The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty

IMM-07348; No of Pages 11 Industrial Marketing Management xxx (2016) xxx–xxx

Contents lists available at ScienceDirect

Industrial Marketing Management

The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty Mumin Dayan a,⁎, Muammer Ozer b, Hanan Almazrouei a a b

United Arab Emirates University, College of Business & Economics, Department of Business Administration, United Arab Emirates City University of Hong Kong, Department of Management, Kowloon, Hong Kong

a r t i c l e

i n f o

Article history: Received 28 January 2014 Received in revised form 21 April 2016 Accepted 21 April 2016 Available online xxxx Keywords: Functional diversity Demographic diversity New product creativity Teams Project uncertainty

a b s t r a c t Earlier studies have shown inconsistency in the impact of team diversity on the effective functioning of New Product Development (NPD) teams. This inconsistency has been attributed to the insufficient amount of research on a possible complex (non-monotonic) relationship between team diversity and team performance and the possible boundary conditions of this relationship. Addressing numerous calls for future studies on these issues, we examined whether an inverted-U relationship exists between team diversity (i.e., functional and demographic) and its outcomes (i.e., new product creativity), using project uncertainty as a key moderator. The results of an empirical study with a sample of 103 new product development teams showed an inverted U-shaped functional diversity–new product creativity relationship. Moreover, the results showed that the direct relationship between functional diversity and new product creativity was stronger when project uncertainty was high as opposed to when it was low. On the other hand, the direct relationship between demographic diversity and new product creativity was weaker when project uncertainty was high as opposed to when it was low. © 2016 Elsevier Inc. All rights reserved.

1. Introduction In this paper, we focus on the relationship between the diversity of new product development teams and new product creativity. In one of the most common categorizations of team diversity, past research has primarily focused on two types of diversity, including social category diversity and informational/functional diversity (van Knippenberg, De Drue, & Homan, 2004). While research on social category diversity deals with differences on such readily identifiable attributes of team members as sex, age, and ethnicity, research on informational/functional diversity deals with their differences in less visible underlying attributes such as functional and educational background (Bantel & Jackson, 1989; Østergaard, Timmermans, & Kristinsson, 2011). The impact of team diversity on the effective functioning of new product development (NPD) teams has been extensively investigated in the product innovation literature (Andersen, Kragh, & Letti, 2013; Crawford & Di Benedetto, 2006; Dayan & Di Benedetto, 2010; Hirunyawipada, Beyerlein, & Blankson, 2010; Mohd Zaki & Othman, 2013; Suh, Bae, Zhao, Kim, & Arnold, 2010; Tsai & Hsu, 2014). However, while such prior studies recognize the influence of team diversity on new product creativity (e.g., Crawford & Di Benedetto, 2006), few

⁎ Corresponding author at: United Arab Emirates University, College of Business & Economics, Department of Business Administration, Al Ain, Po Box 15551, United Arab Emirates. E-mail addresses: [email protected] (M. Dayan), [email protected] (M. Ozer), [email protected] (H. Almazrouei).

studies provide empirical validation of how the diversity would lead to new product creativity at the NPD team level. Furthermore, this literature suggests a complex relationship between team diversity and team creativity (e.g., Dayan & Di Benedetto, 2011). More importantly, past research offers inconsistent results. For example, while several researchers (e.g. Gino, Argote, Miron-Spektor, & Todorova, 2010; Keller, 2001) have argued that diversity would be beneficial due to the broader range of knowledge and expertise brought by functionally diverse team members, others (Joshi & Roh, 2009; Van der Vegt & Bunderson, 2005) have suggested that diversity would be detrimental because people's preference for interacting and collaborating with similar rather than dissimilar participants could make communication difficult and cause conflicts and mistrust. This inconsistency in the literature has usually been attributed to the insufficient amount of research on the direct relationship between team diversity and team performance and the possible boundary conditions of this relationship. Thus, researchers have suggested that future research should investigate the direct relationship between team diversity and team performance, and the boundary conditions of this relationship (e.g., Harrison & Klein, 2007). Past research has used such moderators as temporal team leadership (Mohammed & Nadkarni, 2011), social status category (Chattopadhyay, Finn, & Ashkanasy, 2010), need for cognition (Kearney, Gebert, & Voelpel, 2009), national power distance (Van der Vegt, Van de Vliert, & Huang, 2005), and job stress (Keller, 2001). However, although meta-analyses (Bell & Berry, 2007; Stewart, 2006) have revealed it to be an important potential moderator, the role of task characteristics (e.g., project uncertainty) in

http://dx.doi.org/10.1016/j.indmarman.2016.04.016 0019-8501/© 2016 Elsevier Inc. All rights reserved.

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

2

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

the diversity–performance relationship has not been fully examined, especially given that the role of uncertain tasks in smoothing group interactions is widely recognized (Carbonell & Rodriguez-Escudero, 2013). Because the effect of diversity source on new product creativity will likely differ when the project being worked on is non-routine or uncertain and requires new ways of thinking, we test the moderating role of project uncertainty in the diversity-new product creativity relationship. Considering all the inconsistent findings and different perspectives on the diversity-performance relationship in the general teamdiversity literature and addressing the need to provide empirical validation of how the diversity would lead to new product creativity within the specific context of NPD teams, this study aims to contribute to the literature in four ways. First, following the suggestions of past research that called for diversity research taking a multi-domain perspective (Van Knippenberg et al., 2004), it analyzes the role of both social category diversity (i.e. demographic diversity) and informational/functional diversity on the diversity-new product creativity relationship. Second, it investigates if the role of project uncertainty as a moderator on this relationship would differ between these two types of diversity. Third, this study aims to advance our understanding of the relationship between team diversity and performance by considering a potential curvilinear relationship between diversity and new product creativity that would be another reason for the inconsistency. Fourth, it examines project uncertainty as a key moderator of the relationship between diversity and new product creativity, thus filling a major research gap in the current literature. 2. Conceptual background and hypotheses Team diversity is defined as differences among the participants in a team setting on a shared attribute that may lead to the view that another person is not the same as oneself (e.g., Williams & O'Reilly, 1998). Researchers have made a common distinction in the extant literature, in an effort to organize various types of diversity, ranging from age to sex and from functional background to educational background, and to understand the impact of all of these different types of diversities on performance. This distinction suggests that the most significant difference underlying diversity dimensions is between diversity on readily detectable/observable attributes—differences in, for instance, sex, age, and ethnicity—and diversity with respect to less visible attributes that are mainly job related—differences in, for instance, functional and educational background (Milliken & Martins, 1996; Tsui, Egan, & O'Reilly, 1992). The main reasoning behind this categorization is that when differences among participants are easily detectable, they predominantly evoke a response founded on biases or stereotypes. Thus, based on this categorization several researchers have argued that the impact of diversity on performance can better be understood by considering both the information/decision-making perspective, which assumes that diversity would be beneficial due to the wider range of taskrelevant resources brought by dissimilar participants, and the social categorization perspective, which assumes that diversity would be detrimental to the effective functioning of teams due to people's preference for interacting and collaborating with similar rather than dissimilar participants. Furthermore, past research proposes that while the detrimental effects of diversity should be more likely to be observed for readily detectable/observable attributes than for less visible attributes the positive effects of diversity are more related to less visible attributes (e.g. Milliken & Martins, 1996). Hence, it is argued that diversity has positive effects on performance as long as it leads to informational differences (e.g. Van Knippenberg et al., 2004). Indeed, it has been proposed that although readily detectable/observable attributes, such as demographic differences (sex, age, and ethnicity), may be associated with such informational differences (Cox, Lobel, & McLeod, 1991; Tsui & O'Reilly, 1989), less visible attributes, such as functional background, are more likely to be associated with informational differences (Pelled,

Ledford, & Mohrman, 1999). For instance,1 one may argue that while functional backgrounds also represent identity, for example, an R&D person would identify with R&D and a marketing person will identify with marketing, demographic backgrounds can also be argued to represent different knowledge, for example a younger person and an older person would have different knowledge. Although functional and demographic diversities are both related to knowledge and identity, functional knowledge represents more knowledge than identity demographic diversity represents more identity than knowledge. Indeed, past research suggests that while demographic differences could be associated with such informational differences (Cox et al., 1991; Tsui & O'Reilly, 1989), less visible attributes are more likely to be related to informational differences (Pelled et al., 1999). Consequently, we argue that the positive effects of team diversity would be more likely to occur for diversity on less visible attributes. Even though the theoretical arguments for this reasoning made in the extant literature are well grounded, the empirical findings on the proposition that the impact of diversity is conditional on diversity type (i.e., the information/decision-making perspective vs. the social categorization perspective) have been inconsistent. Past research showed that neither diversity on readily observable attributes nor diversity on job-related attributes is consistently linked to team performance. In general, past research has shown that diversity is a doubleedged sword because it may not only contribute to the rise in diverse ideas, perspectives, and knowledge that can increase new product creativity (e.g. Im & Workman, 2004, Jehn, Northcraft, & Neale, 1999), but may also have a disruptive effect on group processes and performance (for reviews, see Milliken & Martins, 1996). For instance, while Cox et al. (1991) discovered a positive effect of diversity with regard to readily observable attributes (i.e. demographic differences) on cooperative behaviors in teams, Simons, Pelled, and Smith (1999) found a negative effect of job-related diversity in top management teams on performance. Given this inconsistent pattern of results on the diversity– performance relationship, recent research has begun to investigate contextual moderators and mediators to understand how and when diversity might lead to better performance. In this recent research, the role of temporal team leadership (Mohammed & Nadkarni, 2011), social status category (Chattopadhyay et al., 2010), need for cognition (Kearney et al., 2009), national power distance (Van der Vegt et al., 2005), and job stress (Keller, 2001) in the diversity–performance relationship has been widely explored. However, although meta-analyses (Bell & Berry, 2007; Stewart, 2006) have revealed that diversity is more likely to lead to better performance in a non-routine task environment, the role of task characteristics (e.g., project uncertainty) in the diversity–performance relationship has not been carefully examined. In this study, we propose that project uncertainty may influence— that is, act as a moderator with respect to—whether either functional diversity or demographic diversity or both have beneficial or detrimental effects on new product creativity. Our argument on this possible relationship is based on the assumption that diversity source may provide a basis for improved group effectiveness and performance when the project being worked on is non-routine or uncertain and requires new ways of thinking (Kearney et al., 2009). More specifically, past research on the information/decision-making perspective assumes that functional diversity, defined as the extent to which team members differ in their functional backgrounds, would have a positive impact on new product creativity when the project is complex and requires creative problem solving (Amabile, 1988). In the extant literature, several underlying assumptions have been made on the positive moderating effect of task complexity on the functional diversity-new product creativity relationship. For instance, Carbonell and Rodriguez-Escudero (2013) argue that unlike certain tasks, uncertain tasks (e.g., radical product innovation) oblige more elaborate information processing

1

We would like to thank an anonymous reviewer for this example.

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

during the NPD process, and functionally diverse team members would find such tasks desirable and challenging since they have a broader pool of resources and nonoverlapping expertise, from which to draw in making decisions and taking actions. On the other hand, with regard to the moderating effect of task complexity on the demographic diversitynew product creativity relationship, past research on the social categorization perspective assumes that the impact of task uncertainty on this relationship would be detrimental. According to this perspective, team members who have demographic similarities (e.g. the same gender or ethnicity) assume that their mindsets are also similar and, are consequently, likely to be more attracted to each other than to team members who are demographically different from them (e.g. Tsui & O'Reilly, 1989). Thus, demographically diverse team members may perceive that due to lack of similarities individual members may center on subgroup identities and desire to have restricted communications, which are likely to harm team cohesion and creativity required for uncertain tasks (Chiu & Staples, 2013). Another reason for the above-mentioned inconsistency is attributed to the differences in defining performance indicators and lack of research on the diversity of teams for creative outcomes (Williams & O'Reilly, 1998). As a result, we study new product creativity as a performance indicator of the NPD teams. Moreover, in most of the past studies, the relationship between diversity and performance has been investigated as a simple direct (monotonic) relationship, which assumes that increased diversity leads to equivalent increases or decreases in outcome variables. 2.1. The impact of informational/functional diversity on new product creativity According to the information/decision-making perspective (Williams & O'Reilly, 1998), functional diversity is suggested to be beneficial to new product performance in general, and to creativity in new product/service offerings in particular (Østergaard et al., 2011). This perspective adopts the assumption of bounded rationality and stresses the benefits of a wider range of task-relevant resources (e.g., knowledge, skills, and perspectives) brought by dissimilar members during the new product development process (e.g. Argote & Greve, 2007). More specifically, this perspective assumes that the use of functionally diverse teams can result in the development of creative solutions to rapidly changing technology and market problems (e.g., changes in customer demands), since teams with a range of ideas and perspectives are likely to restructure complex problems and produce more alternatives to solve those problems in a creative way (Chen & Kaufmann, 2008; Griffiths-Hemans & Grover, 2006). In line with this perspective, functionally diverse NPD teams with assorted ideas and perspectives can easily recognize new profitable opportunities and deliver better and creative products/ services to customers (Griffiths-Hemans & Grover, 2006; Schulze & Hoegl, 2006). Olson, Walker, and Ruekert (1995), for instance, found that functional diversity in NPD teams improved effectiveness and timeliness when the product being developed was new and creative, due to the benefit of the increased cross-functional exchange of ideas and information provided by functional diversity. In contrast, participants in less functionally diverse teams are inclined to think similarly (i.e., silo thinking) and may not produce novel alternatives to problems during the NPD process. Dayan and Di Benedetto (2010), for instance, argue that less functionally diverse teams may not avoid similar thought patterns (silo thinking) that make them less effective in the decision-making process. Indeed, in the case of turbulent conditions when NPD teams may encounter complex and non-routine problems, more functionally diverse teams, unlike less functionally diverse teams, would likely benefit from a varied range of opinions projected by diversified team members to come up with novel ideas and solutions. In this regard, functional diversity is crucial for bringing together various individual cognitive ideas and perspectives to resolve complex

3

problems during the NPD process (Bantel & Jackson, 1989; Olson et al., 1995). Therefore, from the information/decision-making perspective, more functionally diverse NPD teams are likely to possess knowledge and experience with wide-ranging ideas and perspectives, and are accordingly better able to spawn creative solutions for problems, identify new opportunities, and subsequently develop novel and creative products/services that contribute to the achievement of competitive advantages (Bunderson & Sutcliffe, 2002; Cannella, Park, & Lee, 2008; Pelled et al., 1999). On the other hand, an increased functional diversity of NPD teams is likely to lead to deficiencies during the decision-making process. In fact, past research revealed that common deficiencies that functional diversity may cause during the team process are mainly related to teamwork quality, such as communication, coordination, effort, and cohesion (Dayan & Di Benedetto, 2009; Hirunyawipada et al., 2010; Horwitz & Horwitz, 2007; Keller, 2001). Indeed, the literature indicates that an increased functional diversity may be time-consuming and may make it difficult for team members to reach a consensus in the decisionmaking process (Horwitz & Horwitz, 2007). More specifically, more functionally diverse teams would have communication and coordination problems, and would consequently become less effective in developing creative solutions to problems (Keller, 2001). When the level of functional diversity in NPD teams goes beyond a certain point, further increases in the level of functional diversity may not be beneficial but harmful for the effective functioning of NPD teams (Cannella et al., 2008; Harrison & Sin, 2005). Moreover, past research argue that functional diversity of the members of a team will determine the scope of information to be used by the team (Dahlin, Weingart, & Hinds, 2005; Stasser & Titus, 1985; Wittenbaum & Stasser, 1996). Scope will be influenced by functional diversity in that a NPD team whose members are from within the same or similar new product function (e.g. only marketing and or management) will be more likely to have noteworthy overlaps in what they know than will a NPD team whose members are from within the diverse functions (e.g. marketing, manufacturing, and R&D). For instance, a NPD team whose members are coming from marketing function will utilize a narrower scope of information on a task than a NPD team with the same task composed of a marketing specialist, an engineer, and an accountant. Hence, it is expected that NPD teams composed of members with diverse functions will use a wider scope of information than NPD teams composed of members with similar functions. However, there would be a saturation point above which an increase in diversity may not increase the use of information among team members. In moderately diverse teams information is usually shared at least one person and that is mostly taken into account by the team (Wittenbaum & Stasser, 1996). On the other hand, in highly diverse teams there would not be so much overlap in shared information due to the lower level of motivation to share information among team members (Bunderson & Sutcliffe, 2002), thus there would be limited unique information to be utilized by the team. In essence, functional diversity is essential for an effective teamwork and cross-functional teams are commonly used in new product development processes (Bao, Sheng, & Zhou, 2012; Crawford & Di Benedetto, 2006, p. 303). As discussed above, according to the information/decision-making perspective, unlike less functionally diverse NPD teams, more functionally diverse ones possess required knowledge and experience to develop creative products. However, the more functionally diverse the NPD team is, the less likely new product will be creative due to various deficiencies (e.g., ineffective communication, poor teamwork quality, lack of overlap in shared information) that functional diversity will cause. Taking all of these considerations into account, we propose that the impact of functional diversity on new product creativity is curvilinear: the increase of functional team diversity to a certain level would enhance new product creativity; however, new product creativity would decrease as functional diversity increases after that level. Therefore, we expect that functional diversity would

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

4

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

have a curvilinear effect on new product creativity, which will first increase and then decrease as functional diversity increases.

2.3. The moderating role of project uncertainty on the team diversity–new product creativity relationship

Hypothesis 1. The relationship between functional diversity and new product creativity is non-linear (“∩” shaped).

Project uncertainty is conceptualized as a contextual condition in which it is not possible to predict the success rate of a project due to the difference between the amount of information already possessed by the organization and the amount of information required to complete the project (Perminova, Gustafsson, & Wikstrom, 2008; Tatikonda & Rosenthal, 2000). This definition implies that project uncertainty would have either a beneficial or a detrimental impact on project performance depending on how successfully the organization can generate the missing knowledge required to complete the project. Indeed, a high level of project uncertainty indicates high instability in and ambiguity of the precise methods and procedures for successfully completing the project (Tatikonda & Rosenthal, 2000). Hence, the quality of project outcome, the level of new product creativity in our case, would be affected by the nature of the project as characterized by its uncertainty (Land, Engelen, & Brettel, 2012; Molina-Castillo, Jimenez-Jimenez, & Munuera-Aleman, 2011). We argue that there seems to be a moderating impact of project uncertainty on the diversity–new product creativity relationship. More specifically, we expect that the moderating effect of project uncertainty would be positive for the functional diversity–new product creativity relationship, but would be negative for the demographic diversity–new product creativity relationship, as we explain below: With regard to functional diversity, even though the impact of project uncertainty on the functional diversity–new product creativity relationship has not been extensively studied, there is some evidence in support of this proposition in the extent literature. Jehn et al. (1999), for instance, found that informational diversity was positively related to performance when task complexity was high rather than low. Moreover, the results of a meta-analysis (e.g., Bowers, Pharmer, & Salas, 2000) support a similar argument that more functionally diverse groups would outperform less diverse ones on difficult tasks, whereas less diverse groups would in fact outperform more diverse ones on more simple tasks. The primary reasoning behind the proposition that project uncertainty would play a major moderating role in the functional diversity– new product creativity relationship is that issues of team configuration, particularly the degree of diversity among team members, become even more prominent when the task is complex and requires creative problem solving (Amabile, 1988). Consequently, project uncertainty would be expected to lead to more comprehensive and creative information processing, problem solving, and decision-making. This expectation, in fact, gives rise to the proposition that team functional diversity would lead to product creativity to the extent that creative outcomes require creative and novel idea generation and high-quality decision-making during the NPD process. That is, the performance of NPD teams would benefit from functional diversity in uncertain projects that involve complex and non-routine information-processing and decision-making tasks, where performance is mainly defined in terms of the creativity and novelty of teams' outcomes, such as those facing NPD teams. In fact, past research argues that uncertain tasks would require more elaborate information processing in the earlier stages of the NPD process, setting the stage for the potentially positive effects of the variety of information and perspectives raised by diverse NPD teams (Carbonell & Rodriguez-Escudero, 2013). On the other hand, there seems to be no reason to anticipate that non-complex tasks, such as incremental product innovation, would normally encourage extensive information processing. In fact, the decision-making process for routine tasks may not necessarily be thorough and creative. Thus, project uncertainty should be a key moderator in the team functional diversity–new product creativity relationship. Moreover, past research also argues that project uncertainty would stimulate the need for motivation that helps release the creative potential inherent in functionally diverse teams (Cacioppo, Petty, Feinstein, &

2.2. The impact of social category diversity on new product creativity We base our theory on the social categorization perspective that proposes that the demographic diversity–performance relationship will be positive (Pettigrew, 1998). According to this theory, demographic diversity makes the differences between the social sub-groups and their ideas more salient compared to demographically homogenous groups where individuals tend to be more salient. An increased realization of the differences across different social sub-groups tend to stimulate team members to search for novel solutions to work-related problems, question traditional procedures and methods, benefit from the actions of others, and interact cooperatively with people of a higher or lower status. These competences result in an innovative ambience and in creative interaction processes through which team members recognize, integrate, and benefit from their different demographic backgrounds. There are only a few studies about the positive effects of demographic diversity (e.g., ethnic or racial diversity) on team-level cognitive performance. Cox et al. (1991), for instance, found that ethnically diverse groups came up with more cooperative alternatives than allAnglo groups in a two-party prisoner's dilemma game, suggesting that Anglos seem to be individualistic in a group setting, whereas members of other racial and ethnic groups seem to be more collectivist (Early, 1989). Similarly, McLeod and Lobel (1992) proved that heterogeneous teams with respect to ethnic background generated better-quality ideas in a brainstorming assignment than did more homogeneous groups. However, we suggest that as the demographic diversity in the NPD teams increases beyond a certain threshold, the creativity will start to decrease, as people tend to pay more attention to other people who have the same demographic characteristics and want to spend time with them (Condon & Crano, 1988). This is because the more demographically diverse a team is with respect to age, gender, and ethnicity, the more likely it is that dissimilar members will change roles and be absent. Jackson et al. (1991), for instance, argue that demographic diversity would lead to an uncomfortable situation for all members of a team, causing a lower level of integration and harmony within the team and a higher possibility of turnover. Similarly, Wharton and Baron (1987) found that members of either mainly male or mainly female groups were more pleased than were members of varied-sex groups, suggesting that people have more positive attitudes in more homogeneous work groups in terms of sex. These and related studies (e.g., Barsade, Ward, Turner, & Sonnenfeld, 2000) suggest that people are usually highly motivated and more collaborative when they are not demographically dissimilar to others at their workplace. In fact, in one of the rare empirical studies in the NPD literature, Dayan and Di Benedetto (2010) found an inverted-U relationship between demographic diversity and interpersonal trust in NPD teams. We expect a similar relationship, a non-linear relationship, between demographic diversity and new product creativity as well. Taking all of these considerations into account, we hypothesize an inverted-U relationship between demographic diversity and new product creativity: increasing demographic diversity leads to new product creativity up to a certain point. However, very high levels of demographic diversity may have a detrimental effect on new product creativity. Hypothesis 2. The relationship between social category diversity and new product creativity is non-linear (“∩” shaped).

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

Jarvis, 1996). We posit that high project uncertainty encourages teams to actively seek out and thoroughly process information that is beneficial for creativity; low project uncertainty, on the other hand, may encourage teams to rely on only simple cues, gut feelings, and heuristic judgments that would be harmful for creativity. In support of this argument, past research revealed that task uncertainty led team members to elaborately and persuasively participate in team discussions to come up with novel and creative ideas (Dayan & Di Benedetto, 2011). Therefore, teams should benefit from such constructive contributions primarily when they are related to special knowledge and expertise, as it is usually the case in highly diverse NPD teams. On the other hand, teams benefit to a lesser extent when these contributions are mainly related to routine practices and common knowledge shared by all team members, which is more likely to be the case in less rather than more functionally diverse NPD teams. Furthermore, a high level of project uncertainty offers diverse teams a cognitively challenging task that usually enjoyable and is an opportunity for the team members to explore new ways of thinking and being creative about complex decision problems. Thus, a high level of project uncertainty may stimulate collective team identification that refers to how team members consider team goals as their own and feel “psychologically intertwined with the group's fate” (Mael & Ashforth, 1995, p. 310). Conversely, members of less functionally diverse teams may find it undesirable to work on such challenging tasks, since they lack the knowledge and experience to complete them successfully. Past research also argues that because of the potential positive impact of project uncertainty on collective team identification, project uncertainty lessens the possibility of adverse categorization processes that harm collective team identification and team functioning (Randel & Jaussi, 2003). With regard to demographic diversity, according to the faultline model (e.g., Thatcher & Patel, 2012) an increased level of demographic diversity might have a detrimental effect on group performance, because group members may perceive that they lack the similarities required for effective group performance (Chiu & Staples, 2013; Lau & Murnighan, 2005). The model suggests that if group members fall into two distinct subgroups based on demographic characteristics (e.g., young females and old males), individual members of a diverse work group may focus on subgroup identities rather than entiregroup identities and would prefer to have direct restricted communications and even show an open bias toward others who are not in their own subgroup (Larkey, 1996). Moreover, individuals sharing similar demographic characteristics might place high trust on each other and evaluate their subgroup's members favorably (Kramer, 1999; Phillips, Mannix, Neale, & Gruenfeld, 2004). Lau and Murnighan (2005) have argued that such isolated communication and bias evaluation adversely affect the psychological well-being of a group and its performance. Isolated communication within subgroups would resume to make contributions to group performance, especially if group members recognize the difference between their subgroup's performance and out-group's performance (e.g., Gibson & Vermeulen, 2003). However, interactions between sub-groups may interfere if the task is non-routine because the contribution of group members to group process and performance may be invisible (Lau & Murnighan, 2005). Thus, any constructive critique made by subgroups on the task would be perceived negatively by an outgroup team member (e.g., Sherif & Sherif, 1953). They also argue that if the task is non-routine, the detrimental effect of demographic diversity could be stronger. This effect may be seen in new product teams as well (Brewer, 1995; Dayan & Di Benedetto, 2010). New product team members sharing similar demographic characteristics may inherently trust each other more than members of the “outgroup” due simply to those shared similarities, or due to higher perceived levels of trust and cooperativeness. In doing so, for instance, Akgun, Byrne, Keskin, Lynn, and Imamoglu (2005) argue that uncertain tasks call for more cooperation and coordination between team members. Moreover, if the task is uncertain, teams need to be involved in more learning activities among themselves to be able to complete the

5

task. But different identities in a new product development team would create conflicts or lack of mutual trust and cooperativeness that hurts effective communication among team members. This would be worse when task uncertainty is high since the non-routine information processing and broad search means more chance of disagreement and conflicts among the team members. As a result, we propose that: Hypothesis 3. The direct functional diversity–new product creativity relationship will be moderated by project uncertainty such that it will be stronger when project uncertainty is high as opposed to when it is low. Hypothesis 4. The direct demographic diversity–new product creativity relationship will be moderated by project uncertainty such that it will be stronger when project uncertainty is low as opposed to when it is high.

3. Method 3.1. Procedure and participants The sampling frame was a list of 253 product/service manufacturing firms in an industrial zone of Ankara, Turkey, which were identified by the Ankara Chamber of Commerce. Firms reporting that they had not introduced new products within the previous two years were eliminated from the sampling frame. The overall sample after this elimination step was 187. Of the eligible sample, 103 firms (55%) responded. Of the 103 responding firms, 34 firms (33%) had up to 99 employees, 27 firms (26.21%) had 100–199 employees, 25 firms (24.27%) had 200–299 employees, and 17 firms (16.5%) had N300 employees. The innovations were primary industrial materials (36.3%), industrial services (15.6%), consumer products (26.5%), and consumer services (21.6%). (Type of innovation was not a significant control variable.) Multi-item scales, which were adapted from prior studies for the measurement of constructs, were used to test our hypotheses. Items were first translated into Turkish by a research assistant, who is a native Turkish speaker and fluent in English, and then back translated into English by the first author, who is also a native Turkish speaker and fluent in English, using a parallel translation method; the two translators then jointly reconciled all differences. The final version of the Turkish questionnaire was then pre-tested by five people working in the industry and involved in at least one NPD project. The questionnaires were distributed and collected by three research assistants who were enrolled in different graduate/ postgraduate programs in business in Ankara. We used the key informant methodology and asked the product or project managers, who were knowledgeable about the NPD activities in the company, to complete the survey in order to ensure content validity. Moreover, they tend to have a bigger-picture view of NPD projects than do other team members, a broader view of each member's behaviors, and are expected to provide more reliable and objective data (Akgun, Byrne, Keskin, & Lynn, 2006). It should be also noted that the use of product or project managers as respondents is a common practice in product innovation research (e.g. CarlssonWall & Kraus, 2015; Tsai & Hsu, 2014). The survey focused on the new product development teams in the company and the diversity of those teams in general as well as the creativity of the new products that they developed. 3.2. Measures New product creativity is defined as “the degree to which a new product is novel and its introduction changes marketing thinking and practice” (Moorman & Miner, 1997, p. 94). New product creativity was measured using a seven-item scale that was adapted from Moorman and Miner (1997). The scale ranged from 1 (strongly disagree) to 7

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

6

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

(strongly agree). A sample item was “Challenged existing ideas for this category.” All seven items were loaded on one factor related to new product creativity (Cronbach's Alpha = 0.80). Both demographic diversity and functional diversity were measured by the scales developed by Dayan and Di Benedetto (2010), which were an adaptation from Colquitt, Noe, and Jackson (2002) and Brown and Eisenhardt (1995), respectively. The scale for demographic diversity encompasses commonly cited demographic characteristics of team members, such as age, ethnicity, and gender. Respondents were asked to rate the diversity of the team on these characteristics, with a scale ranging from 1 (strongly disagree) to 7 (strongly agree). The diversity index was created by averaging across those three ratings to form a global measure of demographic diversity. This index ranged from 1 to 7, with 7 representing the highest level of demographic diversity and 1 representing the lowest. Functional diversity was measured as the number of functional areas (e.g. Marketing, R&D, and Manufacturing) represented in the team, whose members were fully involved in the project rather than being ad hoc specialists or consultants who were engaged in the project for only a limited time. This is a commonly used scale in NPD research (e.g. Dayan, Elbanna, & Di Benedetto, 2012). Project uncertainty was measured by the scale developed by Dayan and Elbanna (2011) and was also used by Dayan et al. (2012). We measured project uncertainty with a six-item scale. A sample item was “to what extent were the goals of this project clear for the participants.” All six items were loaded on one factor related to new product creativity (Cronbach's Alpha = 0.87). This scale ranged from 1 (strongly agree) to 7 (strongly disagree), a high score on this scale indicates a high level of project uncertainty, while a low score indicates a low level of project uncertainty. Team size (number of persons in the NPD teams) was used as a control variable based on past research (Dayan & Di Benedetto, 2011; Dayan & Elbanna, 2011). 4. Results Table 1 presents the means, standard deviations, and correlations among the variables. As shown in the table, both functional diversity (r = 0.68, p b 0.01) and demographic diversity (r = 0.55, p b 0.01) were positively related to new product creativity. New product creativity was significantly related to project uncertainty (r = 0.44, p b 0.01). We assessed the discriminant and convergent validities by comparing the average amount of variance (AVE) for which a construct accounts in its own indicators with the amount of variance that the construct shares with other constructs (Fornell & Larcker, 1981). The AVE statistics for new product creativity and project uncertainty were 0.70 and 0.67, respectively. On the other hand, the inter-correlation between these two latent variables was 0.44. These results confirm the discriminant validity of the measures. Fornell and Larcker (1981) suggest that AVE scores can also be used as an index of convergent validity. Because the AVE scores were generally higher than the standard of 0.50, the results indicated sufficient evidence of convergent validity for the measures.

Table 1 Means, standard deviations and correlations among variables. Variable

Mean

SD

1

1. New product creativity 2. Functional diversity 3. Demographic diversity 4. Project uncertainty 5. Size

4.74 5.13 4.87 4.60 5.57

1.03 1.32 1.23 1.13 1.87

– 0.66⁎⁎⁎ 0.55⁎⁎⁎ 0.44⁎⁎⁎

Notes: n = 103 teams. ⁎ p b 0.10. ⁎⁎ p b 0.05. ⁎⁎⁎ p b 0.01.

0.04

2

3

4

5

– 0.66⁎⁎⁎ 0.32⁎⁎⁎ −0.08⁎⁎

– 0.38⁎⁎⁎ 0.09⁎

– 0.16

–

We further assessed the discriminant and convergent validities by using a confirmatory factor analysis and found consistent results. Since only a single item was used to measure both functional diversity and demographic diversity variables, they were excluded from our confirmatory factor analysis. A confirmatory factor analysis that covered the outcome variable (new product creativity) and the moderator (project uncertainty) suggested that the model fits the data well (χ2 (64) = 130.073; p b 0.05; χ2/df = 2.032; CFI = 0.90; IFI = 0.91). It also showed that all of the factor loadings were significant, with the lowest z value 8.13 (p b 0.01). Taken together, all these results confirm the discriminant and convergent validities of our constructs. Furthermore, as can be seen in Table 1, the relatively low to moderate correlations provided further evidence of discriminant validity. Examination of the correlation matrix also indicates no multicollinearity among the variables. The inter-correlations among the central variables of the study ranged from 0.32 to 0.68, which is well below the 0.80 value suggested by Hair, Anderson, Tatham, and Black (1995). Skewness ranged from − 1.03 to 0.54 and kurtosis ranged from − 1.17 to 0.15. These results indicate that the variables were well below the benchmark levels for these indices (skewness of 2 and kurtosis of 5, as suggested by Ghiselli, Campbell, & Zedeck, 1981). Furthermore, for all models, the variance inflation factors' (VIF) values were considerably lower than the upper limit of 10 (range from 1.54 to 4.30). Thus, we can safely conclude that multicollinearity was not a threat to the validity of our regression models. We used a hierarchical multiple regression analysis to assess the impacts of functional and demographic diversities on new product creativity using project uncertainty as a moderating factor. Following the suggestions of Cohen et al. (2003) and Pedhazur (1997), we build our hierarchical models from the most basic (Model 1) to the most complex one (Model 5). These authors also suggest that curvilinear models are extremely sensitive to multicullinearity and individual outliers and as a result models need to be checked accordingly. Following the procedures outlined in Cohen et al. (2003) and Pedhazur (1997), we centered the independent variable and deleted the outliers with z N 2.5. Both Cohen et al. (2003, p. 211) and Pedhazur (1997, p. 527) also suggest to use the final model (Model 5) to test hypotheses because it is theoretically the most comprehensive model. As a result, we use the highestlevel model (Model 5) to test our hypotheses as we discuss below: As shown in Model 5 in Table 2, the coefficient associated with the linear functional diversity and quadratic functional diversity terms was (β = 0.57, p b 0.01) and (β = − 0.23, p b 0.05), respectively. These results suggest that there is a generally positive relationship between functional diversity and new product creativity, but that this positive relationship diminishes as functional diversity increases. As a result, Hypothesis 1 was supported. The table also shows that while the coefficient for linear demographic diversity was not significant (β = 0.07, ns.), the coefficient associated with the quadratic demographic diversity term was positive and significant (β = 0.19, p b 0.05). These results suggest that while there is no linear relationship between demographic diversity and new product creativity, there is a straight U-shaped relationship between the two, indicating that new product creativity decreases at low levels of demographic diversity, but starts to increase as demographic diversity increases. This is just the opposite of what Hypothesis 2 predicted, which is an inverted U-shaped relationship between the two. Thus, Hypothesis 2 was rejected. Fig. 1 shows the non-linear relationship between team diversity (functional and demographic) and new product creativity. We hypothesized that project uncertainty would positively moderate the functional diversity–new product creativity relationship (Hypothesis 3) and negatively moderate the demographic diversity– new product creativity relationship (Hypothesis 4). The coefficient term was positive and statistically significant for the functional diversity–new product creativity relationship (β = 0.29, p b 0.01). The coefficient term was also statistically significant but negative for the demographic diversity–new product creativity relation (β = − 0.40,

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

7

Table 2 The results of regression analysis. Predictors

Size Functional diversity (FD) FD-squared Demographic diversity (DD) DD-squared Project uncertainty (PU) FD ∗ PU DD ∗ PU R-square Adjusted R-square F-value Incremental R-square F-value

Model 1

Model 2

Model 3

Model 4

Model 5

VIF

Beta

SE

t-value

Beta

SE

t-value

Beta

SE

t-value

Beta

SE

t-value

Beta

SE

t-value

0.04

0.47

0.39

0.03 0.50

0.35 0.09

0.36 5.18⁎⁎⁎

0.22

0.10

2.19⁎⁎

0.03 0.39 −0.29 0.18 0.24

0.36 0.08 0.05 0.09 0.04

0.33 3.32⁎⁎⁎ −2.43⁎⁎ 1.93⁎ 2.14⁎⁎

0.02 0.33 −0.21 0.11 0.22 0.25

0.30 0.09 0.04 0.08 0.05 0.07

0.18 3.01⁎⁎⁎ −2.03⁎⁎ 1.13 2.05⁎⁎ 2.43⁎⁎

0.03 0.57 −0.23 0.07 0.19 0.22 0.29 −0.40 0.66 0.63 14.41⁎⁎⁎ 0.08 8.11⁎⁎⁎

0.34 0.08 0.04 0.09 0.05 0.08 0.07 0.08

0.23 5.30⁎⁎⁎ −2.32⁎⁎ 0.31 2.11⁎⁎ 2.46⁎⁎ 2.83⁎⁎⁎ −4.02⁎⁎⁎

0.002 0.008 0.16

0.43 0.43 9.91⁎⁎⁎ 0.43 14.45⁎⁎⁎

0.50 0.48 11.74⁎⁎⁎ 0.05 6.23⁎

0.57 0.55 13.15⁎⁎⁎ 0.07 7.23⁎⁎

1.24 2.22 1.96 2.28 1.62 1.39 2.30 2.73

⁎ p b 0.10. ⁎⁎ p b 0.05. ⁎⁎⁎ p b 0.01.

Our study extends extant research about diversity in teams in several ways. First, noting the calls of past research (e.g., Van Knippenberg et al., 2004) to explore and analyze the role of diversity types (social category diversity and informational/functional diversity) in new product creativity, we provided a theoretical foundation and empirical support for our claim that diversity in teams is a predominantly important variable in developing creative products and services. Second, our study contributes to the diversity literature by showing that social category diversity and informational/functional diversity do not operate similarly. In doing so, this study has extended theory about these two types of diversity to the domain of team performance within the context of NPD teams by showing that while there was an inverted U-shaped relationship between functional diversity and new product creativity there was a U-shaped relationship between demographic diversity and new product creativity.

Third, the findings presented here enrich our current understanding of functional diversity in NPD teams and provide an empirical support for the theoretical assumption in the literature regarding improved effectiveness of diverse teams up to a certain point followed by a reduction in their effectiveness as the effects of diversity are felt (Cannella et al., 2008; Dahlin et al., 2005; Harrison & Sin, 2005). Our results showed that functional diversity has a curvilinear effect on new product creativity, which first increases and then decreases as functional diversity increases. Functional diversity is concerned more with the differences in knowledge held by team members than member identity. This can result in team members identifying more with their function rather than the group as their historical experience is more related to their area of expertise that they have taken with them from project to project, giving them more loyalty to their profession. Therefore, teams composed of members with broad experiences will have a lower tendency to suffer from biases, making it more likely that they will appreciate the implications of their ideas for the functional areas represented by other team members. Alternatively, it would be expected that team members' functions that are based on narrow knowledge areas at the expense of a wider picture might make it difficult for the team members to exchange knowledge. As this research has suggested, it is reasonable to expect that this could increase the likelihood of conflict between group members, thus reducing group effectiveness. Indeed, individuals with specialist knowledge from different functional backgrounds who identify with only their own narrow area of expertise may be less likely to interact with other members from different

Fig. 1. Curvilinear relationship between diversity and new product creativity.

Fig. 2. The moderating role of project uncertainty in the relationship between functional team diversity and new product creativity.

p b 0.01). Thus, both Hypotheses 3 and 4 were supported. Fig. 2 suggests that the functional diversity–new product creativity relationship is stronger when project uncertainty is high as opposed to when it is low. Fig. 3, on the other hand, suggests that the demographic diversity–new product creativity relationship is weaker when project uncertainty is high as opposed to when it is low. Moreover, team size did not show a significant relationship with new product creativity (β = 0.03, ns.). 5. Discussion

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

8

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

Fig. 3. The moderating role of project uncertainty in the relationship between demographic team diversity and new product creativity.

functional backgrounds, believing that others may not understand their point of view (Bunderson & Sutcliffe, 2002). Our results pertaining to the curvilinear relationship between functional diversity and new product creativity have implications for teams tasked with creating new products, as team members with more diverse knowledge will cooperate to facilitate new product creation, although only up to a point. Past this point functional diversity is likely to reduce the probability of successful innovative thinking in teams. This diversity best affected the consideration of information when the diversity of team membership was at low to moderate levels. Beyond this point, too great a degree of diversity increased the breadth of information considered, but reduced the quality of the analysis of that information. Fourth, our results offer an interesting contribution to the current theory on demographic diversity. Results support the curvilinear effect of social category (demographic) diversity on new product creativity, but the direction was not consistent with our theoretical expectations. They showed that there was a U-shaped relationship between demographic diversity and new product creativity, as opposed to an inverted U-shaped relationship between the two as we earlier predicted. This means that making some minor cosmetic changes in the composition of an NPD team (e.g., adding one or two female team members to a male-dominated team) is in fact more detrimental than helpful. If such a team is to be successful, it should be totally diverse with regard to the demographic characteristics of the team members. These results suggest that the relationship between demographic diversity and creativity is more complex than that captured by rubrics measuring the direct relationship. More specifically, the results suggest that moderate level of demographic diversity in NPD teams may not succeed in a condition requiring effective communication and interactive behavior in order to develop creative products. As demographic diversity approaches a moderate level, its positive effects may turn to be negative for creativity. It is likely that as heterogeneity in teams reaches moderate levels, social comparison and categorization processes associated with social identity theory may be more likely to occur. Past research argues that these processes tend to lead such individual behaviors as compliance with the norms of one's group and discrimination against out-groups (e.g. Tajfel & Turner, 1985, Tsui et al., 1992). Thus, cognitive biases and communication problems may increase in NPD teams with moderate levels of demographic diversity and that lead to the problems in cooperation and increased conflict that will be harmful for creativity. While moderate levels of demographic heterogeneity may create some difficulties for effective interactions in NPD teams high levels of heterogeneity could actually weaken these difficulties because team members will be more evenly dispersed demographically and in-group/out-group identities will be reduced (Alexander, Nuchols, Bloom, & Lee, 1995). In NPD teams with high levels of demographic heterogeneity, interaction and communication would be more likely to involve members of

different racial/gender groups. Thus, our results suggest that social comparison and categorization processes that are harmful for effective communication and creativity will be less likely to occur in NPD teams that are less or highly diversified in terms of demographic characteristics. Our results also provide empirical support for the impact of diversity on new product creativity being contingent on the project's uncertainty and type of diversity. For functional diversity, when project uncertainty is low, where the project relies on established bodies of knowledge, and there is a clearly defined way to complete major project tasks, the impact of functional diversity on new product creativity will be less; however, when project uncertainty is high, where team members' work is non-routine, or where the monotony of the elements of the project tasks is low, this impact will be positive and stronger. On the other hand, for demographic diversity, when project uncertainty is low, the impact of demographic diversity on new product creativity will be less; however, when project uncertainty is high, this impact will be negative and stronger. Demographic diversity relates to the differences in identity that each individual brings to the group and relates more to each member's individual identity rather than the knowledge they bring. Different identities among group members, whether they are functional or demographic, can introduce conflict or reduce the level of trust between team members. This can have a detrimental effect on interpersonal communication among team members. This is a critical point as effective communication is of high importance when related to NPD. When task uncertainty is high the effect of poor communication takes on a greater significance, as the non-routine nature of the information involved requires a greater degree of clarity and understanding. Where these are not present the risk of disagreement increases, which also increases the chance of conflict that will have a detrimental impact on NPD creativity. Fifth, although it has been well argued in the literature that both functional diversity and demographic diversity may have a possible effect on NPD team performance (Bantel & Jackson, 1989; Olson et al., 1995), our study identifies a moderator, project uncertainty, between diversity and new product creativity. The results of our study help reconcile opposing conceptual mechanisms in relation to the impact of diversity on creativity in teams, as well as to explain the boundary conditions for existing temporal theories about the interplay between diversity, project uncertainty, and creativity. More specifically, our findings support the findings of Kearney et al. (2009), who suggested that the possibility of a relationship between diversity and performance is built on the assumption that the source of the diversity may provide an opportunity for enhanced group efficacy and performance when the project is uncertain and requires fresh patterns of thought. The higher the project uncertainty is, the more of a negative impact demographic diversity has on new product creativity. A high degree of project uncertainty may discourage group identification, as it presents highly diverse groups with a cognitively too demanding task that may be regarded as unenjoyable and provides a challenge for them to investigate new patterns of thought and creativity. Moreover, high project uncertainty may harm team effectiveness because of a lack of knowledge and familiarity with the task. Due to the possible negative consequences of project uncertainty on identification with the team, project uncertainty increases the likelihood of detrimental social categorization that may damage team identification as well as team performance. Prior research has also shown that neither diversity relating to easily observable factors nor diversity based on job-related characteristics is consistently correlated with team performance. For example, Jehn et al. (1999) found evidence supporting this proposal. Alternatively, Cox et al. (1991) discovered that demographic differences had a positive relationship with performance, but Simons et al. (1999) found that job-related attributes had a negative effect on performance. The current study is the first to investigate the importance of project uncertainty for teams. The results indicate that functional diversity has significant and

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

positive implications for new product development. These findings suggest that organizations can gain a considerable advantage by seeking out and developing functionally diverse NPD teams comprised of members having broad functional experience rather than specializing in a single narrow functional area, especially when they face high project uncertainty. Sixth, our study makes a contribution to the extant literature findings obtained in the context of Turkey where there are few empirical studies on the relationship between diversity and NPD team performance (e.g. Dayan & Di Benedetto, 2010). 6. Limitations and future research In this study, we primarily focused on the relationships between functional and demographic diversities and new product creativity. Future research could also study the roles of cultural, behavioral, and cognitive diversities in order to gain a better understanding of new product creativity. Furthermore, companies are increasingly reaching out to external sources for heterogeneous knowledge (Ozer & Zhang, 2015). As a result, future research can look at the impact of the diversity of interfirm as opposed to intrafirm teams. In addition, we studied the moderating role of project uncertainty in this relationship. However, further research should investigate the moderating roles of other contextual factors (e.g., interpersonal trust, managerial trust, and justice), types of decision-making processes (e.g., intuition and political behavior), and some other control variables (e.g. firm size and industry types). In this regard, future research should also investigate how project uncertainty influences the curvilinear effect of diversity types. We used a diversity index that was created by averaging across three ratings on age, gender, and ethnicity to form a global measure of demographic diversity. Future research should investigate the impact of each demographic diversity type separately on new product creativity using multi-item objective measurement scales. Moreover, in this study, we primary focused on the impact of diversity on the outcome of NPD process, new product creativity. The NPD process consists of a series of activities that firms employ in the complex process of introducing new products to the market. Every new product will pass through a series of stages from idea generation through design, manufacturing, and market introduction. Thus, future research should also investigate the differential effects of functional and demographic diversities on creativity at each stage of this process, particularly at earlier stages (i.e. idea generation and design) where creativity is desired the most (Crawford & Di Benedetto, 2006). Besides the creativity outcome, future research can look at the accuracy of NPD decisions, especially the ones about new product selection (Ozer, 2008). Furthermore, we collected our data in Turkey, which is one of the most dynamic and developing countries. It is also characterized as a collectivist society (Hofstede, 1980). Hence, team diversity and collaborative behavior of people are more highly to be respected in Turkey than in most Western cultures. However, previous literature on diversity (e.g., Chattopadhyay et al., 2010) noted that responses to dissimilarity vary from culture to culture. Hence, the findings of this study should be generalized to countries that share similar values with Turkey. Furthermore, this study should be replicated in other cultural contexts in order to produce a more complete understanding of the complex relationship between team diversity and new product creativity.

9

new product creativity. Similarly, low levels of demographic diversity in NPD teams are harmful for new product creativity, and companies can enhance the creativity of their new products by using a high level of demographic diversity in their NPD teams. The findings suggest that companies need to consider the composition of creative teams fully, ensuring that the teams contain sufficient functionally and demographically diverse members. An adequate variety of talents are important with regard to functional and demographic diversity. Additionally, companies would do well to consider the phases through which the team progresses. Teams develop in phases starting with identifying and understanding the team's goals, taking up their roles, resolving any “power struggles” relating to holding positions such as leadership, and producing the results for which the team was formed (Tuckman & Jensen, 1977). The composition of creative teams is a complex issue requiring much detailed consideration. The correct combination of functional and demographic diversity needs to be married with sensitive selection of suitable personalities to ensure team cohesion and the required level of productivity. Appendix A. Measures New Product Creativity • • • • • • •

This product challenged existing ideas for this category. This product offered new ideas to the category. This product was creative. This product was interesting. This product was very novel for this category. This product spawned ideas for other products. This product encouraged fresh thinking. Project uncertainty

• How confident were the team members that they were making the right choice? • To what extent were the goals of this project clear for the participants? • It was not at all clear what kind of information we should collect so as to finish this project. • We were very uncertain about the actions that should be taken to finish this project. • It was very difficult to predict the outcomes of this project. • Was there a need for extra information before finishing this project? Functional diversity • The number of functional areas (departments) represented on the team whose members were fully involved in the project rather than being ad hoc specialists or consultants who were engaged only for a limited time. Demographic diversity • Rate the diversity of the team on three dimensions: age, ethnicity and gender. Team size

7. Practical implications Our results suggest some practical implications concerning effectively forming and managing NPD teams engaged in time-pressured and creative tasks. Our study suggests that a moderate level of functional diversity and a high level of demographic diversity contribute positively to the development of creative products. Functional dissimilarities among team members tend to contribute to the development of creative products, but beyond a certain level the impact can become detrimental to

• The number of people on the team who were fully involved in the project rather than being ad hoc specialists or consultants who were engaged only for a limited time. References Akgun, A. E., Byrne, J. C., Keskin, H., & Lynn, G. S. (2006). Transactive memory system in new product development teams. IEEE Transactions on Engineering Management, 53(1), 95–111.

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

10

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx

Akgun, A. E., Byrne, J., Keskin, H., Lynn, G. S., & Imamoglu, S. Z. (2005). Knowledge networks in new product development projects: A transactive memory perspective. Information Management, 42, 1105–1120. Alexander, J., Nuchols, B., Bloom, J., & Lee, S. (1995). Organizational demography and turnover: An examination of multiform and nonlinear heterogeneity. Human Relations, 48, 1455–1480. Amabile, T. M. (1988). A model of creativity and innovation in organizations. In B. M. Staw, & L. L. Cummings (Eds.), Research in organizational behavior. 10. (pp. 123–167). Greenwich, CT: JAI Press. Andersen, H. P., Kragh, H., & Letti, C. (2013). Spanning organizational boundaries to manage creative processes: The case of the LEGO group. Industrial Marketing Management, 42, 125–134. Argote, L., & Greve, H. R. (2007). A behavioral theory of the firm — 40 years and counting: Introduction and impact. Organization Science, 18, 337–349. Bantel, K., & Jackson, S. (1989). Top management and innovations in banking: Does the composition of the team make a difference? Strategic Management Journal, 10, 107–124. Bao, Y., Sheng, S., & Zhou, Z. (2012). Network-based market knowledge and product innovativeness. Marketing Letters, 23, 309–324. Barsade, S. G., Ward, A. J., Turner, J. D. F., & Sonnenfeld, J. A. (2000). To your heart's content: The influence of affective diversity in top management teams. Administrative Science Quarterly, 45, 802–836. Bell, M. P., & Berry, D. P. (2007). Viewing diversity through different lenses: Avoiding a few blind spots. Academy of Management Perspectives, 21(4), 21–25. Bowers, C. A., Pharmer, J. A., & Salas, E. (2000). When member homogeneity is needed in work teams. A meta-analysis. Small Group Research, 31, 305–327. Brewer, M. B. (1995). Managing diversity: The role of social identities. In S. E. Jackson, & M. N. Ruderman (Eds.), Diversity in work teams: Research paradigms for a changing workplace (pp. 47–68). Washington, DC: American Psychological Association. Brown, S. L., & Eisenhardt, K. M. (1995). Product development: Past research, present findings, and future directions. Academy of Management Review, 20(2), 343–378. Bunderson, J. S., & Sutcliffe, K. M. (2002). Comparing alternative conceptualizations of functional diversity in management teams: Process and performance effects. Academy of Management Journal, 45, 875–893. Cacioppo, J. T., Petty, R. E., Feinstein, J. A., & Jarvis, W. B. G. (1996). Dispositional differences in cognitive motivation: The life and times of individuals varying in need for cognition. Psychological Bulletin, 119, 197–253. Cannella, A. A., Jr., Park, J. -H., & Lee, H. -u. (2008). Top management team functional background diversity and firm performance: Examining the roles of team member co-location and environmental uncertainty. Academy of Management Journal, 51(4), 768–784. Carbonell, P., & Rodriguez-Escudero, A. (2013). Management control, role expectations and job satisfaction of new product development teams: The moderating effect of participative decision-making. Industrial Marketing Management, 42(2), 248–259. Carlsson-Wall, M., & Kraus, K. (2015). Opening the black box of the role of accounting practices in the fuzzy front-end of product innovation. Industrial Marketing Management, 45(2), 184–194. Chattopadhyay, P., Finn, C. P., & Ashkanasy, N. M. (2010). Affective responses to professional dissimilarity: A matter of status. Academy of Management Journal, 53, 808–826. Chen, M. H., & Kaufmann, G. (2008). Employee creativity and R&D: A critical review. Creativity and Innovation Management, 17(1), 71–76. Chiu, Y. T., & Staples, D. S. (2013). Reducing faultlines in geographically dispersed teams: Self-disclosure and task elaboration. Small Group Research, 44(5), 498–531. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum. Colquitt, J. A., Noe, R. A., & Jackson, C. L. (2002). Justice in teams: Antecedents and consequences of procedural justice climate. Personnel Psychology, 55, 83–109. Condon, J., & Crano, W. (1988). Inferred evaluation and the relation between attitude similarity and interpersonal attraction. Journal of Personality and Social Psychology, 54, 789–797. Cox, T., Lobel, S. A., & McLeod, P. L. (1991). Effects of ethnic group cultural differences on cooperative and competitive behavior on a group task. Academy of Management Journal, 4, 827–847. Crawford, M., & Di Benedetto, A. (2006). New products management (8th ed.). Burr Ridge, IL: McGraw-Hill/Irwin. Dahlin, K. B., Weingart, L. R., & Hinds, P. J. (2005). Team diversity and information use. Academy of Management Journal, 48, 1107–1123. Dayan, M., & Di Benedetto, C. A. (2009). Antecedents and consequences of teamwork quality in new product development projects: An empirical investigation. European Journal of Innovation Management, 12(1), 129–155. Dayan, M., & Di Benedetto, C. A. (2010). The impact of structural and contextual factors on trust formation in product development teams. Industrial Marketing Management, 39(4), 691–703. Dayan, M., & Di Benedetto, C. A. (2011). Team intuition as a continuum construct and new product creativity: The role of environmental turbulence, team experience, and stress. Research Policy, 40(2), 276–286. Dayan, M., & Elbanna, S. (2011). Antecedents of intuition and its impact on the success of new product development projects. Journal of Product Innovation Management, 28(S1), 159–174. Dayan, M., Elbanna, S., & Di Benedetto, C. A. (2012). Antecedents and consequences of political behavior in new product development teams. IEEE Transactions on Engineering Management, 59(3), 470–482. Early, C. P. (1989). Social loafing and collectivism: A comparison of the United States and the People's Republic of China. Administrative Science Quarterly, 34(4), 565–581. Fornell, C. D., & Larcker, F. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18(1), 39–50.

Ghiselli, E. E., Campbell, J. P., & Zedeck, S. (1981). Measurement theory for the behavioral sciences. San Francisco: Freeman. Gibson, C. B., & Vermeulen, F. (2003). A healthy divide: Subgroups as a stimulus for team learning. Administrative Science Quarterly, 48, 202–239. Gino, F., Argote, L., Miron-Spektor, E., & Todorova, G. (2010). First, get your feet wet: The effect of learning from direct and indirect experience on team creativity. Organizational Behavior and Human Decision Processes, 111(2), 102–115. Griffiths-Hemans, J., & Grover, R. (2006). Setting the stage for creative new products: Investigating the idea fruition process. Journal of the Academy of Marketing Science, 34(1), 27–39. Hair, J., Anderson, R. E., Tatham, R. R., & Black, W. C. (1995). Multivariate data analysis (4th ed.). Englewood Cliffs, NJ: Prentice-Hall. Harrison, D. A., & Klein, K. J. (2007). What's the difference? Diversity constructs as separation, variety, or disparity in organizations. Academy of Management Review, 32, 1199–1228. Harrison, D. A., & Sin, H. S. (2005). What is diversity and how should it be measured? In A. M. Konrad, P. Prasad, & J. K. Pringle (Eds.), Handbook of workplace diversity (pp. 191–216). Hirunyawipada, T., Beyerlein, M., & Blankson, C. (2010). Cross-functional integration as a knowledge transformation mechanism: Implications for new product development. Industrial Marketing Management, 39, 650–660. Hofstede, G. (1980). Culture's consequences: International differences in work related values. La Jolla, CA: Sage Publications. Horwitz, S. K., & Horwitz, I. B. (2007). The effects of team diversity on team outcomes: A meta-analytic review of team demography. Journal of Management, 33, 987–1015. Im, Subin, & Workman, J. P., Jr. (2004). Market orientation, creativity, and new product performance in high-technology firms. Journal of Marketing, 68, 114–132. Jackson, S. E., Brett, J. F., Sessa, V. I., Cooper, D. M., Julin, J. A., & Peyronnin, K. (1991). Some differences make a difference: Individual dissimilarity and group heterogeneity as correlates of recruitment, promotions and turnover. Journal of Applied Psychology, 76, 675–689. Jehn, K. A., Northcraft, G. B., & Neale, M. A. (1999). Why differences make a difference: A field study of diversity, conflict, and performance in workgroups. Administrative Science Quarterly, 44, 741–763. Joshi, A., & Roh, H. (2009). The role of context in work team diversity research: A metaanalytic review. Academy of Management Journal, 52(3), 599–627. Kearney, E., Gebert, D., & Voelpel, S. C. (2009). When and how diversity benefits teams: The importance of team members' need for cognition. Academy of Management Journal, 52, 581–598. Keller, R. T. (2001). Cross-functional project groups in research and new product development: Diversity, communications, job stress, and outcomes. Academy of Management Journal, 44(3), 547–555. Kramer, R. M. (1999). Trust and distrust in organizations: Emerging perspectives, enduring questions. Annual Review of Psychology, 50, 569–598. Land, S., Engelen, A., & Brettel, M. (2012). Top management's social capital and learning in new product development and its interaction with external uncertainties. Industrial Marketing Management, 41, 521–530. Larkey, L. K. (1996). Toward a theory of communicative interactions in culturally diverse workgroups. Academy of Management Review, 21, 463–491. Lau, C. D., & Murnighan, K. J. (2005). Interactions within groups and subgroups: The effects of demographic faultlines. Academy of Management Journal, 48, 645–659. Mael, F. A., & Ashforth, B. E. (1995). Loyal from day one: Biodata, organizational identification, and turnover among newcomers. Personnel Psychology, 48, 309–333. McLeod, P., & Lobel, S. (1992). The effects of ethnic diversity on idea generation in small groups. Paper presented at the annual academy of management meeting, Las Vegas, Nevada. Milliken, F. J., & Martins, L. L. (1996). Searching for common threads: Understanding the multiple effects of diversity in organizational groups. Academy of Management Review, 21, 402–433. Mohammed, S., & Nadkarni, S. (2011). Temporal diversity and team performance: The moderating role of team temporal leadership. Academy of Management Journal, 54(3), 489–508. Mohd Zaki, N. H., & Othman, S. N. (2013). Team diversity and new product development performance in manufacturing sector: A conceptual framework. Journal of Global Management, 6(1), 101–112. Molina-Castillo, F. J., Jimenez-Jimenez, D., & Munuera-Aleman, J. (2011). Product competence exploitation and exploration strategies: The impact on new product performance through quality and innovativeness. Industrial Marketing Management, 40, 1172–1182. Moorman, C., & Miner, A. S. (1997). The impact of organizational memory on new product performance and creativity. Journal of Marketing Research, 34, 91–106. Olson, E. M., Walker, O. C., & Ruekert, R. W. (1995). Organizing for effective new product development: The moderating role of product innovativeness. Journal of Marketing, 59(1), 48–62. Østergaard, C. R., Timmermans, B., & Kristinsson, K. (2011). Does a different view create something new? The effect of employee diversity on innovation. Research Policy, 40(3), 500–509. Ozer, M. (2008). Improving the accuracy of expert predictions of the future success of new internet services. European Journal of Operational Research, 184(3), 1085–1099. Ozer, M., & Zhang, W. (2015). The effects of geographic and network ties on exploitative and exploratory product innovation. Strategic Management Journal, 36(7), 1105–1114. Pedhazur, E. J. (1997). Multiple regression in behavioral research (3rd ed.). Orlando, FL: Harcourt Brace. Pelled, L. H., Ledford, G. E., & Mohrman, S. A. (1999). Demographic dissimilarity and workplace inclusion. Journal of Management Studies, 36, 1013–1031. Perminova, O., Gustafsson, M., & Wikstrom, K. (2008). Defining uncertainty in projects: A new perspective. International Journal of Project Management, 26, 73–79.

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016

M. Dayan et al. / Industrial Marketing Management xxx (2016) xxx–xxx Pettigrew, T. F. (1998). Intergroup contact theory. Annual Review of Psychology, 49, 65–85. Phillips, K. W., Mannix, E. A., Neale, M. A., & Gruenfeld, D. H. (2004). Diverse groups and information sharing: The effects of congruent ties. Journal of Experimental Social Psychology, 40, 497–510. Randel, A. E., & Jaussi, K. S. (2003). Functional background identity, diversity, and individual performance in cross-functional teams. Academy of Management Journal, 46, 763–774. Schulze, A., & Hoegl, M. (2006). Knowledge creation in new product development projects. Journal of Management, 32(2), 210–236. Sherif, M., & Sherif, C. (1953). Groups in harmony and tension. New York: Harper. Simons, T., Pelled, L. H., & Smith, K. A. (1999). Making use of difference: Diversity, debate, and decision comprehensiveness in top management teams. Academy of Management Journal, 42, 662–673. Stasser, G., & Titus, W. (1985). Pooling of unshared information in group decision making: Biased information sampling during discussion. Journal of Personality and Social Psychology, 48, 48–1467. Stewart, G. L. (2006). A meta-analytic review of the relationship between team design features and team performance. Journal of Management, 32, 29–54. Suh, T., Bae, M., Zhao, H., Kim, H. S., & Arnold, J. M. (2010). A multi-level investigation of international marketing projects: The role of experiential knowledge and creativity on performance. Industrial Marketing Management, 39, 211–220. Tajfel, H., & Turner, J. C. (1985). The social identity theory of intergroup behavior. In S. Worchel, & W. G. Austin (Eds.), Psychology of intergroup relations (pp. 6–24). Chicago: Nelson-Hall. Tatikonda, M. V., & Rosenthal, S. R. (2000). Technology novelty, project complexity, and product development project execution success: A deeper look at task uncertainty in product innovation. IEEE Transactions on Engineering Management, 47(1), 74–87. Thatcher, S. M. N., & Patel, P. C. (2012). Group faultlines: A review, integration, and guide to future research. Journal of Management, 38(4), 969–1009. Tsai, K. H., & Hsu, T. T. (2014). Cross-functional collaboration, competitive intensity, knowledge integration mechanisms, and new product performance: A mediated moderation model. Industrial Marketing Management, 43(2), 293–303. Tsui, A. S., & O'Reilly, C. A. (1989). Beyond simple demographic effects: The importance of relational demography in superior-subordinate dyads. Academy of Management Journal, 32, 402–423. Tsui, A. S., Egan, T. D., & O'Reilly, C. (1992). Being different: Relational demography and organizational attachment. Administrative Science Quarterly, 37, 549–579. Tuckman, B. W., & Jensen, M. A. (1977). Stages of small group development revisited. Group and Organizational Studies, 2, 419–427. Van der Vegt, G., & Bunderson, J. S. (2005). Learning and performance in multidisciplinary teams: The importance of collective team identification. Academy of Management Journal, 48(3), 532–547.

11

Van der Vegt, G., Van de Vliert, E., & Huang, X. (2005). Location-level links between diversity and innovative climate depend on national power distance. Academy of Management Journal, 48(6), 1171–1182. Van Knippenberg, D., De Drue, C. K., & Homan, A. C. (2004). Work group diversity and group performance: An integrative model and research agenda. Journal of Applied Psychology, 89(6), 1008–1022. Wharton, A. S., & Baron, J. N. (1987). So happy together? The impact of gender segregation n men at work. American Sociological Review, 52, 574–587. Williams, K. Y., & O'Reilly, C. A., III (1998). Demography and diversity in organizations: A review of 40 years of research. In B. M. Staw, & L. L. Cummings (Eds.), Research in organizational behavior — Volume 20. USA: JAI Press Inc. Wittenbaum, G. M., & Stasser, G. (1996). Management of information in small groups. In J. L. Nye, & A. M. Brower (Eds.), What’s social about social cognition? Research on socially shared cognition in small groups (pp. 3–28). Thousand Oaks, CA: Sage. Mumin Dayan is an Associate Professor at the United Arab Emirates University, UAE. He received his M.B.A degree in Marketing from the Bennett S. Le Bow College of Business in Drexel University and his Ph.D. degree in Marketing from the Fox School of Business in Temple University, Philadelphia, PA, USA. His current research areas are new product/ technology development, cognitive/social psychology in innovation and small business management, and decision-making in teams. His work has been published in Industrial Marketing Management, Journal of Product Innovation Management, IEEE Transactions on Engineering Management, R&D Management, Long Range Planning, Research Policy, and elsewhere. Muammer Ozer is a Professor in the Department of Management of the City University of Hong Kong. He holds BS and MS degrees in engineering from the Istanbul Technical University in Turkey and a Ph.D. degree in business administration from the University of Pittsburgh. His primary research interests include new product development and the use of information technologies in new product development. His papers have appeared in leading international journals in these areas. Hanan Almazrouei is an Assistant Professor of Human Resource Management at the United Arab Emirates University. She has a Ph.D. degree from Latrobe University in Melbourne, Australia and a Master's degree in human resources management from Swinburne University in Melbourne, Australia. She has worked in the UAE for nine years, seven in the telecommunications industry and two in municipal services. She has published in the Journal of Business Strategy.

Please cite this article as: Dayan, M., et al., The role of functional and demographic diversity on new product creativity and the moderating impact of project uncertainty, Industrial Marketing Management (2016), http://dx.doi.org/10.1016/j.indmarman.2016.04.016