1 The effect of time pressure in project teams on the relationship between functional diversity and
overall project performance in NPD projects.
Master thesis
Medy van Dijk S1432389
Supervisors:
Georgiana Balau Dr. Matthias de Visser
Second supervisor:
Dr. Yeliz Eseryel
Groningen June 24, 2013
Wordcount: 7080
2 Abstract
This article examines the moderating role of time pressure on the relationship between functional diversity and overall project performance in NPD project teams. It is argued that the level of functional diversity positively influences overall project performance, because heterogeneous teams are able to come up with new ideas due to the different “thought worlds” which are present. Time pressure in terms of the mean level of workload of team members is argued to negatively moderate this relationship. Different tasks and demands from various projects will inhibit good integration within each project and this will result in a lower score on overall project performance. The results do not support the hypotheses, but do support other literature which is able to explain these outcomes. The outcome of this study is that workload positively moderates the relationship between functional diversity and overall project performance. The optimal level of diversity is also moderate; overall project performance will become lower as functional diversity increases. The study shows that the more time pressure is present, the better the project teams seem to communicate in order to meet (interim) deadlines with a higher overall project performance as a result.
3
Table of contents
Introduction ... 4
Literature review ... 6
Functional diversity ... 6
The impact of functional diversity on overall project performance ... 8
The moderating role of time pressure on the relationship between functional diversity and overall project performance ... 9
Methodology ... 10
Data ... 10
Measures ... 11
Methodology ... 12
Results ... 15
Discussion ... 17
Limitations of this study ... 18
Suggestions for further research ... 18
Conclusion and recommendations ... 20
References ... 20
Acknowledgements ... 27
4
Introduction
Project based organizations have become important over the past few decades; firms that are part of growth industries tend to have increased R&D intensity and also tend to organize development and production activities as projects (Söderlund, 2008), research also has shown that project life cycles are shortening; products and systems are becoming more complex and thus R&D activities are increasing, and needs to be successfully managed by project teams (Söderlund, 2008). The R&D activities occur in new product development (NPD) project teams. Firms pursue NPD in order to achieve competitive advantage and enhance its performance trough the development of new competences or the
exploitation of existing competences (Danneels, 2002; De Clercq et al., 2011), fill a growth gap or utilize new technologies (Griffin and Page, 1996). Cohen and Bailey (1997) have defined project teams as a social entity which is embedded inside a larger system and defined as such by its members and out standers. Because of the importance of these teams, knowing how to optimally make use of project based NPD in combination with its workforce, knowledge about the composition of project teams is an important asset for organizations.
Many NPD project teams are functional diverse, members of different departments work together which enables the sharing of knowledge and recourses that are already present within the firm (Workman, 1993; De Clercq and Sapienza, 2001; Bunderson, 2003), and overall project performance is an important indication on the extent to which a team is able to meet organizational objectives;
effective functionally heterogeneous teams are vital for innovative success of organizations (Hoegl and Gemuenden, 2001; Hoegl and Parboteeah, 2003). Many researchers have already examined various aspects which may influence the overall project performance of these kinds of project teams such as demographic in terms of age, gender, and race (Pfeiffer, 1983; Bantel and Jackson, 1989;
Jackson et al., 1993; Tsui et al., 1992, Ancona and Caldwell, 1992). There are two main literature streams with opposing opinions on the impact functional diversity may have on overall project performance. One stream states that involvement of several functional areas of expertise in teams is considered crucial for a high quality outcome (Ancona and Caldwell, 1992; Bantel and Jackson, 1989;
Pelled et al., 1999; Sethi, 2000), because it is positively related to team performance in terms of effectiveness and efficiency (Bantel, 1994). The other stream states the opposite and believes that not functionally diverse teams perform better because of their mutual understandings they already have due to the shared backgrounds, and thus are able to cooperate more harmoniously (O’Reilly et al., 1989; Zenger and Lawrence, 1989; Regans and Zuckerman, 2001).
Another popular subject in NPD literature on functional diversity is the level of integration and communication within project teams (Olson, et al. 2001; Kahn, 1996). Needless to say it is important that teams communicate in order to come up with new products, this is especially important in functional diverse teams because members have different tacit knowledge which must be
communicated to the rest of the project team (Doughtry, 1992; Griffin and Hauser, 1996). When this
5 integration is high within a functional diverse team, its members will have a shared vision and
collective goals which will positively impact the overall project performance (Song and Montoya- Weiss, 2001).
However, no attempt has yet been made to quantify the association between functional diversity and the moderating influence time pressure may have on its relationship with overall project performance. Employees might be pressured to work on multiple projects at the same time, which puts a strain on their ability to comply to their workload (Zika-Viktorsson et al., 2006). Previous research on different relations between functional diversity, time stress and overall project performance has been done by Keller (2001) and Sethi (2001). Keller (2001) studied the impact of cross functional diversity in project teams and found that functional diversity has an indirect effect through job stress on cohesiveness. He argues that this is the result of functional divers team members who need to work together in stressful situations that are the result of speed-to-market pressure (Keller, 2001). Sethi (2001) studied functional diversity as a team characteristic and its influence on new product quality and found that it has no effect. In the same study he also hypotheses a direct effect of time pressure on new product quality and also did not find a direct effect on new product development (Sethi, 2001).
So far, there has been little discussion about the impact time pressure may directly have on the relationship between functional diversity and overall project performance; it is important to address this issue because nowadays it has become a major aspect in businesses as industries are becoming more dynamic. Today’s society and the current economical state demand employees and businesses to swiftly react on changes of the market, which is vital to survive because of great uncertainties which threat jobs, incomes, homes, and education (Cooper, 2012). Another aspect which puts a strain on employees and businesses is the increasing pressure to continuously making sure that products are up- to-date according to the latest technological developments, which causes an increasing pressure from management on employees to work more hours and under many uncertainties (Cooper, 2012). Also, time pressure has been mentioned to be very relevant to study because different projects might be partly dependent of each other (Zika-Viktorsson et al., 2006). Literature has shown that stress is caused by this workload can lead to anxiety, frustration, job dissatisfaction and even depression (Spector, 1987). However, other literature has shown that stress that is caused by workload might actually have a positive impact on performance because of the demands certain levels of work might ask. (LePine et al., 2004; Beehr et al., 2000).
This paper seeks to address the influence time pressure may have on the direct relationship between functional diversity and overall project performance in NPD project teams. Its goal is to make two specific contributions: the first is to clarify the influence of functional diversity on overall project performance. The second contribution is to understand which influence time pressure has on
functionally diverse teams and whether this positively or negatively moderates the relationship between functional diversity and overall project performance. The following sections will provide the
6 theoretical background and the hypotheses will be development subsequently, the methodology will be presented and followed by the result of this research. The main research question will be:
What is the effect of time pressure in project teams on the relationship between functional diversity and overall project performance in NPD projects?
Literature review
Functional diversity
Functional diversity is one aspect which is studied in the field of organizational demography (Pfeffer, 1983). This field focuses on demographic attributes that are only present in organizations and which influence behavior of employees independently from their individual attributes (Lawrence, 1997). The topic of diversity in NPD teams has already been thoroughly examined by scholars in organizational literature and many definitions have been drawn up.
The two major perspectives on diversity which are often referred to in literature, are the information and decision making perspective and the social organization perspective (Simons and Rowland, 2011); the former refers to aspects which are job related such as education, functional expertise, and organizational tenure. These are considered surface-level attributes because they are task related and not demographic (Horwitz, 2005; Simons and Rowland, 2011). The latter refers to demographic aspects which refer to age, ethnicity, and gender. These are considered deep-level because they are inheriting dimensions which make up a person’s personality (Horwitz, 2005; Simons and Rowland, 2011).
Following this definition, this paper will focus on functional expertise, which refers to the different kinds of departments such as marketing, R&D, or manufacturing which are represented mostly in new product development projects (Brettel et al., 2011). Another definition which is also widely used in literature to name teams which consists of multiple departments is cross-functionality (Keller, 2001; Pinto et al. 1993). Functional expertise is part of the information perspective on diversity because it refers to the differences in task orientated backgrounds of team members (Jehn et al., 1999); they have deep expert knowledge on certain areas of the organization and thus different backgrounds, a result of this is that a cross-functional project team will have access to knowledge and resources that would otherwise had remain unknown or unavailable (Horwitz, 2005).
Although many firms successfully make use of cross-functional NPD teams, much debate remains on the inner workings of these teams. According to Ancona and Caldwell (1992) the most important variable of diversity is that of functional (or expertise) diversity. They argue that functional heterogeneous teams have two main advantages; the team members bring in expert knowledge and
7 skills which would otherwise not be available for other functions which are present in the team, and because areas such as production and marketing are present, the whole process from development through market is granted for the new product (Ancona and Caldwell, 1992). For example, Rubera et al. (2012) state that “teams which have a high R&D-marketing integration outperform their rivals because they can exploit their technological capabilities in way that is more consistent with the market’s requirements” (Rubera et al. 2012, p. 767). However, heterogeneity in these teams will only have a positive impact when collaboration is perfect and the problems which can occur due to uncertainty in cross-functional teams are effectively dealt with (Cabrales et al., 2008). Functionally homogeneous teams are able to communicate in a shared language and internal communication and integration is enhanced, these teams will therefore be better suited for tasks that require coordinated activities between team members (Weirsema and Bantel, 1992; Bowers et al., 2000). The pitfall of any cohesive team, either homogeneous or heterogeneous, is that groupthink might occur (Janis, 1982);
this means that its members will thrive for unanimity which in turn overrides critical thinking and may lead to poor decision making (Vanderheyden, 2010; Mullen et al, 1994)
Functionally diverse teams increase frequency of communication and the information flow inside the organization (Randolph and Posner, 1992), and the use of these teams provides
opportunities to enhance utilization of organizational resources because the workforce and capital resources can be used in various different ways (Troy et al. 2008). The frequency of communication and flow of information is the result of how well the team is integrated, and NPD literature uses different definitions for the term (Rubera et al., 2012). Kahn (1996) finds that many managers seem to define integration as the level of interaction which results out of increased contact between
departments (Kahn, 1996). Other literature states that integration is similar to collaboration, which causes a high degree of shared values, goals and behavior which is needed to achieve an acceptable end state of the project. (Lawrence and Lorsch, 1986; Sounder, 1988). Another definition which is used to explain integration is interaction and which is the standardization of tangible goods such as documents and sharing administrative systems (Kahn, 1996); collaboration is the intangible
relationship members of teams build up and which are difficult to keep without joint efforts and is also the most intense form of integration (Kahn, 1996, Kahn and Mentzer, 1998). When integration is mentioned in this study, the extent to which the different functions have a common vision during the project and “the magnitude of interaction and communication, the level of information sharing, and the degree of coordination” (Rubera et al., 2012; p. 767; Song and Montoya-Weiss, 2001).
8 The impact of functional diversity on overall project performance
The success of a project depends on numerous factors such as adherence to budget and whether the project reached its goal; overall project performance is defined by Hoegl and Gemuenden (2001) as the description of how effective and efficient a team performs The effectiveness refers to the quality of the outcome (Hoegl and Gemuenden, 2001; Guzzo and Dickson 1996), consequences working in the group has for its members and the enhancement of the capability to perform effectively in the future (Guzzo and Dickson, 1996). The efficiency of a team refers to the degree in which schedules, dates, and budgets are met; a successful performing team is the result of qualitative team work. It is important to have well performing project teams because resources such as information and
knowledge are scarce and are critical for new product development (Hoegl and Parboteeah, 2003). As has been mentioned before, functional diversity is shown to have a negative impact on project
efficiency (Doughtry, 1987; Ancona and Caldwell, 1992; Zenger and Lawrence, 1989; Keller, 2001).
Because heterogeneous teams in terms of functional background could cause task-related conflicts; the differences in backgrounds dictate how team members do and think about tasks (Jehn et al., 1997).
These functional differences may hinder team productivity because the members have different
“thought worlds” (Griffin and Hauser, 1996), and thus views on what should be done and which priorities should be set; various studies have shown that it hinders internal communication and has a negative influence on technical, schedule and budget performance (Doughtry, 1987; Ancona and Caldwell, 1992; Zenger and Lawrence; 1989, Keller, 2001). The communication within the team may become so time consuming that it hinders the way in which the team works, solves problems or make decisions (Olson et al, 1995, Troy et al. 2008). Bowers et al. (2000) have found that homogeneous teams show a moderate increase in effectiveness on performance tasks. However, other previous research has shown that functional diversity is positively linked with team effectiveness (Guzzo and Dickson, 1996); heterogeneous teams, in which diverse points of view and expertise are present, are more likely to come up with solutions which are not obvious and which can positively influence decision making (Nemeth, 1986; Simons et al., 1999). Because of the positive evidence and the fact that the main reason for the use of functionally diverse NPD projects is the ability to make use of existing knowledge and resources within the organization (Workman, 1993; De Clercq et al., 2001;
Bunderson, 2003) the first hypothesis will be:
H1: In NPD, the level of functional diversity in project teams is positively related to overall project performance
9 The moderating role of time pressure on the relationship between functional diversity and overall project performance
As has been mentioned before, an important aspect which determines the overall project performance in functionally diverse teams is the degree of information integration, which is the extent to which information is shared and communicated between team members and which is vital for the level of overall project performance. When this is not done correctly team members may become
overwhelmed with data and fail to detect links between independent facts which may hinder new idea generation or fresh thinking (Woolley et al., 2008). The major cause for time pressure in projects is the upcoming deadline and as it comes closer, time pressure has an effect on the way team members communicate because the emphasis is put on individual tasks and ideas will no longer be shared (Chong et al., 2012). It influences the behavior of individuals in teams, and the kind of psychological stress that causes people to say that they wish there would be more hours in a day (DeVoe and Pfeffer, 2011), it also triggers the feeling of being constrained and as a result causes shallow communication (Chong et al. 2012). Time pressure forces team members to consider a lesser number of decision alternatives (Karau and Kelly, 1992; Sethi, 2000), which is a result of cognitive closure (Kruglanski and Freund, 1983; Karau and Kelly, 1992).
One way to lessen time pressure is to set clear (interim) goals, use different courses of action and time anchoring (McGrath and O’Conner, 1996). Setting a clear goal for the project is important for any project team, but especially for functionally diverse teams (Locke and Latham, 1990), it creates a shared vision and enables team members to work towards a common goal (Nordqvist et al.
2002). Once a team identity has been formed, communication inside a project teams will be automatically facilitated (Hinds and Mortensen, 2005). Interdependency between team members is inherently related to projects; when interaction and communication is right, cooperation will be encouraged and workload may be shared through the bonds that are created, which in turn lessens the feeling of time pressure (Hackman et al., 2000; Pinto et al. 1993; Nordqvist et al. 2002). Previous research has demonstrated that time pressure causes teams to work less effectively and efficient because members communicate less with each other than teams which do not suffer from time pressure (Chong et al., 2012). Time pressure is found in all project work and is even more influential when projects are highly dependent of one another. (Zika-Viktorsson et al., 2006).
One cause which may trigger time pressure in NPD teams is the number of teams each member might be part of; multiple team membership (MTM) is common practice in NPD and as a result many employees are members of one or more teams (Wheelwright and Clark, 1992; O’leary et al., 2011). Several studies have shown that time pressure may facilitate information exchange because these teams are more motivated to successfully reach the common goal (Pieters and Warlop, 1999).
This is explained by the fact that team members are highly integrated and as a result interact and communicate strongly with each other (Hinds and Kiesler, 2002). However, MTM might cause
10
“project overload” (Zika-Viktorsson et al., 2006), which means that members might be working on too many projects and as a result are less able to work efficiently in each of the projects. The individual workload of team members which is present in project teams is related to the team workload. And thus this is another factor which needs to be reckoned with (Funke et al. 2012). Team workload consists out of taskwork and teamwork (Bowers et al., 1997). Taskwork is different for every individual within the team and relates to working on various different tasks, and making sure these are performed correctly;
teamwork relates to the cooperative effort the team needs to make in order to fulfill their tasks within the team (Bowers et al., 1997; Funke et al, 2012). The negative effect of time pressure within the project team arises when the cumulative number of projects, including the different levels of workload, start to cause communicative problems and hindering of the interaction between team members in functionally diverse teams. Therefore, the second hypothesis will be:
H2: In NPD, the positive effect of functional diversity on overall project performance will be reduced as time pressure in the team increases.
Methodology
Data
This study is part of a larger study on cognitive styles in teams, but because time restrictions which were set on finishing this study, an existing dataset is used to measure the hypotheses. The original idea was to approach Dutch manufacturing companies with NPD departments by telephone and email.
After the initial approach, managers that showed interest were sent an email with further information and contacted a few days later to find out if they would like to participate. When this was the case a follow-up appointment was made to talk about the details of the participation of their company. The plan was to define which project teams were deemed to be fit to participate and to send all employees who were part of the projects. The questionnaire would had consisted out of two main parts: the first part consisted of the control variables, the second part consists out of project specific variables and needs to be filled out for every separate project the employee was part of. Unfortunately, none of the suitable companies were willing to cooperate in this study at this moment. Because the deadline which was set by the university for this master thesis project, a dataset was provided which was selected from a larger sample that was used for an exploratory study on the impact of cognitive styles in NPD project teams by the supervisors of this research project (De Visser, 2013).
The data that was provided was by one company and contained 54 respondents, who were part of 16 projects. The process of writing this thesis was started with a different size of dataset in mind and with fitting items for each of the variables. Fortunately, and although the variables of this dataset
11 were not exactly the same, this dataset could be used for the analysis of this study. Because of the size and the variables that were available, any results which derive from the following section must be interpreted as indicative and exploratory and should be seen as a starting point for more extensive and detailed research. As is well known in statistical literature, any dataset of at least 30 or more
respondents is able to produce results which may statistically be relevant (Keller, 2012). In order to understand the relationship between functional diversity and overall project performance which occurs in this small data set, a scatter plot will be produced. In order to understand the interaction of time pressure on this relationship, a simple hierarchical regression will be conducted for exploratory purposes only.
Measures
Dependent variable
Overall project performance. Overall project performance is measured using the scale by Hoegle and Gemuenden (2001) which entails 10 items on effectiveness (a=.91) and 5 items on efficiency (a=.86) using a 5 -point Likert scale. Ranging from 1“strongy disagree” to 5 “strongly agree”. These items were based on previous research by Gemuenden and Lechler (1997) and focus on project teams. A high mean on this variable indicates a high quality overall project performance and a low mean is indicative for a low quality overall project performance.
Independent variable
Functional background. All respondents were asked to name the department they are working for. For each project the number of different departments was counted and the number indicates whether the team was homogeneous with only one department present or heterogeneous, when two or more departments were present; teams that contain two or three different departments are considered less heterogeneous and teams that consist out of 4 or more departments are considered more
heterogeneous.
Moderating variable
Time pressure. Information on the number of projects that respondents have participated in was used to measure time pressure, this measure was provided by the company. For each project the mean of this number was calculated by adding up the number of project each team member was part of and this is used as an indicator for time pressure. It is used as a continuous variable. Zika-Viktorsson et al
12 (2006) have measured the number of projects in a similar way by asking in a self-reported
questionnaire about the number of projects they were working in.
Control variable
Because other factors can also influence overall project performance, one control variable was entered into the analysis due to the size of the data set (n=16) (Keller, 2012).
Organizational tenure. This tenure refers to the amount of time an individual holds a certain position within the organization and thus has knowledge about the culture, routines and politics. Ng and Feldman (2010) found that high organizational tenure is related to stronger core task performance.
Therefore, the mean of the tenure of all project members is calculated per project. This number will be entered into the regression analysis as the control variable.
Methodology
Table 1 shows the descriptive statistics and correlation matrix between the variables which have been used in this study.
Table 1
A scatter plot was made to give a visual representation of the values of the independent and dependent variable because of the small sample size. In order to understand the moderating role time pressure may have on this relationship, markets are set which indicate low (< mean), medium (mean) or high (mean >) workload as an indication for time pressure.
Summary statistics and correlation matrix
Variable Mean SD α 1 2 3 4 5
1. Functional Diversity 2.88 1.088 1.00
2. Overall Project Performance
3.844 .526 .857 -.199 1.00
3. Time Pressure 4.493 1.803 -.179 .007 1.00
4. Organizational Tenure 7.457 3.004 .149 -.282 -.131 1.00 5. Functional Diversity x
Time Pressure
.8191 -.129 -.368 .192 1.00
1 correlation is significant at p < .01 (2-tailed)
13 Figure 1
The scatter plot in figure 1 reveals this interpretation; it shows that generally overall project performance was perceived as high. Projects in which the average time pressure was high show an inverted U-shape indicating that the overall project performance is low in a homogeneous team, highest in a project with a low level of functional diversity and declines as the level of functional diversity increases. In projects in which the time pressure is moderate also show an inverted U-shape;
overall project performance scores generally very high in moderately functional diverse teams and shows a decline as well as the team becomes more heterogeneous. Projects in which time pressure is low generally score also high on overall project performance and this seems to be evenly distributed for different levels of functional diversity in this dataset. An important note which needs to be made is about the two outliers which can be seen in this figure is the following: one project with a low level of functional diversity scores very low on overall project performance and one project in which
functional diversity is high has a higher overall project performance than seems to be the trend. Even though these outliers will negatively influence the regression analysis, it is important that they are kept in. There may have been factors which have influenced the cooperation in these projects that go beyond the reach of this study but which have influenced overall project performance. Figure 1 also shows the least square line (R2=0.039). This line is plotted into the figure to visually show the
relationship between the level of functional diversity and overall project performance; as can be seen it
14 shows a negative slope. The visualization in this scatter plot reveals a negative relationship between the level of functional diversity and overall project performance, thus rejecting hypothesis 1 which stated that there would be a positive relationship between functional diversity and overall project performance. Hypothesis 2, time pressure negatively influences the relationship between functional diversity and overall project performance would not immediately be rejected. Not taking into account the positive outlier, there seems to be a negative trend when functional diversity increases. In order to understand the effect of workload in the relationship between functional project performance and overall project performance a hierarchical regression analysis is conducted.
As previously has been stated, the size of the dataset is not sufficient enough in order to find clear and significant outcomes in a regression analysis, but it can give an indication about the level of B, possible changes in R-squared, and how the p-value changes in each model. Therefore, a
hierarchical regression is conducted in which the control variable of organizational tenure is also entered into the analysis. Only one control variable is used because of this small data set (Keller, 2012), significance is set to .1 for the same reason (Keller, 2012) and the following table shows the results of this statistical test. The outliers which were visualized in figure 1 are not removed to attempt a more significant result. Before the test can actually be conducted, the requirements for conducting a regression must be met (Osborne et al, 2002). First, the variables are entered into a correlation matrix, showing a significant correlation between the moderator and functional diversity. Secondly, the variables are tested for normality using the Shapiro-Wilk test for which the null hypothesis holds when the significance level is sig. =<.050. In that case, non normality exists, but all show a significance level which is higher and thus all variables meet this requirement and are normally distributed. All variables show a VIF score of less than 10, which means that multicollinearity is not occurring.
Thirdly, a residual plot of the standardized residuals is used to look for heteroscedacity, the residuals should be evenly scattered around 0. This sample size is too small and it is unclear if heteroscedacity occurs; however, the plot does seem to be fairly evenly distributed and homoscedasticious (Osborne et al, 2002). The Koenker (1981) test for heteroscedasticity is used to statistically understand this
assumption; this test is chosen because it is there is a small sample size. It shows the X2 value of 2.273 (df=2.273, sig. =.1316), the null hypotheses (sig.= <.050) holds that homoscedasticisity exist, given this p-value this must be rejected and this assumption to be able to run a significant analysis is not met.
Lastly, The Durbin-Watson value of 2.200 is within the range of 1.50 and 2.50 and shows that the assumption of independence for the regression model is met. Despite the shortcomings in meeting all the assumptions which are required in order to conduct a regression. The test will still be done because in particular case, this is most likely due to the small sample size, the results may reveal points of interest that may be further examined.
15
Results
The results of the hierarchical moderated regression which was done according to Cohen and Cohen (1983), with the independent variables centralized as proposed by Aiken and West (1991) are shown in table 2.
Table 2
Regression analysis (Dependent Variable: Overall Project performance) (n=16)1
Dependent variable: Overall Project Performance Model 1 Model 2 Model 3 Hierarchical moderated regression
Control variable:
Organizational Tenure -.148 -.135 -.277*
Independent variable:
Functional Diversity -.084 -.159
Moderating variable:
Time Pressure .328
Interaction term:
Functional Diversity x Time Pressure .356**
R-squared .079 .104 .274
Adjusted R-squared .014 -.033 .009
Model F 1.207 .758 1.035
1 unstandardized regression coefficients are reported.
* p-value = .117
** p-value = .141
Model 1 shows relationship between the independent variable overall project performance and the control variable of organizational tenure, which shows a negative relationship between the variables.
This model was not significant (sig. =.290) and only accounts for 8% of the population (R-squared = 0.079) Model 2 tests hypothesis 1, which states that the level of functional diversity is positively related to overall project performance. Unsurprisingly, this relationship was also not significant (sig. = .556) and accounts for 10% of the population (R-squared = .104). In this sample, the model shows a slightly negative relationship between the independent and dependent variable (B = -.084) and thus functional diversity does not positively relates to overall project performance, opposite of what the first hypothesis states; the hypothesis must be rejected. Model 3 shows the full regression, including the moderating variable of time pressure. None of the predictor variables are significant, although interestingly, the interactor (functional diversity x time pressure) has a p-value of .141 with a positive B coefficient (B = .356), also the R-squared accounts for 27% of the population, which is a great increase compared to Model 2. This shows that although the interaction cannot be seen as statistically significant, there does seem to be an influence which could indicate a moderator effect. The
significance of the control variable is also decreased to a near significant value (sig. = .117).
Hypothesis 2 states that time pressure negatively influences the relationship between functional
16 diversity and overall project performance, which is contradicted by Model 3. Workload positively influences the relationship between functional diversity and overall project performance.
A simple slope analysis was conducted in order to visualize this probable reaction in the relationship between functional diversity and overall project performance. The graph in figure 2 shows this analysis.
Figure 2
The dependent variable is on the y-axis and also the number of projects in the dataset can be seen, on the x-axis three levels of the independent variable are visible low (mean - one standard deviation), medium (mean) and high (mean + one standard deviation), the three lines show the moderator variable which is also differentiated similarly into low, medium and high as Aiken and West (1991) have proposed. The graph shows a positive influence of workload on the relationship between functional diversity and overall project performance. Taking into account the visual interpretation of the scatter plot and the positions of the outliers, the less non significant interaction of the moderator in the
regression analysis makes sense. Due to the extremely negative outlier, projects in which time pressure is low, an incremental positive slope can be seen for overall project performance; similarly the positive slope which shows the influence of high time pressure on the relationship between functional diversity and overall project performance can be due to the positive outlier which can be seen in the plot.
0 2 4 6 8 10 12 14 16
low med high
Overall Project Performance
Functional Diversity
Simple Slope analysis
Workload high med low Time Pressure
17
Discussion
Both hypothesis 1 and 2 were not supported by the hierarchical regression analysis, but the scatter plot shows an interesting visualization. It indicates that a moderate level of functional diversity (two or three departments) is the optimum balance between functional diversity and overall project
performance. This is in line with the literature stream that supports the notion that less functionally diverse teams will be able to perform better as more harmony exists between the team members (Weirsema and Bantel, 1992; Bowers et al., 2000). Although the results must be seen as indicative due to the small sample size, existing literature does provide explanations which support the results that have been found in the regression analysis. In case of hypothesis 1, functional diversity on itself does not positively influence overall project performance; Ancona and Caldwell (1992) have indeed shown that only in some cases functional diversity positively influences overall project performance, but that in general the thought worlds of the team members are too much apart which influences the
performance of the project (Griffin and Hauser, 1996; Doughtry, 1987; Ancona and Caldwell, 1992;
Zenger and Lawrence; 1989, Keller, 2001), and this results indicates that the literature stream which states that functional diversity negatively influences overall project performance is right. Despite the positive influences functional diversity can have on a team in terms of new insights (Nemeth, 1986;
Simons et al., 1999), performance should be thoroughly monitored throughout the duration of the collaborative process in order to understand the impact of functional diversity on different stages in the NPD process. Surprisingly, results of the hierarchical regression analysis show the completely opposite outcome that what was predicted in hypothesis 2. The interaction model indicates that workload does have an influence on the relationship between functional diversity and overall project performance but the level of overall project performance increases despite a low, medium, or high level of time pressure as indicated by workload; all showing the highest score on overall project performance in functionally most diverse teams. The explanation for this finding could be that time stress has been measured in terms of workload by the average number of projects that team members of the participating projects were part of. This is a physical measurement, however it seems that the teams perceived the workload not as a hindrance but as a motivation to cooperate as effectively and efficiently as possible. Chong et al. (2012) argue that this might be the result of the low psychological distance between team members; these teams easily communicate and share important knowledge and resources (Ashford and Cummings, 1985); and most importantly, the teams engage in spontaneous constructive conversations resulting in a strong team identity (Gittell, 2003) which allows them to function optimally under time pressure. It seems that the highly functionally diverse teams are aware of the pitfalls this kind of team composition brings with it, such as less integration due to the different
“thought worlds” of the various members (Griffin and Hauser, 1996). Also, the organization that the projects are part of may be accustomed to projectized NPD and have already adjusted their
organizational routines and structures accordingly (Arenius et al. 2002); even under high time pressure
18 the competences and training which employees may have had will positively influence decision making and communication within the team (Kerzner, 2003; Chiocchio et al., 2010).
Limitations of this study
As has been explained before, this study was limited by lack of companies which were willing to cooperate within the time frame that was set by the university to finish this master thesis. The data that was used was kindly provided by the supervisors so that this study could still be conducted, albeit the small sample size which was made available and which only produced 16 project teams from one company. All findings should be seen as indicative and a starting point for further research. Also, the study is biased because only one company was measured; there was no comparison available to check whether the results differ between companies. However, this would have also been the case if the study was conducted according to the original plan. Due to the constraints which were imposed on this study because of the fixed deadline, workload was used as an indication for time pressure. This was not a self-reported measure and although literature has shown that workload in terms of number of projects is an important aspect (Zika-Viktorsson, 2006); it does not show how time pressure was perceived within the team.
Suggestions for further research
A number of suggestions for further research can be drawn from this exploratory research as the results show some interesting indications.
Firstly, further research should also aim at a data set of at least 100 project teams, all conclusions that can be drawn about significance levels and interactions will be far more robust. An attempt should also be made to incorporate multiple companies, this will enable between subject analyses and may result in the exposure of differences in organizational culture and routines; showing why one company may perform better under similar time pressure circumstances. This can then be taken into account, examined further, and used as a best practices example for organizations that want to improve their overall project performance and company performance. Aspects that should also be thought of are group size and group tenure (Carroll and Harrison, 1998).
Secondly, future research should incorporate a differentiation between explorative and exploitative NPD. Because the different kinds of goals that are sought after in explorative and exploitative NPD projects, different kinds of team compositions in terms of heterogeneity can be expected to be found; Griffin (1997) has shown that “best practice” organizations are more likely to use functional diverse teams for more innovative projects than for less innovative projects. In the case of less innovative projects, less functional diverse teams are used; although statistically “best practice”
19 organizations tend to use cross-functional teams for this part of NPD as well (Griffin, 1997). The reason for this observation could be that the different functional backgrounds and “thought worlds” are the reason why explorative project teams are able to come up with radical innovations. In exploitative project teams, functional diversity might be counterproductive because of the same arguments why it would positively impact explorative project team; exploitation does not need as much diversity of knowledge as exploration (Nokata and Takeuchi, 1995). In exploitation, routine development and refinement of existing knowledge, technologies and products are pursued (Benner and Tushman, 2002;
Greve, 2007). Significant results have already been made in research on what the influence of different functional departments on various stages of the NPD process is (Song et al. 1998), combining these studies with the effect cognitive styles have on overall project performance under the influence of time pressure may strongly affect the way in which project teams are composed.
Thirdly, this study examined time pressure in terms of the average number of other projects team members were part of. Although this gives an objective indication of time pressure, it does not show the perceived time pressure that is felt by the members of project teams. Therefore, future research should incorporate questions about time pressure in the self-reported questionnaire in order to find statistically significant interactions of time pressure on the relationship between functional diversity and overall project performance.
Fourthly, it would be interesting how the cognitive thinking styles of team members affect the way in which project teams deal with time pressure. The results indicate that individuals are able to make rational decisions in favor of the overall project performance. Taking into account these findings, research should probe into the influence cognitive thinking styles may have on how well project teams deal with time pressure; Basadur and Head (2001) have found that teams that are
heterogeneous in terms of cognitive styles are need less time to complete tasks and are able to come up with creative problem solving solutions (Vanderheyden et al. 2010).
Lastly, overall project performance is measured though effectiveness and efficiency, the two cannot be excluded from one another and when no distinction is made between these aspects, the greater picture might reveal that functional diversity has a negative impact on overall project performance in exploitative NPD teams because functional diversity and a negative impact on explorative NPD teams. Overall project performance should also be measured in twofold (Hoegl and Gemuenden, 2001) by using the average score which was given project members and by using market information and opinions of the project manager or other levels higher up in the organization. In this way outliers might be identified that can be examined in more detail through interviews so that the reason why these projects do not follow the trend can be expose and understood.
20
Conclusion and recommendations
Despite the shortcomings of this research, it does give food for thought. Even though the analysis that has been done for this research should be seen as exploratory and indicative, some points of interest have arisen which demand further investigation. The main research question of this study was whether time pressure causes an effect in the relationship between functional diversity and overall project performance. The answer is that there is a strong indication that it seems that does. As time pressure increases, the overall project performance increases as well. This might be due to the effectiveness members of projects work with as they know that they can expect high time pressure because of their individual workload. The fact that this study was done using the data of only one company and that it shows surprising results, management should observe which routines are reoccurring in well
performing project teams and map the routines which cause these teams to be “best practices”.
Management should especially take note of the optimal balance between functional diversity and overall project performance. The results of this study show that moderately heterogeneous teams show the best scores on project performance in combination with time pressure. Although this study was not done under the best circumstances, some interesting indications can be seen and hopefully other researchers will develop this research further in the future.
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