The impact of diversity beliefs: boost

Transcription

1 The impact of diversity beliefs: boost or barrier? Master Thesis Tycho Keuken 4 Juli 2014

2 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 2 Thesis Circle: Diversity, Status and Performance A quantitative study on the effect of diversity on performance mediated by cohesion, and how diversity beliefs moderate the relationship between diversity and cohesion. Tilburg University Faculty: School for Social and Behavioral Sciences Department: Organization Studies Details of the student Name: Tycho Keuken ANR: Details of the Supervisor Supervisor 1: Supervisor 2: J. van Dijk R.T.A.J. Leenders

3 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 3 Abstract This study examines the relationship between diversity and performance, when mediated by cohesion, and how diversity beliefs moderate the relationship between diversity and cohesion. A sample size of 57 teams from various organizations in various industries was used. Results show that team members differing in terms of age experience lower levels of cohesion compared to homogenous teams. However, team members holding more pro-diversity beliefs weaken the negative effect of age diversity on cohesion. Gender diversity itself appeared to not be significantly related to cohesion. Furthermore, teams will improve the necessary conditions for performance, such as planning and allocation of their work, if they are more cohesive. In turn, these conditions will improve the performance output of teams. Finally, a full model test revealed that the negative consequences of diversity on performance antecedents, mediated by cohesion, are reduced for groups holding more pro-diversity beliefs.

4 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 4 Table of Contents Introduction... 5 Theoretical framework... 7 Methodology Results Discussion Reference Appendix A Appendix B Appendix C Appendix D Appendix E... 48

5 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 5 Introduction Research problem Nowadays organizations become ever more diverse in terms of differences between employees (van Knippenberg & Schippers, 2007). Usually, work groups consist of employees that have a different educational background, ethnic background, sex and age (Homan, Greer, Jehn, & Koning, 2010). This is, among other things, a result of the process of globalization and the tendency of more women entering the labour market (Lückerath-Rovers, 2013; Pelled, Eisenhardt, & Xin, 1999). For example, it has become easier for people to work anywhere in the world, and it is more widely accepted for women to be present in all layers of organizations (Lückerath-Rovers, 2012). As a result of this tendency, managing diversity has become more and more important. Understanding the impact of these diverse work groups on organizations is essential for management strategies (Pelled et al., 1999). Prior research shows that diversity is a 'double-edged sword': it has negative, as well as positive effects (Milliken & Martins, 1996). On the positive side, diverse groups are believed to be able to outperform homogeneous groups, because diverse groups are supposed to host a richer variety in informational resources such as knowledge, perspectives, and information (van Knippenberg, De Dreu, & Homan, 2004). The negative consequences are a result of social categorization, which is the process of distinguishing between group members, based on their characteristics, such as gender and age. Because social categorization leads to the formation of subgroups within a team, diversity is generally thought to reduce group cohesion, and subsequently inhibit performance. In fact, van Knippenberg et al. (2004) propose that the reduced cohesion hinders diverse groups from sharing and integrating their informational resources. As a consequence, diversity researchers have been looking for ways to reduce or even eliminate the negative effects of diversity on cohesion.

6 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 6 Earlier research suggests that positive diversity beliefs may inhibit the negative effects of diversity on cohesion. Diversity beliefs refer to the extent to which individuals believe diversity to be beneficial or detrimental to the group's functioning (van Knippenberg & Haslam, 2003; van Knippenberg, Haslam, & Platow, 2007). If group members have positive feelings towards a diverse group and value diversity, they are more likely to favour diversity (van Knippenberg et al., 2007). Moreover, valuing diversity could enhance the attractiveness of a group, and therefore increase the level of group cohesion (van Knippenberg et al., 2007). Therefore, I suggest that a positive mindset towards diversity might have a positive influence on the relationship between diversity and cohesion, which in turn could improve performance. In order to reach a better understanding of this topic, I defined the following research question: To what extent is the influence of team diversity on group performance mediated by group cohesion, and to what extent do diversity beliefs moderate the relationship between team diversity and group cohesion? Relevance of this research It is important to reach a better understanding of the impact of diversity beliefs, since research on this topic is sparse. Gaining more understanding of this topic has great value, because if group members have positive feelings towards diversity, then category diversity could lead to higher levels of performance. Therefore, conducting this research adds to the current knowledge of the social categorization perspective, and to its effects on group performance. From a practical point of view, this research adds to the current knowledge of diversity and provides new insights for diversity training programs. For organisations developing these programs, understanding the impact of diversity beliefs is of great importance, since creating a positive mindset towards diversity could enhance group performance. Furthermore, this research provides insights for managers who find it difficult to

7 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 7 manage diversity within their team. Creating understanding of the importance of valuing diversity could help managers prevent the negative consequences for the coherence within a work group. Theoretical framework Independent variable: Diversity Van Knippenberg et al. (2004) use the term diversity to refer to any differences between individuals that may lead to the perception that another person is different from oneself (p.1008). Other scholars, such as Jackson, May and Whitney (1995) and Milliken and Martins (1996) made a distinction between less observable and readily detectable diversity. As mentioned by van Knippenberg et al. (2004), less visible attributes of diversity are more job-related, such as functional and educational background. The readily detectable diversity includes attributes, such as sex, age, and ethnicity, which is also known as social category diversity (van Knippenberg et al., 2004; Williams & O Reilly, 1998). Based upon social category diversity, social categorization processes take place, which can be seen as the process by which people tend to place themselves and others into social categories (Webber & Donahue, 2001). However, van Knippenberg et al. suggest that these processes are more complex and they assume that diversity itself is not the reason for categorization processes. Instead, these processes occur through salience of social categorization diversity and, for example, their beliefs toward these categorizations (van Knippenberg et al., 2004). In this study, I focus on social category diversity because, in practise, social category diversity is the most strikingly visible attribute of employees (Pelled et al., 1999). When categorization processes occur, people tend to prefer others that are more or less similar to themselves (van Dijk, van Engen, & van Knippenberg, 2012). As a result, subgroups arise within a team, possibly causing problematic inter-subgroup relations that could influence cohesion (van Knippenberg, 2004). Prior research is inconclusive about the possible positive effects of

8 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 8 social category diversity (van Dijk et al., 2012). Therefore, it is interesting to research the circumstances under which social category diversity could positively influence cohesion, and subsequent performance. Mediator variable: Cohesion Cohesion refers to the extent to which group members are attracted to the group, are satisfied with other members of the group, and to the social interaction among the group members (O'Reilly, Caldwell & Barnett, 1989). Other scholars subdivide cohesion into two aspects, namely social cohesion and task cohesion (Brawley, Carron, & Widmeyer, 1987; Zaccaro, 1991). Social cohesion refers to an individual s attraction to the group due to positive relationships with other members of the group. Task cohesion refers to the commitment group members show towards group tasks. Moderator variable: Diversity beliefs I argue that there could also be a positive relationship between social category diversity and cohesion, namely when members have a positive mindset concerning diversity. Diversity beliefs are the beliefs individuals hold about how group composition affects workgroup functioning, that is, the extent to which individuals perceive diversity to be beneficial for or detrimental to the group's functioning (van Dick, van Knippenberg, Hägele, Guillaume, & Brodbeck, 2008, p.1467). In their research, they rank diversity beliefs on a continuum, ranging from pro-diversity beliefs to pro-similarity beliefs. Research into diversity beliefs is particularly interesting, because it suggests that social category diversity could lead to higher levels of cohesion (Van Dick et al., 2008). Relationship between diversity and cohesion According to van Knippenberg and Schippers (2007), the social category perspective is defined as differences between workgroup members may engender the classification of others as either in-group/similar or out-group/dissimilar, categorizations that may disrupt

9 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 9 group processes (p.517). According to the social category perspective, social categorization is the root cause of problematic intergroup attitudes and behaviour (van Knippenberg et al., 2004). Social categorization could lead to low interpersonal liking, due to the perceptual grouping of people resulting in the formation of subgroups within a team. As mentioned by Webber and Donahue (2001), social categorization causes individuals to have more positive feelings towards their own category (in-group), and more negative feelings towards other categories (out-group). According to Van Dick et al. (2008) these feelings are related to prosimilarity beliefs, which can be seen as the negative feelings individuals hold towards diversity as well as the fact that they value homogenous groups. According to social categorization, due to their default modus, individuals usually are more inclined to hold prosimilarity beliefs compared to their inclinations to appreciate pro-diversity beliefs. The visible attributes of social categorization diversity, such as gender and age, maximize the differences and similarities between groups (Hogg & Terry, 2000). As a result, differences between ingroup and out-group lead to clashes between categories, which are detrimental to group cohesion (Pelled et al., 1999; Webber & Donahue, 2001). Social categorization is also detrimental to group cohesion, because people will not move easily between social categories due to their inability to empathize with the values and beliefs of others (Webber & Donahue, 2001). These differences make it difficult to fully understand people belonging to other social categories. Due to fewer similarities between social categories, it is assumed that people from one group rely on prejudice of group members that belong to another social category (Webber & Donahue, 2001). These prejudices could disperse different social categories even more. As a consequence, people prefer their own group over other groups, dislike other social categories, and subsequently inhibit group cohesion (Webber & Donahue, 2001). Also, when groups hold stronger pro-similarity beliefs, group members will have less desire to remain in a diverse

10 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 10 group and will indentify less with their group. This may negatively affect cohesion, caused by a dispersed interpersonal liking and a reduced shared commitment towards group tasks. In contrast, according to Van Dick et al. (2008), pro-diversity beliefs are associated with positive feelings towards diverse teams. These positive feelings may lead to higher levels of interpersonal liking, and thus to higher levels of cohesion. Pro-diversity beliefs may enhance cohesion for two reasons. Firstly, prior studies (e.g., Brewer, 1979; Tajfel & Turner, 1986; Turner, Hogg, Oakes, Reicher, & Wetherell, 1987) suggest that group members experience higher levels of trust in their own group than in different groups. This indicates that group members are more positively inclined towards their own group, compared to other, dissimilar groups (Williams & O Reilly, 1998). However, if group members have more positive feelings towards diverse groups and value diversity, diverse groups might experience higher levels of trust and therefore acquire the same advantages as homogeneous groups. Secondly, group identification depends on the perception that group members have of their group, rather than the actual differences within the group (Van Dick et al., 2008). If group members have more positive feelings towards their own group, they will have a stronger sense of group identification, and a stronger desire to stay in that particular group. Hence, this would positively affect cohesion. Therefore, it is interesting to research the possible positive effects of diversity on cohesion. This leads to the following hypothesis: H1: Diversity beliefs moderate the relationship between social category diversity and cohesion, in such a way that the relation between social category diversity and cohesion will be more positive for groups holding more pro-diversity beliefs and more negative for groups holding more pro-similarity beliefs. Dependent variable: Performance Hackman (1990) defines group performance as a group's contribution to its embedded organization, to itself, and to its composite members. I will focus on this definition. Earlier

11 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 11 research (e.g. Beal, Cohen, Burke, & McLendon, 2003; Mullen & Copper, 1994) suggests that higher levels of cohesion lead to a higher level of performance. There are three reasons why cohesion may enhance performance. Firstly, Mullen and Copper (1994) found evidence that task commitment, which is related to task cohesion, positively influences group performance. They argue that most likely cohesive groups perform better because of intrinsic motivation. Cohesive groups seem to exert more effort in trying to successfully perform tasks, because they enjoy them. Secondly, Beal et al. (2003) mentioned that cohesive workgroups are able to coordinate their activities successfully better than non-cohesive groups, improving the performance of a group (Beal et al., 2003). Finally, Beal et al. (2003) found evidence that cohesive groups perform better because of interpersonal attraction, which is related to social cohesion. Their arguments stem from the view of Mullen and Coppers (1994), who stated that people in these groups want to help their well-liked group members. This leads to the following hypothesis: H2: Group cohesion is positively related to group performance Based on the previous hypotheses, I expect a positive relationship between social category diversity and performance when mediated by cohesion if group members have more pro-diversity beliefs. For groups holding more pro-similarity beliefs, I expect a negative relationship between social categorization diversity and cohesion due to the reasoning as stated above. Therefore, a higher level of social categorization will probably negatively influence performance, when mediated by cohesion for groups holding more pro-similarity beliefs. This leads to the following hypothesis: H3: The relationship between diversity and group performance is mediated by group cohesion and moderated by diversity beliefs in such a way, that higher levels of social category diversity more negatively affect the level of cohesion and subsequently the level of performance for groups holding more pro-similarity beliefs, and more positively affect the

12 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 12 level of cohesion and subsequently the level of performance for groups holding more prodiversity beliefs. Conceptual model Diversity beliefs + Diversity Cohesion Performance - + Methodology Research design, data collection & sampling strategy In order to test my hypotheses, I conducted a quantitative cross-sectional study. Data was gathered from various teams in various organizations. The unit of analysis in my research is teams within organizations. The unit of observation is individuals within teams. Only team managers were asked to answer questions regarding performance. In my research I used convenience sampling to select organizations. I collected data together with students from my master's circle to obtain the largest possible dataset. Before the questionnaires were distributed, consultation with the managers took place to define the team composition. Once a team was defined, an online questionnaire was used to gather data by using the program ʻQualtricsʼ and an accompanying letter was included. In most cases, the questionnaires were sent to the managers who then distributed them among their employees. In a few cases, questionnaires were sent directly to the employees.

13 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 13 Only teams consisting of persons working interdependently have been included in this research. The size of the teams ranged from a minimum of three team members to a maximum of fifteen team members. Furthermore, only teams with a response rate of 50 per cent or more were included in the dataset to ensure that scores represented the perspective of the whole group. Also, team members needed to acknowledge that they are part of the same team. The total dataset consisted of teams from 42 different organizations. In seven cases, two teams from one organization were included. In one case, three teams were included and in two cases four teams were included from one organization. To make sure none of the teams from one organization would influence another, no teams were included if an employee or manager was part of both teams. In order to obtain as many responses as possible, several reminders were sent to the managers, or in a few cases, to the employees themselves. The total sample of this study consists of 255 respondents coming from 57 different teams. In total 320 questionnaires were sent out, leading to a response rate of 79.7 per cent. On average the response rate per team in this study is 85.5 per cent. Regarding the dataset, 43.1 per cent of the respondents were male, and furthermore the age of the respondents ranged from 18 to 65, with an average age of 38 and 3 months (SD = 12.3). The average team tenure is 5.5 years, ranging from 2.5 months to 20 years (SD = 5.03). The average number of team members is 5.6, ranging from 3 to 15 (SD = 3.23). However, most teams included where relative small, as 66,7 per cent of all teams consisted of 3 to 5 team members. 39 teams (68.4%) came from profit organizations, while 18 teams (31.6%) came from non-profit organizations. Measurements In order to test my hypotheses and answer my research question, a questionnaire of 70 questions was used. Managers were asked to fill in an additional questionnaire of 11 questions in order to measure team performance. Since I collected data together with my peer students, only 18 questions out of 70 from the questionnaire for the employees were used in this

14 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 14 particular research (see Appendix A). The questions for this research are divided into four variables, namely diversity, cohesion, diversity beliefs and performance. Diversity. Diversity is measured according to two dimensions, namely gender and age. Two questions were used to measure diversity, namely what is your gender and what is your age. Following Williams and Meân (2004), I computed the gender scores by using the proportion of women index by dividing the number of women by the total number of individuals in the work group. The proportion of women index does not only provide insights into the effects of diversity itself, but is also about the direction of diversity. The proportion of women was used to test a linear effect of diversity on cohesion, whereas gender diversity itself was tested curvilinear by computing a squared term. In this research, the average proportion of women is.55, ranging from 0 to 1. If a team has a score of 0, the whole teams consists of men, whereas a score of 1 means that the team fully consists of woman. A score of.50 indicates highest diversity score, since there is an equal number of men and woman. Since most teams included were relative small, a few scores of the proportion of women were common. In 19.3 per cent, the proportion of women was 0. In 15.8 per cent, the proportion of women had a value of.33, whereas 7 per cent had a value of.66. Also, 29.8 per cent of all teams fully consists of women. I measured age diversity which is a continuous variable by calculating the standard deviation, and dividing it by the mean (van der Vegt & Janssen, 2002). The average age diversity of all respondents was.22. In this research, values ranged from 0 to.52, in which 0 refers to a team where everyone has the same age, and.52 to a team with the most age heterogeneity (SD =.12). Cohesion. I measured cohesion based on a questionnaire by Chang, Duck and Bordia (2006). This questionnaire divides cohesion into two dimensions, namely task cohesion and social cohesion. I used four items to measure task cohesion, and four items for social cohesion. Participants were asked to indicate how they feel about each statement by

15 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 15 responding on a seven-point scale, whereby one refers to 'strongly disagree' and seven to 'strongly agree'. For example, participants were asked to rate task cohesion by answering whether they think their team is united in trying to reach its goals for performance. An example for social cohesion is members rather go out on their own than as a team. In order to check the validity of the scale a principal component analysis (PCA) was performed. This analysis showed that cohesion consists of two components (see Appendix B). Four questions regarding task cohesion referred to one factor, while questions regarding social cohesion referred to the other factor, which is in line with the findings of Chang et al. (2006). Thereafter, Cronbach's Alpha was measured and showed a value of.85 for task cohesion and.65 for social cohesion. A sum score was computed to create the cohesion variable. Following De Jong, Curşeu and Leenders (2014) the scale's overall score for group cohesion is used in this research, given the internal consistency (α =.77) and meta-analytical evidence of Beal et al. (2003). In their research, they found social cohesion and task cohesion to be significantly related to performance, but those two did not significantly differ from each other (Kozlowski & Ilgen, 2006). Diversity beliefs. I measured diversity beliefs by the positive or negative beliefs individuals hold towards their team composition. Four questions, derived from van Dick et al. (2008), concerning ethnic diversity were transformed into questions regarding age diversity. For example I think that groups should contain people with similar ethnic backgrounds became I think that groups should contain people that have more or less the same age. Questions regarding diversity beliefs about gender diversity are derived from van Knippenberg et al. (2007). An example question regarding gender diversity is: A group performs better if it consists of a roughly equal number of men and women. Diversity beliefs on gender and age are both measured on a seven-point scale, ranging from 'strongly disagree' to 'strongly agree', whereas low scores indicate pro-diversity beliefs and high scores indicate

16 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 16 pro-similarity beliefs. Again, validity was checked by a PCA and showed three factors. Interpreting the result of the PCA, the third factor did not make any sense, since it consisted of one item regarding age diversity and one item regarding gender diversity. I decided to perform a reliability analysis on both age and gender diversity beliefs. Results showed that Cronbach's Alpha regarding age diversity beliefs was.59. However, ʻCronbach's Alpha if item deletedʼ showed that by removing item 4 ( Creating groups that contain people with more or less the same age can be a recipe for trouble ), Cronbach's Alpha would increase to.74. The reliability analysis for gender diversity beliefs resulted in a Cronbach's Alpha of.45. By removing item 5 ( A group performs better if it consists of a roughly equal number of men and women ), Cronbach's Alpha would increase to.80. For that reason, item 4 and 5 were deleted. Both item 4 and 5 represented the third factor in the initial PCA. As a final check, a new PCA was conducted (see Appendix B). This analysis confirmed the two constructs of diversity beliefs. After that a sum score was computed to create a variable for diversity beliefs. Performance. I measured performance by eight items, derived from Stewart and Barrick (2000), and added two items (efficiency and ability to resolve conflicts) from Ancona and Caldwell (1992). Prior studies (e.g Faraj & Sproull, 2000; Alper, Tjosvold, & Law, 2000) have indicated that efficiency and the ability to resolve conflicts are related to performance. Therefore, by adding these two items a wider range of aspects related to performance are covered, and subsequently ensured no relevant information was lacking. To ensure the objectivity of the measurement, I assessed team performance via manager ratings. Managers were asked to rank team performance by a seven-point scale ranging from inadequate to requirements to exceed requirements. For example, they were asked to rate their team on knowledge of tasks. One question from Stewart and Barrick (2000) measured the overall performance of the team, ranging from 1 to 100. In order to include this item in the

17 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 17 performance scale, it was transformed into a seven-point scale by dividing the item by The principal components analysis revealed two factors, which have been used separately to perform analyses. These factors could be interpreted as antecedent of performance and output of performance (see Appendix B). After that, Cronbach's Alpha was calculated and shows a good internal consistency reliability of the scales, since the coefficient for performance antecedents was.83, and.79 for performance output. Again, a variable was computed by using a sum score. Control variables. In this research, team size and team tenure were added as control variables. Team size was measured because it was found to be negatively related to team cohesion (Carron & Spink, 1995, as cited in, De Jong et al., 2014). Team size was established by asking managers. I also took team tenure into account since teams that are working together for a long period of time could be more cohesive. Furthermore, teams working together for a long time have established routines which could positively influence performance. Data aggregation Since my hypotheses are formulated at a group level, individual scores were aggregated to a group level. In order to check whether such aggregation is justified, the interrater agreement r wg(j) and intraclass correlation indices ICC(1) and ICC(2) were calculated (Lebreton & Senter, 2008). According to Lebreton and Senter (2008), r wg(j) values between.71 and.90 are considered strong agreement within a group. Values above.90 to 1.00 are seen as a very strong agreement. ICC(1) values of.01 is considered to be a small effect, whereas a value of.10 represents a medium effect. Values of.25 are seen as a large effect. Following Lebreton and Senter (2008), I consider ICC(2) values above.60 as appropriate to aggregate to a group level. The average r wg(j) for cohesion was 0.92 (median =.95, range =.52 to.99). ICC(1) =.25 and ICC(2) =.64, F = 2.764, p <.05. This means that aggregation of the

18 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 18 individual level to team level is justified. With regards to diversity beliefs, the mean r wg(j) was.89 (median =.92, range =.60 to.99). ICC(1) =.24 and ICC(2) =.63, F = 2.667, p <.05, which also means that aggregation to a group level is justified. Data analysis In order to analyse the data, and to test the hypotheses, I inserted the quantitative data in SPPS. First, all questions that were phrased negatively were reverse coded. Then the data was checked on missing values and outliers. Also, normality, linearity and homoscedasticity were checked (Pallant, 2010). Multiple regression analyses were used to test my hypotheses. In this research, p-values less than.05 (p <.05) are considered to be significant (Field, 2009). Control variables were added in the regression analyses to rule out spurious effects. In order to test mediations effects and to test my full conceptual model, macros had to be installed in SPSS following the steps of Hayes (2009) and Preacher, Rucker and Hayes (2007). Bias corrected bootstrapping with 5,000 samples was applied. To test the significance of the indirect effects, zero should not end up between the lower and upper bound (Hayes, 2009). In case both lower and upper bound show a negative number, the indirect effect is significantly negative, whereas a positive lower and upper bound can be interpreted as a positive mediation effect. Results Before testing my hypotheses, data was checked for multicollinearity. Following Pallant (2010), the correlation between independent variables should be under.70 to make sure no multicollinearity problems arise. As shown in Table 1, there are no multicollinearity issues in this research, which is confirmed by the low VIF scores (highest VIF = 1.41). The means, standard deviations and correlations of this study are presented in Table 1. No significant correlation was found between gender diversity and cohesion. Furthermore, the correlation between age diversity and cohesion (r = -.25) is insignificant. Moreover, no

19 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 19 variables showed significant correlations with performance output, suggesting the absence of any direct effects. The significant correlation (r =.32, p <.05) suggests the presence of an effect between cohesion and performance antecedents. Significant correlations were also found between both types of diversity beliefs and other variables. The correlation between gender diversity and gender diversity beliefs is -.34 (p <.01), suggesting that homogenous groups have more pro-similarity beliefs regarding gender. The same applies for age diversity and age diversity beliefs, where a significant correlation of -.39 (p <.01) was found. The negative correlation suggests that homogenous groups have more pro-similarity beliefs regarding age. Also, a positive correlation (r =.52, p <.01) was found between performance antecedents and performance output, suggesting that certain conditions necessary for performance lead to a higher level of performance. Finally, both types of diversity beliefs appeared to be significantly correlated to the team size and team tenure control variables. Table 1 Means, standard deviations and correlations a 1. Team size Team tenure Proportion of women Gender diversity ** M SD Diversity (age) Team cohesion Diversity beliefs (age) * -.30* ** Diversity beliefs (gender) * -.26 * -.34 ** Team performance (antecedents) * Team performance (output) ** Note: * p <.05 (2-tailed). ** p <.01 (2-tailed). a n = 57 Hypotheses 1 Table 2 and 3 show the results of the hierarchical multiple regression analysis, testing Hypothesis 1. First I tested the effect of age diversity and gender diversity on cohesion, by conducting two regression analyses, since the correlation (r =.06) between age diversity and gender diversity was very low. The proportion of women was used to test a linear effect of

20 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 20 diversity on cohesion, whereas gender diversity itself was tested curvilinear by computing a squared term. Results revealed that gender diversity and the proportion of women were insignificant. Therefore, neither gender diversity, nor the proportion of women were used to test the interaction effect (Mackinnon, 2008). The construct of age diversity beliefs was used to test the interaction effect between age diversity and cohesion. The interaction effect was tested by centering the variables (Aiken & West, 1991). It is apparent from Table 2 that none of the variables regarding the proportion of women and gender diversity are significant under a confidence interval of 95%, meaning that neither the more women present in a team, nor gender diversity itself are a significant predictor for cohesion. Another hierarchical multiple regression analysis was used to test if age diversity significantly predicts cohesion. As presented in Table 3, results show that age diversity is negatively related to cohesion (β = -.27, p <.05), which means that groups more diverse in terms of age are less cohesive compared to age homogenous groups. According to R-square in the second model, the two control variables and age diversity explain 9.6% of the variance, which is a significant improvement compared to the first model. More interesting is the result from the interaction effect, as shown in Table 3. Here, 21% of the variance is explained by adding age diversity beliefs, which is a significant change of the model, as a negative effect was found (β = -.37, p <.05). In order to interpret these results, a graphical representation was made. As presented in Figure 1, it became clear that age diversity is negatively related to cohesion if groups have more pro-similarity beliefs. As seen in Figure 1, there is also a decrease of cohesion if groups have more pro-diversity beliefs, which means that groups holding more pro-diversity beliefs do not have the same advantages as homogenous groups if they value diversity. Therefore, it cannot be stated that groups holding more pro-diversity beliefs experience a higher level of cohesion. To conclude, Hypothesis 1 is partly supported since only age diversity seems to affect cohesion. Also, groups holding more

21 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 21 pro-similarity beliefs experience a lower level of cohesion, but cohesion is not enhanced for groups holding more pro-diversity beliefs. Table 2 Results of the multiple hierarchical regression analysis prediction cohesion. a Step 1:Control variables Note. p <.0.1. * p <.05. ** p <.01. a Standardized coefficients are reported Cohesion Variable Model 1 Model 2 Model 3 Model 4 Model 5 Team size Team tenure Step 2: main effects Proportion of women Gender diversity² Gender diversity beliefs Proportion of women X gender diversity beliefs R² Adjusted R² R² F-change Table 3 Results of the multiple hierarchical regression analysis prediction cohesion. a Cohesion Step 1:Control variables Variable Model 1 Model 2 Model 3 Model 4 Team size Team tenure Step 2: main effects Age diversity -.27* Age diversity beliefs Age diversity X age diversity beliefs -.37* R² Adjusted R² R².03.07*.01.10* F-change Note. p <.0.1. * p <.05. ** p <.01. a Standardized coefficients are reported

22 Cohesion THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 22 Figure 1 7 6,5 6 5,5 5 4,5 4 Pro-diversity beliefs Pro-similarity beliefs 3,5 3 Low Age diversity High Additional analysis of Hypothesis 1. As a robustness check, I conducted an additional analysis testing gender diversity (see Appendix C) following Teachman (1980). However, results did not reveal a significant relationship between gender diversity and cohesion by using Teachman's index (see Appendix D). Based on the arguments of Webber and Donahue (2001), two additional analyses were performed (see Appendix D). Firstly, team tenure was used as a moderating variable to test its effect on the relationship between diversity and cohesion. Webber and Donahue (2001) argue that the negative effects of diversity on cohesion could decrease if employees work together for a longer period of time, because they develop more appreciation for each other and their differences. Results did not reveal any significant effect under a confidence level of 95%, indicating that neither the negative outcomes of gender diversity, nor the proportion of women decrease over time if groups work together for a longer period. Secondly, another analysis was performed to test whether a moderate level of diversity has an effect on cohesion. Subgroup formation is likely to occur under moderate levels of diversity, and less likely for low and high levels of diversity (Webber & Donahue, 2001). As a consequence, a moderate level of diversity would have a larger negative effect on cohesion. In order to test a curvilinear effect of diversity, I adjusted the gender diversity index (see Appendix C). The proportion of women scores were computed

23 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 23 in such a way that, for example, a team that consists of 3 women would have the same diversity score as a team of 3 men. Diversity scores ranged from 0 to 0.5. A score of 0 indicates no diversity, whereas a score of 0.5 indicated the most diversity. Results did not reveal a significant curvilinear effect. Another additional analysis was performed to test whether diverse groups would have more pro-diversity beliefs or more pro-similarity beliefs (see Appendix D). First age diversity was used as an independent variable to test its effects on age diversity beliefs. Results showed that age diversity is negatively related to age diversity beliefs (b = -2.75, p <.001). This result indicates that the more team members differ in age, the more pro-diversity beliefs they have. With regards to gender diversity, results revealed a U-shape relation. As gender diversity increases, groups have more pro-diversity beliefs (b = -1.98, p <.05). When the quadratic term is added, it shows that at a certain point when diversity decreases, groups hold more prosimilarity beliefs again (b = 1.52, p <.05). Hypothesis 2 The next step was to perform two multiple regression analyses between cohesion and performance to test whether a higher level of cohesion would enhance performance antecedents and performance output. Both performance antecedents and performance output were used as dependent variables. Although the performance antecedents construct and the performance output construct are moderately correlated (r =.52), I decided not to include one another in its regression for a practical reason. An additional analysis showed that performance antecedents are a predictor for performance output, indicating a mediation effect between cohesion and performance output. As shown in Table 4, a significant effect was found between cohesion and performance antecedents (b =.41, p <.01). This means that cohesive teams experience a higher level of necessary conditions to perform well. For example, cohesive teams are likely better at the planning and allocating of their work,

24 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 24 moreover they will probably show more initiative towards their jobs. Based on the variance, 16.9% is explained by cohesion. No significant effect was found between cohesion and performance output, see Table 4. For that reason, Hypothesis 2 is partly supported. Additional analysis of Hypothesis 2. More interesting is the result of an additional analysis (see Appendix E). An initial regression analysis between performance antecedent and performance output indicates the existence of a mediation effect between cohesion and performance output (b =.43, p <.01). Reasoning behind this mechanism is that cohesive teams could enhance certain conditions necessary for performance, which leads to a higher level of performance output. This regression analysis showed that 28% of the variance in performance output is explained by performance antecedents. The next step was to test whether the relationship between cohesion and performance output is mediated by performance antecedents. In order to do so, a macro had to be installed in SPSS following the steps of Hayes (2009) and his website ( with guidelines explaining these steps. These macros use the bootstrap method, in which the sample repeatedly gets resampled (Hayes, 2009). Bias corrected bootstrapping with 5,000 samples was applied. To test the significance of the indirect effects, zero should not end up between the lower and upper bound (Hayes, 2009). In case both lower and upper bound show a negative number, the indirect effect is significantly negative, whereas a positive lower and upper bound can be interpreted as a positive mediation effect. The bootstrapping results revealed significant indirect effect between cohesion and performance output, mediated by performance antecedents (effect size =.19, 95% confidence interval [.02,.48]).

25 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 25 Table 4 Results of the multiple hierarchical regression analysis prediction performance. a Performance antecedent Performance output Model 1 Model 2 Model 1 Model 2 Variable b SE B SE b SE b SE Step 1:Control variables Constant 4.90** ** ** **.84 Team size Team tenure -.05* Step 2: main effects Cohesion.41* R² Adjusted R² R².09.08* F * Note. p <.0.1. * p <.05. ** p <.01. a Unstandardized coefficients are reported with standard errors in parentheses Hypothesis 3 For my third Hypothesis, I performed a full model test following Preacher et al. (2007) and Hayes (2009). Again, a macro had to be installed in SPSS. This analysis was performed on the variables of age diversity (X), cohesion (M), age diversity beliefs (W) and performance antecedents (Y), by using model 7 from Hayes templates. The effect of the moderator variable age diversity beliefs on the mediation effect was tested on three levels (-1 standard deviation, mean, 1 standard deviation) by using bootstrapping. Results revealed that low age diversity beliefs (-1 standard deviation) do not significantly influence the mediation effect. At a medium level (mean) of age diversity beliefs, the mediation effect is significantly weaker (effect size = -.46, 95% confidence interval [.-1.84,.02]). Also, at a high level (+1 standard deviation) of age diversity beliefs, the mediation effect is weaker (effect size = , 95% confidence interval [-3.20, -.21]). It has to be mentioned that bootstrapping yields different upper and lower bounds each time the method is applied on the same data (Preacher et al., 2007). Since the number of the lower bound for a medium level of age diversity beliefs is close to zero, I repeatedly performed this analysis and found that in a few cases, the effect was

26 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 26 insignificant. The results of a medium level of diversity beliefs should be interpreted with caution, since the bootstrapping results balance around the critical point of being significant under a confidence level of 95%. In general, the results testing Hypothesis 3 indicate that the negative effects of age diversity on performance, mediated by cohesion are weaker for groups holding more pro-diversity beliefs compared to groups holding more pro-similarity beliefs. Based on the results as shown in Table 2, neither a curvilinear effect was found between gender diversity and cohesion, nor a linear effect for the proportion of women. Therefore, no full model test was performed for gender diversity (Mackinnon, 2008). Thus, Hypothesis 3 is partially supported. Discussion The aim of this research has been to explore the relationships between diversity, diversity beliefs, cohesion, and performance. Some results were particularly evident in this study. Firstly, the results show that the more team members differ in age, the lower the cohesiveness of a group. This kind of effect was not found for gender diversity and for the proportion of women in work groups. Secondly, in this study a negative relationship was found between age diversity and cohesion for groups holding more pro-similarity beliefs. In contrast to what I expected to find, pro-diversity beliefs did not seem to positively affect cohesion. Instead, a negative relationship was found, although weaker if compared with groups holding more pro-similarity beliefs. Thirdly, results revealed that cohesion positively affects certain specific conditions necessary for performance. Cohesion did not appear to be directly related to performance output. Finally, results revealed that a medium level of age diversity beliefs weaken the mediating effect of age diversity on performance antecedents, mediated by cohesion. Pro-similarity beliefs have an even stronger negative effect on the mediation effect, while groups holding more pro-diversity beliefs are not affected by this relationship. Thus, the current findings partially support all hypotheses.

27 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 27 Discussion of the results In this research, a negative effect on cohesion was found for age diversity. Based on the existing literature, a negative relation between diversity and cohesion was also expected. According to the social category perspective (e.g. van Knippenberg et al., 2004), social categorization is the root cause of both bias in intergroup attitudes and of problematic behaviour, since it causes individuals to hold more positive feelings for people of a similar background, and more negative feelings for people belonging to other categories. Also, this research proposed that gender diversity would negatively affect cohesion, but the findings do not support this. First of all, one possible explanation for the absence of a relationship between gender diversity and cohesion is the current acceptance of the presence of women in all layers of organizations (Lückerath-Rovers, 2012). Nowadays mixed teams of men and women have become ever more common. Therefore, the negative impact of gender diversity on cohesion may have decreased in the course of time. Another reason for the absence of the relationship may be because most teams included in this research represented a narrow range of gender diversity. Therefore, diversity scores did not differ much from each other. This is mostly due to the fact that most teams ranged between 3 and 5 employees. This research also aimed to investigate if teams holding more pro-diversity beliefs may reduce or even eliminate the negative effects of social categorization diversity on cohesion, and subsequently on performance. Diversity beliefs, and especially pro-diversity beliefs, are able to facilitate these positive outcomes on cohesion and subsequently on performance (van Dick et al., 2008). However, in contrast to what I expected to find, prodiversity beliefs did not enhance cohesion. This research only showed that pro-diversity beliefs weaken the negative effects of social categorization on cohesion. There are several potential explanations for the lack of positive relationship between social category diversity and cohesion. First, prior studies mostly researched the ethnical background of work groups.

28 THE IMPACT OF DIVERSITY BELIEFS: BOOST OR BARRIER? 28 Ethnical diversity might have more impact on diversity beliefs since it is associated with racism and prejudice (van Dick et al., 2008). Secondly, team members may have given socially desirable and ideology-driven answers regarding diversity beliefs, while their behaviour is not compliant with their perspective. For example, people in diverse groups may have given the theoretical indication that they appreciate and value diversity, while in practice they would still interact more closely to those more similar to themselves. As a consequence, groups indicating that they value diversity may still experience a dispersed cohesion. Moreover, van Dick et al. (2008) already mentioned that for ethnical diversity, changing a mind-set is difficult since it is associated with racism and prejudice. This argument may also be valid for gender and/or age diversity beliefs. Prejudiced opinions on others are difficult to change. For example, a man who believes that women are bad drivers will not change his mind-set by seeing one good female driver. It is even more difficult if this opinion is formed by negative experiences in the past, since these feelings will shape future beliefs (Homan et al., 2007). Homan et al. (2007) have also argued that positive experiences could positively shape future beliefs. Based on the above argumentations, I argue that pro-diversity beliefs are not able to positively affect cohesion, since these beliefs will not be associated with cohesion. Moreover, it may be that researchers overestimated the importance of diversity beliefs. Therefore, more research is necessary to find out if scholars truly are overestimating diversity beliefs and their actual positive effects in different research settings or contexts. Yet another aspect was found regarding to the relationship between cohesion and performance. Over the last 15 years, in their meta-analytic reviews, several researchers found that cohesion is positively related to performance (Kozlowski & Ilgen, 2006). This research clearly showed that cohesion is positively related to performance antecedents. According to Beal et al. (2003), performance antecedents generally are more closely related to cohesion than to performance output. Therefore cohesion is more strongly related to performance