14th October 2013
Diversity in Entrepreneurial Teams
A new perspective on how diversity in motivation,
information and network influences team
performance
Master Thesis
Supervisor: Dr. Tsvi Vinig Student Name: Jos Eisberg Student Number: 10425888
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Abstract
The effect of diversity on performance in new venture teams has caused controversial discussion. Scholars have mostly focused on researching the impact of diversity in demographic variables on team performance, with the result of creating little consistent evidence. This thesis proposes a new set of variables derived from the Golden Circle model and based on effectuation theory. These new building blocks are merged with existing theories and empirical evidence to offer a list of testable propositions for future empirical work. In doing so, I build a new model of diversity in entrepreneurial teams that explains how diversity in motivation, information and network influences new venture team performance.
Two case studies with venture-backed startups are carried out to test and refine the model. The study illustrates how the model can be applied to real business cases and offer ground for further research and experiments.
With regards to diversity in motivation, not the total amount of diversity seems to be decisive for performance, but rather the distribution. The outperforming team showed very low diversity in motivation in two particular items, indicating importance of a common motivation that team members agree upon.
The results for information diversity are mixed, which could be due to difficulties in measurement or misspecification of items used. Network diversity seems to positively relate to performance.
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Acknowledgement
This thesis would not be the same without the involvement of many people that supported me over the past months. I feel deep thankfulness for the company I received on the sometimes stony path.
First and foremost I am grateful for my thesis supervisor and entrepreneurship professor Prof. Dr. Tsvi Vinig for his guidance and inspiration. Entrepreneurship has no better ambassador.
I would further like to express my gratitude to Prof. Dr. Wietze van der Aa for taking the unrewarding role of the second supervisor; to Prof. Dr. Stefan Mol for valuable feedback and profound research insight into diversity constructs, HR literature and using Qualtrics; professors Noam Wasserman, Erik Monsen, Daniel Forbes, Leon Schjoedt, Bart Clarysse, Thomas Cooney, Page West and Kelly Shaver for great advice on data sources, literature recommendations and fruitful email correspondence; Simon Sinek for his inspirational book which provides the basis for this thesis; my fellow students Sebastiaan and Luuk for coffee breaks, for being great companions in this lengthy process and for their continuous motivational efforts; the best friends and proof-readers one could imagine being Roman Grabenhorst, Torben Wolf, Thies Grüning, Christoph Buss and Miles Stoll; the team at 1&12 ventures, especially Hans Roeland Poolman, Odile Basedow and Chatib Sjarbaini, for their time, trust, expertise, patience, reflection and ever flowing stream of new ideas; Techreturns Nederland, especially Joost de Kluijver and Marcel Stiphout, for sponsoring the survey; all teams that participated in the survey and last but not least my family for their support and trust.
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Table of content
List of Figures ... 5
List of Tables ... 6
1.0 INTRODUCTION ... 7
2.0 RESEARCH QUESTION & OBJECTIVES ... 9
3.0 ENTREPRENEURIAL TEAMS, DIVERSITY and EFFECTUATION ... 10
3.1 Literature Gap ... 11
3.2 Entrepreneurial teams... 12
3.3 Status quo - Diversity in entrepreneurial teams ... 13
3.4 Diversity constructs ... 15
3.5 Diversity in work and top management teams ... 17
3.6 Effectuation ... 18
4.0 MODEL DEVELOPMENT ... 20
4.1 Information- and motivation-related variables ... 20
4.2 Team processes & interaction ... 24
4.2.1 Processes and interaction - Conflict ... 26
4.2.2 Processes and interaction - Communication, Cohesion and Decision-Making ... 28
4.3 Performance of entrepreneurial teams ... 31
4.4 The “Golden” diversity model ... 33
5.0 METHODOLOGY ... 34
5.1 Research Design ... 34
5.2 Target Group ... 35
5.3 Data Collection ... 36
5.4 Questionnaires ... 37
5.4.1 Questionnaire 1 – Entrepreneurial Teams ... 37
5.4.2 Questionnaire 2 – Team Performance ... 39
6.0 ANALYSIS & DISCUSSION ... 40
6.1 Motivation ... 41
6.2 Information and Network ... 47
6.3 Team processes, interaction and performance... 50
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6.3.2 Conflict ... 52
6.3.3 Cohesion ... 53
6.3.4 Decision-making ... 54
6.3.5 Satisfaction and Commitment ... 54
6.3.6 Overall performance ... 55
6.4 Key Findings ... 56
6.5 Implications for managing entrepreneurial teams... 57
7.0 Conclusion ... 59
8.0 Limitations and Future Research ... 60
Bibliography ... 62
Appendix A – Diversity as separation and variety ... 66
Appendix B – Model of team effectiveness ... 67
Appendix C – Diversity and team effectiveness ... 67
Appendix D – Questionnaire One ... 69
Appendix E – Questionnaire Two ... 72
Appendix F - Variables, items and diversity construct overview ... 75
List of Figures
Figure 1: The Golden CircleFigure 2: Determinants of entrepreneurial team performance Figure 3: Relationship of the “Golden Circle” and effectuation
Figure 4: Impact of diversity in two major groups of variables on team performance Figure 5: Team processes influenced by information and motivation-related variables Figure 6: The role of team processes and interaction: Conflict
Figure 7: Impact of diversity in motivation- and information-related variables on the functionality of team processes & interaction
Figure 8: How team member diversity influences team performance based on the Golden Circle and Effectuation
6 Figure 9: Motivation in Perceptum: Modus and range
Figure 10: Motivation in ASI: Modus and range Figure 11: Variety in higher education
Figure 12: Variety in experience in different types of organizations Figure 13: Variety in job roles
Figure 14: Communication in A and P Figure 15: Conflict in A and P
Figure 16: Cohesion in A and P
Figure 17: Decision-making effectiveness and efficiency in A and P Figure 18: Overall performance evaluation
Figure 19: Type and Amount of diversity
Figure 20: Heuristic Model of Group Effectiveness
Figure 21: Relationship between different categories of diversity and work group performance Figure 22: Model of work group diversity impact on performance
List of Tables
Table 1: Motivation items comparison: Means and Standard Deviation Table 2: Information items compared: Blau’s Index
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1.0 INTRODUCTION
Many entrepreneurs face the problem to hire the “right” people for their venture. Fact is that some entrepreneurs are able to create better functioning teams than others, thus some entrepreneurial teams operate more successfully. Next to performance differences, the team composition is essential for the overall success of the venture (Eisenhardt & Schoonhoven, 1990; Kamm et al., 1990; Mellewigt & Späth, 2002; Cooney, 2005; Wasserman, 2012). According to a study of more than 10.000 start-ups in the technological and life sciences sector in the United States, 65% of high-potential ventures fail because the team was dysfunctional (Wasserman, 2012). The main reasons for failure are the interpersonal tensions between co-founders, the investor’s that are brought in and the employees that are hired to support and complement the entrepreneur (Wasserman, 2012). This high number of failures associated with problems in new venture teams is the starting point for the proposed research into how team composition affects team performance.
As companies grow from seed start-ups to early stage high growth companies, the skill set needed to run a company changes (Lindell, 1991). New employees must be chosen to join the team for further growth. Entrepreneurs must carefully select employees, partners and investor’s to construct a successful venture. Very little is known about how successful teams are brought together and which skills entrepreneurs should look for in prospective employees and partners. The need for theory becomes obvious when looking at current literature on teams. Most articles take a managerial perspective, which can be valuable for large organizations, but does not fit with how most new ventures today operate (Cooney, 2005; Harper, 2008; Schjoedt et al., 2013). Theory that takes an entrepreneurial perspective instead of a managerial one is therefore urgently needed.
An important question concerns diversity versus similarity of team members with regard to different team characteristics. Many studies evolve around the question whether differences in gender, age or other demographics influence team performance (e.g. Polzer, Milton & Swarm, 2002; Webber & Donahue, 2001; Kaiser & Müller, 2013). Researchers have found evidence that there are problems associated with both extreme heterogeneity and homogeneity in team characteristics. The short term benefits of a homogeneous team are proposed to be speed and ease in setting up the business and starting operations (Wasserman, 2012). Solutions and accordance can be achieved quicker among similar team members, and trust is a smaller issue. It is also likely that founders have easier access to people that are similar to them due to their personal network (Wasserman, 2012). But there are also longer-term risks associated with homogeneous teams. For example in turbulent and complex environments, homogeneity limits the amount of alternatives developed by a team to respond to environmental change (Vyakarnam
8 & Handelberg, 2005). Furthermore, homogeneity can lead to groupthink and insufficient conflict (Eisenhardt & Schoonhoven, 1990). The discussion on whether heterogeneity has positive or negative is ongoing and lengthy. Different studies provide opposing conclusions as proposed in several meta-studies that summarize findings on the effects of diversity in teams (Williams & O’Reilly, 1998; Mellewigt & Späth, 2002, Van Knippenberg & Schippers , 2007).
The idea behind this thesis is that the answer to the homogeneity versus heterogeneity discussion is not either or, but rather both. Some researchers in line with this argumentation started proposing that both homogeneity and heterogeneity are needed in teams (e.g. Webber & Donahue, 2001; Katzenbach & Smith, 2003; Boni & Weingart, 2012; Wasserman, 2012). The underlying logic of these models is that teams need members that conform in some areas and are diverse in others. In combination, this makes them perform better than the sum of their parts.
The underlying model for this thesis is provided by the “Golden Circle” theory proposed by Simon Sinek (2009). Applied to the context of entrepreneurial teams, this model may explain part of why some teams function better than others. In his influential book and TED talk, Sinek claims to have identified the pattern that successful leaders apply in business. Sinek defines success as the
ability to attract an inspired following with regards to the stakeholders of a company, most importantly customers and employees. The key is that successful organizations and business leaders always communicate why they do things first, and only then do they address how they conduct business and what distinguishes their business from others. In terms of employees in a
business, people must be bound together by core values and beliefs that everyone in the organization shares to be successful. Therefore the goal should not only be to hire the people that have the skills the organization needs, but also to hire people who believe what the organization represents. What great leaders are able to do is to find good fits for their organizations, whereas most companies hire by matching the job description to the experience and skills of the applicant. This leadership perspective shall be transferred to the realm of entrepreneurship, in particular to entrepreneurial teams that make up most new ventures.
As can be seen in Figure 1, the central aspect of the Golden Circle is “WHY” people join an organization or team, the purpose and common goal that holds them together. The “HOW” layer represents the unique way an organization is run, the processes it applies and the way business is conducted. The outer layer described as the “WHAT” represents the output a team or company produces,
"A company is a culture. A group of people brought together around a common set of values and beliefs" Sinek,, S. (2009, p. 90)
Fig. 1: The Golden Circle. Adapted from Sinek, S. (2009)
9 for example a companies’ products or services. According to Sinek (2009), many companies communicate what they do first instead of why they do it, an essential mistake that successful companies and business leaders avoid by communicating the why, their motivation, first.
Applying this model to how entrepreneurs build teams allows for a new perspective on team composition. The three circles of the model can be translated into testable team characteristics and performance outcomes. The approach is to look at how diverse or similar team members are in different characteristics related to the Golden Circle categories and then to examine whether the pattern of the Golden Circle applies.
Whereas the Golden Circle provides the idea and inspiration for this thesis, it will be executed by using profound entrepreneurial theory. Translating the Golden Circle into a diversity construct for entrepreneurial teams will be done by using “Effectuation theory” as proposed by Sarasvathy (2001). Contrary to most current approaches that transfer variables and methodology from management theory to entrepreneurial teams and thus include the underlying theories on management, the model developed in this research takes a truly entrepreneurial perspective. The power of the Golden Circle lies in the provision of an explanation for which team characteristics diversity positively relates to performance and for which it negatively relates. Since looking at diversity versus similarity per se has yielded no evidence for positive or negative impact, looking at individual characteristics derived from a powerful model is a logical way of resolving the conflicting views.
In summary, this change in perspective both in underlying theory and conceptual model is valuable for two reasons. It transfers the pattern of successful organizations and leaders to entrepreneurial teams and thus adds a new, possibly valuable perspective to entrepreneurial team literature. Secondly, it provides a possible explanation for the puzzling results on the effects of diversity on performance in entrepreneurial teams.
2.0 RESEARCH QUESTION & OBJECTIVES
Although comprehensive research has been undertaken, no model was found that examines team composition in light of effectuation theory. Thus this thesis investigates entrepreneurial team composition in light of effectuation theory for the first time. Using the Golden Circle model to determine which characteristics positively or negatively relate is a second novelty. In light of the two new perspectives introduced, the following question is at the heart of this research:
For which team characteristics does team member diversity positively relate to entrepreneurial team performance and for which does it relate negatively?
10 The research objectives derived from this question state the following:
1. to identify and re-conceptualize variables that influence entrepreneurial team performance 2. to identify and apply diversity constructs applicable to entrepreneurial teams
3. to identify findings in existing theory on diversity in teams that can inform a model on diversity in entrepreneurial teams
4. to examine the extent to which existing theory on diversity in teams is applicable in the entrepreneurial context
5. to derive from the Golden Circle model on which characteristics team members need to be similar and on which they need to be diverse to make a better performing team
6. to test and distinguish variables where team diversity positively influences team performance from variables where diversity negatively influences performance
7. to take a next step towards explanatory theory that reveals the effect of diversity in different team characteristics and how this influences performance in entrepreneurial teams
8. to contribute to an understanding why some entrepreneurial teams perform more successful than others related to the diversity of team members
9. to link Effectuation theory, the Golden Circle and current theoretical findings on entrepreneurial teams in an explanatory model that describes the relationships between team member diversity and team performance.
3.0 ENTREPRENEURIAL TEAMS, DIVERSITY and EFFECTUATION
This chapter lays the foundation for building a conceptual model about the relationship between diversity in specific variables and performance in entrepreneurial teams. It summarizes relevant literature findings on team composition, diversity and performance in work- and entrepreneurial teams. It thereby investigates mainly two different areas of business studies, entrepreneurship and human resource management (HRM). Within entrepreneurship theory, the focus lies on previous research on entrepreneurial teams and discussing Effectuation as the underlying theory. Within HRM, the focus is on the impact of diversity in work and top management teams.
Literature about the effect of diversity on work and top management teams’ performance is well developed and provides useful insight about the relationship between diversity in different team characteristics and team performance. Although findings are often empirically tested by multiple studies, the applicability of variables chosen and research findings in general to the entrepreneurial context is a major concern. Since the majority of conceptualizations in research on work and top management teams
11 are based on economic theories such as the resource-based view (e.g. Barney, 1986) or upper echelon theory (e.g. Hambrick & Mason, 1984), they often do not or partly apply.
Literature on entrepreneurial teams provides definitions and concepts. Unfortunately, most of the papers on entrepreneurial teams use the same variables and underlying theories as papers on management teams. An example is the frequent use of demographic variables such as gender, age and ethnicity with regards to their influence on performance. This direct transfer of methodology and conceptualization is rather useless as research on teams is highly context sensitive (Williams & O’Reilly, 1998). Therefore the second contribution of entrepreneurship literature is the theory of effectuation as proposed by Sarasvathy (2001).
The literature review provides an overview on four general topics, namely entrepreneurial teams, different types of diversity and diversity in work and top management teams. The part is rounded off by a discussion on effectuation, which constitutes the perspective from which all findings will be analyzed and merged together. The intent is to provide the reader with a general understanding of four critical areas relevant for the development of the model and the subsequent discussion.
In the subsequent part of model development, team characteristics relevant to entrepreneurial teams are identified. Variables will be categorized along the lines of the Golden Circle theory and examined in light of effectuation. Throughout this process, the impact of different levels of diversity within entrepreneurial teams and their effect on performance will be analyzed and hypotheses on relationships established.
3.1 Literature Gap
Schjoedt et al. (2013) note that entrepreneurs behave fundamentally different than managers and conclude that theory on entrepreneurial teams must be developed separately from theory on teams of managers. In line with this urge for distinctive theory development, authors consistently point towards a gap in the literature on both economic and behavioral frameworks for entrepreneurial teams (e.g. Kamm et al., 1990; Cooney, 2005; Harper, 2008, Schjoedt & Kraus, 2009).
The absence of well-developed theory may not be surprising as researches have just begun to delve into the subject of what entrepreneurial teams are, how they come to existence and how they function (Shrader & Siegel, 2007). What is surprising on the other hand is the fact that although most fast growth ventures are created by more than one founder, most of the entrepreneurship literature and attention has been devoted to individual
Gu zhang nan ming – ‘It is Difficult to Clap With One Hand’ - Traditional
12 entrepreneurs and their success stories (Cooney, 2005; Wasserman, 2012). This becomes even more surprising in light of another empirically tested fact: team ventures are generally more successful than ventures initiated by a single founder (Mellewigt & Späth, 2002). Therefore the real gap exists between individual entrepreneurship theory on the one hand and well-established theories on work and top management teams in HRM on the other hand (Cooney, 2005; Harper, 2008; Schjoedt et al., 2013).
Kamm et al. (1990) is an early exception worth noting for two reasons. Firstly, they accumulated studies and data that showed most successful new ventures are founded by teams, thus they were the first to prove significance of entrepreneurial teams in new
venture creation. Secondly, they were the first to acknowledge a direct relationship between entrepreneurial teams and firm performance. In combination, these two findings let them urge for theory that informs entrepreneurs how to form and maintain effective teams (Kamm et al., 1990, p. 10). Unfortunately, the call
for hypotheses on what makes entrepreneurial teams effective has been largely unheard, since compelling and comprehensive theoretical constructs are still absent today.
3.2 Entrepreneurial teams
A precise definition of the concept “entrepreneurial team” needs to be developed to described the unit of analysis. A combination of different authors’ conceptualizations is most appropriate as none of the current definitions fits entirely with the focus of this research. Forbes et al. (2006) broadly define an entrepreneurial team as “a group of people involved in the creation and management of a new venture”. This broad definition needs to be narrowed down to make it explicit and workable. Specification is sought in the dimensions motivation and involvement, legal entity and time. The definition chosen is built upon characteristics and descriptions provided by Kamm et al. (1990), Cooney (2005), Harper (2008), Schjoedt & Kraus (2009) and Kaiser & Müller (2013). It states the following:
“Two or more individuals that participate actively in the development of an early phase venture that significantly contribute to and directly benefit from building a valuable, profit-oriented company.”
Following this definition, entrepreneurial teams for example in large companies, in student projects and non-profit organizations are excluded. On the other hand, it includes all people working in a new venture as a team and not only focus on the founders that have financial stake in the company Opposing some authors (Cooney, 2005; Schjoedt & Kraus, 2009), this follows the notion that all members, key employees and founders, contribute substantially to the performance of the start-up (Kaiser & Müller,
“Strategy scholars have examined management teams, while entrepreneurship scholars have mostly concentrated on individual founders” – Shrader & Siegel,
13 2013). It is therefore also irrelevant whether team members join before or after the foundation of the company. On the other hand, the definition excludes freelancers and outsourcing parties as they do not directly benefit from building a valuable company.
An important dimension to consider with regards to the venture is the stage in which the company currently is. A business life cycle can be divided into various stages from birth until decline and extinction (Jawahar & McLaughlin, 2001; Lindell, 1991) and only one part of the life cycle lies within the scope of investigation.
The organizational life cycle model of Jawahar & McLaughlin (2001) starts with foundation of a legal entity and divides the subsequent phases of development of the business into startup, emerging growth, mature and decline stage, with particular characterstics attached to each of those phases. The start-up phase consists of developing and implementing the business model, receiving initial financing and entering the market place with a product or service. Entrepreneurs also start forming the “first layer management team. The main concern in this phase is survival and founders typically work closely together in a small team (Jawahar & McLaughlin, 2001). This research focusses precisely on teams in the above described startup phase.
In light of the behavioral perspective of this paper, the addition below adequately completes the picture on what characterizes an entrepreneurial team:
“[…] individuals who attempt to work together to achieve a set of imperfectly overlapping and negotiated superordinate organizational goals, potentially for different reasons and often in spite of conflicts emerging from their backgrounds, personalities, and individual motives.” - (Schjoedt et al., 2013, p. 4)
This addition already touches upon some of the issues discussed later, but is necessary to acknowledge the focus on the people working within the new venture.
To sum up, an entrepreneurial team consists of at least two members in an early-stage, profit-oriented startup. Members work actively in the team and contribute significantly to value creation, but also benefit from growing the venture. Entrepreneurial teams include all team members active in a startup company, including employees, first management layer and co-founders.
3.3 Status quo - Diversity in entrepreneurial teams
In recent years, authors have moved from defining what an entrepreneurial team is towards more detailed studies how they function (Cooney, 2005). Whereas some authors focus on building economic theories (e g. Harper, 2008), most authors examine behavioral aspects (e.g. Ucbasaran et al., 2003; Forbes et al., 2006; West, 2007; Schjoedt & Kraus, 2009; Schjoedt et al., 2013).
14 By comparing what we knew in 1990 when Kamm et al. (1990) first coined the term to what we know now, it can be seen that although there is progress made, there is still very little theory on the factors that make entrepreneurial teams effective. Kamm et al. (1990) proposed that functional expertise, management skills, decision-making styles, and experience should be “balanced” in an effective entrepreneurial team. The second proposition was that it is critical for all team members to have the same “vision” in line with the purpose of the venture. Both argumentations are in line with the notion of the Golden Circle. It is also worth noting that the central role of diversity is already implicitly included in this early notion on entrepreneurial teams.
A recent paper on determinants of entrepreneurial team performance reveals more details. Schjoedt & Kraus (2009) distinguish three determinants for entrepreneurial team performance, the
external environment, team composition and team processes (Fig. 2). The external environment influences
venture performance directly but also indirectly through the entrepreneurial team’s response. In turbulent environments, a more diverse team is supposed to perform better because it develops more alternatives for action and vice versa in stable times a more homogeneous team functions better.
In terms of team composition, Schjoedt & Kraus (2009) acknowledge a difference between surface level and deep-level variables. They propose that research on surface level characteristics like educational and industry experience should be separated from deep-level characteristics such as personality, values and attributes, because diversity in those two categories may have differing effects on team performance. Again, a parallel to the notion of this research can be drawn as the Golden Circle also distinguishes different levels of team characteristics, from the deep sitting motivation (WHY) to the possession of information (WHAT). Although this distinction is valuable, their advice stays generic in that they propose to reach and maintain an appropriate “balance” of heterogeneity and homogeneity in the team to perform well
15 (Schjoedt & Kraus, 2009, p. 517). This concept will be refined in the conceptual model, but the notion of deep and surface level characteristics as well as the determinants stay relevant.
The third group influencing performance is team processes like conflict and communication. They mediate the relationship between team composition and team performance, thus team composition has both a direct and indirect influence on performance. The results presented on the effect of team processes are rather vague and inconclusive. Conflict can be constructive and destructive, communication may enhance ET performance (Schjoedt & Kraus, 2009, p. 518f). In their concluding remarks, Schjoedt & Kraus (2009) point out that their model is far from exhaustive and that explanation of varying ET performance is lacking, emphasizing that these are fruitful areas for further investigation. In line with these concluding remarks, Van Knippenberg & Schippers (2007) point out that the explanation for team performance with regards to team member diversity is still generic which may be due to an overly simplistic approach towards the concept of diversity in different team characteristics.
Taking into account the relatively little progress that has been made in the past two decades on how diversity in different team characteristics influences team performance, it cannot be surprising that researchers repeatedly urge for developing theories that allow a deeper understanding how team composition and diversity in team characteristics influence team performance (Ensley & Carland, 2004; Vyakarnam & Handelberg, 2005; Knippenberg & Schippers, 2007; Schjoedt et al., 2012).
3.4 Diversity constructs
Diversity studies on teams are inconclusive and inconsistent (Jehn, Northcraft & Neale, 1999; Van Knippenberg & Schippers, 2007). Authors urge for a closer examination of the concept of diversity (Harrison & Klein, 2007; Van Knippenberg & Schippers, 2007). The first important aspect to acknowledge is that a unit, like a team, is not diverse per se, but rather along one or more specific characteristics (Harrison & Klein, 2007). The diversity of a specific attribute within a unit can be defined as “the distribution of differences among the members of a unit with respect to a common attribute X, such as tenure, ethnicity, conscientiousness, task attitude, or pay.” (Harrison & Klein, 2007, p. 1200). Thus the unit of analysis includes the entire entrepreneurial team as
defined in section 2.1. Within the team, individual differences between team members along different attributes will be measured.
Distinguishing types of diversity is particularly relevant with regards to the differing effects that diversity can have.
“Individual differences form the basis for a heterogeneous ET.” - (Schjoedt
16 Different types of diversity can be classified according to their distribution within the team. Harrison and Klein (2007) divide separation, variety and disparity and define a minimum, maximum and moderate distribution for each type (Fig. 19 in Appendix A). Separation and variety are relevant categorizations that fit with the type of variables that will be used in the model. For separation, homogeneity on the attribute is generally predicted to have a positive effect independent of a high or low score in a particular attribute. Maximum negative effect is expected when exactly half of the team is high and the other half scores low on a particular attribute. For variety, members of a team differ qualitatively, for example on the amount of information or network they have available or the functional background they have. High variety is associated with positive outcomes as it broadens the cognitive and behavioral capital of the team. It is important to note that this type of diversity cannot be scored on a scale, either there is a variation or not. The maximum variety is present when all team members belong to a different category of a characteristic, the minimum when all belong to the same, for example only business students.
All attributes under research will be categorized according to one of the two relevant types of diversity defined above. Analyzing which type of diversity is prevalent allows for better measuring, contrasting and for a more precise debate on the nature and effect of the attribute under investigation which will increase the value of predictions made.
Whereas authors generally assume that the impact of diversity is highest at the maximum or minimum level, some authors acknowledge that for many characteristics a moderate level of diversity may have the optimal influence on team performance (West, 2007; Van Knippenberg & Schippers, 2007 Wasserman, 2012). In developing the model, special attention will be drawn to variables for which this prediction may hold true.
In summary, research has reached a point where the effects of diversity are not regarded as negative or positive per se anymore, but where diversity can have positive and negative effects at the same time. Whereas diversity can lead to social categorization and dysfunctional conflict on the one hand, it can enhance decision-making and quality of outputs on the other hand (Van Knippenberg & Schippers, 2007). Benefits of additional human capital can be offset by dysfunctional conflict. This bidirectional effect allows for deeper investigation into the relationships of diversity between distinct team characteristics and team performance.
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3.5 Diversity in work and top management teams
Katzenbach & Smith (2005, p. 165) define a team as a small group of people with complementary skills working together for a shared goal. Defined like this, entrepreneurial teams and work teams in larger organizations seem to be similar if not the same. Yet only part of the research on work and top management teams can be applied to entrepreneurial teams.
An influential and convincing model on work teams is that of Cohen & Bailey (1997). In their heuristic model, they capture 7 factors influencing team effectiveness (see Figure 20, Appendix B). Some of their ideas can be applied to entrepreneurial teams. Cohen and Bailey (1997) establish an interdependent relationship between team processes and psychological traits. This relationship is likely to exist in entrepreneurial teams as well. Secondly, both processes and psychological traits influence team effectiveness, an assumption that can be transferred to entrepreneurial teams as well. Their predictions on task design, group composition and organizational context (Appendix B) is less applicable. During model development, this part will be replaced by knowledge, skills and abilities brought in by individuals that are predicted to influence process variables (Bowers, Pharmer & Salas, 2000). This replacement is more applicable in the entrepreneurial context because teams are likely to be influenced by “What people know” (Sarasvathy, 2001) rather than the organizational context they are in like hierarchy and reward systems (Cohen & Bailey, 1997).
Another example for part-applicability of a model from behavioral and management literature is the similarity attraction model (Byrne, 1971). For existing teams, the main prediction is that diversity in characteristics such as values and personality limit the cohesion of a team, which negatively influences group functioning (Williams & O’Reilly, 1998). Another group of attributes is related to the amount of information available to a team. Diversity in attributes such as tenure, range of network and functional background increase the human capital and thus information availability and decision-making quality (Williams & O’Reilly, 1998). Although these two groups of variables match with the general idea of the conceptual model for entrepreneurial teams, the conceptualization and measurement of variables cannot be transferred since variables are mostly of demographic nature like age, tenure, sex and ethnicity.
An interesting fact about research on work teams is that studies on heterogeneity and homogeneity remain largely inconclusive with regards to the effect on performance (Williams & O’Reilly, 1998; Bowers, Pharmer & Salas 2000; Van Knippenberg & Schippers, 2007). Jehn, Northcraft & Neale
“Diversity research may concern any possible dimension of differentiation, but in practice diversity research has
primarily focused on differences in gender, age, ethnicity, tenure,
educational and functional background”
– Van Knippenberg & Schippers, 2007, p. 517
18 (1999) summarize that in some studies, homogeneous work groups outperform heterogeneous groups, whereas other studies predict the exact opposite result. Mellewigt & Späth (2002) note that benefits of heterogeneity including additional cognitive resources are offset by a higher likelihood of conflict within the team. Another reason for these puzzling might be that researchers do not yet understand the versatile and complex effects of different types of diversity and diversity in different individual and team characteristics. Van Knippenberg & Schippers (2007) remark that although conceptualizations of diversity have become more complex, much is still unclear about the precise effects. Paying increasing attention to mediators and moderators has not yielded fruitful results yet (Van Knippenberg & Schippers, 2007).
In line with Williams & O’Reilly (1998), they urge for the development of more in-depth theoretical frameworks that sheds light on the complex effects of diversity. Whether researchers use insignificant variables or overly simplistic models, the impact of diversity is still a mysterious area of research in work and top management teams. In the following sections, a
selection of studies will be used to build the conceptual model. The paramount problem with findings from teams in large organizations is that the research is mostly based on neoclassical theory, upper echelon theory or the resource-based view, thus most variables and concepts used are not applicable in the entrepreneurial context.
The dependent variable in most research on team performance is team effectiveness. Effectiveness can be measured at the individual, team, business unit or organizational level (Cohen & Bailey, 1997), with only the team level being applicable in this research. Team effectiveness can be categorized into 1) performance effectiveness in terms of quantity and quality of outputs 2) member attitudes and 3) behavioral outcomes (Cohen & Bailey, 1997, p. 243). In the entrepreneurial team context, only member attitudes and behavioral outcomes like employee satisfaction and commitment are applicable. Previous research further shows that diversity is likely to have a curvilinear effect, with some variables positively affecting performance and others that have negative impact (Williams & O’Reilly, 1998). The precise categorization of team characteristics will be established during the process of model building.
3.6 Effectuation
It is important to understand the relationship between effectuation theory and the model which will be developed. Effectuation theory describes three sets of means which entrepreneurs make use of to reach a number of possible, yet unknown outcomes (Sarasvathy, 2001). The means available are “Who the
“Until consideration is given to the
impact of different types of diversity in work groups, further advancement in our understanding of this
phenomenon will be difficult to achieve” – Webber & Donahue, 2001,
19 entrepreneur is”, “What he/she knows” and “Who he/she knows”. These categories can be translated into practical variables for research, but first the effectuation theory needs to be applied to teams. The entrepreneurial method stems from and is designed for research on individual entrepreneurs and has not yet been applied in papers on entrepreneurial teams.
This is surprising as the three concepts of the means of an entrepreneur can easily be applied to entrepreneurial teams. The first category represents the “identity” of the team or “Who the team is”, the second the “information” the team members possess, essentially “What the team knows” and the third category represents the aggregated “network” ties of the team “Who the team knows”. Thus the first group concerns the core values and motivation of the team, the second the experience and expertise and the third the network ties of team members. The three means that entrepreneurs use to build companies can thus be translated into three categories of team characteristics. They provide the logical basis for the model and determine the behavior of the team.
The second step is to link effectuation to the Golden Circle model. Successful organizations attract a following around a common “WHY”, a group of people brought together around a shared set of values and beliefs. Only then should companies look for people that have the skills they need, represented by “WHAT” they know. In term of effectuation, “WHY” represents team identification, the collective resource of “who the team is”. “WHAT” team members know is related to the other two assets of teams in effectuation, “what team members” and “who team members” know. Figure 3 illustrates the link between the “Golden Circle” and effectuation. The “HOW” layer of the circle is purposefully left out at this moment because it will be discussed in the section on “Team processes & interaction” (p. 23f.).
20 The above illustration shows that effectuation applies to entrepreneurial teams equally well as to individual entrepreneurs. With slight amendments, the entrepreneurial method is an excellent foundation to develop theories for entrepreneurial teams. One of the most important implications of using effectuation as the framework is that most variables used in previous research are irrelevant because they are based on managerial frameworks. On the other hand, it is precisely this shift of perspective that can lead to new insights about the effects of diversity in entrepreneurial teams.
4.0 MODEL DEVELOPMENT
The previous part provided relevant information on general issues discussed in entrepreneurial team, diversity and work group research. Building upon this foundation, the coming part gathers specific research findings relevant to establish a new model about the impact of diversity in different team characteristics on entrepreneurial team performance. In this regard, it is important to keep the three main concepts in mind that constitute the backbone of the model: the Golden Circle, the diversity constructs of separation and variety, and Effectuation. The notion of how particular sets of variables are related to team performance stems from the Golden Circle model. Diversity is defined according to the framework of Harrisson & Klein (2007) as described above. The perspective and theoretical foundation of this research root in effectuation theory.
This chapter will link the three concepts in a new conceptual model. Relevant variables will be identified, re-conceptualized and classified into a new, “golden” model of diversity. Secondly, hypotheses how the variables relate will be established, based on both research findings and on the basis of the Golden Circle. The aim is to merge empirical evidence of previous research with entrepreneurial concepts to be able to better explain relationships than existing concepts.
4.1 Information- and motivation-related variables
Research findings on diversity show an inconsistency of results, both in work and entrepreneurial teams (Webber & Donahue, 2001; Mellewigt & Späth, 2002; Polzer, Milton & Swarm 2002; Vyakarnam & Handelberg 2005; Van Knippenberg & Schippers 2007). This may be due to the application of generic concepts and misspecification of relevant variables (e.g. Van Knippenberg & Schippers 2007). On the other hand, some of the findings, if interpreted within the entrepreneurial context, can provide useful insight for the conceptual model. The challenge lies is separating applicable and non-applicable evidence.
Many scholars have come to the conclusion that heterogeneity is a double-edged sword (Webber & Donahue, 2001; Mellewigt & Späth, 2002; Boni & Weingart, 2012; Wasserman, 2012; Schjoedt et al.,
21 2013; Kaiser & Müller, 2013). Therefore authors recently began urging researchers and entrepreneurs to be aware of different types of diversity (Wasserman, 2012). Webber & Donahue (2001) distinguish highly- and less job related diversity, Wasserman (2012) distinguishes tangible and intangible differences, Schjoedt et al. (2013) distinguish deep- and surface level diversity. These distinctions acknowledge that there are two fundamentally different groups of diversity characteristics. The first group contains visible and tangible aspects like demographics, knowledge, network and education whereas the second group contains deeply rooted characteristics within team members like core values, attitudes and beliefs. Looking at the two groups separately, authors propose that whereas high diversity in the second group is detrimental, it is beneficial in the first group. This generally accepted relationship is depicted in Fig. 4.
Fig. 4: Impact of diversity in two major groups of variables on team performance; adapted from Pelled, Eisenhardt & Xin, 1999; Jehn, Northcraft & Neale, 1999; Van Knippenberg & Schippers., 2007; Schjoedt & Kraus., 2009; Boni & Weingart, 2012.
The underlying explanation for the positive impact of diversity in group one variables is that complementary technical and functional expertise and various backgrounds are positive due to the versatile demands of skills in a start-up (Wasserman, 2012; Boni & Weingart, 2012). This logical argumentation appears convincing, yet there is also economic reasoning behind these relationships that root in the resource-based view. In this view, firms are seen as idiosyncratic bundles of resources (Barney 1986) that can form the basis for sustainable competitive advantage under certain conditions (Barney
22 1991). According to this view, having more diverse team members increases social and human capital which positively influences the overall performance of the venture (Mellewigt & Späth; 2002, West, 2007, Shrader & Siegel, 2007). On the other hand, if these team members bring in the same or similar resources and capabilities, the effect can be assumed minimal. In conclusion, diversity in knowledge, skills and abilities (KSA) is predicted to have a positive effect on performance. Surprisingly, only two of the commonly tested proxy variables for KSA consistently show significant positive empirical impact across different studies. These two variables are educational background and functional/industry experience (Schjoedt & Kraus, 2009). Demographic variables such as diversity in age, gender, and race seem to have no significant impact (Schjoedt & Kraus, 2009). The reason for this contradiction between logical explanation and underlying theory on the one hand and empirical evidence on the other hand could lie in the misconceptualization of the variables that approximate the KSA group. A second reason may be a wrong underlying diversity concept.
The conclusion is that although this group of commonly researched variables could be directly related to the “WHAT” category of the Golden Circle, a closer examination of the exact variables is necessary. Therefore the KSA group will be re-framed into an information-related group of variables throughout the process of model development. The two empirically tested variables experience and education will be applied to the entrepreneurial context. These literature findings build a strong basis for further development of an information-related group of variables.
For the second group of commonly used variables, the logical argumentation predicts that similarity on these variables creates harmony and commitment and aligns team members behind shared goals (Van Knippenberg & Schippers, 2007; Boni & Weingart, 2012). Diversity, on the contrary, leads to dysfunctional conflict (e.g. Ucbasaran, doctoral work; Kaiser & Müller, 2013). Manifestations of the importance of core values, attitudes and believes (CBA) can be found in some definitions of entrepreneurial teams. They include common commitment and shared vision as a prerequisite for the existence of entrepreneurial teams (Schjoedt & Kraus, 2009). The concept roots in the “similarity attraction” theory as described by Byrne (1971). Though stemming from psychology, similarity attraction has been a major concern in work group research. Even in entrepreneurship research, evidence for similarity attraction in entrepreneurial teams is one of the most empirically tested and proven concepts. Aldrich, Carter & Ruef (2004) use the Panel Study of Entreprenerial Dynamics (PSED) to investigate mechanisms affecting group composition. The one mechanism they find proof for is “homophily”, the tendency to found with entrepreneurs that are similar with respect to gender, ethnicity and occupation (Aldrich, Carter & Ruef, 2004, p. 308). They conclude that team formation is driven by similarity, not difference. Negative effects associated with diversity in value-related variables are social categorization,
23 emergence of sub groups, lower trust and cohesion (Van Knippenberg & Schippers, 2007). More homogenous groups thus have higher cohesion and lower turnover than more heterogeneous groups (Van Knippenberg & Schippers, 2007).
Having established these relationships could lead to hypotheses development already, yet as has been pointed out, there are some important aspects missing in the conceptualizations of these sets of commonly used variables.
Wasserman (2012) makes an important remark about the role of network diversity. The focus of research and also that of founders lies on diversity of skill sets. Another important factor that is often neglected is diversity in network. Teams with diverse networks are predicted to have better access to various corporate partners like potential investor’s, clients and suppliers (Wasserman, 2012; Kim & Aldrich, 2005). The network of individuals and teams constitutes a large amount of the social capital (Mellewigt & Späth, 2002). Although not empirically proven, network diversity in entrepreneurial teams is assumed to have positive effects on team performance (William & O’Reilly, 1998; Gedajlovic et al., 2013). Ultimately, the group of information-related variables should not only represent “What team members know” but also “Who team members know”, thus network variables must be added to the group of information-related variables.
In conclusion, together with experience and education, network builds the group of
information-related variables, representing the “WHAT” layer of the Golden Circle.
Also for the second group of variables, a different concept will be used. Core values and beliefs are not the only variables related to team identification and the reason “WHY” people work for a start-up. Furthermore, CBA are difficult to test as they are deeply rooted within team members (Webber & Donahue, 2001). Wasserman (2012) and the PSED study test the motivation of entrepreneurs in relation to performance. This measurement can also be applied to teams as a proxy variable for CBA. The CBA group will therefore be reframed as a motivation-related group of items. Three sub groups that are taken from Wasserman (2012), the PSED study and own thoughts will make up this group.
For both groups, motivation and information, the hypotheses based on the Golden Circle and the literature findings can be stated as follows:
H1: High diversity in information-related variables positively influences team performance. H2: Low diversity in motivation-related variables positively influences team performance.
A discussion and description of the exact items tested in both groups follows in the methodology section.
4.2 Team processes & interaction
The dimensions “WHY” and “WHAT” have been categorized into two distinguishable sets of variables, motivation- and information-related variables. The part of the “Golden Circle” that is still missing is the “HOW” dimension. “HOW” an organization or team conducts business has largely to do with the processes it applies. In a team context, it applies to processes carried out together such as joint decision-making and problem-solving. Up to this point, there is considerable
confusion and conflict among scholars with regards to the relationship of information- and motivation-related variables. Schjoedt & Kraus (2009) believe that deep-level and surface-level characteristics are independent of each other and urge for separate exploration when examining entrepreneurial teams. This contradicts earlier conceptualizations around the trait models, in which a direct linkage between these two groups was
assumed (Donahue & Weber, 2001). Jehn, Northcraft & Neale (1999) find that informational diversity positively relates to actual workgroup performance. Interestingly, value diversity moderates this effect. This means that informational diversity is predicted to have a higher impact when the level of diversity in values is low. The same is valid for their social category variable. For completion, the full model of Jehn, Northcraft & Neale (1999) is displayed in Appendix C where Figure 21 shows this relationship. A limitation of their study is that the social category only embraces the variables age and gender, which are variables that have shown to be only marginally related to group performance in most studies (see e.g. Schjoedt & Kraus, 2009). Further, some of their variable measures are self-reported, which means there is a possibly same-source bias involved.
The model of Cohen & Bailey (1997) as discussed in the section on ‘diversity in work and top management teams’ (see Appendix B) provides the basis for a discussion on group processes and describes the relationship to “WHY” and “WHAT”. Applying the model of Cohen & Bailey (1997) to how information-related and motivation-information-related variables affect team processes is displayed in Figure 5. Team processes and interaction between team members thus takes a mediating role between diversity variables in the two groups and team performance. Not all relationships of the original model are transferred, which does not mean they don’t exist but rather that they are not relevant at this point of discussion.
“Many group
researchers have argued that effective group process is a precursor to effective group
performance” – Williams
25
Figure 5: Team processes influenced by information and motivation-related variables, adapted from Cohen & Bailey, 1997
Whereas Cohen & Bailey (1997) describe team processes only, team interaction is added because Mellewigt & Späth (2002) find empirical evidence that team composition affects team interaction. Team interaction includes variables such as cohesion, communication and conflict, which directly influence performance (Mellewigt & Späth, 2002). Team processes include decision-making, problem-solving and coordination of team members that also directly influence performance (Van Knippenberg & Schippers, 2007; Ucbasaran et al., 2003). Although mentioned separately in the literature, there is considerable overlap of processes and interaction variables, thus they will be treated as one group. Regarded as performance proxies, this group represents the behavioral performance outcomes (Van Knippenberg & Schippers, 2007) of the diversity level of variables in motivation and information variables.
Remembering the inconclusive results on the effect of information- and motivation-related variables offers space for new concepts. By assuming that both categories influence group processes rather than performance individually and directly, the influence of diversity in team characteristics and the role of team processes can be interpreted in a new light. If team processes are shaped by different levels of diversity in underlying characteristics and team processes are treated as behavioral performance outcomes, some of the confusion in the field may be resolved.
An article that supports the asserted relationship in the entrepreneurial context is an empirical longitudinal study on new technology-based new ventures. In their study, Shrader & Siegel (2007) show that team experience is related to strategy development. In line with this finding, Wasserman (2012) outlines that entrepreneurial teams with greater shared work experience have higher levels of social
“The key question in diversity research is how differences between work group members affect group processes and performance” –Van
Knippenberg & Schippers, 2007, p. 517
26 integration, a variable related to team interaction. Both findings strengthen the prediction that team processes are shaped by information-related variables.
A problem with the study of Shrader & Siegel (2007) is the approach. They use strategic management concepts and variables to test whether upper echelon theory applies in new ventures. This leads them to use the concept of strategy to approximate performance. The concept of strategy in a new venture differs substantially from that in large organizations. For example, the time horizon is shorter, uncertainty is higher and there is less information on past performance. In general, strategy is less important relative to execution in a start-up (e.g. Bhide, 1994). A second misconceptualization of the study lies in the choice of the dependent variables approximating new venture performance. Shrader & Siegel (2007) use profitability and sales growth, thus financial performance measures, which are measures less applicable in new venture performance. Accordingly, although they predict a long-term positive effect of team experience on performance, the evidence for a direct relation of team experience and venture performance is weak and inconsistent (Shrader & Siegel, 2007). Although the study proves the link between team characteristics and team processes in entrepreneurial teams, it shows that using the same variables and methodology as in management theory is likely to yield inconsistent overall results.
All in all, the model holds that team processes and interaction variables mediate the relationship between the two underlying groups of information- and motivation-related variables and team performance. Therefore diversity in motivation and information directly shapes team processes and interaction, but only indirectly influences team performance.
Even though the overall relationship is now clear, the exact factors that either positively or negatively influence team processes and interaction need to be developed. These cause-effect relationships will be examined by means of looking at conflict as an example in the next part and then applied to other variables to complete the model.
4.2.1 Processes and interaction - Conflict
In an empirical study, Kaiser & Müller (2013) discuss a central effect of heterogeneity in entrepreneurial teams, that of conflict. In the model developed so far, conflict would fall into the category of “HOW” related variables or the team processes & interaction variables group. There are several findings about different types of conflict and their causes and effects in teams and entrepreneurial teams of which some shall be discussed to draw a clear picture how process and interaction variables fit into the model.
Polzer, Milton & Swarm (2002) for example distinguish relationship and task conflict. Their essential finding is that whereas relationship conflict leads to social categorization with a negative or
27 moderating effect on team performance, task conflict can
influence performance positive at a moderate level. The cause for this positive effect is ascribed to team members that
bring in their individual thinking and acting due to diverse backgrounds and come up with differing alternatives, goals and priorities (Polzer, Milton & Swarm, 2002, p. 302).
Another interesting perspective on conflict is provided by Ucbasaran (Doctoral work) that looks at how leaders of jazz bands handle diversity and conflict. They find that jazz leaders seek to maximize diversity to maximize creativity, yet a natural consequence of this is “dysfunctional” conflict. Contrary to “functional” conflict that is associated with new ideas and creativity, dysfunctional conflict leads to high turnover in team members. In their model, functional and dysfunctional conflict are inextricably interlinked because the jazz leaders acknowledged that by bringing in diverse talents, dysfunctional conflict would arise. To handle the issue, leaders applied a framework to coordinate the team and align it towards common goals. The aim was then to achieve maximum diversity within that coordinative framework. Although this article includes a leadership perspective, the distinction of functional and dysfunctional conflict valuable as it shall categorize the two effects that process and interaction variables like conflict can have.
Kaiser & Müller (2013) distinguish two similar types of conflict, affective and cognitive conflict. Cognitive conflict is predicted to positively relate to performance because it for example avoids group think, fosters reconsideration of suggestions and decisions and generates a variety of perspectives. Whereas cognitive conflict is rather based on rational thinking, affective conflict happens on an emotional level. It is considered to have negative effect because it lowers commitment, can block strategic consensus and slow down decision-making. Kaiser & Müller (2013) cite previous research that shows both types of conflict “often occur simultaneously” (p. 5).
As can be seen throughout these studies, there seem to be negative and positive types of conflict. Whether called “relationship”, “affective” or “dysfunctional” conflict, there is conflict that negatively impacts team performance. On the other hand, “task”, “cognitive” and “functional” conflict is associated with positive influence. Adding this finding to the model results in the relationships as depicted in figure 6. The essential novelty in the way of thinking about these variables are the underlying causes for dysfunctional or functional process and interaction variables. Whereas some authors have described that both types of conflict are interlinked (Ucbasaran, doctoral work; Kaiser & Müller, 2013) and thus one cannot be present without the other, the view in this thesis will be that there are distinct causes for functional conflict and distinct causes for dysfunctional conflict. Diversity in information-related variables is believed to cause functional conflict and diversity in motivation-related variables is believed to cause
“Eizer K’negdo – a helper against him”
– Wasserman, 2012, on conflict within founding teams
28 dysfunctional conflict. This twist in thinking may resolve the dilemma that authors describe as the bidirectional effect of diversity. It also provides a possible explanation how functional conflict can be stimulated and dysfunctional conflict can be avoided by composing the team. Diversity in information must be maximized and diversity in motivation must be minimized.
Figure 6: The role of team processes and interaction: Conflict
Acknowledging that team processes & interaction variables mediate the relationship between information- and motivation-related variables in a positive and negative way is an important step in understanding the “double-edged sword” of the effects of team heterogeneity that researchers describe. Understanding the underlying causes and effects of team process and interaction variables a second, equally important step. Building upon the previously established hypotheses H1 and H2, the following hypotheses propose that high diversity in information-related variables and low diversity in motivation-related variables lead to maximum functional conflict and minimal dysfunctional conflict. Vice versa, low diversity in information-related and high diversity in motivation-related variables would lead to
maximum dysfunctional conflict and minimum functional conflict. The hypotheses state as follows: H3a: High diversity in information-related variables maximizes functional conflict.
H3b: Low diversity in motivation-related variables minimizes dysfunctional conflict.
4.2.2 Processes and interaction - Communication, Cohesion and Decision-Making
Based on the established example of (1) conflict, the assumption is that all team processes and interaction variables chosen for investigation are characterized by the same dynamics, influenced by either high or low diversity in team characteristics in the two groups of underlying variables. The following four variables are predicted to have “functional” and “dysfunctional” characteristics. These
29 variables are (2) communication (Mellewigt & Späth, 2002; Cohen & Bailey, 1997), (3) cohesion (Webber & Donahue, 2001; Vyankarnam & Handelberg, 2005; West, 2007; Harrison & Klein, 2007), (4)
decision-making (West, 2007). As can be seen, all variables have been under research in previous studies. The
difference lies in the conceptualization and way of measurement of these variables. In light of the previous explanation, it is possible to foster the positive extreme of functionality and to minimize the negative extreme of dysfunctionality.
To be more precise with predictions, each variable is shortly examined in turn to establish fitting hypotheses. Cohesion is a variable that is deemed to be related mainly to less job-related variables (Webber & Donahue, 2001), in this case motivation-related variables. On the other hand, information diversity may also influence cohesion in that it lowers shared background. Cohesion, like conflict, can be functional and dysfunctional. Cohesion is functional when team members share resources and value the work of other members. Thus diversity in information-related variables such are predicted to have positive effect on functional cohesion. On the other hand, cohesion can become dysfunctional if the team sticks together too much. Wasserman (2012, p. 99) states that the crucial aspect in an entrepreneurial team is “the development of a cohesive working relationship that include opposition and the tension that arises from partners with different skills, experiences, responsibilities and motivations.” (P. 99). Thus an example for dysfunctional cohesion is when loyalty among team members prevails over customer or supplier demands, which can negatively influence team performance. Cohesion is dysfunctional where information or facts become undermined by too much loyalty among team members leading to suboptimal outcomes for the company. Hypothesis H4a and H4b describe the described relationships:
H4a: High diversity in information-related variables maximizes functional cohesion. H4b: Low diversity in motivation-related variables minimizes dysfunctional cohesion.
A similar line of argumentation can be applied to communication in team interaction. Communication among team members is functional when relevant issues are discussed and communication is efficient because team members communicate within the same frame of reference. On the other hand, communication is dysfunctional when team members share redundant information or do not share a common frame of reference, which means they communicate on different technical or emotional levels. When diversity in motivation is high, communication is predicted to become dysfunctional because team members do not share information relevant to fulfilling their common motivation. Irrelevant and misleading information flow is the effect of such dysfunctional communication. Communication “without understanding each other” leads to low communication in the long run, which
