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Cultural Diversity and Team Innovation Sibel Sakin Pons

10842047 Master’s Thesis

Graduate School of Communication Track: Corporate Communications

Supervisor: Pernill van der Rijt Submission date: 27.01.2016

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Abstract

Previous research reports mixed findings (positive, negative, or no relationship) regarding the effect of cultural diversity on team innovativeness. Thus, this study

investigated whether there are other factors that may play a role in this relationship. More specifically, the role of knowledge sharing practices, diversity climate, and innovation climate are examined. All variables were measured on team level, as new ideas are likely to be introduced and implemented by teams in organizations. The results suggest that cultural diversity, knowledge sharing practices, diversity climate, and innovation climate separately lead to team innovation. Moreover, it was found that diversity climate positively predicts knowledge sharing practices within a team. Statistical analyses indicate that diversity climate may have an indirect influence on team innovation via knowledge sharing practices. Though, it was not possible to prove this mediation effect. Therefore, future research is required to further investigate the relationship between these variables.

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Introduction

While organizations have different motivations for opening their doors to cultural diversity, some business models cannot survive without it. Today many companies operate beyond their nations’ boundaries as a result of increased internationalization and globalization. For instance, multinational companies have a branch in several different countries and many companies, no matter whether they are multinational or not, employ ethnic minorities due to changing population characteristics of the country they are based in. Consequently, dealing with cultural diversity is a daily routine for the employees of these organizations and the challenge for the organizations is to make these people to function in harmony in order to enhance competitive advantage.

There are three perspectives regarding how cultural diversity is perceived by

organizations (Thomas & Ely, 1996). The discrimination and fairness paradigm emphasizes the importance of equal opportunity, fair treatment, and recruitment of all groups within a society. The access and legitimacy paradigm focuses on employing diverse people in order to understand and serve diverse groups in a society. The Learning and effectiveness paradigm, while

acknowledging the benefits of the other two paradigms, allows the organization to internalize differences among employees and accepts those differences as an important resource to learn from. It is suggested that the type of perspective an organization holds about cultural diversity has an effect on how diverse teams will function (Thomas & Ely, 2001). Although this is a relevant point, there are many other factors that may influence the functioning of culturally diverse teams.

There are several studies that tested the effect of cultural diversity on team innovation (e.g., De Dreu & West, 2001; Stahl, Maznevski, Voigt, & Jonsen, 2010; Hülsheger, Anderson, & Salgado, 2009; Winkler & Bouncken, 2011). However, these studies report mixed findings

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(positive, negative, or no relationship). Thus, it is hard make general assumptions regarding how such teams operate. Scholars (e.g. Stahl et al., 2010; Milliken & Martins, 1996) draw attention to the need of testing the role of possible mediators and moderators in the relationship between cultural diversity and team innovation, yet this knowledge is still scarce. For instance, the way a team communicates, more specifically whether its members share their knowledge with each other or not, may effect its innovativeness. Moreover, climate components, constituting the context a team functions in, can support or hinder its outcomes. This study, in order to fill this theoretical gap, will test the influence of knowledge sharing practices, diversity climate, and innovation climate in the relationship between cultural diversity and team innovation. Since employing people with diverse cultural backgrounds may not automatically result in positive outcomes, more specifically with innovation, this study can benefit the management of culturally diverse organizations by increasing their awareness about how culturally diverse teams should be managed in order to harvest its advantages. The following research question is formulated for the purposes of this study:

“To what extent do knowledge sharing practices, diversity climate, and innovation climate affect the innovativeness of culturally diverse teams?”

Theoretical Background

Diversity research has developed in two main streams: “social category diversity” and “informational/functional diversity” (Hülsheger et al., 2009). The former concept benefits from self-categorization, social-identity, and similarity attraction theories and refers to the differences that are readily detectable such as sex, age, and ethnicity. According to self-categorization (Turner, 1985) and social identity (Tajfel, 1981) theories, individuals use similarities and differences as a basis for categorizing self and others into groups. This process results into

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classifications distinguishing between one’s own in- and out-groups. In-group members are liked, trusted, and thus preferred over out-group members (Fiske, 1998). These findings are consistent with similarity/attraction theory (Newcomb, 1961), which suggests that similarity on attributes such as attitudes, values, and beliefs will facilitate interpersonal attraction and liking. This implies that workgroup members are more positively inclined toward their own group and the people within it when group members are similar rather than dissimilar to the self (Williams & O’Reilly, 1998). According to this line of thought, categorization processes may hinder social processes by producing subgroups within the workgroup (e.g., “us” and “them”), and

consequently give rise to negative outcomes (Hofhuis, Van Der Zee, & Otten, 2012; Mannix & Neale, 2005).

For example, in a quantitative study, which consisted 151 groups and 1705 respondents, Tsui, Egan, and O'Reilly (1992) demonstrated that as individuals were more demographically different from their workgroups, they became less psychologically attached, had lowered intentions to remain in the firm, and had higher levels of absenteeism. Additionally, social category diversity that is operationalized as heterogeneity in age and sex is found to increase relationship conflict in workgroups (Jehn, Northcraft, & Neale, 1999). Literature suggests that some level of task-based conflict that relates to discussions and debates about the work being done is considered to be good for creativity, and thus for innovation (Kurtzberg & Amabile, 2010). However, one should remember that even a task-based conflict could escalate to an emotional and personal level quickly (Hüttermann & Boerner, 2011). Thus, conflicts, which are detrimental to functioning of a team and intra-group communication (Jehn, 1995; Bouncken & Winkler, 2010), are not desirable.

The second concept, informational/functional diversity, refers to differences in less visible underlying attributes that are more job-related, like functional and educational

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background. This type of diversity is believed to have different consequences than social category diversity that has negative outcomes. Research on informational/functional diversity assumes that diverse groups should outperform homogeneous groups, as diverse groups are more likely to possess a broader range of task-relevant knowledge, skills, abilities, and experience and have different opinions and perspectives about the task at hand (Van Knippenberg, De Dreu & Homan, 2004). As a consequence diverse groups do not only have access to a larger pool of resources, but also exposure to diverging and potentially surprising perspectives may lead to more creative and innovative ideas and solutions (e.g., Milliken & Martins, 1996; West, 2002). Bantel and Jakson (1989) examined the relationship between the social composition of top management teams and innovation adoptions in a sample of 199 banks. They concluded that more innovative banks are managed by more educated teams who are diverse with respect to their functional areas of expertise. Shin and Zhou (2007), using a sample of 75 research and development teams, concluded that teams with greater educational specialization heterogeneity exhibit greater team creativity, when transformational leadership is high. Additionally, Jehn et al. (1999) demonstrated in a field study that informational diversity positively influences group performance and this effect is mediated by task conflict.

As explained above, findings regarding the effects of diversity are mixed. Some studies report positive whereas others report negative outcomes. The crucial point is that two dimensions of diversity (“social category diversity” and “informational/functional diversity”) are not always mutually exclusive (Van Knippenberg, et al. 2004). In other words, one can be diverse in both dimensions. For instance, someone, who has a different cultural background (social category diversity) compared to another, is also likely to have a different education, knowledge, and skills (informational/functional diversity), which are influenced by one’s unique culture.

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Cultural Diversity and Team Innovation. Diversity can be defined as the differences

between individuals on any characteristic that may lead to the impression that another person is different from self (Van Knippenberg et al., 2004). In their review of management research Milliken and Martins (1996) listed fourteen types of diversity: race and ethnic background, nationality, sex, age, personality, cultural values, socioeconomic background, educational background, functional background, occupational background, industry experience,

organizational membership, organizational tenure, and group tenure. While diversity is a broad concept, this study will only focus on national diversity. One’s nationality is also indicative of his culture, as each nation shares a common history, language, and traditions through which a unique culture comes into existence. Thus, the terms “national diversity” and “cultural diversity” will be used in exchange throughout the study.

Innovation in the workplace is considered to be an important determinant of

organizational performance and success, as it is a source of competitive advantage (Anderson, Potočnik, & Zhou, 2014; Bouncken & Winkler, 2010). While innovation can take place on individual, team, and organizational levels, this study will focus on team innovation. This is due to the fact that within organizations new ideas are likely to be proposed and pursued toward implementation by work teams (Hülsheger et al., 2009). Team innovation, which refers to the introduction or application of ideas, processes, products, or procedures that are new to a team and that are designed to be useful (Chi, Huang, & Lin, 2009), depends on creativity that is the generation of novel and useful ideas (West, 2002).

Since people from different gender, nationality, and ethnic groups hold different attitudes and perspectives on issues, cultural diversity is likely to increase team creativity and innovation (Cox & Blake, 1991; Kurtzberg & Amabile, 2010). For instance, Watson, Kumar, and

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teams score lower than culturally homogenous teams on interpersonal interaction and performance effectiveness. However, as the amount of time that the group members spent together increased, the between-group differences converged. More interestingly, after a specific time period, culturally diverse groups had become more efficient than homogenous groups on tasks like identifying problem perspectives and generating solution alternatives. Furthermore, a field study demonstrated that groups composed of Asians and whites were more creative and better able to implement new ideas than all-white groups or those of other ethnic composition (O’Reilly, Williams, & Barsade, 1997 as cited in Williams & O’Reilly, 1998). Another experimental study that compared the performance of ethnically diverse to ethnically

homogeneous groups on a brainstorming task demonstrated that heterogeneous groups produced higher quality ideas than homogeneous groups (McLeod & Lobel, 1992). Since identifying new problem perspectives and solution alternatives, generating high quality ideas, implementation of new ideas, and creativity are important factors for innovation to take place the following

hypothesis is formulated:

Hypothesis 1: Cultural diversity will have a positive direct effect on team innovation.

Knowledge Sharing Practices. Intra-team communication can play a crucial role for a

culturally diverse team to deliver positive outcomes like innovation. Knowledge sharing (KS) practices, which is a form of communication, within a team is especially important. KS can be defined as the process where individuals mutually exchange their knowledge and jointly create new knowledge (Van Den Hooff & De Ridder, 2004). Knowledge is any organization’s

intellectual capital that is crucial to promote competitive advantage (Ndofor & Levitas, 2004; Osterloh & Frey, 2000) and, in order to benefit from existing knowledge to its highest capacity, individual members of organizations should share it with co-workers (De Vries, Van den Hooff, & De Ridder, 2006). Thus, team innovation cannot take place without such a practice among

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team members. Literature supports this claim. Findings imply that cultural diversity does not automatically lead to team innovation and there are other factors that might play a role in this relationship. For instance, effective communication, in particular KS practices, within a

culturally diverse team can support a team to deliver positive outcomes like innovation. In line with this argument, Ancona and Caldwell (1992), in their quantitative study of 45 product teams, suggested that a group’s functional diversity increases team members’ outside the workgroup communication and in return this communication leads to higher levels of innovation.

Other scholars contributed to the literature with findings indicating a possible relationship between cultural diversity and KS practices. For instance, Stahl et al. (2010), in a meta-analysis, demonstrated that culturally diverse teams do not experience less effective communication than homogenous teams. Dinsbach, Feij, and De Vries (2007), by their quantitative study of an ethnically diverse organization in the Netherlands, concluded that ethnic minority employees report higher scores on communication about their role, tasks and the organization than their ethnic majority colleagues. This finding suggests that culturally heterogeneous teams are likely to score higher in job related knowledge sharing compared to culturally homogenous teams. Additionally, Cox, Lobel, and McLeod (1991) concluded that the groups composed of Anglos, Hispanics, Asians, and Blacks were more cooperative than the groups composed of only Anglos. This finding implies that ethnic diversity, as a source of cultural differences, would enhance cooperative behavior that is an important indicator of KS between teams. Based on these findings, the following hypothesis is formulated:

Hypothesis 2: Cultural diversity will have a positive direct effect on KS practices. Others investigated whether there was a link between KS practices and innovation. For instance, Van Wijk, Jansen, and Lyles (2008), in a meta-analytic review, suggested that KS has a positive influence on innovation. In other words, innovativeness was found to increase, as KS

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increased. Jansen, Van den Bosch, and Volberda (2006), in a quantitative study, demonstrated that connectedness, which increases opportunities of KS between different business units, has a positive significant effect on innovation. Similarly, West and Anderson (1996), in a quantitative study, demonstrated that participation, which requires KS and involvement in decision-making, predicted innovation. Since connectedness and participation are important indicators of KS, the following hypotheses are formulated.

Hypothesis 3: KS practices will have a positive direct effect on team innovation. Hypothesis 4: KS practices will mediate the relationship between cultural diversity and team innovation.

Besides the possible influence of KS practices in the relationship between cultural diversity and team innovation, there are several studies that emphasized the role of different climate measures on the functioning of a team (e.g., Kivimäki et al, 2000; West & Wallace, 1991). Consequently, this study will specifically focus on the role of diversity and innovation climate measures with regard to the relationship between cultural diversity, KS practices and team innovation. The role of both climate measures are especially relevant, as they can be influenced by the organizations in order to improve the way a culturally diverse team functions.

Diversity Climate. Hofhuis et al. (2012) define “diversity climate” as the extent to which

an organizational climate facilitates the presence of cultural differences, and views this diversity as a positive asset. Diversity climate is composed of two aspects; openness to and appreciation of diversity (Luijters, Van der Zee, & Otten, 2008). The former concept refers to the possibility to choose one’s own work style and maintain important cultural habits, even though these habits may differ from what is perceived as “normal”. The latter concept refers to a status quo where diversity is seen as an added value within an organization (Hofhuis et al., 2012). In other words,

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this concept refers to the situation in which diversity among employees is seen as an advantage, and not as an issue.

KS practices in a team depends highly on the social capital, which can be defined as networks together with shared norms, values, and understandings that facilitate co-operation within or among groups, in an organization (Van den Hooff & Huysman, 2009; Yu, Hao, Dong, & Khalifa, 2013). In other words, the higher a team scores on social capital, the more likely its members will share their knowledge with each other (Van Wijk et al., 2008). From this

perspective, it can be argued that an organization’s social capital will not be very strong, if its employees think of themselves along cultural lines and categorize the ones who do not belong to the same group. In turn, categorization of team members, while lowering the social capital, is expected to lead to lower levels of KS within a team and thus to decrease team innovation. However, a strong diversity climate can prevent categorization and limit possible negative effects of cultural diversity. Consequently, it can be claimed that KS among team members with different cultural backgrounds will be higher in organizations with a strong diversity climate. Thus, the following hypothesis is formulated:

Hypothesis 5: Diversity climate in a team will moderate the relationship between cultural diversity and KS practices in such a way that cultural diversity will be more positively related to KS practices when diversity climate is high than when diversity climate is low.

Innovation Climate. It is not easy to prescribe actions that will lead to innovation, as it

requires divergent thinking and creativity. For instance, extrinsic rewards that can be a good motivator for one’s performance diminish creativity, whereas freedom of choice increases it (George & Jones, 2012; Amabile, Hennessey, & Grossman, 1986). Though this does not mean that innovation cannot be supported. Team innovation through cultural diversity is a group process and thus, the way a group interacts and communicates is likely to have an influence on

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its innovativeness. Although KS is an important step for innovation to take place, there are other factors that can support this process. For instance, Liao, Fei, and Chen (2007) demonstrated that KS has a positive effect on innovation capability only via absorptive capacity that can be defined as the ability to recognize the value of new information, to assimilate it, and apply it to

commercial ends.

One way to motivate innovation is through norms. Group norms can be defined as guidelines for acceptable and unacceptable behavior that develop through interactions among group members and are informally agreed on by group members (Ehrhart & Naumann, 2004). Such norms can be a powerful tool to enhance team-level innovation by creating a climate that secures social approval for activities such as participation in discussions, trying new ways of doing things, and tolerating mistakes (Caldwell & O’Reilly, 2003). In such an environment team members would be more likely to take risks to implement new ideas. For instance, West and Anderson (1996), in a longitudinal study of functioning of top management teams in 27 hospitals, demonstrated that innovation climate has a positive effect on team innovation. Additionally, a meta-analysis of team-level antecedents of creativity and innovation concluded that support for innovation is positively associated with innovation (Hülsheger et al., 2009). In this sense, it is expected that the relationship between KS practices and team innovation will be stronger when innovation climate is high. Put differently, the interaction of KS practices with innovation climate is expected to lead higher levels of innovation compared to the situation where KS is alone predicting team innovation. Thus, the following hypothesis is formulated:

Hypothesis 6: Innovation climate in a team will moderate the relationship between KS practices and team innovation in such a way that KS will be more positively related to team innovation when innovation climate is high than when innovation climate is low.

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Figure 1: Conceptual Model

Methods

The data is collected by an online cross-sectional survey created in Qualtrics, which is an online research tool, in November 2015. Using snowball-sampling method that is a form of convenience sample (Briner, 2012), the link to access the survey was sent to a group of contacts with the help of electronic mail and social media like facebook, LinkedIn, and Twitter. In line with this approach, contacts were asked to send the link to people in their network and ask them to fill in the survey. For ethical considerations, the data was collected only from people who were eighteen years old or above. Moreover, the survey targeted people who were working in a team environment at the time of data collection. Respondents were explained that they are participating to a study about “innovation in teams” via the fact sheet that constituted the first variable on the survey. Moreover, informed consent form was obtained from all the respondents.

In total 206 people participated in the survey. However, when people who did not meet the requirements (those who were below eighteen years old, who were not currently working in a team environment, and who did not complete the survey) were excluded, this resulted in a

sample size of 136 (N=136). Men constituted 58,1 % of the final sample and the mean age for all Diversity Climate Cultural Diversity Knowledge Sharing Practices Team Innovation Innovation Climate

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respondents was 38,68 (SD=9,82). The mean for team tenure was 3,98 years (SD=4,43). In total, 26.5 % of the respondents moved to another county at least once due to the job requirements and the mean of the time they spent abroad was 3.86 (SD=4,2) years.

Cultural Diversity. Cultural diversity is operationalized as the diversity of nationality in

one’s team. Thus, this variable is measured by asking respondents to indicate the number of team members, including themselves, belonging to each nationality based on a list of countries

provided. First respondents’ team size was calculated adding up the number of team members belonging to each nationality. Second, Blau’s (1977) index of heterogeneity (B = 1-∑pi2), where

P is the proportion of individuals in a category and i is the number of categories, was used to calculate the actual cultural diversity for each respondent’s team.

Team Innovation. This variable was measured with six 5-point Likert-type items,

ranging from one (1=don’t agree at all) to five (5=agree very much), that were used in the study by Chi et al., (2009). Items were modified to specify one’s team (e.g., “my team” instead of “this team”). The scale is comprised by calculating the mean for six items and includes statements such as “My team members often implement new ideas to improve the quality of our products and services”, “My team gives full consideration to new and alternative methods and procedures for doing their work”, and “My team seeks out and acquires information that maybe useful in developing multiple solutions to problems”. The Cronbach’s alpha for this scale was .93 (α=0.93, M= 21.46, SD= 4.79). Items regarding this scale can be found in Appendix A.

Knowledge Sharing Practices. This variable was measured with eight 5-point Likert-type

items, ranging from one (1=don’t agree at all) to five (5= agree very much), that were used in the study by Van den Hooff & Huysman (2009). Items were modified using the phrase “team

members” instead of the word “colleagues”. The scale is comprised by calculating the mean for eight items and includes statements such as “I like to be kept fully informed of what my team

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members know”, “When I need certain knowledge, I ask my team members about it”, and “When I have learned something new, I make sure my team members learn about it, too. I share information that I acquired with my colleagues”. The Cronbach’s alpha for this scale was .83 (α=0.83, M= 32.79, SD= 3.99). Items regarding this scale can be found in Appendix A.

Diversity Climate. This variable was measured with six 5-point Likert-type items,

ranging from one (1=don’t agree at all) to five (5= agree very much), that were developed by Luijters et al. (2008). Items were modified using the phrase “my team” instead of “our branch”. The scale is comprised by calculating the mean for six items and includes statements such as “In my team we think positively about cultural differences of colleagues”, “In my team we

understand and accept different cultures”, “In my team we recommend working with people with different cultural backgrounds”. The Cronbach’s alpha for this scale was .91 (α=0.91, M= 24.44, SD= 4.62). Items regarding this scale can be found in Appendix A.

Innovation Climate. This variable was measured with seven 5-point Likert-type items,

ranging from one (1=don’t agree at all) to five (5= agree very much), that were used in the study by Caldwell and O’Reilly III (2003). Items were modified using the phrase “my team” instead of “our group”. The scale is comprised by calculating the mean for seven items and includes

statements such as “Risk taking is encouraged around here”, “Management provides rewards and recognition for innovation and trying new things”, and “My team has a strong belief in the importance of hard work”. The Cronbach’s alpha for this scale was .84 (α=0.84, M= 24.40, SD= 5.28). Items regarding this scale can be found in Appendix A.

Covariates: Gender, Age, Team Tenure, Task interdependence, and Goal

interdependence. The respondents were asked to indicate their age and gender (male=0,

female=1) by two separate questionnaire items. Katz (1982), in his quantitative study of 50 R&D project groups, concluded that the longer project groups have been together, the less they

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communicated with key information sources, scanned the environment, and engaged in external communication. However, external communication is vital for innovation, as it provides teams with new information and inspiring clues (Kivimaki et al. 2000; Hülsheger et al., 2009). Since, team tenure can hinder the generation and implementation of new and useful ideas, it was decided to control for this variable. This variable was measured by questionnaire item “For how many years have you been working in your current position?” Task interdependence (TI) is found to influence behavior in heterogeneous teams (Van der Vegt & Janssen, 2003), whereas goal interdependence (GI) is found to positively correlate with innovation (Hülsheger et al., 2009). TI was measured by three items ranging from one (1=don’t agree at all) to five (5= agree very much), that were developed by Campion, Medkser, and Higgs (1993). The scale is

comprised by calculating the mean for three items and includes statements such as such as “I cannot accomplish my tasks without information or materials from other members of my team” and “Other members of my team depend on me for information or materials needed to perform their tasks”. The Cronbach’s alpha for this scale was .80 (α=0,80, M= 14.39, SD= 3.16). GI was measured by four items ranging from one (1=don’t agree at all) to five (5= agree very much), that was developed by Janssen, Van de Vliert, and Veenstra (1999). The scale is comprised by calculating the mean for four items and includes statements such as “In my team, success for one team member implies success for other team members” and “In my team, benefits for one team member involve benefits for other team members”. The Cronbach’s alpha for this scale was .82 (α=0,82, M= 11.06, SD= 2.87). Items regarding TI and GI can be found in Appendix A.

Results

In this section, first, multicollinearity and, second, the findings of correlation analysis are discussed. Then, mediation and moderation analyses were run to test the hypothesized

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relationships. Lastly, an additional mediation analysis was run based on the findings of initial analyses and a new model is proposed.

The correlation coefficient, which lies between -1 and 1, is considered to be substantial when r is above .8 or .9 (Field, 2013). There were no substantial correlations in any of the analyses conducted. Furthermore, regarding all the regression analyses tested, the VIF values were below 10 and all the tolerance values were above .2. Therefore, multicollinearity was not an issue. Moreover, since a correlation coefficient of ± .1 is a small effect, ± .3 is a medium effect, and ± .5 is a large effect (Field, 2013), it was decided not to use the control variables with a small effect (r < ± .3). This decision resulted with two control variables to be used in the analyses; GI and TI. You can find Table 1 that represents the correlation matrix in Appendix B.

Hypotheses 1, 2, 3, and 4 were tested by performing a mediation analysis using “PROCESS” software of Andrew F. Hayes (model=4). The regression model (Total Effect Model) with team innovation as dependent variable and cultural diversity as independent variable, controlling for GI and TI, is significant, F (3, 132) = 9.15, p < .001. The regression model can therefore be used to predict team innovation, 17 per cent of the variation in team innovation can be predicted on the basis of cultural diversity and the control variables (adjusted R2 = .17). Cultural diversity, b = .41, t= 2, p< .05, 95% CI [0.01, 0.82], and GI, b = .37, t= 4.44, p< .001, 95% CI [0.21, 0.54], have a significant relationship with team innovation. Thus, hypothesis 1, which stated that cultural diversity will have a positive direct effect on team innovation, is supported. On the other hand, TI does not have significant result. The results of this analysis can be found on Table 2 in Appendix B.

The regression model with KS practices as dependent variable and cultural diversity as independent variable, controlling for GI and TI, is significant, F (3, 132) = 14.36, p < .001. The regression model can therefore be used to predict KS practices within a team and 25 per cent of

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the variation in KS practices can be predicted on the basis of cultural diversity and the control variables (adjusted R2 = .25). Cultural diversity does not have significant result. Thus, hypothesis 2, which stated that cultural diversity will have a positive direct effect on KS practices, is rejected. On the other hand, GI, b = .17, t= 3.41, p <. 001, 95% CI [0.07, 0.27], and TI, b = .17, t= 3.93, p < .001, 95% CI [0.08, 0.25], have a significant relationship with KS practices. The results of this analysis can be found on Table 3 in Appendix B.

The regression model with team innovation as dependent variable and KS practices and cultural diversity as independent variables, controlling for GI and TI, is significant, F (4, 131) = 8.19, p < .001. The regression model can therefore be used to predict team innovation and 20 per cent of the variation in team innovation can be predicted on the basis of KS practices, cultural diversity, and the control variables (adjusted R2 = .20). KS practices, b = .31, t= 2.14, p < .05, 95% CI [0.02, 0.59], and GI, b = .32, t= 3.71, p < .001, 95% CI [0.15, 0.49], have a significant relationship with team innovation. Thus, hypothesis 3, which stated that KS practices will have a positive direct effect on team innovation, is supported. Cultural diversity has a marginally

significant result, b = .36, t= 1.75, p = .08, 95% CI [-0.05, 0.76], whereas TI does not have a significant result. The results of this analysis can be found on Table 4 in Appendix B.

Hypothesis 4 stated that KS practices will mediate the relationship between cultural diversity and team innovation. The results show that the indirect effect of cultural diversity on team innovation through KS practices is not significant, b = .05, BCa CI [-0.01, 0.19]. Thus, hypothesis 4 is rejected. You can find a full representation of the mediation analysis in Figure 2, in Appendix B.

Hypotheses 5 and 6 were tested by performing two moderation analyses via “PROCESS” software of Andrew F. Hayes (model=1). The regression model with KS practices as dependent variable, cultural diversity, diversity climate, and the interaction of cultural diversity with

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diversity climate as independent variables, controlling GI and TI is significant, F (5, 130) = 11.10, p < .001. The regression model predicts 31 per cent of the variation in KS practices (adjusted R2 = .31). The interaction of cultural diversity with diversity climate does not have significant result. Thus, hypothesis 5, which stated that diversity climate in a team will moderate the relationship between cultural diversity and KS practices, is rejected. Moreover, cultural diversity does not have a significant result either. On the other hand, diversity climate, b = .18, t= 2.90, p < .01, 95% CI [0.06, 0.30], GI, b = .12, t= 2.02, p < .05, 95% CI [0.00, 0.23], and TI, b = .17, t= 3.95, p < .001, 95% CI [0.09, 0.26], have a significant relationship with KS practices. The results of this analysis can be found on Table 5, in Appendix B.

The regression model with team innovation as dependent variable, KS practices, innovation climate, and the interaction of KS practices with innovation climate as independent variables, controlling for GI and TI is significant, F (5, 130) = 21.09, p < .001. The regression model predicts 44 per cent of the variation in team innovation (adjusted R2 = .44). The interaction of KS practices with innovation climate does not have a significant result. Thus, hypothesis 6, which stated that innovation climate in a team will moderate the relationship between KS practices and team innovation, is rejected. Innovation climate, b = .57, t= 6.04, p < .001, 95% CI [0.39, 0.76], and KS practices, b = .28, t= 2.45, p < .05, 95% CI [0.05, 0.50], have a significant relationship with team innovation. On the other hand, GI and TI do not have significant results. The results of this analysis can be found on Table 6, in Appendix B.

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Figure 3.

Additional Analysis: The indirect effect of diversity climate on team innovation via KS practices: The results of previously conducted analyses suggest that diversity climate has a

positive direct effect on KS practices and KS practices has a positive direct effect on team innovation. According to correlation matrix (see Appendix B), KS was significantly associated with team innovation (r = .32, p< .001) and diversity climate (r = .38, p< .001). Furthermore, diversity climate was significantly associated with team innovation, (r = .43, p< .001). Since all the correlation coefficients were above > ± .3 and statistically significant, it was decided to test whether KS practices mediate the relationship between diversity climate and team innovation.

The regression model with KS practices as dependent variable and diversity climate as independent variable, controlling for GI and TI, is significant, F (3, 132) = 19.90, p < .001. The regression model can therefore be used to predict KS practices within a team and 31 per cent of the variation in KS practices can be predicted on the basis of diversity climate and the control variables (adjusted R2 = .31). Diversity climate, b = .19, t= 3.85, p <. 001, 95% CI [0.09, 0.29],

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GI, b = .11, t= 2.17, p <. 05, 95% CI [0.01, 0.21], and TI, b = .17, t= 4.36, p <. 001, 95% CI [0.09, 0.25], have significant results. The results of this analysis can be found on Table 7 in Appendix B.

The regression model with team innovation as dependent variable and diversity climate and KS practices as independent variables, controlling for GI and TI, is significant, F (4, 131) = 11.58, p < .001. The regression model can therefore be used to predict innovativeness of a team and 26 per cent of the variation in team innovation can be predicted on the basis of diversity climate, KS practices, and the control variables (adjusted R2 = .26). Diversity climate, b = .33, t= 3.76, p < .001, 95% CI [0.15, 0.50], has a significant result whereas KS practices does not. Additionally, GI, b = .24, t= 2.78, p < .01, 95% CI [0.07, 0.40], also has a significant effect on team innovation, whereas TI does not. The results of this analysis can be found on Table 8, in Appendix B.

The regression model (Total Effect Model) with team innovation as dependent variable and diversity climate as independent variable, controlling for GI and TI, is significant, F (3, 132) = 14.97, p < .001. The regression model can therefore be used to predict team innovation and 25 per cent of the variation in team innovation can be predicted on the basis of diversity climate and the control variables (adjusted R2 = 25). Diversity climate, b = .36, t= 4.35, p< .001, 95% CI [0.19, 0.52], and GI, b = .25, t= 3.04, p< .01, 95% CI [0.09, 0.42], have a significant effect on team innovation. However, TI does not have a significant result. The results of this analysis can be found on Table 9 in Appendix B.

The results show that the indirect effect of diversity climate on team innovation through KS practices is not significant, b = .03, BCa CI [-0.03, 0.10]. Thus, mediation effect is not supported. You can find a representation of the mediation analysis in Figure 4, in Appendix B.

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Discussion

This study investigated the research question “to what extent do knowledge sharing practices, diversity climate, and innovation climate affect the innovativeness of culturally diverse teams?” Although statistical analyses failed to support many of hypothesized relationships, findings regarding the research question are notable. First, analyses revealed that the cultural diversity has a positive direct effect on team innovation and this relationship is statistically significant. This finding is in line with the literature that suggests cultural diversity is likely to increase team creativity and innovation, as people from different gender, nationality, and ethnic groups hold different attitudes and perspectives on issues (Kurtzberg & Amabile, 2010). Thus, organizations that employ a diverse workforce should truly value variety of perspectives and insights that result from cultural diversity in order to learn from and grow with them (Thomas & Ely, 1996).

Second, diversity climate had a positive direct influence on KS practices. When a team does not operate in a surrounding that is tolerant for diverse perspectives, its members with unique perspectives may be reluctant to pay the social and psychological costs necessary to share their ideas and perspectives (Mannix & Neale, 2005). Accordingly, statistical analyses conducted by this study revealed that people show more willingness to share their knowledge with co-workers in an environment, where there is openness and appreciation towards cultural diversity. Furthermore, analyses revealed that diversity climate has a positive direct effect on team

innovation. These findings indicate that, through a strong diversity climate, all employees, regardless of their cultural background, may work more efficiently with each other and in turn this may reduce the negative effects of categorization (e.g. conflicts) due to cultural differences that are often reported (Tsui et al., 1992; Hofhuis et al., 2012; Van Knippenberg et al., 2004). Put differently, it would be easier to harvest the positive effects of diversity that stem from the

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presence of different viewpoints and backgrounds, when employees feel comfortable to retain and display their cultural differences at work. Although it is not easy to create a strong diversity climate, management of organizations can benefit from cultural awareness trainings that aim to increase the understanding of employees regarding cultural differences and their possible effect in team outcomes (Cox & Blake, 1991; Maznevski, 1994).

Third, in line with the study by West and Wallace (1991), it was found that KS practices within a team have a positive direct effect on team innovation. This finding suggests that the more members of a team share their knowledge with each other, the more innovative that team will be. Therefore, since intra-team communication is something that can be influenced by the management of organizations (Van Den Hoff & Huysman, 2009), it would be beneficial to spend efforts aiming to increase the extent of KS within individual teams. This could be achieved through developing strong and trustworthy relations between the members of a team (Van Wijk et al., 2008). In turn, such relations would enhance cooperation and support knowledge sharing between team members, and thus lead to innovation.

Fourth, it was found that innovation climate has a positive direct effect on team innovation and this effect is in line with the existing literature (e.g., Anderson et al., 2014; West & Anderson, 1996). As Caldwell and O’Reilly (2003) pointed out, employees are more likely to propose new and creative solutions to issues when teams work in an environment that risk taking is both accepted and promoted and that mistakes are expected when trying new things. Consequently, management of organizations should promote such a climate that will support team innovation. While doing so, it is important to find a balance between truly supporting the members of a team about the development and the implementation of new ideas and at the same time monitoring and critically evaluating their initiatives (Hülsheger et al., 2009).

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Regarding the effect of control variables, consistent with previous research, GI is found to have a positive direct influence on team innovation (Hülsheger et al., 2009; Van Der Vegt & Janssen 2003). This finding implies that the team innovativeness will improve, as team members depend on each other to accomplish their goals. Furthermore, both GI and TI are found to positively effect KS practices. Put differently, KS practices within a team will increase, as team members depend on each other to accomplish their goals and tasks. Thus, organizations can benefit from setting common goals and tasks, instead of individual ones, in order to improve the functioning of teams. This can be achieved by providing continuous feedback and personal incentives for the accomplishment of group rather than individual goals (Hülsheger et al., 2009).

The results of this study suggest that organizational communication has a vital role to promote innovation in a culturally diverse team. First, KS practices that is a communication element is found to be effective in increasing innovativeness of a team. Second, only through internal communication, organizations can influence diversity and innovation climate measures that lead to team innovation. For instance, the way organizations communicate about cultural diversity can shape employees’ perceptions about this concept and can give an idea about how cultural diversity should be treated within the organization (Maznevski, 1994). In an

organization, where cultural diversity is valued and its positive and negative consequences are openly communicated, employees would be more successful to harvest the benefits that stem from cultural diversity while dealing with the tensions that it might lead to. Moreover, internal communication can also help to set the norms about what is expected from employees regarding being innovative. Through such a communication, organizations can encourage risk taking and trying new ways of doing things that will eventually lead to innovations. Therefore,

organizations should carefully plan and internally communicate their standpoint about how they define innovative employee behavior.

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Limitations and Future Research

Although hypothesized relationships suggested by this study were based on theory, findings did not support many of these relationships. First, statistical analyses failed to support the relationship between cultural diversity and KS practices. This finding suggests that KS practices within a team will not be hindered by cultural diversity, although it will not be supported either. Second, KS practices did not mediate the relationship between cultural

diversity and team innovation. Third, diversity climate did not moderate the relationship between cultural diversity and KS practices and innovation climate did not moderate the relationship between KS practices and team innovation. Lastly, although analyses suggested that diversity climate predicts KS practices and KS practices predict team innovation, this study failed to support the indirect effect of diversity climate on team innovation via KS practices. Thus, future research is required to look further for the relationship between these variables.

The findings of this study, of course, are subject to a number of limitations. First, measures of main variables (KS practices, diversity climate, innovation climate, and team innovation) tested in this study are based on self-report that could interfere with the results. For instance, social desirability bias, which can be described as the tendency of respondents to answer self-report questions in a way that will be viewed favorably by others, might have played a role in the way people responded to items (Bryman, 2012). Nevertheless, the size and the strength of the effects found allows for confidence in the validity of findings. Second, this study only focused on the actual cultural diversity of individual respondents’ teams. However,

someone who does not work in a highly diverse team may perceive the diversity high and in turn sensitivity towards dissimilar others may reflect on the employee’s behaviors (Milliken & Martins, 1996). Consequently, it would be beneficial to test also the effect of perceived diversity on team innovativeness in future studies.

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Third, although mediation analyses assume causality in the predicted direction, this cannot be proven using a cross-sectional study (Bryman, 2012). Future studies should benefit from longitudinal designs to overcome the issues related to causality. Additionally, in order to determine the generalizability of the effects found, the models proposed in this study should be replicated using different samples. Fourth, due to the design of this study, it was not possible to take into account possible time effects on the relationships tested in this study. As one can imagine, before a team can start benefiting from cultural diversity, it may take some time for the members of the team to understand each other’s value systems and to develop a ‘unique’

communication pattern (Kurtzberg & Amabile, 2010; Watson, Kumar, & Michaelsen, 1993). Thus, future research should also consider the effect of time on the functioning of culturally diverse teams.

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Appendix A 1. Knowledge Sharing Practices

1. I like to be kept fully informed of what my team members know. 2. When I need certain knowledge, I ask my team members about it. 3. I regularly inform my team members of what I am working on.

4. When I have learned something new, I make sure my team members learn about it too.

5. I share information that I acquired, with my team members.

6. I ask my team members about their skills when I want to learn particular skills. 7. I consider it important that my team members are aware of what I am working on. 8. When a team member of mine is good at something, I ask him/her to teach me.

2. Diversity Climate

1. In my team we think positively about cultural differences of colleagues. 2. In my team we understand and accept different cultures.

3. In my team we recommend working with people with different cultural backgrounds.

4. Differences in cultural backgrounds are discussed openly in my team.

5. In my team we take differences in traditions and habits (like religion, celebrations) into account.

6. In my team we see the advantage of differences in cultural backgrounds of employees.

3. Innovation Climate

1. Risk taking is encouraged around here.

2. Management provides rewards and recognition for innovation and trying new things.

3. My team has a strong belief in the importance of hard work.

4. Successful innovation is important for career success in this organization. 5. Management encourages people to try new things.

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7. Entrepreneurial skills are important if you are going to be successful in my team.

4. Team innovation

1. My team members often implement new ideas to improve the quality of our products and services.

2. My team gives full consideration to new and alternative methods and procedures for doing our work.

3. My team members often produce new services, methods or procedures. 4. My team seeks out and acquires information that may be useful in developing multiple solutions to problems.

5. Using skills we already possess, my team learns new ways to apply these skills to develop new products that can help attract and serve new markets.

6. Overall, my team is innovative.

5. Goal Interdependence

1. In my team, goal attainment for one team member facilitates goal attainment for other team members.

2. In my team, success for one team member implies success for other team members. 3. In my team, benefits for one team member involve benefits for other team

members.

4. In my team gain for one team member means gain for other team members.

6. Task Interdependence

1. I cannot accomplish my tasks without information or materials from other members of my team.

2. Other members of my team depend on me for information or materials needed to perform their tasks.

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Appendix B Table 1. Correlations Matrix

Cul. Div. KS Pr. Team Inn. Div. Clim. Inv.

Clim. Age Gender

Team Tnr. GI TI Cul. Div. 1.000 KS Pr. .144 1.000 Team Inn. .151 .321** 1.000 Div. Clim. .280** .382** .428** 1.000 Inv. Clim. 0.160 .235** .618** .333** 1.000 Age .162 .043 .053 .008 .204* 1.000 Gender -.054 .093 -.057 -.020 -.152 -.193* 1.000 Team Tnr. -.110 -.038 -.105 -.115 -.036 .288** -.032 1.000 GI -.043 .364** .377** .309** .349** .112 -.152 .099 1.000 TI .143 .415** .180* .109 .259** .173* -.101 -.003 .306** 1.000 Note. N=136 *p < 0.05. ** p < 0.01.

Table 2. Dependent Variable: Team Innovation – Total Effect Model b Constant 1.93*** Cultural Diversity .41* GI .37*** TI .04 Adjusted R2 .17 F 9.15*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

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Table 3. Dependent Variable: KS Practices b Constant 2.80*** Cultural Diversity .18 GI .17*** TI .17*** Adjusted R2 .25 F 14.36*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

Table 4. Dependent Variable: Team Innovation b Constant 1.07* KS Practices .31* Cultural Diversity .36 GI .32*** TI -.01 Adjusted R2 .20 F 8. 19*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

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Table 5. Dependent Variable: KS Practices

b

Constant 3.06***

Diversity Climate .18**

Cultural Diversity .04

Diversity Climate* Cultural Diversity -.06

GI .12* TI .17*** Adjusted R2 .31 F 11.10*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

Table 6. Dependent Variable: Team Innovation b

Constant 3.28***

Innovation Climate .57***

KS Practices .28*

Innovation Climate* KS Practices .05

GI .15 TI -.07 Adjusted R2 .44 F 21.09*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

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Table 7. Dependent Variable: KS Practices b Constant 2.30*** Diversity Climate .19*** GI .11* TI .17*** Adjusted R2 .31 F 19.90*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

Table 8. Dependent Variable: Team Innovation b Constant .63 Diversity Climate .33*** KS Practices .17 GI .24** TI .03 Adjusted R2 .26 F 11.58*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001.

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Table 9. Dependent Variable: Team Innovation – Total Effect Model b Constant 1.01* Diversity Climate .36*** GI .25** TI .06 Adjusted R2 .25 F 14.97*** Note. N = 136 *p < 0.05. ** p < 0.01. *** p < 0.001. Figure 2.

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