BEYOND DEMOGRAPHIC HETEROGENEITY:
AN EXPLORATION OF PERCEIVED SIMILARITY IN TEAMS
Mary E. Zellmer-Bruhn
University of Minnesota
Carlson School of Management
321 19th Avenue South
Minneapolis, MN 55455
612-625-2342
612-626-1316 (fax)
mzellmer-bruhn@csom.umn.edu
Mary M. Maloney
University of Minnesota
Carlson School of Management
321 19th Avenue South
Minneapolis, MN 55455
612-625-9009
612-626-1316 (fax)
mmaloney@csom.umn.edu
Anita D. Bhappu
Southern Methodist University
Cox School of Business
P.O. Box 750333
Dallas, TX 75275-0333
214-768-2204
214-768-4099 (fax)
abhappu@mail.cox.smu.edu
Rommel O. Salvador
Tulane University
A.B. Freeman School of Business
7 McAlister Drive
New Orleans, LA 70118
504-865-5532
504-865-6751 (fax)
The authors thank Philip Bromiley, Mel Fugate, Theresa Glomb, Laurie Milton, Gerardo Okhuysen,
and Pri Shah for helpful comments on earlier drafts of this manuscript.
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BEYOND DEMOGRAPHIC HETEROGENEITY:
AN EXPLORATION OF PERCEIVED SIMILARITY IN TEAMS
ABSTRACT
Recent research suggests that how teams perceive their differences influences team identity
and social integration (Harrison, Price, Gavin, & Florey, 2002; Polzer, Milton, & Swann, 2002). We
explore the formation and changes in team perceived similarity in a longitudinal sample of 25 teams.
Results suggest that initially, perceived similarity about both surface and deep differences is driven
by social category diversity. Over time, deep informational and value diversity produce conflict,
which subsequently reduces perceptions of similarity. Finally, although initial levels of perceived
similarity change, they have a powerful effect and persist, continuing to influence subsequent
perceptions of similarity.
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Today’s organizations increasingly rely on teamwork involving diverse members. Yet mixed
empirical findings on diversity and team effectiveness have left unanswered theoretical and practical
questions about how best to manage diverse teams. In an effort to address these questions, scholars
called for more research incorporating intervening variables and multiple types of diversity (Milliken
& Martins, 1996; Williams & O’Reilly, 1998; Pelled, Eisenhardt, & Xin, 1999). Recent research
suggests that one such intervening variable, how groups perceive their differences, may be as
important as the differences themselves to understanding the effects of team diversity (Earley &
Mosakowski, 2000; Harrison, Price, Gavin, & Florey, 2002; Polzer, Milton, & Swann, 2002). The
argument is that “perceptions of diversity reflect the psychological importance of, and carry the
substantive impact of, actual diversity to team outcomes” (Ashforth & Mael, 1989; cf. Harrison et
al., 2002: 1033). Understanding how group perceptions of team diversity form and evolve over time
has the potential to provide insight into the complex relationship between team diversity and
performance. Although the effects of diversity vary longitudinally (Watson et al., 1993), as is the
case in many areas of management research (Mitchell & James, 2001) studies of the temporal aspects
of diversity remain underrepresented in the literature.
Our study contributes to the emerging body of research on perceptions of diversity by
elaborating how perceived similarity - the degree to which members view themselves as having few
differences - develops over the life of a team. We further develop this literature by proposing that
conflict plays a role in the updating of perceived similarity. By contributing additional knowledge
about perceived similarity in diverse teams, particularly how perceived similarity forms and changes
during a team’s time together, this research moves beyond the static view of diversity in teams. In
fact, we conceptualize perceived similarity to be an “emergent state” (Marks, Mathieu, & Zaccaro,
2001). As an emergent state, perceived similarity describes a cognitive state that is dynamic in
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nature, influenced by the dispersion of static individual characteristics, and varying as a function of
team experiences. Therefore, we expect perceived similarity to change during the life of a team.
We examine the influence of multiple types of diversity on perceived similarity over time.
Specifically, recent research makes the distinction between surface and deep diversity (Harrison,
Price, & Bell, 1998). Surface diversity involves overt characteristics reflected in visible, physical
features such as sex and race (Harrison et al., 1998:97), and deep diversity involves differences such
as values, that are communicated through behavior and learned through interaction (p. 98). The key
distinction is that surface diversity can be quickly assessed from visible cues, but deep diversity
requires interaction and time to be revealed
There are multiple categories of diversity that could be assessed as surface or deep. For
surface diversity, we examine social category diversity, which is explicit, visible differences in social
category membership such as race, sex, and ethnicity (Pelled, 1996; Jehn, Northcraft & Neale, 1999).
For deep diversity, we examine informational and values diversity. Informational diversity involves
differences in knowledge and perspectives that arise from work background, experience, education,
and training, and values diversity involves differences in team members’ goals, and emphasis placed
on various outcomes (Jehn et al., 1999). We expect that surface diversity (social category) and deep
diversity (informational, value) exert different influences on perceived similarity over time because
of the relative ease of assessment of surface diversity and the need for interaction to assess deep
diversity. Furthermore, we argue that conflict influences perceived similarity (Jehn, 1997), with
conflict acting as the group process mechanism that reveals informational and value diversity.
Figure 1 depicts our hypothesized relationships, which we now describe in detail.
-------------------------------------Insert Figure 1 about here
--------------------------------------
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PERCEIVED SIMILARITY IN DIVERSE TEAMS
Perceived similarity captures “a process assumed to occur but rarely assessed in diversity
research (Riordan, 2000): the transmission of effects of actual team member diversity through
perceptions of such differences” (Harrison et al., 2002: 1029). Team members base their perceived
similarity of one another on individual traits or characteristics that are psychologically salient in their
groups such as sex, race, or status (Lau & Murnighan, 1998). A number of studies and theoretical
perspectives note the importance of perceived similarity. For example, perceived similarity enhances
interpersonal attraction among individuals (Byrne, 1971; Secord & Backman, 1964), and perceived
similarity in personal characteristics leads to stronger group attachments (Earley & Mosakowski,
2000; Harrison et al., 2002; Polzer et al., 2002). As such, perceived similarity intervenes between
team diversity and team actions. For instance, Earley and Mosakowski (2000) theorized that team
diversity influences the formation of hybrid team cultures through member’s perceptions of the
presence of distinguishable subgroups. If members perceive very high diversity, they are more likely
to develop a hybrid culture than if they perceive moderate levels of diversity. Earley and
Mosakowski concluded that hybrid cultures are a key to performance success in highly diverse,
multicultural teams, demonstrating the important role of perceptions of diversity in the
diversity/performance chain. It should be noted that while this research identified the key role of
perceptions, and perceived similarity was part of Earley and Mosakowski’s conceptual argument,
perceived similarity was not directly measured in their study.
Two subsequent studies provide empirical evidence that team members’ perceptions about
their team diversity influence team outcomes such as social integration, and thereby strengthen
evidence for the value in examining perceived similarity in efforts to refine theory about diversity’s
influence in teams. Harrison et al. (2002) found that the actual diversity of student groups positively
influenced perceived team diversity, which in turn decreased team social integration. Polzer et al.
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(2002), included perceived similarity as a control variable when modeling interpersonal congruence
and diversity in MBA teams, and also found that perceived similarity positively influenced team
social integration and group identification. Both studies provide evidence that perceived similarity is
an important intervening variable between team diversity and team outcomes. However, these
studies examine perceived similarity at a single point in time, and do not address the possibility of
temporal changes.
Perceived Similarity is Dynamic
We know from the literature that the influence of team diversity on team performance varies
over time (Watson et al., 1993), that the influence of team diversity on team processes such as
conflict is bounded by team longevity (Pelled, 1996), and that different types of diversity are not
revealed simultaneously (Harrison et al., 2002). Harrison et al. (1998) argue that as members interact
over time, they will uncover more deep diversity that may or may not align with their more obvious
surface social category diversity. Team members may initially perceive themselves to be quite similar
based on observable social category characteristics but find out that they are indeed very different
after interacting, or vice versa. Hence, perceived similarity, as a cognitive appraisal of team
diversity, can be regarded as an emergent psychosocial state that is fluid and mutable: a condition
that changes as a function of time (Marks et al., 2001). Therefore, we expect that:
H1: Perceived similarity changes during the time teams are together.
Perceived Similarity at Team Formation
When a team first forms, particularly if the team is composed of unfamiliar individuals,
members operate with very little information from which to draw conclusions about each other.
Even so, individuals quickly form impressions of others using whatever information is available
(Ambady & Rosenthal, 1992) to ease discomfort stemming from uncertain expectations and to
predict likely behaviors of their teammates (Allport, 1954). Under such conditions, where
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individuals are uncertain about each other or the situation, they typically engage in selfcategorization (Grieve & Hogg, 1999; Mullin & Hogg, 1998) and social-categorization (Tajfel, 1978)
by cognitively placing themselves and others into salient social groups. Salient social groups are
often demarcated by observable and accessible demographic characteristics such as race, sex, and
age (Allport, 1954; Jehn et al., 1999) in newly formed teams because there is a lack of information
about other individual differences, such as information or values diversity. Therefore, teams use
social category diversity to form initial perceptions about their similarity.
By categorizing others and themselves, team members immediately have a basis for building
relationships, and for forming behavioral expectations of each other because social category diversity
is likely to influence their perceptions via social identity effects (Tajfel & Turner, 1986; Turner,
Hogg, Oakes, Reicher, & Wetherell, 1987). Members with similar social categories assume they
share information and values (Elsass & Graves, 1998), and probably have common past experiences
(e.g. Pfeffer, 1983), which provides a basis for relational development. In fact, when members of
newly formed teams are similar on social categories, they not only identify as belonging to the same
in-group, but they actually minimize any observed differences among themselves (Brewer, Manzi, &
Shaw, 1993), thereby reinforcing their perception of similarity (Brewer, 1987). However, if members
of newly formed teams are different on social categories, they are likely to perceive themselves as
being dissimilar, both in these visible categories and in other underlying dimensions (Chattopadhyay,
1999). Therefore, we expect that:
H2:
At team formation, surface (social category) diversity negatively influences perceived similarity about
both surface and deep differences.
The Role of Conflict
It takes time for teams to develop a complete understanding of their team diversity because
unlike surface differences, deep differences cannot be easily detected before team interaction. Even
though teams base their initial perceptions of both surface and deep similarity on social category
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differences, teams may actually discover that they have more or less in common than they initially
assumed once they begin to interact. Therefore, any changes in perceived similarity are influenced
both by initial perceptions of team diversity based on surface social category diversity, which affect
early feelings of group identification (Polzer et al., 2002), and by deep differences such as
informational and values diversity that become apparent as team members interact.
How do teams recognize deep differences? We know that “diversity has its impact through
the crucible of conflict” (Griffith & Neale, 2001: 399) and that conflict influences team outcomes
(Alagna, Reddy, & Collins, 1982; Jehn et al., 1999; Jehn, Chadwick, & Thatcher, 1997; O’Reilly,
Williams & Barsade, 1998; Pelled, 1996; Griffith & Neale, 2001; Jehn, 1995; Jehn et al., 1999;
Williams & O’Reilly, 1998). Also, past research demonstrated that deep differences, on such
characteristics as education, work experience, functional background, values, and personality (Jehn et
al., 1999; Harrison et al., 1998), increase conflict. Specifically, informational diversity increases task
conflict (Jehn et al., 1999) while value diversity increases task and relationship conflict (Jehn et al.,
1999). Task conflict may spill over into relationship conflict because “it is difficult for individuals to
present and receive criticism, and often the critic is blamed for the adverse reaction” (Jehn, 1997:
532). Therefore, we assert that latent, deep differences produce task and relationship conflict during
team interactions. Thus, we expect that:
H3: Once a team begins to interact, deep (informational, value) diversity increases conflict.
The eruption of conflict in a team may cause members to see their team as diverse and result
in them updating their perceptions of similarity. Updating perceptions occurs through two channels.
First, conflict involves expressing contradictory opinions, and teams typically reject members for
expressing deviant opinions which in turn reduces feelings of attraction within the team (Byrne,
1971). Jehn (1995) found that conflict within teams reduced interpersonal liking among members.
Research on the relationship between similarity and attraction (Byrne, 1971) suggests that reduced
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interpersonal liking stemming from conflict should decrease perceptions of similarity. Second,
although previous research has emphasized conflict as an outcome of team diversity, we believe
conflict also acts as a carrier of information about team diversity, which precipitates changes in
perceived similarity. Without conflict, teams may not be aware of deep diversity in knowledge,
approaches to work, and values. By revealing deep diversity, conflict illuminates important
underlying variation among team members, which lowers their perceived similarity.
The mechanisms of reducing interpersonal attraction and carrying information about
differences should particularly affect perceptions of deep differences because initial perceptions on
these dimensions were formed on tenuous information about social category diversity. Perceptions
of surface differences are based on social category diversity that is present at formation, and doesn’t
change over time. Therefore, perceptions of deep differences should be subject to updating based
on emergent conflict. Therefore, we expect that:
H4: Once a team begins to interact, conflict reduces perceived similarity about deep differences.
The Persistence of Initial Perceived Similarity
Information about deep diversity, which emerges as conflict during team interaction may
not, however, result in sufficient updating of perceptions of similarity. In other words, although
perceptions of similarity change over time, they may not change enough, and initial levels of
perceived similarity may influence the change. Person perception theory (Allport, 1954) and
attribution theory (Shaver, 1975) demonstrate that initial perceptions are tenacious. Early
information helps to organize subsequent information (Asch, 1946). Initial information receives
much more weight in the formation of perceptions than later information, even if later information
is disconfirming of earlier information. Perceivers fail to sufficiently adjust their initial perceptions
accordingly (Kahneman & Tversky, 1979). Thus, initial perceptions of similarity based on social
category diversity at team formation may act as an anchor (Kahneman & Tversky, 1979) for
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subsequent perceptions of similarity regardless of any new information about team diversity, or the
lack thereof, which emerges during team interaction. Therefore, although perceived similarity
changes during a team’s life, we expect that:
H5: Initial perceived similarity influences final perceived similarity.
METHODS
Sample and Procedure
Our sample consisted of first-semester, full-time Master’s of Business Administration (MBA)
student teams at a large Mid-Western university. Before the semester, the MBA admissions office
used sex, race, country of origin, previous education, and job experience to create four to six
member teams. Once assigned, members of each team completed team project assignments for all
required core courses during their first semester, and competed in an end-of-semester business
simulation. Because these team projects accounted for a significant portion of students’ grades and
learning opportunities, students took their membership and performance in the first-semester core
teams very seriously.
We collected data from first-semester core teams for two years’ incoming classes. We
collected demographic data from admission records and surveyed team members to obtain
information about perceived similarity, conflict, values diversity, and frequency of meetings.
Students came from 38 different countries with 31% coming from countries other than the United
States. Of the 241 individuals in our initial sample, 67% percent were Caucasian, 22% were Asian,
5% percent were Hispanic, 3% were Black and South Asian, respectively, and 23% were female. We
surveyed teams at three different times during their first semester: at team formation before the start
of the semester (T1), half way through the semester (T2), and during the final week of classes (T3).
To strengthen the quality of our results, we only included in our analyses teams that had a withinteam response rate of 50% or more in all three time periods. This strict criterion resulted in final
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sample of 25 teams, or a 54% team response rate.
We conducted analyses to ensure that the teams
retained in our final sample were not statistically different from those excluded due to low within
team response rates. Among the set of individuals included in the final sample, fewer countries were
represented than full sample (18 versus 38), but team diversity scores for nationality did not differ.
ANOVA for all other variables in our model also revealed no statistically significant differences
between the teams included in our final sample and those excluded.
Given our research questions, data from these particular MBA teams have many desirable
properties. The teams worked together in multiple classes and completed several projects together
over a 15-16 week period. Teams performed meaningful work with significant consequences and
had to manage different, potentially competing individual and team task priorities, making them
similar to many teams in workplace settings. In addition to complex task demands with real
consequences, the teams in our sample have another desirable characteristic. The team formation
timing and launch process allows us to assess team perceptions at formation, before any significant
interaction had occurred, enabling us to isolate the effects of surface versus deep diversity on
perceived similarity over time. In organizational settings it would be difficult to find a set of teams
with a common “zero” point. Previous studies of perceived similarity included teams where
individuals may have known each other for longer and/or may have had previous interactions. For
instance, Harrison et al. (2002) measured perceptions of teams of students enrolled in upper division
undergraduate and graduate courses (and who were not new students) between the fifth and seventh
week of the semester. Members of these teams had opportunity to interact and learn about each
other before completing surveys about their perceptions. More similar to our design, Polzer et al.
(2002) used MBA student teams put together by administrators, and used a measure of perceived
similarity taken after 10 minutes of interaction. It is possible that the findings of these studies were
affected by the choice of timing of data collection (Mitchell & James, 2001). Our sample and design
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allow us to incorporate both aspects of these previous empirical studies: measurement of perceived
similarity immediately upon team formation, and after several weeks of interaction.
Measures
In addition to the basic description of each measure, we provide information on withinteam agreement. Since several of our variables were created by aggregating data reported by
individuals about their team (Klein & Koslowski, 2000), we calculated two indices of within-group
agreement: the Lindell, Brandt, and Whitney (1999) revised version of the James, Demaree, and
Wolf (1984) index, r*WG, or the r*WG(J) for J-item scales, and an Average Deviation Index, AD(J), for
J-item scales (Burke & Dunlap, 2002 ). The r*WG index ranges from 0 (no agreement) to 1 (complete
agreement) (James, Demaree, & Wolf, 1984). An acceptable cut-off criterion to demonstrate
agreement is 0.60 (Glick, 1985). The AD(J) index is a measure of inter-rater agreement that
computes the absolute average distances of group scores from that group’s median. Lower AD
scores indicate smaller differences among team responses, with 0 indicating perfect agreement.
Because the AD index does not have a fixed number as an upper bound, an appropriate test of
statistical significance demonstrates within-group agreement (Dunlap, Burke & Smith Crowe, 2003).
Perceived Similarity. We measured perceived similarity at T1 and T3 using an 8-item scale
we developed to indicate the extent to which team members felt their team is similar with respect to
cultural background, nationality, ethnicity, work habits, interaction styles, communication style, work
ethic, and personalities. Items were rated on a Likert-type response scale (1 = disagree strongly, 7 =
agree strongly). The first factor, consisting of three items (ethnicity, nationality, cultural
background), represents perceived similarity about surface differences (alpha T1 = .92; T3 = .93). The
second factor, consisting of five items (work habits, interaction styles, communication styles, work
ethic, personalities), represents perceived similarity about deep differences (alpha T1 = .84; T3 = .88). A
confirmatory factory analysis supported the two factor solution (at T1 CFI = 0.94, NNFI = 0.90,
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and at T3 CFI =.93, NNFI = .88) (Bentler, 1990). For both perceived similarity about surface
differences, and perceived similarity about deep differences, we aggregated individual ratings of
perceived similarity by first calculating the mean for each set of items for each team member. We
then computed the average of these means, obtaining a score for each form of perceived similarity at
the team level. The median r*WG(10) was 0.62 at T1 and 0.60 at T3. Moreover, teams attained
statistically significant AD indices on the eight items, on average.1 Both suggest adequate withinteam agreement.
Social Category Diversity. Social category diversity concerns differences in social
categories like ethnicity and sex (Pelled, 1996). We measured social category diversity using
individual demographic information for each team member from MBA admissions records on sex,
nationality, and race. The final sample included students from 18 different countries; we coded each
country separately. We coded racial/ethnic background in five categories: Asian, Black, Caucasian,
Hispanic or South Asian. Because each type of social category diversity we used in this study is a
categorical variable, we used Teachman’s index (1980) to create a heterogeneity score for each. The
higher the score, the more numerous and distributed the categories of heterogeneity are on a team.
In the final sample, sex heterogeneity had a mean of .43 (s.d. = .27), national heterogeneity had a
mean of .75 (s.d. = .27), and ethnic heterogeneity had a mean of .70 (s.d. =.32). Following Jehn et
al. (1999), we combined the three types, using an average, to create an index of social category
diversity.
Informational Diversity. Informational diversity involves different knowledge and
background perspectives in the team commonly arising from education and experience differences
(Jehn et al., 1999: 743). We measured informational diversity using years of work experience and
undergraduate major.
1
Years of work experience is the number of years worked before entering the
Median AD(8) was 0.77 at T1 and 0.76 at T3.
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MBA program, for which we calculated a coefficient of variation with mean = .53 (s.d. = .21). We
used nine categories of undergraduate majors to create a Teachman score for the second component of
informational diversity (mean = 1.35; s.d. = .18). Again, following Jehn et al. (1999), we combined
years of work experience diversity and undergraduate major diversity to create an index of
informational diversity.
Values Diversity. To measure values diversity, we used eight items from the Personal Values
Questionnaire (McBer & Company) to capture diversity in individual members values for achievement
and for power. Achievement values involve the degree to which we value outperforming others and
have high standards of excellence. Power values involve the degree to which we value being strong,
influential, and controlling. Values diversity was measured at team formation. Individuals rated
how important a set of items was to them. Sample items for achievement values are, Opportunities to
take on more difficult and challenging goals and responsibilities, and Continual opportunities for personal growth and
development. Sample items for power values are, Doing things that have a strong effect on others, and Taking
forceful action. The rating scale ranged from 1 = “not important to me” to 5 = “extremely important
to me.” The scale had an alpha of .76. For both need for power and need for achievement, we
computed a coefficient of variation for each team as an indication of diversity. We combined the
two scores to create an index of values diversity.
Conflict. We measured intra-group conflict using six items reflecting task conflict and
relationship conflict, based on the scales developed by Jehn (1995). For example, an item for task
conflict read, Conflicts regarding ideas are very frequent in our team, and an item for emotional conflict
read, Personality conflicts are evident in this team. The rating scale ranged from 1 = “disagree strongly” to
5 = “agree strongly”. We created a single composite score for conflict, computed as the average of
all six items, based on a confirmatory factory analysis (CFI = 0.93, NNFI = 0.89, RMR = 0.06) that
suggest the existence of a one-factor structure for conflict. Using a single composite score for task
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and relationship conflict is consistent with research indicating that individuals are not able to
distinguish among the different types of conflict (Griffith & Neale, 2001; Williams & O’Reilly, 1998;
Pelled, 1996). Moreover, the subscale for task conflict also highly correlated with the subscale for
relationship conflict (r = 0.63, p < 0.001). Internal consistency for the 6-item scale was 0.82 (alpha).
Intra-group agreement was satisfactory, with a median r*WG(6) of 0.67 and 83% of the teams attaining
statistically significant AD indices on all 6 items2, so we calculated the mean of the individual
conflict ratings for the team to obtain a group-level measure for conflict.
Controls. There may be subtle differences in the core MBA curriculum across two years of
our data collection. For example, there were minor differences across the years in faculty and
structure of orientation for the first semester. These differences may produce variations in team
processes so we included a dummy variable for year in our models. There is pressure toward
uniformity of attitudes in groups such that over time, as members interact more frequently, they
perceive they are more similar -- or may actually become more alike – because they need to reduce
cognitive dissonance (Festinger, 1954), so we included meeting frequency. Individual team members
indicated the number of times their team met face-to-face since the beginning of the semester (1 =
“1 to 4 times”, 2 = “5 to 9 times”, 3 = “10 to14 times”, 4 = “15 to 19 times” and 5 = “20 or more
times”). These ranges were coded as ‘1’ for the lowest range and ‘5’ for the highest with mean =
3.7 (s.d. = .81). Median rWG was 0.60 at T2 and 0.88 at T3. Finally, we also controlled for team size
since our sample contains teams of four to six members.
RESULTS
Descriptive statistics and correlations are presented in Table 1.
-------------------------------------Insert Table 1 about here
-------------------------------------2
Median AD(6) = 0.50.
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Hypothesis 1 (H1) proposed that perceived similarity changes during the time teams are
together. We tested H1 with paired t-tests. For perceived similarity about surface differences, the
mean at T1 was 2.80 (s.d. = .36) and the mean at T3 was 2.62 (s.d. = .30). The decrease of 0.18 was
marginally significant (t = 1.45, p < .10). For perceived similarity about deep differences, the mean
at T1 was 3.88 (s.d. = .15) and at T3 was 3.25 (s.d. = .18). The decrease of 0.63 was statistically
significant (t = 4.99, p < .001). Thus, both perceived similarity about surface differences and
perceived similarity about deep differences changed over time. Specifically, in this sample, although
both types of perceived similarity decreased, the change in perceived similarity about deep
differences was larger.
For the remainder of our hypotheses, our model consists of a system of equations wherein
error terms across the equations could be correlated. In systems of equations like this, estimating
each equation separately using OLS regression will only produce desirable properties if the error
terms across equations are uncorrelated (Kmenta, 1986). To account for this possible error term
correlation, we estimated the models using Zellner’s seemingly unrelated regression (SUREG)
(Greene, 2000). Hypothesis 2 (H2) proposed that, at team formation, social category diversity
would negatively influence both perceived similarity about surface and deep differences. Equations
one and four for initial perceived similarity in Table 2 present a test of H2. The coefficient for social
category diversity is negative and statistically significant for both perceived similarity about surface
differences (b = -5.53, p < .001) and for perceived similarity about deep differences (b = - 0.87, p <
.01), supporting H2.
-------------------------------------Insert Table 2 about here
-------------------------------------Hypothesis 3 (H3) proposed that once a team interacts, deep differences increase conflict.
Equations two and five for conflict in Table 2 present a test of H3. The coefficients for
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informational diversity and value diversity are positive and significant for both perceived similarity
about surface differences (b = 2.13, P < .01, and b = 3.76, p < .05) and for perceived similarity
about deep differences (b = 2.14, p < .01, and b = 3.72, p < .05), supporting H3.
Hypothesis 4 (H4) proposed that conflict reduces final perceived similarity about deep
differences. Equation six for final perceived similarity about deep differences in Table 2 presents a
test of H4. The coefficient for conflict is negative and statistically significant (b = -0.82, p < .001),
supporting H4.
Hypothesis 5 (H5) proposed that initial perceived similarity influences final perceived
similarity about both surface and deep differences. Equations three and six for final perceived
similarity in Table 2 present a test of H5. The coefficient for initial perceived similarity is positive
and significant for both final perceived similarity about surface differences (b = .60, p < .001) and
final perceived similarity about deep differences (b = .83, p < .001), supporting H5.
DISCUSSION AND CONTRIBUTIONS
Prior research presumed perceived similarity to be static during the time a team is together.
The results of our study suggest otherwise. Initial perceived similarity about both surface and deep
differences, in teams of unfamiliar members, is based on social category diversity. Visible
demographic information at team formation fuels social categorization processes causing team
members to form stereotypical behavioral expectations of, and in-group relationships with, each
other (Elsass & Graves, 1997). Teams with higher social category diversity have lower initial
perceived similarity about both surface and deep differences. Furthermore, informational and values
diversity were associated with increased conflict during team interactions and subsequently with
reduced final perceived similarity about deep differences. In fact, perceived similarity about deep
differences decreased more than perceived similarity about surface differences in our sample,
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suggesting that team members do update their initial assumptions about underlying individual
differences once they begin to interact and learn more about each other.
Our results have several implications for future research on diversity in teams. They are
consistent with the results of other studies that have moved beyond an exclusive emphasis on
demographic characteristics to include “deeper” forms of diversity as predictors of team perceptions
and outcomes (Harrison et al., 1999; Harrison et al., 2002; Jehn et al., 1999), a step that cannot be
ignored by future research addressing questions about the complex relationship between team
diversity and performance. Our findings also extend research on the longitudinal effects of team
diversity (Watson et al., 1993). By establishing that perceived similarity varies over time, this
research offers intriguing clues as to why empirical findings on diversity and team effectiveness are
mixed. Previous research has not fully attended to the temporal dynamics of diversity in teams and,
therefore, has cast perceived similarity as a static construct, an assumption we now know to be false.
As an emergent state, perceived similarity is a product of diversity and team experiences, and
changes over time as experiences vary. Emergent states become inputs into subsequent team
processes and outcomes (Marks et al., 2001). Therefore, any conclusions reached about diversity
and perceived similarity in teams need to be qualified by the time point of measurement in a team’s
life. Future research on diversity and perceived similarity in teams should consider temporal aspects
to assure that important theoretical relationships are accurately identified (Mitchell & James, 2001).
Although perceived similarity changes over time, we also found that initial perceived
similarity still influences final perceived similarity, suggesting that initial categorizations based on
social category differences among team members bias and anchor their perceptions of team
diversity. This finding is consistent with research on the establishment of routines in teams, which
emphasizes the crucial role of “early interaction” in setting the stage for subsequent team
performance (Gersick & Hackman, 1990). Future research on teamwork should consider the
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significance of initial impressions of team diversity by recognizing the automatic formation
processes of perceived similarity and planning interaction at the early stages of team development to
emphasize or de-emphasize the salience of certain attributes. While some individual differences
among team members are immutable, it is possible to change perceived similarity in teams. For
example, at team launch, team leaders might detail common backgrounds, training, and personal
goals to supplement surface diversity information that team members automatically attend to.
Pointing out commonalities may be more important if a team has high variance in surface diversity,
so managers should determine if it would be beneficial to develop higher perceived similarity to aid
in team integration. Simply understanding this fact should motivate both researchers and managers
to discover new approaches to team formation that promote a “positive perception cycle,” perhaps
by emphasizing common goals and the shared organizational memberships of team members.
Conflict precipitates subsequent updates of perceived similarity about deep differences. We
theorized that conflict acts as a carrier of information about team diversity, revealing underlying
differences in information and values among team members. Conflict may offer another possibility
for influencing perceived similarity in teams. Indeed, our study provides a different perspective on
conflict than previously established in the literature on diversity in teams. Past research has
consistently framed conflict as an outcome of team diversity (e.g., Jehn et al., 1999). While our
results support this perspective, they also suggest that conflict acts as a carrier of information about
deep diversity. Conflict, or the lack thereof, influences perceptions of team diversity by reinforcing
or undermining initial stereotypical assumptions about underlying individual differences. Therefore,
the effective management of conflict may be another way to promote a “positive perception cycle”
and enhance group development in diverse teams. For example, conflict can be expressed in
different ways. Open task conflict involving disagreement may more strongly decrease perceived
similarity than other methods of raising disagreement. Constructive controversy is a group process
19
technique wherein members use respectful communication to raise opinions and have norms of
careful listening to alternative viewpoints (Alper, Tjosvold & Law, 1998). Training teams in these
techniques may enable them to benefit from the value of their diverse viewpoints without risking the
reduction in social integration that may occur if perceived similarity is reduced by open task conflict.
From a practical standpoint, our results reinforce the idea that managers must exercise great
care in forming and designing teams. Particular attention should be given to highlighting similarities
among members during early interactions in diverse teams. We are not saying that individual
differences should be muted, but rather that initial assessments of team diversity should be tempered
by more explicit information about the homogeneity of team members so that initial perceived
similarity is not biased by the salient social category diversity of the team. In essence, we are
advocating for managers to create an environment in which team members are initially focused on
their similarities, leading to positive social integration and group identification and potentially
enabling team members to better manage conflict that may emerge as their underlying individual
differences manifest during team interactions. In fact, a heightened sense of in-group membership
at team formation could actually cause team members to minimize emerging differences and anchor
subsequent perceptions of similarity.
Limitations & Concluding Comments
Although our research design and analyses provide a rigorous test of our hypotheses, all
studies are limited in some respects. While the teams in our sample consisted of adults working on
multiple group projects that affected their grades, and therefore other personal goals and outcomes,
the external validity of our findings can only be verified through replication in workforce teams.
Having said that, there are some important characteristics of our design that could be difficult to
replicate elsewhere. Our ability to control data collection that corresponded immediately with team
formation allowed us to isolate more clearly the formation of initial perceived similarity. Finding a
20
similar cohort of teams at this point of team development in other field settings would be difficult,
and experimental designs including multiple projects over more than sixteen weeks are similarly
improbable. Thus, while the use of student teams may limit some generalizability of our results, this
sample allowed us to isolate and study the phenomena that we set out to investigate.
Survey length restrictions and limitations on the availability of archival diversity data
restricted the types of diversity that we could investigate. While we did include multiple types of
diversity (social category, informational, and values) in our study, other forms of diversity might also
be important in determining perceived similarity in this and other samples. Future research should
include additional analysis of what forms of diversity are salient in different settings, since processes
of self-categorization have a situation base, meaning that the characteristics that are most salient to a
team might vary across different contextual situations (Fiske & Taylor, 1991).
In conclusion, our study adds to the literature on diversity in teams by contributing
additional knowledge about perceived similarity in diverse teams. In particular, we illustrate how
perceived similarity, as an “emergent state,” forms and changes during a team’s time together. We
hope that the results of this research pique the interest of other scholars to follow the path we have
taken and to continue developing an understanding of the dynamic nature of group perceptions and
the role that they may play in translating diversity into team action.
21
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25
TABLE 1
Descriptive Statistics and Correlation Coefficientsa (n=25 teams)
Mean s.d.
10
11
Variables
1
2
3
4
5
6
7
8
9
1. T1 P Similarity Surface
2.78
1.73
1.00
2. T1 P Similarity Deep
3.81
0.84
0.71
1.00
3. T3 P Similarity Surface
2.62
1.51
0.95
0.63
1.00
4. T3 P Similarity Deep
3.25
0.92
0.70
0.73
0.62 1.00
5. T2 Meeting Frequency
3.48
0.75
0.22
0.36
0.11 0.20
1.00
6. T3 Meeting Frequency
4.53
0.63 -0.03 -0.01
0.10 -0.17 0.25
1.00
7. T2 Conflict
2.53
0.57 -0.33 -0.45 -0.28 -0.52 -0.07 0.06
1.00
8. Social Category Diversity (Surface)
0.60
0.23 -0.81 -0.37 -0.85 -0.50 -0.02
0.02 0.16
1.00
9. Informational Diversity (Deep)
0.93
0.12 -0.07 -0.17 -0.01 -0.18
0.21
0.23
0.44 -0.04 1.00
10. Value Diversity (Deep)
0.14
0.04 -0.17 -0.20 -0.19 -0.05 -0.19 -0.28
0.32
0.07 -0.15 1.00
0.07
1.00
11. Team Size
5.37
0.57 -0.12 -0.10 -0.20 -0.10
0.28 -0.10 -0.03
0.01 0.25
0.11
12. Class Year
0.52
0.51 -0.52 -0.72 -0.50 -0.49 -0.19
0.04
0.17
0.26
0.21 -0.12
a For correlations with absolute values greater than or equal to 0.49, p  .05 and with absolute values greater than or equal to 0.52, p  .01.
26
TABLE 2
S.U.R.E. Regression Results (n=25 teams)
Perceived Similarity: Surface
Equation 1:
Equation 2:
Equation 3:
Initial Perceived
Conflict
Final Perceived
Similarity
(T2)
Similarity
(T1)
(T3)
Team Size
-0.18
(0.27)
-1.12
(0.31)
Class Year
***
T2 Meeting Frequency
-0.13
(0.15)
-0.06
(0.20)
-0.01
(0.13)
-0.25
(0.16)
-0.16
(0.21)
T3 Meeting Frequency
Social Category
Diversity (Surface)
Informational
Diversity (Deep)
Value Diversity (Deep)
0.24
(0.14)
-5.53
(0.64)
***
-0.60
(1.31)
-4.03
(3.77)
0.20
(0.76)
2.13
(0.74)
3.76
(20.9)
Initial Perceived
Similarity Surface (T1)
-1.45
(0.71)
**
*
-0.05
(0.12)
Initial Perceived
Similarity Deep (T1)
0.65
(0.87)
-1.32
(2.34)
0.60
(0.11)
-0.87
(0.36)
**
-0.26
(0.75)
-3.24
(2.14)
0.42
(0.40)
2.14
(0.74)
3.72
(2.11)
-0.36
(0.48)
**
*
.83
122.55
***
.37
14.83
*
Standard errors are in parentheses.
-0.07
(0.21)
.93
326.70
1.03
(1.05)
3.62
(2.87)
***
-0.07
(0.22)
Conflict (T2)
R2
Chi-Square
*
Perceived Similarity: Deep
Equation 4:
Equation 5:
Equation 6:
Initial
Conflict
Final Perceived
Perceived
(T2)
Similarity
Similarity
(T3)
(T1)
-0.05
-0.12
-0.06
(0.16)
(0.15)
(0.19)
-1.04 ***
-0.08
0.19
(0.26)
(0.32)
-0.01
(0.14)
-0.18
(0.17)
***
.70
58.34
***
.37
14.72
*
0.83
(0.24)
-0.82
(0.25)
.72
63.38
***
***
***
+ p < .10, * p < .05, ** p < .01, *** p < .001
27
FIGURE 1
Summary of Hypothesized Relationships Between Types of Diversity, Perceived Similarity, and Conflict
T1
Surface
Diversity
>Social Category
-
Initial
Perceived
Similarity
+
Final
Perceived
Similarity
Deep Diversity
>Informational
>Values
+
Conflict
-
T2
T3
28