“An Act of Balance: The Impact of Team Cognitive
Style Composition on Team Creativity and Time
Efficiency”
Master thesis Msc BA - Strategic Innovation Management
June 2017
by
DANIËL NIJKAMP s3058689
Supervisor: Prof. Dr. Dries Faems
Co-assessor: Prof. Dr. B.A. Bernard Nijstad
University of Groningen Faculty of Economics and Business MSc BA Strategic Innovation Management
Abstract
Introduction
In R&D settings, the degree of performance is a result of the ability of teams to come up with creative solutions to emerging problems. At the same time though, teams should make sure that important deadlines and milestones are reached. Existing literature points to this tension as a balancing act between team creativity and time efficiency (Kratzer, Gemuenden & Lettl, 2008). On the one hand, it is emphasized that creative problem solving is time-consuming with the risk of causing delays. On the other hand, an emphasis on time efficiency is often described as a factor that hampers a creative climate (Amabile, Conti, Coon, Lazenby & Herron, 1996).
Whereas several studies implicitly or explicitly refer to this trade-off (e.g., Chang & Birkett, 2004; Kratzer et al., 2008; Bstieler & Hemmert, 2010), studies on how teams can deal with this trade-off are rare. In this study I aim to address this issue by investigating a factor that is argued to influence this tension. Cognitive styles refer to individual differences in organizing and processing information and experiences (i.e. analytical versus intuitive) (Sagiv, Arieli, Goldenberg & Goldschmidt, 2010). Existing research found links between different types of cognitive styles and team creativity and time efficiency outcomes (Woodman, Sawyer & Griffin, 1993). Nonetheless, it is yet unexplored how managers should optimally configure their R&D teams in order to balance the opposing demands of creativity and efficiency. Finding the optimal configuration might help R&D managers to deal with this tension within teams. Therefore, I want to address this gap by investigating the following question: How does team composition in terms of cognitive styles impact team creativity and time efficiency?
generation and creativity at the individual level. However, some studies suggest that cognitive styles can also explain team-level behavior and effectiveness (Visser, Faems, Visscher & De Weerd-Nederhof, 2014). These studies have conceptualized team cognitive style as a “team’s pooled preferences” (Post, 2012, p. 559). Given that the pursuit of creative goals requires the consideration of a broad spectrum of possible solutions, paying attention to a wide range of external information, and divergent thinking (Chang & Birkett, 2004; Mumford, 2000; Ford, 1996), creativity is often linked with an intuitive processing style. At the same time, it is argued that intuitive processing and associated divergent thinking may slow down innovation projects (De Visser et al., 2014). Based on these arguments I hypothesize that R&D teams with a stronger intuitive information processing style will achieve higher levels of team creativity, while at the same time achieving lower levels of time efficiency.
Conversely, analytic processing is associated with the use of routines, logic, focus and convergent thinking (Epstein, Pacini, Denes-Raj & Heier, 1996). While these attributes are deemed necessary to accomplish productivity goals (Chang & Birkett, 2004; Simons, 1995), they suppress departure from current beliefs and might therefore restrict idea generation (Visser et al., 2014). Therefore, I hypothesize that R&D teams with a stronger analytical processing style will achieve lower levels of team creativity, while achieving higher levels of time efficiency.
have asked team members to provide information about each NPD project in which they are or have been involved.
The findings show clear support for the positive effects of intuitive processing on team creativity, and analytical processing on time efficiency. In contrast, no significant negative effects are found for both cognitive styles on either creativity or efficiency. Furthermore, a significant positive correlation found between team creativity and time efficiency questions the supposed tension between the two. All in all, these findings extent the literature on cognitive styles and innovation in teams by suggesting that team composition of cognitive style significantly influences a team’s balance between creativity and efficiency. Hence from a managerial perspective, the findings provide valuable recommendations on how to configure R&D teams as to optimize performance in terms of creativity and efficiency.
In the next section of this paper I will discuss the theoretical background underlying this research and present the hypotheses. Thereafter, I will further elaborate the methodology used to test the hypotheses. Finally, I will discuss the results of this study and provide theoretical and managerial implications.
Theoretical background
and innovators (Kirton, 1976), (2) activists and reflectors (Kolb, 1976), (3) analysts and wholists (Riding & Buckle, 1990), and (4) sequential and connective styles (Jabri, 1991). Although the labels differ, each of these theories is built on the concept of two fundamentally different ways of processing information (Visser et al., 2014). Relying on the insights of Epstein et al. (1996), this study makes a conceptual distinction between intuitive and analytical ways of processing information. In the next paragraphs I aim to explain how these two different cognitive styles may affect the creativity – time efficiency trade-off.
Intuitive Versus Analytical Thinking
Cognitive Styles on the Team Level
Whereas a major part of the literature has researched the innovation performance implications of individuals, organizations increasingly rely on teams for their R&D projects (Ancona & Caldwell, 1992; Post, 2012). Scholars that have conducted team-level analyses of cognitive styles (e.g., Kearney, Gebert & Voelpel, 2009; Post, 2012; Visser et al., 2014), conceptualize team cognitive styles as “a pooled concept that reflects the average preference of team members to process information in a particular way” (Visser et al., 2014, p. 1169). Given that these scholars frame team cognitive style as the average product of its team members’ cognitive preference, it is assumed that any member entering or leaving the team with an above-average analytical/intuitive processing style will have an influence on the team’s cognitive style. As elaborated in the methods section, this conceptualization yields an unreliable image of team cognitive style within the scope of my sample. Therefore, I have chosen to conceptualize team cognitive styles as the average perception of a team’s cognitive style among its team members. Insightful studies in the field have provided evidence showing that team cognitive styles can substantially influence innovative output (Post, 2012; Visser et al, 2014). However, these studies do not disentangle the opposing demands of creativity and efficiency incorporated in R&D projects.
Balancing Creativity and Time Efficiency
creativity might be directly affected by their cognitive style (Woodman et al., 1993; Amabile et al., 1996). Nonetheless, scholars emphasize that although necessary, creativity alone is not a sufficient condition for innovation (Amabile et al., 1996). Existing research emphasizes that in order to be successful, R&D teams face a constant tension between enhancing team creativity on one hand, and dealing with time efficiency on the other hand (Hoegl & Gemuenden, 2001). Consequently, the management is often trapped between these two contradictory performance assets (Kratzer et al., 2008).
Scholars who have attempted to define the relationship between time efficiency and creativity within teams, have come up with mixed results. One study used three experiments to demonstrate that groups under a high need of closure performed less creatively (Chirumbolo, Livi, Mannetti, Pierro & Kruglanski, 2004). Additionally, the same study showed that conformity pressure mediates the negative relationship between time pressure and creativity. Similar results were found by Kelly & Karau (1993), who demonstrated that group members working on a joint task, displayed greater levels of creativity when under mild than under acute time pressure. Others found an inverted U-shaped time pressure-creativity relation for employees who scored high on openness to experience, while simultaneously receiving support for creativity (Baer & Oldham, 2006). In turn, Hsu & Fan (2010) argue that time pressure should be seen as a moderator between organizational innovation climate and creative outcomes. Their study found that in a strong organizational innovation climate, time pressure hinders creative outcomes. However, that in weak organizational innovation climates, time pressure enhances creative outcomes.
that determine success in innovation and the degree of R&D performance (Amabile et al., 1996; Kratzer et al., 2008). Relying on the insights from cognitive styles and R&D literature, I expect that the composition of R&D teams may substantially influence this tension. Below, hypotheses are developed on the differential impact that team cognitive styles may have on team creativity and time efficiency.
Hypotheses
The Impact of Team Cognitive Styles on Team Creativity
Creativity requires divergent thinking, taking into account different perspectives and combining previously unrelated matters (Amabile, 1996). Mumford & Gustafson (1988) argue that the generation of creative ideas is the result of cognitive and motivational processes within individuals, albeit enhanced by interactions within teams. A few studies have examined the relation between individual’s cognitive style and creative outcomes (e.g., Masten & Caldwell-Colbert, 1987; Kirton, 1994). In most of these studies, creativity has been linked to the innovative style of Kirton’s (1976) innovators – adaptors scale (e.g., Keller, 1986; Lowe & Taylor, 1986). Similarly, Noppe & Gallagher (1977) found that field independent individuals were more creative than field dependent individuals.
2001). By simultaneously handling information from various viewpoints, intuitive thinkers are more likely to generate new solutions to problems (Isaksen, 1987). Extending these insights to the team level, I therefore expect that teams characterized by high levels of intuitive information processing are likely to display higher levels of team creativity.
Conversely, analytical information processing is argued to hamper the identification of new information, data or approaches (Visser et al., 2014). In particular, Goncalo & Staw (2006) argue that analytical thinking may suppress the departure from current beliefs and values, thereby restricting idea generation. These individuals tend to be rather risk-averse and are therefore more likely to reject radical ideas involving high uncertainty (Kirton, 1989). Their intolerance for mistakes has been argued to hinder creative thinking (Miron-Spektor, Erez & Naveh, 2011). Based on these arguments and extending them to the team-level, I expect that teams characterized by high levels of analytical information processing are likely to display lower levels of team creativity. This leads me to the formation of the following two hypotheses:
Hypothesis 1: The stronger the team’s intuitive information processing, the
stronger the team creativity
Hypothesis 2: The stronger the team’s analytical information processing, the
weaker the team creativity
The Impact of Team Cognitive Styles on Time Efficiency
important role of productivity (Chang & Birkett, 2004). Only companies capable of timely delivering R&D outcomes can cope with the ever-increasing pace of today’s competitive business arenas (Hoegl & Gemuenden, 2001; Kratzer et al., 2008). This puts pressure on managers, knowing that having sufficient time resources is one of the major ingredients for stimulating creativity (Amabile, 1996).
The pursuit of efficiency goals requires focus, logical thinking, the use of routines, and convergent thinking (Chang & Birkett, 2004). These attributes strongly resemble the characteristics of individuals with an analytical cognitive style, who favor logic, and a controlled, systematic problem solving approach (Armstrong & Priola, 2001). Whereas analytical information processing is argued to hamper the execution of explorative activities, it proved very productive for executing exploitative activities and triggers a focus on efficiency (Visser et al., 2014). Furthermore, research on practices that improve efficiency of new product teams found that the setting of a clear, engaging direction was an effective practice (Bstieler & Hemmert, 2010). Particularly when time efficiency is a primary goal, having consistent project goals keep teams focused and on track (Barczak & Wilemon, 2003). Empirical research has shown that individuals with a predominantly analytical cognitive style tend to favor such structure and are more task-oriented (Kirton, 1976; Witkin & Goodenough, 1977). Therefore, these individuals are considered to be more efficient at bringing ideas into practice (Olson, 1985). Extending these insights to the team-level I expect that teams characterized by high team-levels of analytical information processing will reach higher levels of time efficiency.
less structure and more ambiguity (Kirton, 1976). In their work environment, they tend to be nonconformist, avoiding reaching conclusions rapidly (Armstrong & Priola, 2001). Therefore, Olson (1985) explains that intuitive thinkers are valuable in the ideation phase, but not so efficient in bringing ideas into practice. Hence, extending these insights to the team-level, I expect that teams drawing more on intuitive information processing will display lower levels of time efficiency. This leads me to the formation of the following two hypotheses:
Hypothesis 3: The stronger the team’s analytical information processing, the
stronger the time efficiency
Hypothesis 4: The stronger the team’s intuitive information processing, the
weaker the time efficiency
Methodology
Research Settingproject documentation system, all R&D projects initiated in the past 3 years were identified. In the end, 95 projects were identified.
Sample
For each single project, the project manager and the organizational members that made a significant contribution on that particular project were identified. Based on time-accounting data present in the documentation system, team members that spend at least 20 hours on a project were selected. Next, project managers verified whether the selected members made a significant contribution and could be considered part of the project team. The team was then defined as the group of all organizational members responsible for the development of a product or product component in a particular project.
After this process of linking individuals and R&D projects, surveys were distributed to all involved team members. This survey consisted of two parts. Firstly, team members were asked about their personal backgrounds and characteristics. In the second part, team members were asked to provide information about each of the R&D projects they were involved in. Additionally, project managers were asked to provide information about each project they had managed. To help the respondents, clear information was provided about each of the projects they had to provide information on. On average, each respondent was involved in 2.75 projects.
Measures
Dependent variables: team creativity and time efficiency. To measure team
creativity, I followed the example of Farh, Lee & Farh (2010), who adapted two creativity items from Oldham & Cummings (1996) and added a third item. Hence, team members were asked to indicate the extent to which the team output was “creative” and “original and practical” and whether the team output demonstrates that the team is capable of using existing information or resources creatively. To measure time efficiency, I adopted two variables previously used by Bstieler (2005) and asked team members (1) how quickly and time efficient the project was undertaken; and (2) whether the project was launched on time. Both team creativity and time efficiency were measured on a 7-point Likert-scale ranging from 1 (strongly
disagree) and 7 (strongly agree). An exploratory factor analysis was run on all items
to assess reliability. The results of the two-factor model in Table 1 show significant factor loadings for both the 3 creativity items (α = .82), and the 2 time efficiency items (α = .89).
Table 1 Results of Exploratory Factor Analysis
Item Team Creativity Time Efficiency
Going by the status of the project, the team output can be considered creative
.893
Going by the status of the project, the team output can be considered original and practical
.866
The team output demonstrates that the team is capable of using existing information or resources creatively
.771
The project is/was undertaken quickly and in a time-efficient manner
.925
The project adheres/adhered to its time schedule (i.e., follows closely to its schedule / launched in time)
Independent variables: team analytical and intuitive processing. To measure
the degree to which teams process information intuitively and analytically, I adapted two items from the rational-experiential inventory of Epstein et al. (1996). One was adapted from the “Faith in intuition” scale and asked respondents on a 7-point Likert scale to what extent their team liked to rely on their intuitive impressions. The other was taken from the “Need for cognition” scale and asked members on the same scale to what extent their team relied on a logical mind. Next, these team-level scores were averaged into team analytical- and intuitive scores. This approach differs from previous scholars in the field (e.g., Post, 2012), who averaged team members’ individual analytical- and intuitive-processing scores into a team analytical style measure and a team intuitive style measure. The reason for this choice is because only a fraction of all team members returned the questionnaire (<50% for all projects). Subsequently, following this approach would provide an unfair representation of the team cognitive style scores. Therefore, I have chosen to average team level analytical- and intuitive scores. This is in line with my conceptualization of team cognitive styles as the average perception of a team’s cognitive style among its members.
Control variables. Firstly, I will control for organizational tenure as this has
Furthermore, I will control for any influences of project radicalness. Radicalness refers to the degree of novelty of a project (Danneels & Kleinschmidt, 2001), which includes both the project’s core technology and the target market (Garcia & Calantone, 2002). Existing research (Tushman & Smith, 2002) argues that more radical projects are associated with explorative activities, which are closely related to intuitive thinking. Subsequently, it can be assumed that more radical projects demand higher levels of creativity. To measure this, respondents were asked to indicate whether the core technology and the target market were known to the company, new to the company or even new to the world. Scores were than averaged for each project and included as dummy variable to conduct analyses. Lastly, some scholars emphasize that team creativity and time efficiency may be affected by cooperation with external partners, such as other companies and Universities (Alves, Marques, Saur & Marques, 2007). Therefore, I also added a dummy variable to control for effects of external cooperation within projects (1 indicating external collaboration, 2 indicating no such cooperation).
Manager ratings. The main objective of this study is to disentangle between
Therefore I have distributed a third survey, specifically aimed at project managers. In this survey two items from the team member questionnaire were taken to indicate project managers’ perception of their team’s creativity and efficiency levels. Measured on a 5-point Likert-scale, managers were asked (1) to what extent they thought the team output could be considered highly creative, and (2) to what extent the project was on schedule.
Additionally, I followed prior research (Bonner, Ruekert & Walker, 2002; Hoegl, Weinkauf & Gemuenden, 2004) in defining project performance as the extent to which a team is able to meet established project objectives. Subsequently, I adopted the 5-item scale from Hoegl et al. (2004) to capture overall project performance. All managers were asked to evaluate project performance using this 5-point Likert-scale (α = .98). See Table 2 for a full description of the items and the results of the factor analysis, justifying the use of this instrument. In the end, for 44 out of the 59 projects in my sample a manager survey was returned.
Table 2 Results of Exploratory Factor Analysis
Item Overall Project Performance
Going by the status of the project, it can be regarded as successful .978
Going by the status of the project, the project team is satisfied with its performance
.972
Going by the status of the project, all project goals have been achieved .962
Going by the status of the project, our top management can be fully satisfied with the progress of this project
.958
Results
Having collected the data as discussed in the methodology, statistical analyses have been conducted in order to answer the research question. The next paragraphs will display the outcomes of these analyses, as well as robustness checks and validity and reliability measures.
Descriptive Statistics
Table 3 displays descriptive statistics for the continuous variables, whereas Table 4 shows the correlations between them. As can be seen in Table 4, a positive significant correlation exists between team creativity and time efficiency. Also, a positive significant correlation between team creativity and intuitive information-processing, as well as a positive significant correlation between time efficiency and analytical information-processing can be observed. Lastly, project size in terms of hours spend on the project is significantly and positively correlated with the number of members assigned to a project team.
Table 3 Descriptive Statistics
Variable Mean Standard Deviation N
Team Creativity 4.8300 .76519 58
Time Efficiency 3.6473 1.43256 59
Team Intuitive Processing 4.0858 1.03972 59
Team Analytical Processing 5.3136 .71619 59
Project Size (hours) 2737.3051 10106.90216 59
Project Radicalness 2.0339 .55604 59
Mean Company Experience (years) 20.8814 8.38530 59
Impact of Intuitive and Analytical Information Processing
Table 5 summarizes the findings of the general linear model analyses, in which team creativity and time efficiency were used as dependent variables. As shown by model 3, a significant positive relationship was found between team’s creativity levels and their intuitive information-processing levels (B=.289, t=2.867, p <.01). This is in line with my first hypothesis. In contrast, no negative relationship was found between team’s analytical information-processing and team creativity, as hypothesized in H2. Instead, a positive, but non-significant effect was found.
Regarding time efficiency, the results in Table 5 confirm my third hypothesis by pointing out a positive relationship between team’s analytical information-processing and time efficiency (B=.620, t=2.397, p <.05). In turn, the results show no support for my fourth hypothesis, which suggested a negative relationship between time efficiency and team’s intuitive information-processing levels. Instead, the results display a positive, but insignificant relation.
Finally, with regards to the control variables, only one significant effect can be observed. Merely model 2 suggests a negative relationship between project radicalness and time efficiency (B=-.613, t=-1.718, p <.1). This rejects any significant influence of team size, project size, external cooperation or company experience on the dependent variables.
Manager Ratings
(as rated by team members). According to Table 6, the only significant effects come from the control variables company experience and project radicalness.
With regards to overall project performance, Table 7 displays the results of the ANOVA analyses in which overall project performance has been taken as dependent variable. From model 1, it can be observed that only manager ratings’ of time efficiency (B=.455, t=3.669, p <.01) are positively related to project performance. In turn, this positive relation turns insignificant when taking team member ratings of time efficiency in model 2. Team creativity proves insignificantly related to performance, regardless of whether the rater was a team member or manager. Additionally, model 2 shows that the only significant direct relationship between team cognitive style and overall project performance is a negative one. Taking team member ratings of efficiency and creativity as input results in a negative relationship between analytical information processing and overall project performance (B=-.592,
t=-2.229, p <.05). Lastly, model 2 displays a positive relationship between company
experience and overall project performance (B=.056, t=2.310, p <.05).
Robustness Checks
of .69 for time efficiency meets the recommended cut-off value (Bliese, 2000; Glick, 1985).
Discussion and Conclusion
Existing literature on R&D in teams has repeatedly pointed at the importance of balancing both creativity and time efficiency in order for teams to be successful. While several scholars emphasize a tension between the two, a practical recommendation on how to deal with this trade-off is lacking. The results of this study show that team composition in terms of psychological factors has significant predictive value in explaining project performance. In particular, the analyses suggest that differences in team creativity and time efficiency outcomes may be explained by team cognitive styles. By disentangling these two often-regarded contradicting performance measures, this study aims to extent both R&D and cognitive styles literature, and provide practical recommendations to managers on how to compose their project teams. Firstly, I will discuss the impact of cognitive styles on team creativity and time efficiency separately, followed by the theoretical implications of the combined findings. Thereafter, I will discuss the use of manager ratings in this study and how my findings relate to the creativity-efficiency trade-off as proposed in the literature. Then, I will provide practical recommendations to managers on how to optimally compose R&D teams, by discussing the managerial implications of my findings. Lastly, I will point out the limitations of this study and address future research directions.
Cognitive Styles and Creativity
related with an intuitive team cognitive style. In other words, R&D teams that deploy high levels of intuitive information processing can be expected to produce high levels of team creativity. In contrast, scholars have argued that an analytical cognitive style restricts the generation of new ideas (Goncalo & Staw, 2004) and hampers exploration activities (Visser et al., 2014). Therefore, I expected analytical information processing to be detrimental for team creativity. However, the results show no significant evidence for any negative relationship between an analytical cognitive style and team creativity. Theoretically, this means that teams who deploy high levels of analytical information processing, will not see any negative effects of their preferred cognitive style in terms of team creativity. Rather, on a creativity scale they can expect to be outperformed by teams that benefit from a more intuitive processing style. A possible explanation for these findings may be found by looking at structure approach towards creativity (Sagiv et al., 2010). According to this study, intuitive individuals are more creative than systematic ones under free conditions. However, the authors argue that systematic (i.e., analytic) individuals could become as creative as intuitive ones if they worked under highly structured conditions. Given that the company used to collect data in this study has a fairly high structured approach towards innovation, perhaps this explains why analytic processing is not hampering creativity.
Cognitive Styles and Efficiency
findings. In other words, deploying high levels of analytical information processing proves beneficial to time efficiency within R&D projects. On the other hand, relatively little attention has been paid to any links between intuitive information processing and time efficiency. Given that intuitive thinkers tend to favor less structure and more ambiguity (Kirton, 1976) I expected a negative relationship between intuitive cognitive style and time efficiency. However, no significant evidence was found to support this hypothesis. This means that whereas the literature provides indications that a team’s preference for intuitive information processing is harmful for efficiency, there is no proof this is the case.
Theoretical Implications
Manager Ratings
Additionally, some scholars have pointed at the value of supervisory ratings when assessing performance (e.g., Anderson, Potočnik & Zhou, 2014; Yuan & Woodman, 2010). Therefore, the same hypotheses have been tested with manager ratings of team creativity and time efficiency. Interestingly, the results of these analyses do not yield any significant relationships between team cognitive styles and both performance measures. This implies that R&D project managers hold different perceptions over teams’ creativity and efficiency performance than the team members involved. It could also be that no significant relationships were found, because the model connects team member perceptions of team cognitive style with manager perceptions of creativity and efficiency. Perhaps if manager perceptions of team cognitive style were available as well, this would yield significant relations. Either way, it might be interesting for future research to investigate what causes differences in perception of team creativity and time efficiency among members and managers of R&D teams.
Overall Project Performance
Looking at major studies in the field of creativity, this is not completely surprising. For example Amabile et al. (1996) state that creativity should be seen as a starting point, rather than a sufficient condition for innovation. In this sense, creativity can definitely be regarded a catalyzer for success, however it is not a guarantee for performance by itself. Eventually, performance depends on how efficient a team puts it creative capabilities to work.
The Creativity-Efficiency Trade-off
creativity and time efficiency might be the result of a weak organizational innovation climate.
Most importantly, the findings question the current perception in the literature that regards simultaneously pursuing efficiency and creativity goals as problematic. Thereby this study extends the innovation literature and opens the discussion for viewing creativity and efficiency as mutual reinforcing elements. This means that rather than composing teams to manage a tension, managers have to critically evaluate their primary project goal.
Managerial Implications
greatly enhance the team’s efficiency, intuitive thinkers have proven to be inductive for team creativity. Hence, both contribute in their own way, and finding the right mix might be the ultimate key to success.
Limitations and Future Research
Besides the afore-mentioned limitations, it must be stressed that the data used in this study is based on subjective perceptions. Also, the team-level variables that I have used to draw my conclusions were established by aggregating individual scores. However, the ICC(2) value for team creativity mentioned in the results section, does not meet the recommended cut-off value (Bliese, 2000; Glick; 1985). This leaves room for discussion on whether or not group-aggregation for this variable is justified. Applying more objective measures for team creativity, time efficiency and team cognitive styles would therefore be a logical step for future research. The latter could for example be achieved by making use of yet existing tests to determine cognitive style, rather than asking team members to assess their own or their team’s preference. An example of a more objective approach to measuring efficiency could be comparing the time, money, and the number of people involved in a each project.
Furthermore, it can be argued that the sample, comprising 95% males, relatively old of age and a pre-dominant analytical style, was fairly homogeneous in these aspects. This does not only hold for the sample used to collect data, but proved to be the case for the vast majority of the company. Therefore, it might be interesting for future research to see if the results of this study also hold for companies with more varying demographics.
be useful to search for models that explain a bigger portion of the variance and check if the main findings of this study still hold under those circumstances.
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