2013 46th Hawaii International Conference on System Sciences
Cultural Diversity, Group Interaction, Communication Convergence, and
Intra-group Conflict in Global Virtual Teams: Findings from a Laboratory
Experiment
Souren Paul
Graduate School of Computer and Information Sciences
Nova Southeastern University
Fort Lauderdale, Florida
[email protected]
Sumati Ray
Indian Institute of Social Welfare and Business
Management
Kolkata, India
[email protected]
communication technology (Maznevski and Chudoba
2000). The technology mediated interaction pattern
among team members is adding some challenges in
the functioning of the teams. As virtual teams cut
across organizational, national, and functional
boundaries, diversity is an inherent aspect of these
teams. Members of culturally diverse global virtual
teams have differences in norms, beliefs, and
experiences which affects free interaction among
team members. Moreover, interaction among the
members of these teams usually generates diverse
views and information and thus the development of
common understanding among the team members
becomes critical. The problem exacerbates
considerably when group members interact using
collaboration technologies, which, with the exception
of audio and video conferencing systems, employ
lean media.
The use of lean media hinders
transmission of non-verbal cues (such as, gestures
and facial expressions) and constrains the team
members to rely primarily on written interactions to
perform the group task. While these communication
media usually support fast transmission of
information, they have limitations regarding the
processing of transmitted information (Dennis,
Fuller, and Valacich, 2008). The limitation regarding
information processing becomes critical in situations
that do not have well-established norms and involve
unfamiliar tasks (Dennis et al., 2008). The use of
collaboration technology tools that support
convergence of transmitted information helps the
team members to develop a shared understanding in
these situations. Although technology support for
convergence of information is important for
culturally diverse virtual teams, not many empirical
studies have addressed this issue. This motivates us
Abstract
In this paper we report the findings of a
laboratory experiment in which global virtual teams
used IBM’s Lotus Sametime to work on decisionmaking tasks. We restricted our study to shortduration virtual teams. We find that national cultural
diversity adversely affects interaction among team
members. We also find that interaction among team
members has a curvilinear (an inverted U)
relationship with intra-group conflict in these teams.
Our statistical analyses reveal a curvilinear
relationship between the use of polling and ranking
tools of collaboration technology and intra-group
conflict. The findings of the study provide motivation
for future research on the use of collaboration
technology support and social interaction in short
duration virtual teams.
1. Introduction
Virtual teams are groups of geographically,
organizationally and/or temporally dispersed
individuals brought together by information and
telecommunications technologies to accomplish one
or more organizational tasks (Powell, Piccoli, and
Ives, 2004). With the globalization of business,
virtual teams have become almost indispensable for
many business organizations and global virtual teams
have been formed.
Global virtual teams are
internationally distributed groups of people with an
organizational mandate to make or implement
decisions with international components and
implications. The members of these teams rarely
meet in person. Most of their interactions and
decision-making activities rely on the use of
1530-1605/12 $26.00 © 2012 IEEE
DOI 10.1109/HICSS.2013.156
343
344
to explore the following research questions in this
study:
x
Does cultural diversity adversely affect
interaction among the members in shortduration virtual teams?
x
Does the interaction among team members
affect manifestation of conflict in short
duration virtual teams?
Global virtual teams usually consist of individuals
from different countries with diverse cultural
backgrounds.
Diversity is, thus, an inherent
characteristic of global virtual teams.
As the
members of global virtual teams do not usually meet
face-to-face, they do not immediately perceive the
surface-level diversity. However, they perceive
differences in cultural backgrounds through the
language used in conversation, as D’Anglegan and
Tucker (1973) observed that even sophisticated
bilinguals in Canada sometimes fail to correctly
interpret a monolingual’s message.
Deep-level
diversity in global virtual teams usually results from
the cultural heterogeneity of the team members.
Difference in culture is a major cause of perceived
dissimilarity and it is manifested through different
cognitive processes. Culture is defined as the set of
deep-level values associated
with societal
effectiveness, shared by an identifiable group of
people (Maznevski, Gomez, Noorderhaven, and
Peichuan, 1997). Culture plays a major role in
information processing of individuals.
Cultural
values influence the perceptual filter through which a
person interprets information needed to make
decisions (Adler, 1997; Hofsted, 1980). Thus, in a
cross-cultural team, different members’ analyses and
interpretation of facts and events can differ
significantly.
National culture is the collective programming of
the mind, which distinguishes one group or category
(nation) from another (Hofstede, 1980). National
culture helps us understand why people from
different countries may think, feel, and behave
differently when faced with problems. The critical
question is whether the cultural differences can affect
group behavior. We discuss this in the next subsection of the paper.
x
Does use of collaboration technology tools
that facilitate convergence of information
weaken intra-group conflict in shortduration virtual teams?
In this paper, we present three hypotheses that
represent these research questions. We also report
the findings of a laboratory experiment that was
conducted to validate our hypotheses.
In the next section we review the literature on our
study constructs and present our hypotheses. Next,
we discuss the research method, which is followed by
the presentation of the results. We end the paper with
a discussion on the findings, the limitations of the
study, and the conclusion.
2. Literature review
2.1. Global Virtual Teams and Cultural
Diversity
Diversity within a work group refers to its
composition in terms of the distribution of
demographic traits and cognitive differences
manifested as surface-level and deep-level attributes
(Chidambaram, 2005). Surface-level diversity is
defined as difference among team members in overt
demographic characteristics, which include age,
gender, and race/ethnicity and are often reflected in
differences in physical features.
Surface-level
diversity is important in face-to-face teams. Team
members can make reasonable estimates of age,
gender, or racial/ethnic background of the other
members and therefore, of that person’s (dis)
similarity to themselves almost immediately
(Jackson, May, and Whitney, 1995). Deep-level
diversity refers to differences among team members’
psychological characteristics, including personalities,
values, and attitudes (Jackson et al., 1995; Harrison,
Price, and Bell, 1998). Clues to these latent
individual differences are taken from members’
interactions with one another as they unfold over
time. Those clues are expressed in behavioral
patterns, verbal and nonverbal communications, and
exchange of personal information (Harrison, Price,
Gavin, and Florey, 2002).
2.2. Diversity and its effect on group behavior
Prior research highlights both positive and
negative effects of diversity on the functioning of the
small groups (Jackson, 1991). Heterogeneous groups
are more creative and more likely to reach highquality decisions than homogeneous groups
(McGrath, 1984; McLeod, and Lobel, 1992; Triandis,
Hall, and Ewen, 1965; Willems and Clark, 1971).
The people of different cultures bring a variety of
perspectives and outlooks to a task (Adler, 1990).
Diversity reduces the probability of groupthink
(Janis, 1982), a phenomenon that occurs when
homogeneous and cohesive groups dedicated to
unanimity do not explore the full range of available
345
344
H1: In short-duration virtual teams, national
cultural diversity will have a U-shaped
curvilinear relationship with group interaction
such that the interaction among the team
members will be low for moderately
heterogeneous teams and will increase for both
homogeneous and completely heterogeneous
teams.
solutions and, hence, can make drastic errors in
decision-making (Janis, 1982). Diversity is related to
lower levels of interpersonal attraction, more stress,
and more turnover. Diversity has the effect of greatly
increasing the complexity of the process that must
occur in order for the group to realize its full
potential (Adler, 1990).
Members of diverse
backgrounds may require more time to reach a
decision (Fisher, 1980). Diversity has a negative
impact on communication and interpersonal
attraction (Adler, 1990; Steiner, 1972; Storey, 1991;
Triandis, 1959). Heterogeneous groups suffer from
delayed transmission of messages, message
distortion, and restriction of communication channels
(Rogers and Bhowmick, 1971). The cultural values
also influence members’ preferences for social
interaction norms (Bettenhausen and Murnighan,
1991; Earley, 1993). Because of these hidden
influences, multicultural groups may find cooperative
decision-making difficult (Kirchmeyer and Cohen,
1992; Watson, Kumar, and Michaelsen, 1993).
Watson et al (1993) find that heterogeneous groups
are low performers in the short run; however, the
performance improves in the long run.
In this paper, we focus on national cultural
diversity and its influence on group interaction in
global virtual teams. We attempt to build up this
relationship in the next sub-section of the paper.
2.4. Intra-group Conflict and Global Virtual
Teams
Conflict is broadly defined as perceived
incompatibilities or perceptions by the parties
involved that hold discrepant views or have
interpersonal incompatibilities (Boulding, 1963).
Thus, conflict in any team is concerned with
relationship issues and with task issues (Guetzkow
and Gyr, 1994; Jehn, 1997). Relationship conflicts
arise from differences in personal taste, political
preference, values, and ideology, whereas task
conflicts are conflicts about the distribution of
resources, about procedures and policies, and about
judgments and interpretation of facts (De Dreu and
Weingart, 2003). The relationship conflict, which is
based on emotional or interpersonal issues, is
detrimental to the functioning of a team. On the
contrary, task conflict is actually beneficial to the
team effectiveness (Van de Vilert and De Dreu,
1994). Task conflict focuses on the task content
and/or process and it causes team members to
consider more alternatives. Consideration of diverse
opinions and strategies enable a group to arrive at a
better solution (Pelled, Eisenhardt, and Xin, 1999).
Jehn (1997) finds that the type of task that group
members perform determines whether conflict helps,
hinders, or has no significant impact on individual
and group performance.
Conflicts in virtual teams are different from those
of face-to-face teams. According to Hinds and
Bailey (2000), virtual teams experience two direct
consequences of their virtuality: mediated
communication and unshared context. Mediated
communication causes higher levels of affective and
task conflict as group members neglect to censor
their comments and to accommodate the preferences
of their team members. However, Short, Williams,
and Christie (1976) argue that mediated
communication reduces the extent to which
participants and the interpersonal relationship are
salient in the interaction. Similarly, Sproull and
Kiesler (1991) argue that computer- mediated
communication depersonalizes the interaction,
2.3. National Cultural Diversity and Group
Interaction
Interaction among the members of a team can
increase when each team member understands others’
views and has similar ways of thinking, which is the
case with homogeneous teams. On the contrary, the
members of multi-cultural global virtual teams have
diversity in their beliefs and line of thinking, which
calls for extra effort to understand others’ views.
Two different scenarios can emerge in culturally
diverse virtual teams. In moderately heterogeneous
teams, members with similar cultural background
have easy interaction amongst themselves; these
members are less inclined to understand the
comments of others whose cultural backgrounds are
different. However, the members of completely
heterogeneous teams do not get the opportunity to
form sub-groups; they attempt to develop shared
understanding and group identity (Early and
Mosakowski, 2000). Thus, we expect that the
moderately heterogeneous global virtual teams will
have the minimum intra-group interaction. We,
therefore, hypothesize:
346
345
leading to greater concentration on the message
rather than the interacting persons.
However, concentration on messages may not
result in common understanding unless group
members have a sufficient level of interaction. The
problem is critical for multi-cultural virtual teams
whose members have different beliefs and norms.
Inadequate exchange of messages among the
members of these teams will aggravate
misunderstanding and will result in conflict. We
expect that an optimum level of interaction is
necessary to reduce the extent of perceived
incompatibility among team members. Hence:
H2: In short-duration virtual teams, group
interaction will have an inverted U-shaped
curvilinear relationship with intra-group conflict.
The members of short duration global virtual
teams have limited opportunity to socialize. In
addition, when these team members communicate in
a synchronous mode, they do not have sufficient time
to process the messages that they receive from others.
Although these communication processes may
convey a large volume of information, the team
members cannot converge on any abstract
information unless they process the transmitted
information. When team members do not know each
other and/or are unfamiliar with the task and
communication media, the development of shared
interpretation about task goal and strategies rely more
on convergence processes than on conveyance
processes (Dennis et al., 2008).
The use of
collaboration technology that offers tools to support
convergence of information will help team members
to negotiate and adjust differences and develop
shared understanding (Dennis et al, 2008). These
tools provide support for voting, ranking, and multiattribute decision-making activities.
Thus, we
hypothesize:
H 3: In short-duration global virtual teams, the
use of tools to support convergence of
information is negatively related to intra-group
conflict.
communication technology and familiar with Internet
and web-based applications. The students enrolled at
the US university represented different cultural and
ethnic backgrounds. Each participant was trained on
Lotus Sametime. In the training sessions, the
participants used Lotus Sametime to work on a task
that was similar to the experimental task. Altogether
28 three-member teams participated in the
experiments. However, one of these teams had only
two members and was, therefore, not considered in
the data analyses. Each team was assigned to one of
the following two categories:
x
Homogeneous – Participants were from the
same national cultures.
x
Heterogeneous - Participants were from
different national cultures.
There were 16 homogeneous teams and 11
heterogeneous teams in the experiment.
Due to the nature of the study, the approximate 10
½ hour time difference between the two countries,
and the schedules of the students in each location,
completely random assignment of subjects to groups
was not possible. However, once the availability of
the students in each location was known and the time
differences, class schedules, etc. were accounted for,
students were randomly assigned to either
homogeneous or heterogeneous teams, based on their
availability.
The teams were asked to assume the role of an
advisory
committee
that
would
make
recommendations to the administration of a fictitious
university regarding 5-6 proper uses of the
technology fees that were collected from the students
of the university. There were two versions of the
task: basic and modified. The modified version was
created by adding an extra component to the basic
version. 13 teams performed this basic version of the
task, whereas the remaining 14 teams worked on the
modified version. These teams suggested the
allocation of technology fees to the 5-6 uses that they
identified through discussion during the experiment.
3. Research Method
3.1. Subjects and Tasks
3.2. Experimental Procedures
In order to validate our hypotheses, we used the
data collected from a laboratory experiment. We
used Lotus Sametime of IBM, which is a
collaboration technology that supports electronic
meetings. Volunteer subjects enrolled in graduate
business programs at a major Midwestern US
university participated along with graduate students
from a major management school in India. All
subjects were experienced with information and
The subjects used IBM’s Lotus Sametime to work
on the experimental task. Anonymity among group
members was maintained. Each group was under the
control of a facilitator, who communicated using the
“instant messaging” option of Lotus Sametime. The
facilitator monitored the discussions and dealt with
any technical question that any participant had during
the session; the facilitator did not interject anything
into the discussion regarding the task or the decision
347
346
regarding allocation of the technology fee.
session consisted of the following:
Each
x
Activity 1: Commenting on advantages and
disadvantages of each option of using
technology fees.
x
Activity 2: Selecting 5-6 options of using
technology fees.
x
Activity 3: Allocating technology fees to the
selected options (only fourteen groups
performed this activity as an additional task
in the modified version).
x
Activity 4: Voting the final decision.
x
Activity 5: Completing questionnaires used
to collect data of the experiment.
the screens of Lotus Sametime when subjects used
polling and ranking tools.
3.3. Variable Identification
This study involved two independent variables
(national cultural diversity of virtual teams and the
use of tools to support convergence of information),
and two dependent variables (group interaction and
intra-group conflict). We used objective measures
for the variables of our study.
National cultural diversity: The participants
indicated their nationality in a questionnaire that they
completed after the experiment. Each nationality was
considered as a category of national culture.
Following the standard approach for categorical
variables, we calculated entropy-based indices
(Teachman, 1980) to measure national cultural
diversities of the teams. The entropy-based index is
calculated as:
Diversity= ∑-Pi ln(Pi),
where, Pi indicates the proportion of group members
belonging to each category of diversity. Thus, if all
three members of a group were from the same nation,
the national cultural diversity would be 0.000. In a
group that had two members with the same
nationality, the diversity index would be 0.637.
Group interaction:
Group interaction was
measured by counting the number of messages
exchanged among the team members during the
course of the meeting. A researcher of this study
analyzed the meeting log to count the messages that
could be labeled as components of group interactions.
Intra-group conflict: Number of episodes of task
and relationship conflicts in each session, identified
through content analyses of team members’
discussions in each session.
Use of tools to support convergence of
information: Number of times a group used polling
and ranking tools of Lotus Sametime. Figure 1 show
Figure 1.
Lotus Sametime – Participants
using polling and ranking tools
4. Results
4.1. Hypotheses Testing
We conducted multiple regression to test our
hypotheses. A level of significance of 0.05 was
considered to validate each hypothesis. Any weak
significance level in the range of .05 to .10 was
treated as suggestive of the nature of relationship
between the variables.
Since the relationships hypothesized were either
an U-curve (hypothesis 1) or inverted U-curve
(hypothesis 2), a quadratic model was selected:
Z = E0 + E1X + E2X2 + E3Y + H (1)
The standard precautions associated with
polynomial regression were adopted (Montgomery
and Peck, 1980). These included keeping the order
of the model as low as possible, progressive
348
347
introduction of polynomial terms, and proscriptions
about extrapolating beyond the observed data range.
SAS was used to develop the General Linear Models
(GLM) for the regression analyses.
For each
polynomial regression, we also conducted linear
regressions to ensure that the polynomial model was
a significant improvement over the linear one in
terms of adjusted R2.
Table 1 presents the regression results to test
hypothesis 1. Figure 2 presents the hypothesized
relationship between the national cultural diversity
index and the predicted value of group interaction.
Table 2 presents the regression results to test
hypotheses 2 and 3.
Figure 3 presents the
hypothesized relationship between group interaction
and the predicted value of intra-group conflict.
Table 2. Results of regression analysis for
intra-group conflict
Independent Variable
Group Interaction
204.500 (20.941)****
National cultural
diversity
National cultural
diversity2
Adjusted R2
-274.098 (115.109)**
0.025 (0.014)*
Group interaction2
-0.00004 (0.00004)
-0.063 (0.101)
0.210
F
3.22
Prob. (F)
0.04
N
Hypotheses Supported?
26
H2: Weak support
H3: No
* p<0.10; ** p<0.05; *** p<0.01; **** p<0.001
0.348
7.68
Prob. (F)
0.003
Hypotheses Supported?
Group interaction
156.124 (109.049)
F
N
-0.423 (1.194)
Use of tools to support
convergence of
information
Adjusted R2
Table 1. Results of regression analysis for
group interaction
Independent Variable
Group Interaction
Intercept
Intercept
26
H1: Yes
* p<0.10; ** p<0.05; *** p<0.01; **** p<0.001
Figure 3. Plot for intra-group conflict and group
interaction
5. Discussion
In this study, we examined the effect of the
cultural heterogeneity on group interaction in global
virtual teams. We have found that the members of
culturally homogeneous teams have the highest level
of group interaction. We also found that the
minimum level of group interaction took place in the
teams that were moderately heterogeneous. The
findings support the concept of sub-group formation
in virtual teams (Early and Mosakowski, 2000). The
results indicate that group interaction in completely
heterogeneous teams is better than that in moderately
heterogeneous teams. This is an interesting finding
Figure 2. Plot for group interaction and national
cultural diversity
349
348
and has implications for the management of global
virtual teams. The managers of global should be
careful about the formation of sub-groups in these
teams.
We found weak support for hypotheses 2 and did
not find any support for hypothesis 3.
After
analyzing the results and the operationalization of
variables, we realized that the voting and ranking,
tools could lower conflict only after these tools were
used by each team (i.e. in activities 2, 3, and 4 of the
experiment). In our regression analysis we included
the conflict episodes for the entire session which
involved discussion among the participants (with no
use of polling and ranking tools) and making group
decision (using polling and ranking tools). Thus, it
was necessary to measure the conflict episodes that
took place in the decision making phase of each
session (i.e. after activity 1) and conduct two separate
regressions to test hypotheses 2 and 3. We tested
hypothesis 2 by regressing the number of conflict
episodes in the entire session over group interaction.
Hypothesis 3 was tested by regressing the number of
conflict episodes in the decision making phase of the
session (i.e. activities 2, 3, and 4) over the number of
times the polling and ranking tools was used in the
session. Our results reveal strong support for
hypothesis 2 (as shown in table 3).
understand the true relationship between the study
variables and identified an inverted U-curve
relationship between intra-group conflict and the use
of polling and ranking tools (as shown in 4). This
suggests that an optimum use of polling and ranking
tools leads to the reduction of intra-group conflict.
Thus is an interesting finding and will be explored
extensively in our future research on global virtual
teams.
Figure 4. Plot for intra-group conflict and use
of polling and ranking tools of Lotus Sametime
Table 3. Results of revised regression analysis
for intra-group conflict
Independent Variable
Group Interaction
Intercept
5.1. Limitations
-0.815 (1.001)
Group interaction
2
Group interaction
0.027 (0.013)
-0.00005 (0.00003)
Adjusted R2
0.292
F
4.76
Prob. (F)
0.02
N
Hypotheses Supported?
We focused on national cultural diversity of the
virtual teams in our experiment. However, these
teams also had other forms of diversity, such as
educational specialization diversity and diversity in
the proficiency of using collaboration technology
tools. We plan to examine different forms of
diversities in our future research on global virtual
teams.
The participants of the study were from the US
and India and were separated temporally (about 10 ½
hours). As the meetings were synchronous, there was
a variation in the actual working condition of the
team members. Some members worked during their
normal work hours (i.e. daytime) while others had to
compromise and work at night to participate in the
teamwork.
This might have impacted group
interaction in our study.
The findings of this study are relevant for global
virtual teams that are ad hoc and are engaged in
short-duration tasks. However, we recognize that
cultural diversity may have a different influence on
group interaction in virtual teams that are engaged in
long-duration tasks.
**
26
H2: Yes
* p<0.10; ** p<0.05; *** p<0.01; **** p<0.001
Our revised test for hypothesis 3 did reveal a
significant result. However, our result indicate that
intra-group conflict has a significant positive
relationship with the use of polling and ranking tools
of collaboration technology (β=0.135, p=0.005,
adjusted R2=0.025). This contradicts the proposed
negative relationship between the study variables.
We conducted additional regression analyses to
350
349
6. Conclusions
[10]
Although this study marks the beginning of
research on the group interaction, intra-group
conflict, and information processing support in shortduration virtual teams, we can draw some
conclusions from the results. We have found that
group interaction is severely impaired in global
virtual teams that have moderate level of national
cultural diversity. We have also found that an
optimum level of group interaction is necessary to
reduce intra-group conflict in global virtual teams.
Our study also indicates the importance of using
communication convergence tools that help team
members to overcome disagreements in online
discussions. Although we did not find any support
for hypothesis 3, our additional statistical analyses
suggest an important polynomial relationship
between intra-group conflict and the use of polling
and ranking tools of collaboration technology.
[11]
[12]
[13]
[14]
[15]
7. References
[1] Adler, N.J.,
International Dimension of
Organizational Behavior, 2nd Edition, PWS,
Boston, MA, 1990.
[2] Adler, N.J.,
International Dimensions of
Organizational Behavior, South-Western College
Publishing, Cincinnati, OH, 1997.
[3] Bettenhausen, K.L. and J.K. Murnighan, “The
development and stability of norms in groups
facing interpersonal and structural challenge”,
Administrative Science Quarterly, 36(1), 1991,
pp. 20-35.
[4] Boulding, K., Conflict and Defense, Harper and
Row, New York, 1963.
[5] Chidambaram, L., “Diversity: Is there more than
meets the eye?”, Proceedings of the ThirtyEighth Annual Hawaii International Conference
on Systems Sciences, 2005.
[6] D’Angeljan, A. and G. Tucker, “Communicating
across cultures: An empirical investigation”,
Journal of Cross-Cultural Psychology, 3, 1973,
pp. 121-136.
[7] De Dreu, C.K.W. and L.R. Weingart, “Task
Versus Relationship Conflict, Team Performance,
and Team Member Satisfaction: A MetaAnalysis”,
Journal of Applied Psychology,
88(4), 2003, pp. 741-749.
[8] Dennis, A.R., R.M. Fuller, and J.S. Valacich,
“Media, Tasks, and Communication Processes: A
Theory of Media Synchronicity”, MIS Quarterly,
32(3), 2008, pp. 575-600.
[9] Earley, P.C., “East meets west meets mideast:
Further explorations of collectivistic and
[16]
[17]
[18]
[19]
[20]
[21]
[22]
[23]
351
350
individualistic work groups”, Academy of
Management Journal, 36(2), 1993, pp. 319-348.
Early, P.C. and E. Mosakowski, “Creating
Hybrid Team Culture: An Empirical Test for
Transnational Team Functioning,” The Academy
of Management Journal, 43(1), 2000, pp. 26-49.
Fisher, B.A., Small group decision making.
Communication and group process. 2nd Edition,
McGraw-Hill, New York, 1980.
Guetzkew, H. and J. Gyr, “An analysis of
conflict in decision making groups”, Human
relations, 7, 1994, pp. 367-381.
Harrison, D.A., K.H. Price, and M.P. Bell,
“Beyond relational demography: Time and the
effects of surface- and deep-level diversity on
work group cohesion”, Academy of Management
Journal, 41, 1998, pp. 96-107.
Harrison, D.A., K.H. Price, J.H. Gavin, and
A.T. Florey,
“Time, Teams, and Task
performance: Changing effects of surface- and
deep level diversity on group functioning”
Academy of Management Journal, 45(5), 2002,
pp. 1029-1045.
Hinds, P.J. and D.E. Bailey, “Virtual teams:
Anticipating the impact of virtuality on team
process and performance”, Academy of
Management Proceedings, 2000.
Hofstede, G.,
Culture's Consequences:
International Differences in Work-Related
Values. Sage, Newbury Park, CA, 1980.
Jackson, S.E.,
Team composition in
organizational settings: Issues in managing an
increasingly diverse workforce. In Group process
and productivity, S. Worchel, W. Wood, and J.
Simpson (eds.), Sage, Newbury Park, CA, 1991,
pp. 138-171.
Jackson, S.E., K.E. May, and K. Whitney,
“Understanding the dynamics of diversity in
decision making teams” In Team decisionmaking effectiveness in organizations, R. A.
Guzzo and E. Salas (Eds.), Jossey-Bass, San
Francisco, 1995, pp. 204-261.
Janis, L.L., Groupthink. 2nd Edition, Houghton
Miffin, 1982.
Jehn, K., “A qualitative analysis of conflict types
and dimensions of organizational groups”,
Administrative Science Quarterly, 42, 1997, pp.
530-557.
Kirchmeyer, C. and A. Cohen, “Multicultural
groups: Their performance and reactions with
constructive conflict”, Group and Organizational
Management, 17(2), 1992, pp. 153-170.
Maznevski, M.L. and K.M. Chudoba, “Bridging
space over time: global virtual team dynamics
and effectiveness”, Organization Science, 11(5),
2000.
Maznevski, M.L., C.B. Gomez,
and P.W.
Noorderhaven,
“The cultural orientations
framework and international management
research,” Academy of International Business
[24]
[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
[39]
Experimental social Psychology, 7(3), 1971, pp.
304-312.
Annual Meeting, Las Vegas, NV, 1997, pp. 227231.
McGrath, J.E.,
Groups: Interaction and
Performance. Prentice-Hall, Englewood Cliffs,
NJ,1984.
McLeod, P.L. and S.A. Lobel, “The effects of
ethnic diversity on idea generation in small
groups”,
Proceedings
of
Academy
of
Management, Las Vegas, NV, 1992.
Montgomery, D.C. and E.A. Peck, Introduction
to Linear Regression Analysis. John Wiley, New
York, 1982.
Pelled, L.H., K.M. Eisenhardt, and K.R. Xin,
“Exploring the black box: An analysis of work
group diversity, conflict, and performance”,
Administrative Science Quarterly, 44, 1999, pp.
1-28.
Powell, A., G. Piccoli, and B. Ives, “Virtual
Teams: A Review of Current Literature and
Directions
for
Future
Research”,
The
DATABASE for Advances in Information
Systems, 35(1), 2004, pp. 6-36.
Rogers, E. and D.K. Bhowmik,
Homophilyheterophily: relational concept of communication
research. In Speech Communication Behaviour:
perspectives and principles, Barker, L. and E.
Kibler, E. (Eds.), McGraw-Hill, New York, 1971.
Short, J., E. Williams, and B. Christie, The
Social Psychology of Telecommunications. John
Wiley & Sons, London, U.K, 1976.
Sproull, L. and S. Kiesler, Connections: New
Ways of Working in the Networked
Organization, MIT Press, Cambridge, MA, 1991.
Steiner, I.D., Group Process and Productivity,
Academic Press, New York, 1972.
Storey, B., “History and homogeneity: Effects
of perceptions of membership groups on
interpersonal communication”, Communication
Research, 18(2), 1991, pp. 199-221.
Teachman, J.D.,
“Analysis of Population
diversity”, Sociological Methods and Research,
8, 1980, pp. 341-362.
Triandis, H.C.
“Cognitive similarity and
interpersonal communication in industry”,
Journal of Applied Psychology, 43, 1959, pp.
321-326.
Triandis, H.C., E.R. Hall, and R.B. Ewen,
“Member heterogeneity and dyadic creativity”,
Human Relations, 18, 1965, pp. 33-55.
Van de Vilert, E., and C.K.W. De Dreu,
“Optimizing performance by stimulating
conflict”, International Journal of Conflict
Management, 1994.
Watson, W.E., K. Kumar, and L.K. Michaelsen,
“Cultural diversity's impact on interaction
process
and
performance:
Comparing
homogeneous and diverse task groups”,
Academy of Management Journal, 36(3), 1993,
pp. 590-602.
Williems, E.P. and R.D. Clark, “Shift toward
risk and heterogeneity of group,” Journal of
352
351