13
Master thesis
Effect of cognitive styles on overall project
performance in NPD teams: moderated by the
intensity of interdepartmental collaboration
By J. Spronk
Inhoud 0. Abstract ... 2 1. Introduction... 2 2. Theoretical foundation ... 5 2.1. Team composition ... 5 2.2 Cognitive theories ... 6
2.2.1 Dual process theory ... 6
2.2.2 Cognitive-experiential self-theory ... 6
2.3 Definition concepts ... 8
2.3.1 Overall project performance (DV) ... 8
2.3.2 Cognitive styles: Intuitive and analytic (IV) ... 8
2.3.3 Intensity of interdepartmental collaboration (MV) ... 9
2.4 Hypothesis ... 10
2.4.1 Relation between cognitive team average and overall project performance ... 10
2.4.2 The role of intensity of interdepartmental collaboration on the relationship between cognitive styles and overall project performance ... 14
3 Methodology ... 16
3.1 Sample and data collection ... 16
3.2 Measure... 16 3.2.1 Dependent variable ... 16 3.2.2 Independent variables ... 17 3.2.3 Moderator variable... 18 3.2.4 Control variables ... 18 4 Analysis... 20 4.1 Sample fit ... 20 4.2 Descriptive analysis... 21 5 Results ... 23 6 Discussion ... 26 6.1 Discussion of results ... 26
6.2 Limitations & future research ... 28
7 Conclusion ... 30
0. Abstract
In this modern world the importance of NPD projects is increasing for several reasons. Consequently the subject of project team composition is becoming more important. While several researchers investigated the question how to compose a successful theme, this paper wants to dig a bit deeper into the psychological aspects within a group. Cognitive styles or information processing modes are the center of attention. This paper tries to exemplify how a group cognitive style influences the overall project performance. In addition, this thesis tries to find answers to the question how the intensity of interdepartmental collaboration moderates the relation between a team’s cognitive style and the overall project performance. The results are based upon a dataset which consist out of 232 respondents in 73 NPD teams. Findings suggest that the interaction effect between intuitive cognitive and interdepartmental collaboration has a positive effect on overall project performance. Surprisingly, the direct effect between the intensity of interdepartmental cognitive styles and overall project performance is negative. Thus, probably it is important when to collaborate with different departments with regard to different cognitive styles.
1. Introduction
Large companies set up major initiatives involving teams or groups with the desired goal to improve their products that could create an advantage of their products compared to others. Especially, project teams are particularly prevalent in an attempt to achieve this competitive advantage. Project teams could be defined as ‘temporary entities that execute specialized time-constrained tasks and then disband (e.g., new
product development)’ (Sundstrom et al, 2000). The importance of project teams is underlined in research
by their capacity to do multiple activities simultaneously, rather than sequentially, which saves time; this could be one the reasons why, companies are expanding their use of project teams in response to time-based competition (Stalk & Hout, 1990). Furthermore, literature suggests that project teams successfully deal with solving complex issues regarding new technologies with the help of interdependencies between functional departments (Song et al., 1998). In result, the pervasive uses and advantages of project teams in organizations led to great interest of researchers in the topic of project teams. Considering the obvious willingness of companies to succeed in their projects, it would be important to examine the overall performance of a project.
focuses upon the team. One driver which is expected to influence overall project performance is the interplay between employees within a team. As a result, several scholars focused on how to compose a project team.
Team composition is the configuration of member attributes in a team (Levine & Moreland, 1990) and research suggests that it has a powerful influence on team outcomes (Kozlowski & Bell, 2003). The understanding of these member attributes could shed a better light on team composition. Consequently team composition could serve as a valuable tool for selecting and constructing effective teams. Literature creates a distinction in team composition between surface- and deep-level team members’ attributes (e.g. Bell, 2007). Surface-level variables (also referred to as overt demographic variables, see Bell, 2007) are easily to observe, easily measurable. In contrast, deep-level composition variables (Harrison, Price & Bell, 1998) are less readily apparent to observe or measure. Most studies who examined the performance of team characteristics have focused on demographic variables, like education and functional background, age, and organizational tenure (e.g., Ancona and Caldwell, 1992; Hulsheger et al., 2009; Lovelace et al., 2001). For example, Ancona (1992) suggests that the more heterogeneous the team in terms of tenure, the higher the overall project performance. Despite demographic differences have been shown valuable to team performance, underlying psychological characteristics have been found to be better predictors of team performance over time (Bell, 2007; Harrison et al., 2002). To give an example, Bell (2007) found evidence that personality factors (e.g agreeableness and conscientiousness) had a positive effect on the team performance. Mostly ignored in research, however, is the cognitive aspect of the capacity of team members within a NPD project. Literature state that the cognitive style is of significant importance when dealing with complex issues and achieving project success (Agor, 1986; Armstrong, 1999; Doktor, 1978; Kirton, 1988; Leonard and Strauss, 1997; Taggart et al., 1985).
According to Messick (1984), cognitive styles are the individual differences in the way of organizing and processing information. Relying on this term, research provides us with two different ways of organizing and processing information: the intuitive and the analytical cognitive style. While most research has focused upon the impact of cognitive styles on the individual, there is firm evidence that team members’ cognitive styles influence team performance (Armstrong et al., 2011). Based upon the former prediction, it is believable that the members’ cognitive styles could have an impact on the performance of the project.
different departments stimulate cooperation which should result in improved product quality, costs and time to market (Katzenbach and Smith, 1993). Under the condition of varying intensities of interdepartmental collaboration, this paper addresses the question which cognitive team style performs best.
The purpose of this thesis is twofold, namely to examine (I) the effect of a project team’s cognitive styles on overall project performance, and exploring (II) how the intensity of interdepartmental collaboration moderates the relationship between the project team´s cognitive styles and the overall project performance.
2. Theoretical foundation
This chapter starts with a broader overview of the context of this thesis, namely team composition. After that, the applied cognitive theories will be explained. The theory about the development of cognitive theory gives the foundation for the formulation of the hypothesis. Next, is the explanation of the most important concepts. The last part of this chapter provides reasoning for the hypotheses.
2.1. Team composition
Team composition is the configuration of member attributes in a team (Levine & Moreland, 1990). Critical in the understanding of the concept of team composition is ‘the diversity among individuals’. Diversity refers to differences between attributes of individuals that consequently influence the perception on the individual (Jackson, 1992; Triandis, Kurowski, & Gelfand, 1993; Triandis, Hall, & Ewen, 1965; Williams & O'Reilly, 1998). In theory, creating teams with diverse talents seems likely to result in positive team outcomes (Cox & Blake, 1991; Devine, Clayton, Philips, Dunford, & Melner, 1999; Easely, 2001). However, practice teaches us that the use of diverse teams creates unique challenges and often results in suboptimal performance. In other words, team diversity can potentially lead to positive organizational synergy, but those idiosyncratic expertise and experience could also result in difficulties resulting from coordination, tension and intra/intergroup conflict (Jackson, May, & Whitney, 1995; Jehn, Chatwick, & Thatcher, 1997; Jehn, Northcraft, & Neale, 1999). Hackman (1987) stated with regard to team composition that:
In general, team composition is thought to be related to team performance because it affects the amount of knowledge and skill team members have to apply to the team task—in terms of both task completion and working interdependently In addition, the diversity of the team could lead to benefits, but this is not
without challenges.
relationship between team-members (e.g. gender, ethnicity). The author states that individual differences between team members directly affect task performance by influencing the objectives of the team. In addition, those individual differences may also affect performance indirectly by influencing the social interactions between team members.
2.2 Cognitive theories
2.2.1 Dual process theory
Over the years researchers developed the theory of cognitive styles which held the assumption that the two modes of cognitive styles are at ends of the continuum (e.g Kirton, 1976). Recent studies suggest otherwise. They claimed that cognitive styles could be projected as independent, parallel and interactive (Kahneman, 2003), which resulted in the occurrence of the dual process theory. In brief, dual process theory states that people are capable of possessing both modes of processing (rational and experiential) at the same time (Pacini and Epstein, 1999). Consequently, this means that both cognitive styles contribute
in human being behavior which could vary independent from low to high contribution in both processing styles (Pacini and Epstein, 1999). Derived from this dual processing theory is the cognitive-experiential
self-theory (CEST; Epstein 1998).
2.2.2 Cognitive-experiential self-theory
According to Epstein (1996) the proposition of CEST is presented as people that process information by two parallel, interactive systems: the rational (or analytic) and the experiential (or intuitive) system. Explained by CEST theory is the difference in processing information. Epstein (1996) defines both modes of information processing as (1) the analytic system, which operates at the conscious level and is intentional, analytic, primarily verbal, and relatively affect free, and (2) the intuitive system which is considered as to be automatic, preconscious, holistic, associationistic, primarily nonverbal, and intimately associated with affect.
perceived as being more able to cope with casual ambiguity (Kirton, 1976), while they will be ill-suited for problem solving which requires logical analysis (based on their intuitive cognitive score).
2.3 Definition concepts
2.3.1 Overall project performance (DV)
Overall project performance is definable as the ability of a team to meet established quality, cost and time objectives (Gemuenden, 1990; Schrader and Goepfert, 1996; Gemuenden and Lechler, 1997). In other words, the project performance could be seen as the extent to which a project team accomplishes its goals or mission (Devine & Phillips, 2001). Within a project team, team members must interact interdependently in order to be successful. For that reason, team members have to engage in several team processes or “interdependent acts that convert inputs to outcomes through cognitive, verbal, and behavioral activities directed toward organizing task work to achieve collective goals” (Marks, Mathieu, & Zaccaro, 2001, p. 357). In order to achieve success with any project team, a project team requires members who can complete the technical portion of the team goals or mission (i.e. possess specialized expertise on the development of new products), as well as effectively navigate team processes (i.e how to communicate with each other) (Bell, 2007).
2.3.2 Cognitive styles: Intuitive and analytic (IV)
A way to explain the behavior of people in teams is through examining different cognitive styles. Messick (1984) defines cognitive styles as consistent individual differences in ways of organizing and processing information. Important to note is the innate nature of cognitive styles and the lack of influence upon cognitive styles over time. Furthermore, the definition of Messick (1984) has been seen as modes of organizing and processing information. Messick (1984) refers to ‘organizing’ as cognitive styles who contribute to the selection, combination and sequencing of substance and process, and he means by ‘processing’ the role of cognitive styles in regulating the direction, intensity, range and speed of functioning.
have provided ground for this reasoning; whereas participants marked as possessing a predominantly analytic cognitive style lead to expressed behavior such as: a more structured, less ambiguous and more technique-oriented environment (Kirton, 1976), more task oriented (Witkin & Goodenough, 1977), more impersonal (Pascual-Leone, 1989) and more dominant (Allison, Armstrong & Hayes, in press). As where the predominant intuitive individuals are likely to behave more emotionally expressive, submissive, relatively friendly (Witkin & Goodenough, 1977), warmer, more personal (Pascual-Leone, 1989); prefer less structure and more ambiguity in their work environment (Kirton, 1976). Because of these differences in actual behavior and personal characteristics, it is likely that cognitive styles are not limited to the individual but also affect the environment in which they display their behavior.
2.3.3 Intensity of interdepartmental collaboration (MV)
Literature has a clear consensus that high levels of cross-functional collaboration improve new product development processes (e.g. Gupta & Wilemon, 1986; Kahn, 1996; Moenaert et al., 1994; Souder, 1977). This cross-functional collaboration could be termed interdepartmental collaboration. Literature state that this depends on linking, which means that a complex array of specific insights must be gathered and brought together (Dougerthy, 1992). According to Dougherty (1992) there are several barriers which inhibit product development, which prevent people from frame-breaking learning and from gathering and connecting diverse insights. At the organizational level, routines (Nelson and Winter, 1982) can inhibit new product development. These could be defined as regular and predictable behavior patterns, which prevent NPD through (1) their effect on the organizational memory (= how things are done in that organization); (2) represent a network of practices which are difficult to alter; (3) and are standards which keep managers from changing. However, only a few scholars have investigated this but focused more on culture and structure (e.g. Galbraith 1982; Kanter 1983), and not in particular on new product development.
insights. Because of departmental specialization, certain issues would be understood best by that specific thought world, but the same thought world would also ignore essential information which is needed to complete the project (Dougerthy, 1992).
2.4 Hypothesis
The first two hypotheses are dedicated to finding a direct relation between both cognitive styles in a team and overall project performance. The last two hypotheses predict a relationship between the cognitive team average and overall project performance, which are moderated by the intensity of interdepartmental collaboration.
2.4.1 Relation between cognitive team average and overall project performance
Research in group dynamics suggests that individual characteristics are important in determining group effectiveness (Armstrong, 1999; Shaw, 1981). As cognitive style influence personal behavior through the way in which processing information results in actual expressed behavior and personality characteristics (Grigorenko & Sternberg, 1995; Riding & Rayner, 1998), this thesis presumes that the intuitive and analytic modes of processing information in NPD projects teams result in different average group scores of overall project performance. The argumentation is based upon the work context of NPD; this refers to the technical nature and the complexity of the NPD process. Because of different preferences between team members in expressed behavior and personality characteristics based on their mode of processing information, cognitive theory could partly explain why certain team members in projects perform better or worse under the conditions of NPD processes.
integrate their interpretations into the mental model and subjective theories that guide their actions’ (Hayes & Allinson, 1998, p. 850). Furthermore, cognitive styles are innate and stable characteristics. This means that people cannot easily shift between styles to adapt to environmental demands (Clapp, 1993). Consequently, a match between the job demands and one’s style preferences is expected to yield positive outcomes (e.g., job satisfaction, organizational commitment, career success), whereas a mismatch is expected to lead to negative outcomes (e.g., increased turnover, less motivation, higher levels of work-related stress, interpersonal conflicts) (Fuller & Kaplan, 2004; Sadler- Smith & Badger, 1998). Thus, in the situation that there is a match between one’s cognitive style preferences and job demands, performance of the individual is likely to increase.
As theory describes that a match between work context and cognitive lead to better performance, how does the NPD context and cognitive styles interact with regard to performance. Jablokow and Booth (2006) tested this assumption that individuals in NPD context performed better when there was a match between work context and their cognitive style. In their study, they used KAI (Kirton’s Adapter-Innovator) theory to increase the effectiveness of a high-performance product development organization. With regard to the NPD environment, they placed intuitive styled persons in research and design and total quality management. The analytical persons were assigned in the group of maintenance of the current production system. They encountered that every individual exhibited more creativity if placed within an environment that matched their cognitive style. A citation from their study describes the importance of cognitive theory in project performance from the perspective of the manager: ‘In general, [this study] supports the proposition that engineering managers and team leaders can learn to mentor individuals and tailor work assignments based on problem solving levels and styles, leading to improved performance overall” (p. 330). In addition, Kirton (2003) emphasizes that not only managers, but that each individual could be seen as problem solvers and thus each person is an agent of change.
vice-presidents, and people with responsibility for introducing new products within research and development departments (NPD). Literature examined, in addition, how cognitive style influence people’s work environment preferences (Allinson & Hayes, 1996; Hirsch & Kummerow, 2000; Kirton, 1994; Whooten et al., 1994). The main overlapping finding from these studies is that analytic thinkers prefer to work in well-defined, stable, structured, ordered, and relatively impersonal situations, in which they can function within existing rules and procedures and prevailing structures. In contrast, people with an intuitive style favor unstructured, changing, highly involving, innovative, flexible, dynamic, relatively personalized environments, in which they can work autonomously and in freedom from rules and regulations.
On the group-level, research state that mechanistic and organic settings could result in higher overall project performance dependent on the fit between the task environment and the cognitive style (Burns & Stalker, 1994). Where organic settings are unstructured and ambiguous, a high intuitive team average probably performs better. As where mechanistic setting are more structured and less ambiguous leads to better performance when there is a high analytical team average (Burns & Stalker, 1994) . The NPD context, however, seems to be a dynamic environment (e.g. Olin & Shani, 2003). It has been characterized as complex to organize and manage. A former study emphasized a trend which led to the transition from a traditional (structured) approach to a more flexible NPD approach for developing products on ‘internet time’. The author, defines internet time as ‘the ability to respond to environmental future evolutions in markets and/or technologies that are occurring rapidly (Iansiti and MacCormack, 1997; MacCormack et al., 2001). These flexible approaches are characterized by the ability to respond to new information that arises during the course of a new product’s development and by designers who begin the process without knowing how the precise idea will end. According to Olin & Shani (2003) this will definitely impact the competence and profile of the engineers. Given this situation, I assume that the NPD teams are complex to organize and manage and thus need flexibility.
NPD environment (good fit with an unstructured, changing and flexible environment), thus the overall project performance will increase. In contrast, a high average score on the analytic cognitive style in a group means that the team members perform better in a NPD environment weak fit with a unstructured, unchanging and flexible environment, thus the overall project performance will decrease.
Given the NPD context:
H1: The higher the intuitive team average, the higher the overall project performance.
2.4.2 The role of intensity of interdepartmental collaboration on the
relationship between cognitive styles and overall project performance Dougherty (1992) sets out that the difficulty of interdepartmental collaboration is partly due to different thought worlds. Out of qualitative research, she found that each team member from different departments had essential information for the development of the products, but they focused on different aspects of the development and conceives of the whole in a different way. The analogy with the eyewitnesses by accidents was made by Dougherty (1992).
She states that:
‘It is more like the tales of eye witnesses at an accident, or of individuals in a troubled relationship—each tells a "complete" story, but tells a different one’.
Despite the potential benefits of interdepartmental collaboration, departmental thought worlds separate essential information which limits the possibility of comprehensive understanding. The inward focus of team members from different departments reduces the possibility of learning and gaining essential information. According to Dougherthy (1992) to overcome the focus of the different thought worlds on their own (Fleck, 1979), managers have to encourage collaborative and collective action. As the cognitive styles sees a difference in expressed behavior with regard to collaboration (e.g. intuitive style person’s tend to be more personal), this could lead to an improvement of project performance. While several researchers studied how to coordinate the behavior of individuals in interdepartmental NPD groups (e.g Johnson, 17, p. 241), only few have focused on the innate stable cognitive styles of these individuals within the project group.
with others and question the thought world of authority (Allinson & Hayes, 1996). With regard to high levels of interdepartmental collaboration, their outward focus increases the possibility of learning, gaining essential information which lead to better project performance (Dougherthy, 1992). In contrast, analytical individuals tend to prefer less personal and more formal work relationship. They function better alone than within a team because of their inward focus. With respect to high levels of interdepartmental collaboration, their inward focus reduces the possibility of learning, gaining essential information which reduces the performance of the project. In the case of low intensity of collaboration between departments, essential information won’t be shared and team members do not learn from each other which results in a
lower performance of the project. For a intuitive cognitive team, their outward preference will lead to missing essential information which is not shared by others and essential information and learning aspects are not recognized which result in lower project performance. For the analytical thinkers in a project team, essential information and learning is not noted by them. Thus, this won’t have an effect on the overall project performance.
H3a: When the intensity of interdepartmental collaboration is high, then the positive relationship between the intuitive group average and the overall project performance becomes more positive.
H3b: When the intensity of interdepartmental collaboration is high, then the negative relationship between the analytical group average and the overall project performance becomes more negative.
H4a: When the intensity of interdepartmental collaboration is low, then the positive relationship between the intuitive group average and the overall project performance becomes negative.
3 Methodology
3.1 Sample and data collection
As part of a larger study, this study examines the influence of cognitive styles on overall project performance moderated by the intensity of interdepartmental collaboration. The sample in this study is based on the methodology used in the study of Gladstein et al. (1992). Due to limited time and upcoming deadlines, we (I and two other masterstudents) received a dataset from our supervisor. This dataset has been gathered by a group of researchers. In total, the dataset consist out of 102 NPD teams gathered from four Dutch technological companies in different industries (rubber tires, sensor and controls, membrane technologies and pipeline system industries). All four firms have provided access to the researchers in their documentation system of all the NPD projects that had been conducted in the past five years. Next to that, the researchers obtained time-accounting data of all projects. This enabled them to compose a list of all the members who participated on the projects. A prerequisite to be able to participate was that the objective had to be to develop a product or product component in a project setting. This was verified by the project managers.
Some details about the total sample (N = 102). The researchers distributed 352 questionnaires, which result in 261 returned questionnaires (82%). Teams were included only if at least two-third of the team members had responded. For this reason the total sample was reduced to 95 project teams. The respondents’ background was divided into engineering or research and development (74%), the residual of the respondents were mostly from manufacturing or marketing.
3.2 Measure
3.2.1 Dependent variable
Overall project performance. In this study, I define overall project performance as the ability of a team to
variable by calculating the mean score of the individual factor scores of the team members. A high mean on this variable indicates a high score on overall project performance and a low mean is indicative for a low score on overall project performance.
3.2.2 Independent variables
Cognitive styles, experiential (intuitive) and rational (analytical). To measure the degree to which NPD
team members process information intuitively, I used the ‘Faith in intuition’ scale (Epstein et al., 1996; Pacini and Epstein, 1999). For analytical processing of team members, the ‘Need for cognition’ scale has been used (Epstein et al., 1996; Pacini and Epstein, 1999). In both cases, the selection was based on the highest factor loadings, which were found in the latest version of the ‘Need for cognition’ and ‘Faith in intuition’ instrument (Pacini and Epstein, 1999).
This study examines the appropriateness of the item by (1) by conducting a exploratory factor analysis for each original dimension (by extracting one factor); and (2) by checking the reliability of both group of items; According to Field (2005), the KMO have to be above 0,5 to speak of an adequate sample. This was the case in both scales (Faith in Intuition, KMO = 0,806; Need for cognition, KMO = 0,769). In this study, the amount of items for both scales has been changed from 10 to 9. For the reason of low communality scores (below 0,5) and low factor loadings (below 0,6). The reversed item: ‘I don’t reason well under pressure’ has been deleted because of that reason. The results are displayed in Table 2 and 3. To compute the variables intuitive cognitive team and analytic cognitive team, I calculated the mean scores on both scales of all team members.
Table 2 Faith in intuition dimension: Results of exploratory factor analysis (a = 0,817)
Communalities extraction (Eigenvalue =1)
Factor loadings
I like to rely on my intuitive impressions. 0,535 0,732
Using my gut feeling usually works well for me in figuring out problems in my life.
0,564 0,751
I believe in trusting my hunches. 0,605 0,778
Intuition can be a very useful way to solve problems.
0,555 0,745
I often go by my instincts when deciding on a course of action.
Table 3 Need for cognition dimension: Results of exploratory factor analysis (a= 0,847)
Communalities extraction (Eigenvalue =1)
Factor loadings
I like to rely on my intuitive impressions. 0,622 0,789
Using my gut feeling usually works well for me in figuring out problems in my life.
0,666 0,816
I believe in trusting my hunches. 0,724 0,851
Intuition can be a very useful way to solve problems.
0,775 0,880
3.2.3 Moderator variable
Intensity of interdepartmental collaboration. This variable measures the question how the intensity of
interdepartmental collaboration moderates the relationship between the groups’ cognitive style and the overall project performance. Based upon two items from earlier research (De Visser, 2013), the intensity of interdepartmental collaboration will be measured. The first item investigates the use of interdepartmental collaboration in NPD project, varying between yes or no. The second item measures the intensity of the interdepartmental collaboration. This could vary from 1 ‘Very intensive’ to 5 ‘Not intensive’. To compute the variable intensity of interdepartmental collaboration, I calculated the mean scores of the intensity of the second item of all team members if they collaborate with other departments.
3.2.4 Control variables
For NPD teams, project group size and organization tenure are likely to be of particular importance to project performance (Keller, 1986).
Organizational tenure Previous studies have found significant influences of organizational tenure on
Project group size Given the technical nature and complexity of the product development process, project
4 Analysis
4.1 Sample fit
Before analyzing the results, it is considered important to check how normal the independent and
dependent variables are distributed. The Shapiro-Wilkonson test has been used to test for normality of the distributions. The different companies function as four different groups. The results show that all
components are normally distributed, except the intuitive group average for company A (p = 0,01). I take this into account when examining and discussing the results. Furthermore, a Levene’s test was conducted to test for equality in variance. The output showed some significant results for the variables analytical group average (p = 0,08) and overall project performance (p = 0,041). This means that the samples from the different companies are not equal in their variance, which makes the results less robust. This lack of homogeneity in variance will also be taken into account in the discussion of the results.
4.2 Descriptive analysis
For this study, a subset of 78 project teams and 242 respondents were used to find statistical prove for the relation between cognitive styles and overall project performance in a NPD context. This number has been reduced to 7
3
because of incomplete questionnaires with regard to the dependent, independent and moderator variable(s).
This resulted in a total sample of 73 project teams with 232 respondents divided over four companies. The average age of the respondents in the sample is 41,73 years. As where the average group size is 3,72.In self-report measures, reviewers continue to cite common method bias as worrisome (Spector, 2006). To test against common method bias (CMS), Harman’s single factor test could give initial evidence if this is a problem. Luckily, CMS is not a major problem in this study because the variance of all the variables is limited to 26,0%. Another concern is the influence of other independent variables on the tested independent variable, also called multicollinearity. With regard to the risk of multicollinearity, I
standardized the variables and tested the VIF scores for potential threats. Table 4 gives an overview and shows that multicollinearity is not a threat since the variables do not exceed 10 (Hair et al., 1995).
Table 4 Collinearity Statistics (Dependent variable: overall project performance)
Variable VIF
Zscore: Intuitive mode 1,678
Zscore: Analytical mode 1,307
Zscore: Project group 1,059
Zscore: Company experience 1,138
Zscore: Interdepart. collaboration 1,165
Zscore: Intuitive mode * Zscore: IC 1,568
Zscore: Analytical mode* Zscore: IC 1,260
Table 5 Descriptive statistics (N=73) Mean Std. Deviation Overall project performanc e Intuitive group average Analytical group average Interdep. collaboration Organizati onal tenure Overall project performance 3,6771 0,5583 - Intuitive group average 4,5888 0,6339 0,077 - Analytical group average 5,2748 0,7391 0,042 0,150 - Interdep.. collaboration 2,6421 0,9094 -0,309** -0,062 -0,116 - Organizational tenure 14,788 4 8,13054 0,140 0,130 -0,062 -0,283* -
5 Results
In this exploratory study the field of cognitive styles and their effect in teams on overall project performance moderated by the intensity of interdepartmental collaboration has been investigated. To compute the strength of the relationship, General Linear Modeling has been used. The choice for GLM has been based upon the categorical (Company A, B, C and D) and the continuous variables that are present in the model. Table 6 gives an overview of the results of General Linear Modeling (GLM).
hypothesis 4b builds further on the presumption that hypothesis 1 en 2 are supported. In contrast to hypothesis 3a, when there is low intensity of interdepartmental collaboration then the increase in intuitive team average leads to a decline of the performance of the project. Hypothesis 4a considered this negative effect. For this reason, hypothesis 4a is partly supported. The interaction effect between the analytical group average and the intensity of interdepartmental collaboration has resulted in no significant relationships. Therefore, I reject hypothesis 3b. Hypothesis 4b assumes that there is a relationship, but that this is not affected by interdepartmental collaboration. Because of the non-existing relationship between analytical team average and overall project performance, no evidence is found that it is not affected by the intensity of interdepartmental collaboration. Therefore, I reject this hypothesis. Next to the continuous variables, this model also took the different companies into account. Table 6 indicates that there are significant differences in overall performance in favor of Company D compared to Company A. For the other companies (Company B and C), there were no statistical differences between them and Company D.
Table 6 GLM (B) (Dependent variable: Overall project performance)
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
Intercept (Company D) 0,339 0,486* 0,519* 0,583** 0,567** 0,625**
Company A -0,763** -0,761** -0,762** -0,927** -0,637* -0,685*
Company B -0,144 -0,430 -0,490 -0,547 -0,605 -0,695
Company C -0,318 -0,547 -0,591 -0,644 -0,700 -0,776
ZProject Group size 0,029 0,024 0,026 -0,024 0,013
ZCompany Experience 0,179 0,190 0,201 0,179 0,202
ZIntuitive group average 0,065 -0,053 0,034
ZAnalytical group average 0,148 0,148 0,106
ZInterdep Collaboration (IC) -0,284** -0,249** ZIntuitive * ZIC 0,225* ZAnalytical * ZIC -0,089 R2 8,0% 9,8% 10,3% 12,2% 22,5% 19,6% Adj. R2 4,0% 3,1% 2,1% 4,2% 11,5% 8,1%
Figure 1The effect of intuitive team average on the overall project performance at different intensity-levels of interdepartmental collaboration.
Table 7 Hypothesis Hypothesis Supported/Rejected 1 Rejected 2 Rejected 3a Partly supported 3b Rejected 4a Partly supported 4b Rejected 0 0,2 0,4 0,6 0,8 1 1,2
low med high
6 Discussion
6.1 Discussion of results
This study has two goals. The first was to examine if there was a direct relationship between the cognitive team average (whether analytical of intuitive) and the overall project performance. The second goal was to examine if the intensity of interdepartmental collaboration played a role on the relationship between the cognitive team average and the overall project performance. Some findings were quite surprising. The findings did not reveal a direct effect of cognitive team average on overall project performance. However, the findings suggest that the moderator variable has an effect on the cognitive team average and overall project performance.
project performance. In the explorative setting, they state that a high analytical team average scores lower on performance than a low analytical team average. Surprising is that de Visser (2013) state that both high and low analytical processing in a team is beneficial in terms of performance. This is probably due to the nature of the projects (e.g. solving technological problems). The rejection of both hypothesis 1 and hypothesis 2, however, suggest that the NPD project need more specific classification in the projects to see when it performs better. Therefore it is interesting to discuss how cognitive styles affect performance when the interdepartmental collaboration gets more intense.
According to Keller (2001) the cross-functional makeup provides the advantages of multiple sources of communication, information and perspectives. Literature has a clear consensus that high levels of cross-functional collaboration improve new product development processes (e.g. Gupta & Wilemon, 1986; Kahn, 1996; Moenaert et al., 1994; Souder, 1977). According to Cuijpers et al. (2011) inter-departmental collaboration increases the exchange of information thereby benefiting innovation processes and outcomes. However, the results in this study contradict this consensus in literature. The findings in this study suggest that: the more intense the interdepartmental collaboration, the lower the project performance. At the same time, Cuijpers et al. (2011) argues that interdepartmental collaboration has also been identified as a source of increased costs (e.g. project delays). These costs come forth out of the different task priorities and persuasion of incongruent objectives. In addition, differences in educational backgrounds could also harm the project performance. Termination of the project could be the consequence of the rise of dysfunctional conflict due to interdepartmental collaboration. Other papers also emphasis the difficulty of interdepartmental collaboration. For example, Dougherty (1992) state that different thought worlds is not easily shared and different though worlds are not easily accepted by others.
nature of the projects (e.g. solving technological problems) in the sample does not need interdepartmental collaboration to achieve higher scores of overall project performance. The argumentation for this reasoning is that the project needs analytical persons within the team to solely solve complex issues which require unique expertise only possessed by themselves and not by team members from other departments. So, these analysts collaborate with others who do not have the needed expertise to solve problems or come with better solutions. Their preference to work in an impersonal environment (Kirton, 1994), therefore doesn’t stimulate them to perform better and therefore it doesn’t have an effect on project performance.
In the case of low intensity of interdepartmental collaboration, a low intuitive group average results in better performance than a high intuitive group average. This could be interpreted as when the project team gets more intuitive (on average), a more personal work environment doesn’t create the essential information and learning because essential information and learning is prohibited by low intensity of collaboration with other departments (Dougherty, 1992). This partly supports hypothesis 4a. For the analytical team average under the condition of low intensity of interdepartmental collaboration, the increase in performance doesn’t depend on the amount of collaboration between other departments. It could be interpreted that a high analytical team solely focuses on their own expertise and doesn’t need the input of other departments to perform.
6.2 Limitations & future research
The field of cognitive styles in NPD teams is relatively new. Therefore, the results are preliminarily and come with several limitations. These limitations could be the starting point for further research. From a methodological perspective, reliability and validity could not be assured. One reason is due to the small amount of projects (N=73). Although this gives a good impression, a larger dataset would give a better overview of the significant differences. Furthermore, the data consists out of four different companies, each company provided data for approximately 15 projects. The results are, therefore, less robust because of the differences between those companies. For instance, the used definition of overall project
Another point is the subjective perception of overall project performance. In addition, the subjective items rely on projects finished over the past 4 years. The elder the date of the finished projects, the less reliable and valid are the results. This 5-scaled item of overall project performance gains reliability and validity if these measures were objectively measured. Limited by the given dataset, only the intensity of interdepartmental collaboration is measured by 1-item. This could perhaps be extended by items explaining with which departments has been collaborated or cooperated. Various scholars has investigated in which departments collaboration lead to performance increases (e.g. Song et al., 1998), but not in the interaction with both processing styles.
7 Conclusion & managerial implications
This study contributes to existing literature in two ways. First, it shows that the intensity of interdepartmental collaboration doesn’t have to impact overall project performance positively. Second, highly intuitive teams tend to perform better when collaborating with different departments. As where highly analytical teams probably do not see the advantage of interdepartmental collaboration. In addition, there are some interesting managerial implications.
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