54) in the present

study; thus, it was not included in further analyses.

Task and Relationship Conflict

Conflict was measured using Jehn’s Intragroup Conflict

Scale (ICS; 1994). The scale contains four items related to

the task conflict dimension (e.g., There are differences of

opinion regarding the task in my work group), and four

items related to the relationship conflict dimension (e.g.,

There are personality clashes present in my work group).

Participants are asked to rate the extent to which they

agreed with each item on a scale from 1 (strongly disagree)

to 7 (strongly agree). Alphas for these scales were .85 (task

conflict) and .87 (relationship conflict).

Cohesion

Cohesion was measured using two items from Podsakoff and

MacKenzie’s (1994) Substitutes for Leadership Scale and

four items from Zaccaro (1991). Each of the 6 items consists

of a short statement regarding the cohesion of the individ-

ual’s team (e.g., I generally get along well with my fellow

group members). Respondents are asked to rate the extent to

which they agreed with each item on a scale from 1 (strongly

disagree) to 7 (strongly agree). Alpha for the scale was .75.

Team Efficacy

Team-efficacy was assessed with a 2-item scale con-

structed specifically for this study (e.g., My team works as

an effective unit and My team has an effective plan for

completing the bridge task). Respondents rated the extent

to which they agreed with each item using a 7-point scale

from 1 (strongly agree) to 7 (strongly disagree). Alpha for

this scale was .73.

Team Task Performance

Task performance was measured as the extent to which a

team was able to complete the task and the quality of the

finished product (i.e., the bridge replica). Following com-

pletion of the task, a photograph was taken of each team’s

bridge. Next, each photograph was evaluated by a group of

5 raters familiar with the task. Ratings were made on a

5-point scale from 1 (non-standing structure) to 5 (arched

bridge with 5 cross pieces and perfect joints). After each

member of the research group provided their initial rating,

the entire group came to consensus on a single rating for

the bridge (mean level of agreement in the initial ratings

across raters was 88 %). The consensus rating was used as

the measure of team performance.

Procedure

All participants completed the values measures during the

week preceding their participation in the bridge task. On

the day of the simulation, all participants first viewed the

task overview presentation as a group and then were bro-

ken up into their teams and assigned to separate team

rooms to complete the task. Teams completed each phase

of the bridge task, and then each participant individually

completed the team process measures.

Results

All analyses were conducted at the team-level. To assess

diversity, the variance across team members for each of the

ten value scales was computed (e.g., Barrick et al. 1998;

Mohammed and Angell 2003; Neuman et al. 1999).

Descriptive statistics and intercorrelations for the compo-

sition of team value types are shown in Table 1. Statistics

are presented for the team-level for mean composition of

values (control variables) and the average degree of within-

team variance in each value (diversity variables). Alpha

values for each value scale are also presented in Table 1.

Team process was assessed as the aggregate (mean) score

across team members on each of the process measures (task

and relationship conflict, cohesion, and team efficacy).

Descriptive statistics and intercorrelations for the team

process criterion variables are presented in Table 2.

Here, it is important to note that the use of these

aggregated variables as indicators of team level processes

J Bus Psychol (2013) 28:107–121 113

123

T
a

b
le

1
D

e
sc

ri
p

ti
v

e
st

a
ti

st
ic

s
&

in
te

rc
o

rr
e
la

ti
o

n
s

fo
r

e
a

e
v

e
l

m
e

a
n

s
&
te

a
m

le
v

e
l

a
ri

a
n

c
e

in
v

a
lu

e
v
a
ri

a
b

le
s

M
S

D
1

2
3

8
9

1
0

1
1

1
2

1
3

1
4

1
5

1
6

1
7

1
8

T
e
a

m
m

e
a
n

1
.

e
n

e
v

o
le

n
c
e

4
.6

7
.3

3
(.

6
6

)

2
.

U
n

e
rs

a
li

sm
4

.1
6

.4
3

.5
0

(.
7

9
)

3
.

e
lf

-d
ir

e
c
ti

o
n

4
.5

3
.3

7
.2

6
.1

9
(.

6
4

)

4
.

S
ti

m
u

la
ti

o
n

4
.2

0
.4

8
.3

7
.3

3
.6

1
(.

6
9

)

5
.

e
d

o
n

is
m

4
.5

9
.4

8
.5

1
.1

6
.5

6
.6

5
(.

7
4

)

6
.

c
h

ie
v

e
m

e
n

t
4

6
1

.4
5

.2
8

.0
6

.5
5

.6
6

.6
5

(.
8

0
)

7
.

P
o

e
r

3
.6

1
.5

1
.0

4
–

.1
1

.4
5

.4
0

.4
7

.5
9

(.
6

6
)

8
.

e
c
u

ri
ty

4
.3

5
.4

2
.3

9
.2

9
.4
3
.3
5
.4

7
.4

1
.2

1
(.
6
1
)

9
.

C
o

n
fo

rm
it

y
4

.3
1

.4
1

.3
8

.3
0

.1
0

.2
0

.2
7

.3
0
.1
1

.4
8

(.
6

5
)

T
e
a

m
v
a

ri
a

n
c
e
1
0

.
B

e
n
e
v
o
le
n
c
e
.5
0
.5
9

–
.2

9
–

.2
6

–
.2

0
–

.2
2

–
.3

3
–

.0
6

–
.0

3
–

.3
6

–
.3
5
1
1

.
U

n
iv

e
rs
a
li

sm
.6

5
.6

6
–

.0
4

–
.0

9
.0

0
–

.0
3

–
.0

4
.1

5
.1

0
–
.2
0
–
.2

8
.6

2
1
2

.
S

e
lf
-d
ir
e
c
ti
o
n

.5
2

.5
7

–
.2
6
–
.1
6
–
.3

1
–

.2
4

–
.3

8
–

.0
6
–
.0

5
–

.3
1

–
.1

5
.6

0
.6

1
1
3
.
S

ti
m

u
la

ti
o

n
.8

7
.5

2
.1

0
–

.0
7

–
.0
4
–

.1
4

.0
4
.0
3
–
.1
2
.1

2
–

.2
1

.2
6

.3
4

.4
0
1
4

.
H

e
d
o
n
is
m

.6
9

.7
6

–
.2
0
–

.0
8

–
.0
1
–
.1
0
–
.3
3
–

.0
5

–
.0
1
–
.1
6
–
.3

8
.7

2
.6

2
.5

9
.4
7
1
5

.
A

c
h
ie
v
e
m
e
n

t
.8

5
.9

3
–

.0
1

.0
7
–
.3
0
–
.3
8

–
.4

2
–
.4
1
–
.2
4
–
.2
1
–
.3
1
.5

0
.3

7
.4
1
.2
5
.6
3
1
6

.
P

o
w

e
r

.9
6

.8
1

.0
0

.0
4
–
.0
1
–

.1
3

–
.0

2
.0

0
.1

3
.1

5
.0

4
.2

5
.2

1
.2
4
.1
4
.3
0
.4
1
1
7
.
S
e
c
u
ri
ty

.5
3

.5
3
–
.2

7
–

.0
6
–
.1
3
–
.1
0
–
.2
9
–
.1
3
.0
4

–
.5

1
–

.2
9

.4
8

.3
7

.4
0
.0
7

.4
6

.3
8
.2
0
1
8

.
C

o
n

fo
rm

it
y

.7
1

.8
4

–
.1

0
.0

5
–

.1
5

–
.1
8
–
.2
8
–
.1
8
–
.2
9
–
.3
3
–
.4
5
.5
9
.4
7
.5
2

.5
1

.5
9
.5
3

.1
7

.4
8

N
o

e
.

‘T
e
a
m

M
e
a
n

’
st

a
ti
st
ic

s
re

p
re

se
n

ts
th

e
a
v

e
ra

g
e

v
a
ri

a
b

le
sc

o
re

a
m
o
n

g
te

a
m

m
e
m

b
e
rs

a
c
ro

ss
te

a
m

s
fo

e
a
c
h

v
a
lu

e
.
‘T
e
a
m

V
a
ri

a
n

c
e
’

st
a
ti

st
ic
s
re
p
re
se
n

t
th

e
a
v
e
ra
g
e
a
m

o
u

n
t

o
f

v
a
ri
a
n
c
e
in
e
a
c
h
v
a
ri
a
b

le
a
m

o
n
g
te
a
m
m
e
m
b
e
rs
a
c
ro

ss
a
ll

te
a
m

s.
N

=
6

0
.

S
c
a
le

le
v
e
l

a
lp

h
a
s

a
re

li
st

e
d

n
th

e
p

a
re
n
th

e
se

114 J Bus Psychol (2013) 28:107–121

123

requires sufficient agreement across team members to

warrant aggregation (James 1982; James et al. 1984). Thus,

before aggregating, we examined the level of agreement

across team members. To assess interrater reliability, we

calculated intraclass correlations coefficients (ICCs) where

ICC = (MSbetween – MSwithin)/MSbetween (Shrout and Fle-

iss 1979). The ICC estimates across all teammates were .62

for team efficacy, .77 for team cohesion, .78 for role con-

flict, and .85 for task conflict. Landis and Koch (1977)

suggest that interrater reliabilities above .61 should be

considered substantial level of agreement. Nonetheless,

recent research indicates that ICC’s tend to underestimate

levels of agreement (LeBretton et al. 2003). Thus, we also

calculated rwg(j) for each of these variables for each team
1
.

Results (included in Table 2) indicate adequate agreement

to justify aggregation, (i.e., overall mean rwg(j) was

approximately .85).

Next, we examined the zero-order correlations between

diversity in each of the value types and the five criterion

variables. These correlations (presented in Table 3) indi-

cate that team diversity with respect to seven of the values

is significantly related to one of the outcome variables, and

six of these are related to at least two of the four team

process variables. Task performance was not related to

diversity in any of the values. Previous research has indi-

cated that the team’s mean (across team members) level of

deep-level attributes is often a significant predictor of team

performance criteria (e.g., Barrick et al. 1998), and thus the

mean level may confound the amount of variance in these

attributes (Bedeian and Mossholder 2000). Consequently, it

is important to control for teams’ mean level (i.e., ‘‘team-

level’’) before interpreting the impact of variability. As

stated by Steiner (1972, p. 667), ‘‘a completely satisfactory

description of the composition of groups must deal with

members’ average scores on attributes as well as with their

dispersion around those averages.’’ Thus, we next exam-

ined the independent influence of diversity on the team

effectiveness criteria (e.g., Mohammed and Angell 2004).

Specifically, for each significant zero-order correlation

between a component of effectiveness and a value diversity

variable, we conducted a hierarchical regression such that

the effectiveness variable was regressed first on the team-

level (i.e., mean) and then on team diversity (i.e., variance).

A significant beta weight and semi-partial correlation

provided indication of the unique relationship between

diversity variables and effectiveness. As noted previously,

diversity with respect to the nine values investigated had no

effect on team performance. For the team process

variables, however, of the 18 significant zero-order corre-

lations, 14 were still significant after controlling for team-

level (see Table 3, coefficients in bold). Of note, team

diversity on two of the values (security and self-direction)

was significantly related to all of the team process out-

comes, and diversity with respect to achievement was

Table 2 Descriptive statistics & intercorrelations for team effectiveness and team level variances in value variables

M SD 1 2 3 4 5 6 7 8 9 10 11 12 13 14
Team
Effectiveness

1. Task
Performance 2.42 1.33 1.0

2. Task Conflict 2.45 .72 .00 (.92)
3. Relationship
Conflict 1.80 .56 .15 .68** (.96)

4. Cohesion 5.55 .51 .06 -.53** -.58** (.94)
5. Team
Efficacy 5.60 .62 .00 -.59 -.63** .62** (.94)

Team Variance

6. benevolence .50 .59 .06 .16 .35* -.08 -.21* 1.0

7. universalism .65 .66 -.05 .17 .17 -.06 -.09 .62 1.0

8. self-direction .52 .57 .12 .31** .49** -.25* -.36** .60 .61 1.0

9. stimulation .87 .52 -.15 -.03 .10 -.02 -.10 .26 .34 .40 1.0

10. hedonism .69 .76 .07 .22* .23* .06 -.20 .72 .62 .59 .47 1.0

11. achievement .85 .93 .05 .35** .27* .02 -.28* .50 .37 .41 .25 .63 1.0

12. power .96 .81 -.08 .23* .21* .01 -.20 .25 .21 .24 .14 .30 .41 1.0

13. security .53 .53 .12 .30** .41** -.23* -.25* .48 .37 .40 .07 .46 .38 .20 1.0
14. conformity .71 .84 .08 .10 .25* -.04 -.16 .59 .47 .52 .51 .59 .53 .17 .48 1.0

Note. ‘Team variance’ statistics represent the average amount of variance in each variable among team members across all teams. Numbers inside
parentheses represent the average agreement level (rwg(j)) across teams. N = 60

** p \ .01

1
We calculated rwg(j) using the uniform expected null distribution.

J Bus Psychol (2013) 28:107–121 115

123

significantly related to all but cohesion. In addition,

diversity on three other values (benevolence, hedonism,

and power) was significantly related to two of the four

process variables. In all cases, results indicate the impact of

team diversity was such that higher levels of similarity

(i.e., less diversity) across team members was positively

related to process outcomes (i.e., more similarity resulted

in more team cohesion and efficacy and less conflict).

The analyses presented above provide an indication of the

extent to team member diversity on each of the value

dimensions individually relates to the team process out-

comes. Also of interest is the extent to which all of the sig-

nificant value dimensions together account for variance in the

team effectiveness measures as well as the relative impor-

tance of each dimension. To assess the overall impact of the

value dimensions, we conducted a hierarchical regression in

which each of the four team process outcomes was first

regressed on the value dimension team means and second on

the value dimension team diversity (variability). The change

in R2 from step 1 to step 2 provides an indication of the total

proportion of variance in the team process variable accounted

for by team member diversity on the set of significant value

dimensions. These values (reported in Table 3) ranged from

10 % for cohesion to 24 % for relationship conflict.

In order to assess the relative impact of each of the

significant value dimensions we conducted a dominance

Table 3 Independent effects of value diversity after controlling for value mean level on team effectiveness criteria

Deep-level diversity variables Unstandardized Standardized Correlations Relative importance
b

B SE b t Zero-order Semi-partial

Dependent variable: task conflict mean

Self-direction .387 .166 .308 2.33 .311 .294* 28.56

Hedonism .156 .128 .165 1.22 .223 .160 –

Achievement .282 .106 .365 2.67 .352 .333** 25.88

Power .211 .114 .238 1.84 .234 .237* 9.82

Security .530 .194 .393 2.73 .302 .340** 35.74

Multiple R
2 a

.26 .19*

Dependent variable: relationship conflict mean

Benevolence .309 .121 .326 2.55 .354 .320** 14.65

Self-direction .451 .118 .464 3.8 .485 .451** 35.06

Hedonism .084 .095 .116 .89 .228 .117 –

Achievement .159 .084 .265 1.89 .273 .242* 11.97

Power .146 .089 .213 1.64 .207 .213 –

Security .444 .146 .426 3.05 .408 .374** 28.73

Conformity .210 .096 .317 2.18 .245 .277* 9.58

Multiple R2 a .38 .24**

Dependent variable: cohesion mean

Self-direction -.241 .121 -.269 -1.99 -.246 -.255* 50.00

Security -.288 .142 -.299 -2.02 -.232 -.259* 50.00

Multiple R
2 a

.10 .10*

Dependent variable: team-efficacy mean

Benevolence -.199 .141 -.190 -1.42 -.210 -.184 –

Self-direction -.366 .139 -.341 -2.63 -.364 -.329** 42.94

Achievement -.215 .092 -.324 -2.32 -.279 -.294* 31.36

Security -.309 .171 -.268 -1.81 -.250 -.233* 25.71

Multiple R2 a .19 .14*

Note. N = 60 teams. The results displayed are associated with a model in which the variance of the deep-level attribute was entered in the second
step following the mean level of the deep-level attribute

* p \ .05, ** p \ .01. All zero-order correlations were significant at p \ .05
a

Multiple R
2

values represent the squared correlation between the criterion measure and all of the diversity variables listed (zero-order) and the

correlation between the criterion measure and all of the diversity variables listed after controlling for the corresponding team level variables

(semi-partial)
b

Relative importance values are based on dominance analysis (Budescu 1993) and represent the average percentage of the variance accounted

for across all possible subsets of predictors attributable to the specific value dimension

116 J Bus Psychol (2013) 28:107–121

123

analysis (Azen and Budescu 2003; Budescu 1993). Domi-

nance analysis is a procedure that is based on an exami-

nation of the R2 values for all possible subsets of models

derived from a set of predictors. It provides for an indi-

cation of the relative importance of each predictor as the

ratio of the average (across all possible subsets of predic-

tors) squared semi-partial correlation to the total R2. For

the present study, we conducted dominance analyses to

examine the relative impact of team member diversity on

each of the significant value dimensions over and above

team means on all of the value dimensions (i.e., we con-

trolled for team mean on each of the value dimensions). In

essence this provides an indication the unique variance

accounted for by each value dimension relative to the

others. Results of the dominance analyses are also pre-

sented in Table 3. Examination of these results indicates

that the relative importance of team member diversity on

the value dimensions differed for each of the team process

variables. For example, diversity with respect to self-

direction and security was equally important with respect

to cohesion. However, security was the most influential

predictor for task conflict; self-direction the most influen-

tial for both relationship conflict and team efficacy.

Discussion

Our goal in the present study was to explore the impact of

team member diversity with respect to general values on

both team process and task performance. In addition, we

chose to study values within a comprehensive framework

(Schwartz’s ten value types) such that all components

values were examined. Results indicate that task perfor-

mance was neither positively nor negatively affected by a

lack of congruence across team members with respect to

any of the value types examined. This finding is in line

with the meta-analysis of Bell (2007) suggesting that in lab

settings, only negligible effects are observed in the rela-

tionships between value diversity and team performance. A

very different picture emerged, however, with respect to

team process criteria. Diversity on values had a significant

unique effect on all of the team process variables (i.e., task

and relationship conflict, cohesion, and efficacy). In addi-

tion, results are consistent across values and team pro-

cesses. Specifically, the impact of team diversity was such

that greater diversity was negatively related with process

outcomes. That is, diversity resulted in lower team cohe-

sion, lower team efficacy, and more conflict.

Not surprisingly, relationship conflict appears to be the

team process variable most strongly related to value

diversity, both in terms of the number of diversity variables

and the overall magnitude of effect (i.e., seven of the

values were significantly related to relationship conflict and

accounted for approximately one-third of the total vari-

ance). In contrast, team cohesion was least affected; it was

related to diversity on only two values, accounting for

approximately ten percent of the total variance.

Diversity with respect to two values (self-direction and

security) emerged as important for all of the team process

measures. Upon reflection this finding is not surprising that

these two values emerged in tandem in that self-direction

and security represent polar opposites in the Schwartz

circumplex model of values (see Fig. 1) and thus should

negatively covary. More importantly, they reflect the gen-

eral motivational goals of novelty and mastery versus order

and harmony, which has clear implications for team

functioning. The impact of differences across team mem-

bers with respect to these values is thus conceptually, as

well as empirically, significant with respect to team inter-

action processes. Results of the dominance analyses indi-

cate that self-direction had the highest relative impact of all

of the values for three of the four processes outcomes. This

suggests that much more attention should be focused on the

role of this value dimension for team interactions.

Achievement and benevolence also emerged as impor-

tant for all of the process variables except cohesion. Again

it is important to note that these values are polar opposites

in the circumplex model and thus should negatively covary.

More importantly, they reflect the general motivational

goals of personal versus collective advancement. Similarly,

both power and hedonism values reflect a highly individ-

ualistic orientation (and are proximal to achievement in the

circumplex model) and team member differences on these

values were significantly related to both task and rela-

tionship conflict. So as might be expected the general value

dimensions of mastery versus harmony and individual

versus collective orientation appear to readily manifest in

team member interactions.

Our results highlight several potential areas for future

research. For example, our results do not speak of the

potential interactive effects of diversity in two or more

value types and team processes and performance. For

instance, it may be very likely that the impact of diversity

with respect to a specific value dimension may depend on

the both the mean (e.g., team) level and variability of one

or more other dimensions. From a causality approach, it

could be examined if team processes, such as relationship

conflict or team effectiveness, act as mediators between

team diversity and performance.

It is also important to note that the effects of value

diversity on team process outcomes emerged in a relatively

short-term team task. Team members in the present study

did not know each other before their participation in the

study and worked together for approximately 75 min. This

indicates that values can play a significant role in team

processes very early in team development and is an

J Bus Psychol (2013) 28:107–121 117

123

important finding. This finding is consistent with a recent

study, that utilizing data from studies conducted in the last

25 years, indicates that even in newly created teams and

conducting tasks of short duration, team processes such as

conflict, cohesion or potency, tend to emerge at very early

stages of the life of a team (Allen and O’Neill 2010). How-

ever, the role of time with respect to the impact of values

should be addressed in future research. A number of ques-

tions emerge with respect to the role of time. For example,

will diversity continue to have an impact as teams develop-

ment and form a common history and/or identity. In addition,

it is possible that diversity pertaining to different specific

values may be more or less impactful at different stages of a

team history. Finally, what contextual factors or interven-

tions might moderate the impact of value diversity? These

are all important avenues for future research.

Finally, it is important to consider that while value

diversity impacted team process outcomes, there was no

effect on task performance. While this might be a function of

the task, here again the role of time should be considered.

Specifically, it is possible that the negative effects of value

diversity on team processes might result in task performance

decrements over the long term functioning of the team. Thus,

while these effects did not emerge in our study, the might

with teams that interact over longer time frames. Again this is

an important avenue for future research.

Implications for Managing Team Diversity

The results of the present study point to several implica-

tions for managing team diversity in practice. First and

foremost, it is important to recognize that not all aspects of

diversity are directly visible. Deep-level diversity with

respect to psychological variables such as values play as, if

not more, important a role in determining team effective-

ness than do surface-level characteristics. Moreover, our

results suggest that diversity with respect to basic values

may impact team process outcomes very quickly. Specifi-

cally, despite the fact that values are not directly obser-

vable, we found significant effects of value diversity in

novel teams that interacted for a relatively short period of

time. Thus, these effects are very likely to compound over

time. Finally, when value diversity does impact team pro-

cess variables, these effects are uniformly consistent with

the pessimistic view of diversity—value diversity leads to

more conflict, less team efficacy, and lower team cohesion.

The results of the present study suggest that it may be

important to actively manage team development even in

cases where team member diversity is not readily apparent.

From a practical perspective, we suggest facilitators of

teambuilding efforts could consider adding to their agendas

a session with team members to analyze and discuss the

combined value profiles of their team. Utilizing a graphical

representation like the one presented in Fig. 1 could

facilitate this type of exercise. This kind of exercise could

help team members to assess their potential for conflict,

cohesion, and team efficacy based on their value diversity.

Another important practical consideration for managing

diversity is that the impact of team member value diversity

may manifest very quickly in the team development pro-

cess. This finding suggests that those seeking to manage the

impact of deep-level diversity need to take action sooner

rather than later as teams form and develop.

Limitations

As with any laboratory-based study, the results of the

present study must be considered in light of some limita-

tions. First, the teams used in the present study were

composed of undergraduate students, which may not be

directly representative of non-student, organizational

teams. The characteristics, skill sets, lifestyles, and priori-

ties of undergraduate students may be different than those

of most organizational team members. For example, com-

pared to the variability indices reported by Neuman et al.

(1999) from an organizational sample, this student popu-

lation is less diverse with respect to values than the typical

working organizational population. Also, the importance of

this laboratory exercise to these students’ lives was likely

substantially less than the importance that organizational

team members attach to the team-tasks in which they are

involved. Nonetheless, these limitations likely serve to

attenuate the impact of team diversity rather than enhance

it. That is, our results may actually underestimate the

effects in more variable and more personally relevant

organizational contexts. In addition, we used an ad-hoc

team task lasting under 2 h. As noted by Hackman and

Morris (1975), the problem with such an environment is

that each team, ‘‘does not have a chance to develop its own

history or its unique normative structure’’ (p. 59). In

addition, participants completed only one problem solving/

production task. This task was highly interdependent and

had one unique, ideal outcome. The findings of the present

study may be quite different among teams of longer life

spans, pursuing different or multiple tasks, and operating in

a much less controlled environment.

Furthermore, this study did not include any contextual

variables that may moderate the influence of deep-level

diversity attributes on team outcomes. Gladstein (1984)

noted that contextual variables such as reward structure or

resource availability influence components of team effec-

tiveness. Other factors such as socialization processes,

organizational climate, and culture are important elements

of a typical organizational context that were not accounted

for here. Additional research is certainly warranted along

these lines.

118 J Bus Psychol (2013) 28:107–121

123

Despite these limitations, this is one of the first studies

to highlight the unique impact of many unexamined, spe-

cific components of team diversity with respect to values

on team effectiveness criteria. These results indicate that

there is worth in proposing that disparity among teammates

in many of these values may have important implications

on subsequent team-level phenomena.

Overall, the present findings add to the emerging

research suggesting that diversity among team members

with respect to deep-level characteristics is related to

effectiveness criteria, especially with respect to individual

values. The popular view that increased diversity will lead

to a direct improvement in the quality of team performance

may need to be carefully considered. Diverse team mem-

bers may perceive and interpret the environment and

interactions they engage in differently. Managers need to

be prepared to take steps to mitigate these negative con-

sequences. Finally, researchers and practitioners alike must

realize that the effects of diversity will be moderated by a

number of variables including the type of diversity attri-

bute, the type of task, and the context within which the

team operates.

Acknowledgments The participation of the second author in this
project was supported by the Asociación Mexicana de Cultura A.C.

Appendix

See Table 4.

References

Aitken-Schermer, J., Feather, N. T., Zhu, G., & Martin, N. G. (2008).

Phenotypic, genetic, and environmental properties of Portraits

Values Questionnaire. Twin Research and Human Genetics, 11,
531–537.

Allen, N. J., & O’Neill, T. A. (2010, July). The trajectory of
emergence: Mining the literature for clues. Extended abstract
presented at the annual meeting of the Interdisciplinary Network

for Group Research, Washington, DC.

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.

Amason, A. C., & Schweiger, D. M. (1994). Resolving the paradox of

conflict, strategic decision making, and organizational perfor-

mance. International Journal of Conflict Management, 5,
239–253.

Applebaum, E., & Batt, R. (1994). The new American workplace.
Ithaca, NY: ILR

Press.

Arciniega, L. M., & Castañón, M. A. (2002). El puente chino: un reto
de equipo. [The Chinese bridge: A team challenge]. Department
of Management, ITAM. Mexico.

Azen, R., & Budescu, D. V. (2003). The dominance analysis approach

for comparing predictors in multiple regression. Psychological
Methods, 8, 129–148.

Baron, R. A. (1991). Positive effects of conflict: A cognitive

perspective. Employee Responsibilities and Rights Journal, 4,
25–36.

Barrick, M. R., Stewart, G. L., Neubert, M. J., & Mount, K. (1998).

Relating member ability and personality to work-team processes

and team effectiveness. Journal of Applied Psychology, 83(3),
377–391.

Beal, D. J., Cohen, R. R., Burke, M. J., & McLendon, C. L. (2003).

Cohesion and performance in groups: A meta-analytic clarifica-

tion of construct relations. Journal of Applied Psychology, 88,
989–1004.

Table 4 Brief definitions of the 10 value constructs and examples of
the PVQ items

Value definitions

POWER: Social status and prestige, control or dominance over

people and resources (e.g., He likes to be in charge and tell
others what to do. He wants people to do what he says)

ACHIEVEMENT: Personal success through demonstrating

competence according to social standards (e.g., Being very
successful is important to him. He likes to stand out and to
impress other people)

HEDONISM: Pleasure and sensuous gratification for oneself (e.g.,

He really wants to enjoy life. Having a good time is very
important to him)

STIMULATION: Excitement, novelty, and challenge in life (e.g.,

He looks for adventures and likes to take risks. He wants to have
an exciting life)

SELF-DIRECTION: Independent thought and action-choosing,

creating, exploring (e.g., He thinks it’s important to be interested
in things. He is curious and tries to understand everything)

UNIVERSALISM: Understanding, appreciation, tolerance and

protection for the welfare of all people and for nature (e.g., He
thinks it is important that every person in the world should be
treated equally. He wants justice for everybody, even for people
he doesn’t know)

Table 4 continued

Value definitions

BENEVOLENCE: Preservation and enhancement of the welfare

of people with whom one is in frequent personal contact (e.g.,

He always wants to help the people who are close to him. It’s
very important to him to care for the people he knows and likes)

TRADITION: Respect, commitment and acceptance of the

customs and ideas that traditional culture or religion provide the

self (e. g., He thinks it is important to do things the way he
learned from his family. He wants to follow their customs and
traditions)

CONFORMITY: Restraint of actions, inclinations, and impulses
likely to upset or harm others and violate social expectations or
norms (e.g., He believes that people should do what they’re told.
He thinks people should follow rules at all times, even when no

one is watching)

SECURITY: Safety, harmony and stability of society, of

relationships, and of self (e.g., The safety of his country is very
important to him. He wants his country to be safe from its
enemies)

Note. The content of this table was adapted from the definitions
provided in Schwartz et al. (2001)

J Bus Psychol (2013) 28:107–121 119

123

Bedeian, A. G., & Mossholder, K. W. (2000). On the use of the

coefficient of variation as a measure of diversity. Organizational
Research Methods, 3(3), 285–297.

Bell, S. T. (2007). Deep-level composition variables as predictors of

team performance: A meta-analysis. Journal of Applied Psy-
chology, 92, 595–615.

Bettenhausen, K. L. (1991). Five years of group research: What have

we learned and what needs to be addressed. Journal of
Management, 17(2), 345–381.

Budescu, D. V. (1993). Dominance analysis: A new approach to the

problem of relative importance of predictors in multiple

regression. Psychological Bulletin, 114, 542–551.
Byrne, D. E. (1971). The attraction paradigm. New York: Academic

Press.

Campion, M. A., Medsker, G. J., & Higgs, A. C. (1993). Relations

between work group characteristics and effectiveness: Implica-

tions for designing effective work groups. Personnel Psychol-
ogy, 46, 823–850.

Chiocchio, F., & Essiembre, H. (2009). Cohesion and performance: A

meta-analytic review of disparities between project teams,

production teams and service teams. Small Group Research,
40, 382–420.

Cox, T. H., & Blake, S. (1991). Managing cultural diversity:

Implications for organizational competitiveness. Academy of
Management Executive, 5, 45–56.

De Dreu, C. K. W., & Weingart, L. R. (2003). Task versus

relationship conflict, team performance, and team member

satisfaction: A meta-analysis. Journal of Applied Psychology,
88, 741–749.

Easley, C. A. (2001). Developing, valuing, and managing diversity in

the new millennium. Organizational Development Journal,
19(4), 38–50.

Eby, L. T., & Dobbins, G. H. (1997). Collectivism orientation in

teams: An individual and group-level analysis. Journal of
Organizational Behavior, 18, 275–295.

Evan, W. (1965). Conflict and performance in R&D organizations.

Industrial Management Review, 7, 37–48.
Fisher, S. G., Macrosson, W. D. K., & Yusuff, M. R. (1996). Team

performance and human values. Psychological Reports, 79,
1019–1024.

Fotopoulos, C., Krystallis, A., & Pagiaslis, A. (2011). Portrait value

questionnaire’s (PVQ) usefulness in explaining quality food-

related consumer behavior. British Food Journal, 113, 248–
279.

Giberson, T. R., Resick, C. J., & Dickson, M. W. (2005). Embedding

leader characteristics: An examination of homogeneity of

personality and values in organizations. Journal of Applied
Psychology, 90(5), 1002–1010.

Gibson, C. B. (1999). Do they believe they can? Group-efficacy and

group performance across tasks and cultures. Academy of
Management Journal, 42, 138–152.

Gibson, C. B., Randel, A. E., & Earley, P. C. (2000). Understanding

group efficacy: An empirical test of multiple assessment

methods. Group and Organization Management, 25, 67–97.
Gladstein, D. L. (1984). Groups in context: A model of task group

effectiveness. Administrative Science Quarterly, 29, 499–517.
Gully, S. M., Incalcaterra, K. A., Joshi, A., & Beaubien, J. M. (2002).

A meta-analysis of team-efficacy, potency, and performance:

Interdependence and level of analysis as moderators of observed

relationships. Journal of Applied Psychology, 87(5), 819–832.
Hackman, J. R. (1987). The design of work teams. In J. W. Lorsch

(Ed.), Handbook of organizational behavior (pp. 315–342).
Englewood Cliffs, NJ: Prentice Hall.

Hackman, J. R., & Morris, C. G. (1975). Group tasks, group

interaction process, and group performance effectiveness: A

review and proposed integration. In L. Berkowitz (Ed.),

Advances in experimental social psychology (Vol. 8,
pp. 45–99). New York: Academic Press.

Harrison, D. A., Price, K. H., & Bell, M. P. (1998). Beyond relational

demography: Time and the effects of surface- and deep-level

diversity on work group cohesion. Academy of Management
Journal, 41(1), 96–107.

Harrison, D. A., Price, K. H., Gavin, J. H., & Florey, A. T. (2002).

Time, teams, and task performance: Changing effects of surface-

and deep-level diversity on group functioning. Academy of
Management Journal, 45(5), 1029–1045.

Hofstede, G. (1991). Cultures and organizations: Software of the
mind. London: McGraw Hill.

Hollenbeck, J. R., DeRue, D. S., & Guzzo, R. (2004). Bridging the

gap between I/O research and HR practice: Improving team

composition, team training, and team task design. Human
Resource Management, 43(4), 353–366.

Horwitz, S. K. (2005). The compositional impact of team diversity on

performance: Theoretical considerations. Human Resource
Development Review, 4(2), 219–245.

Horwitz, S. K., & Horwitz, I. B. (2007). The effects of team diversity

on team outcomes: A meta-analytic review of team demography.

Journal of Management, 33, 987–1015.
Ilgen, D. R. (1999). Teams embedded in organizations: Some

implications. American Psychologist, 54, 129–139.
Jackson, S. E., May, K. E., & Whitney, K. (1995). Understanding the

dynamics of diversity in decision-making teams. In R. A. Guzzo

& E. Salas (Eds.), Team effectiveness and decision making in
organizations (pp. 204–261). San Francisco: Jossey-Bass.

Jackson, S. E., & Rudermann, M. (1997). Diversity in workteams.
Washington, DC: APA Books.

James, L. R. (1982). Aggregation bias in estimates of perceptual

agreement. Journal of Applied Psychology, 67, 219–229.
James, L. R., Demaree, R. G., & Wolf, G. (1984). Estimating within-

group interrater reliability with and without response bias.

Journal of Applied Psychology, 69, 85–98.
Jehn, K. (1994). Enhancing effectiveness: An investigation of

advantages and disadvantages of value-based intragroup conflict.

International Journal of Conflict Management, 5, 223–238.
Jehn, K. A., Chadwick, C., & Thatcher, S. M. B. (1997). To agree or

not to agree: The effects of value congruence, individual

demographic dissimilarity, and conflict on workgroup outcomes.

International Journal of Conflict Management, 8(4), 287–305.
Jehn, K. A., & Mannix, E. A. (2001). The dynamic nature of conflict:

A longitudinal study of intragroup conflict and group perfor-

mance. Academy of Management Journal, 44, 238–251.
Joshi, A., & Roh, H. (2008). A contextual reexamination of work

team diversity research: Review and future agenda. In E. Mannix

& M. Neale (Eds.), Research on managing groups and teams
(Vol. 11, pp. 25–53). Emerald Publishing, Bradford.

Kirkman, B. L., & Shapiro, D. L. (2001). The impact of team

members’ cultural values on productivity, cooperation, and

empowerment in self-managing work teams. Journal of Cross-
Cultural Psychology, 32, 597–617.

Klein, K. J., Knight, A. P., Ziegert, J. C., Lim, B. C., & Saltz, J. L.

(2011). When team members’ values differ: The moderating role

of team leadership. Organizational Behavior and Human
Decision Processes, 114, 25–36.

Kluckhohn, C. (1951). Values and value-orientations in the theory of

action. In T. Parsons & E. Shils (Eds.), Toward a general theory
of action (pp. 388–433). Cambridge, MA: Harvard University
Press.

Kravitz, D. A. (2005). Diversity in teams: A two-edged sword

requires careful handling. Psychological Science in the Public
Interest, 6(2), i–ii.

Landis, J. R., & Koch, G. G. (1977). The measurement of observer

agreement for categorical data. Biometrics, 33, 159–174.

120 J Bus Psychol (2013) 28:107–121

123

LeBretton, J. M., Burgess, J. R., Kaiser, R. B., Atchley, E., & James,

L. R. (2003). The restriction of variance hypothesis and interrater

reliability and agreement: Are ratings from multiple sources

really dissimilar? Organizational Research Methods, 6, 80–128.
Liem, G. A. D., Martin, A. J., Nair, E., Bernardo, A. B. I., & Prasetya,

P. H. (2011). Content and structure of values in middle

adolescence: Evidence from Singapore, the Philippines, Indone-

sia, and Australia. Journal of Cross-Cultural Psychology, 42,
146–154.

Mannix, E., & Neale, M. A. (2005). What differences make a

difference?: The promise and reality of diverse teams in

organizations. Psychological Science in the Public Interest,
6(2), 31–55.

Maznevski, M. L., DiStefano, J. J., Gomez, C. B., Noorderhaven, N.

G., & Wu, P. C. (2002). Cultural dimensions at the individual

level of analysis: The cultural orientations frame work. Interna-
tional Journal of Cross Cultural Management, 2, 275–295.

Milliken, F. J., & Martins, L. L. (1996). Searching for common

threads: Understanding the multiple effects of diversity in

organizational groups. Academy of Management Review, 21(2),
402–433.

Mohammed, S., & Angell, L. C. (2003). Personality heterogeneity in

teams: Which differences make a difference for team perfor-

mance? Small Group Research, 34(6), 651–677.
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.
Morgan, B. B., & Lassiter, D. L. (1992). Team composition and

staffing. In R. W. Sweezey & E. Salas (Eds.), Teams: Their
training and performance (pp. 75–100). Norwood, NJ: Ablex.

Moynihan, L., & Peterson, R. S. (2001). A contingent configuration

approach to understanding the role of personality in organiza-

tional groups. In B. M. Straw & R. I. Sutton (Eds.), Research in
organizational behavior (Vol. 23, pp. 327–378). Greenwich, CT:
JAI Press.

Mullen, B., & Copper, C. (1994). The relation between group

cohesiveness and performance: An integration. Psychological
Bulletin, 115, 210–227.

Neuman, G. A., Wagner, S. H., & Christiansen, N. D. (1999). The

relationship between work-team personality composition and job

performance of teams. Group and Organizational Management,
24, 28–45.

O’Reilly, C. A., Chatman, J., & Caldwell, D. F. (1991). People and

organizational culture: A profile comparison approach to

assessing person-organization fit. Academy of Management
Journal, 34, 487–516.

Podsakoff, P. M., & MacKenzie, S. B. (1994). Substitutes for

leadership and the management of professionals. The Leadership
Quarterly, 4(1), 1–44.

Rodriguez, R. A. (1998). Challenging demographic reductionism: A

pilot study investigating diversity in group composition. Small
Group Research, 29, 744–759.

Rokeach, M. (1979). Understanding human values: individual and
societal. New York: Free Press.

Rosenbaum, M. E. (1986). The repulsion hypothesis: On the non-

development of relationships. Journal of Personality and Social
Psychology, 51, 1156–1166.

Schneider, B. (1987). The people make the place. Personnel
Psychology, 40, 437–454.

Schwartz, S. H. (1992). Universals in the content and structure of

values: Theoretical advances and empirical tests in 20 countries.

In M. P. Zanna (Ed.), Advances in experimental social psychol-
ogy (Vol. 25, pp. 1–65). San Diego: Academic Press.

Schwartz, S. H., Melech, G., Lehmann, A., Burgess, S., Harris, M., &

Owens, V. (2001). Extending the cross-cultural validity of the

theory of basic human values with a different method of

measurement. Journal of Cross-Cultural Psychology, 32(5),
519–542.

Shea, G. P., & Guzzo, R. A. (1987). Group effectiveness: What really

matters? Sloan Management Review, 28(3), 25–31.
Shrout, P. E., & Fleiss, J. L. (1979). Intraclass correlations: Uses in

assessing rater reliability. Psychological Bulletin, 2, 420–428.
Smith, P. B., & Schwartz, S. H. (1997). Values. In J. W. B. Berry, M.

H. Segall, & C. Kagitcibasi (Eds.), Handbook of cross cultural
psychology: Social behaviors and applications (Vol. 3,
pp. 77–118). Needham Heights, MA: Allyn & Bacon.

Steiner, I. D. (1972). Group process and productivity. New York:
Academic Press.

Steinmetz, H., Isidor, R., & Baeuerle, N. (2012). Testing the circular

structure of human values: A meta-analytical structural equation

modelling approach. Survey Research Methods, 6, 61–75.
Swezey, R. W., & Salas, E. (1992). Guidelines for use in team-

training development. In R. W. Swezey & E. Salas (Eds.),

Teams: Their training and performance (pp. 219–245). Nor-
wood, NJ: Ablex.

Tajfel, H. (1978). Differentiation between social groups: Studies in
the social psychology of intergroup relations. New York:
Academic Press.

Tajfel, H., & Turner, J. (1986). The social identity theory of

intergroup behavior. In S. Worchel & W. G. Austin (Eds.), The
social psychology of intergroup relations (pp. 7–24). Chicago:
Nelson-Hall.

Turner, J. C., & Haslam, S. A. (2001). Social identity, organizations

and leadership. In M. Turner (Ed.), Groups at work: Theory and
research (pp. 25–65). London: Erlbaum.

Tziner, A. (1985). How team composition affects task performance:

Some theoretical insights. Psychological Reports, 57, 1111–
1119.

Van Knippenberg, D., & Schippers, M. C. (2007). Work group

diversity. Annual Review of Psychology, 58, 515–541.
van Woerkom, M., & van Engen, M. L. (2009). Learning from

conflicts? The relations between task relationship conflicts, team

learning and team performance. European Journal of Work and
Organizational Psychology, 18, 381–404.

Vodosek, M. (2007). Intragroup conflict as a mediator between

cultural diversity and work group outcomes. International
Journal of Conflict Management, 18, 345–375.

Webber, S. S., & Donahue, L. M. (2001). Impact of highly and less

job-related diversity on work group cohesion and performance:

A meta-analysis. Journal of Management, 27, 141–162.
Zaccaro, (1991). Nonequivalent associations between forms of

cohesiveness and group-related outcomes: Evidence for multi-

dimensionality. Journal of Social Psychology, 131(3), 387–399.

J Bus Psychol (2013) 28:107–121 121

123

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

c.10869_2012_Article_9267

Exploring the Effects of Value Diversity on Team Effectiveness
Abstract
Purpose
Design/Methodology/Approach
Findings
Implications
Originality/Value
Defining Diversity
Theoretical Underpinnings of Potential Diversity Effects
The Pessimistic Perspective
The Optimistic Perspective
Previous Findings on Value Diversity
Schwartz Model of Values
Team Effectiveness
Present Study
Method
Participants
Task
Measures
Values
Task and Relationship Conflict
Cohesion
Team Efficacy
Team Task Performance
Procedure
Results
Discussion
Implications for Managing Team Diversity
Limitations
Acknowledgments
Appendix
References

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Belbin’s team role theory: For non-managers also?
Fisher, S G;Hunter, T A;Macrosson, W D K
Journal of Managerial Psychology; 2002; 17, 1/2; ABI/INFORM Collection
pg. 14

Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.

Turn in your highest-quality paper
Get a qualified writer to help you with

“ LIT REVIEW ”

Get high-quality paper

NEW! AI matching with writer

Still stressed with your coursework?

Get quality coursework help from an expert!

Order now