CROSS-FUNCTIONALITY DURING THE NPD PROCESS ON NEW PRODUCT PERFORMANCE: THE MODERATING EFFECTS OF SUPERORDINATE IDENTITY
By
Eldrick van der Biezen
S2270102e.e.f.van.der.biezen@student.rug.nl University of Groningen Faculty of Economics and Business
MSC BA: SIM June 2019
Supervisor: Hans van der Bij Co-assessor: Philip Steinberg
ABSTRACT
Nowadays products need to be developed and delivered with an ever-increasing pace and therefore there is a need for efficient cross-functional teams. Research has shown that the degree of cross-functionality in companies can lead to positive new product performance and that superordinate identity may have an influence on this relationship. This research centers around cross-functionality per stage in the new product development process and its effects on new product performance and the moderating effects of superordinate identity on this relationship. The questions are: What is the effect of cross-functionality on new product project performance? And how does superordinate identity moderate the relationship between cross-functionality on new product project performance? In this vein, cross-functionality is defined as the amount of different functions that participate in a project. Furthermore, superordinate identity is defined as the extent to which members identify with the team and perceive a stake in the success of the team.
Insights from the information processing theory are used to explain cross-functionality while social identity theory is used to explain superordinate identity. Next, a survey was sent to managers or supervisors, as well as project leaders or team members of SMEs, who were asked questions about the most recent project that they took part of. The analysis of the responses revealed associations between cross-functionality and new product performance and superordinate identity on the main relationship. This means that cross-functionality in the launch stage has an inverted-U relationship with new product performance, while superordinate identity has a positive interaction effect on the main relationship in the idea generation and screening stage. Practitioners, therefore, must constantly look for the right balance in participating functions in order to maximize performance. Future research is needed to further test these relationships with a larger sample, as well as by involving several control variables that were found to have a direct effect on new product performance.
Keywords:
1 INTRODUCTION
Nowadays, consumers are faced with an ever-increasing number of products, and new products appear every day (Olson, Walkert & Reukert, 1995). This is in fact true, as firms need to be able to develop new products in order to gain certain competitive advantages relative to others (De Jong & Vermeulen, 2006). Some of these competitive advantages can be achieved when departments and individuals actively work together towards a common goal (Ashforth & Mael, 1989; Sethi, 2000b). The new product development process is seen by many researchers as complex, and it involves numerous uncertainties such as rapid technological change, flexible production processes, and global competition which nowadays require products to be introduced in a timely manner in order to become profitable (Brettel, Heinemann, Engelen & Neubauer, 2011; Kong, Li, Feng & Sun, 2014; Olson, Wlaker, Reukert & Bonnerd, 2001; Song, Thieme & Xie, 1998). This process can be simplified by forming cross-functional teams during the NPD process (Brettel et al., 2011).
Cross-functionality in teams during the NPD process is generally accepted as a mechanism that leads to higher new product performance (Engelen, Brettel & Wiest, 2012; Song & Xie, 2000; Troy, Hirunyawipada & Paswan, 2008; Kong et al. 2014). Several authors have argued that the effectiveness of the amount of functions in a cross-functional teams varies depending on which stage of the NPD process the project is at (Brettel et al., 2011; Kong et al., 2014; Olson et al., 2001; Song et al., 1998). Furthermore, several researchers have noted that superordinate identity can be used to explain how a team’s identity can affect new product performance (Sethi, 2000b; Ashforth & Mael, 1989). Therefore, the premise of this research involves cross-functionality in all stages of the NPD process and superordinate identity.
Nowadays, the time to market for new products is ever decreasing, and cross-functional teams require more parties from different backgrounds present during the NPD process (Lovelace, Shapiro & Weingart, 2001; Wu & Lai, 2019). Moreover, there needs to be a willingness to work together present in those groups through forming a group identity (Sethi, 2000a; Sethi, 2000b; Ashforth &Mael, 1989). Thus, it is necessary to understand the relationship between cross-functional teams and new product performance and how this relationship can be affected by superordinate identity.
will look at the actual cross-functionality of many functions in all stages of the NPD process as was defined by Avlonitis, Papastathopoulou & Gounaris (2001).
Lastly, Hüttermann & Boerner (2011) stated that the main relationship between cross-functionality and new product performance might be “contingent on moderating variables” because most results of this relationship were inconsistent (Hüttermann & Boerner, 2011, p. 834). The most prominent factor that can affect this inconsistency stems from the idea that members of the cross-functional group may not want to work together due to being from different departments (Sethi, 2000b; Ashforth & Mael, 1989). Forming a superordinate identity in the groups might tackle this potential issue (Sethi, 2000b). Therefore, it is proposed that when representatives from a department identify with the cross-functional group, the chances may be higher to achieve better new product performance.
This leads to the following research questions:
RQ1: What is the effect of cross-functionality on new product performance?
RQ2: How does superordinate identity moderate the relationship between cross-functionality on new
product performance?
An empirical research method is used, where a survey study of employees in SMEs is conducted and their answers are used as data for the research. This is to test a handful of hypotheses with the goal to find out what the relationship between cross-functionality and new product performance is, and to find out if superordinate identity has an interaction effect with the main relationship.
This research contributes to the literature in the following ways. Firstly, the study made use of the inverted-U mechanism presented by Haans, Pieters & He (2016), where cross-functionality in the launch stage was found to have an inverted-U relationship with new product performance. Secondly, superordinate identity appears to have some relevance by having a positive effect on the relationship between cross-functionality and new product performance in the idea generation and screening stage. Lastly, the other stages in the NPD are revealed to not have had an effect on new product performance. These relationships may be contingent on some of the control variables, which were found to have a direct influence on new product performance. These variables can be used in future research and can perhaps reveal an entire new perspective that has not yet been researched.
Practitioners should be wary about deciding the optimal degree of cross-functionality in the launch stage during the development of new products, because the team needs to make sure that the new product must be delivered in a timely manner to the market to reap as much profits as possible. Therefore, it might be prone to delays if, for example, the degree of cross-functionality is too much to handle which can lead to information overload (Wu & Lai, 2019; Galbraith,1973; Dwivedi, Wade & Schneberger, 2012).
2 THEORY AND HYPOTHESES Literature Review
Information processing theory. Nowadays, working in teams has become quite complex as tasks are increasingly intellectual and cognitive in nature, and a necessary requirement to simplify these tasks might thus be information-processing (Gabaldon, Kanadlı & Bankewitz, 2018). Information should be collected, translated and integrated when it comes to making decisions in organizations, which can be described as information processing(Tushman & Nadler, 1977). Therefore, due to the importance of information processing, information processing theory is relevant in this study. This theory, developed by Galbraith (1973), states that in case there exists a gap between information-processing requirements and information-processing capacity, there needs to be an aim to make a fit between these two concepts in order to perform well (Galbraith, 1973; Tushman &Nadler, 1977; Zelt, Schmiedel & vom Brocke, 2018). Of particular interest is the uncertainty that may arise if such gap exists between information-processing requirements and capacity. Galbraith (1973) states that “the greater the task uncertainty, the greater the amount of information that must be processed among decision makers during task execution in order to achieve a given level of performance” (Galbraith 1973, p. 4; Dwivedi et al., 2012). Cross-functionality and new product performance are elaborated below.
Social identity theory. Social identity theory started with the argument by Tajfel (1969) that “the etiology of intergroup relations cannot be properly understood without the help of an analysis of their cognitive aspects, and this analysis cannot be derived from statements about motivation and about instinctive behavior” (Tajfel, 1969, p. 81).
Tajfel (1969) also stated that:
Much of what happens to us is related to the activities of groups to which we do or do not belong, and that the changing relations between these groups require constant readjustments of our understanding of what happens, as well as constant causal attributions about the why and the how of the changing conditions of our life (p. 81).
Ashforth & Mael (1989) have built upon SIT by looking at several factors that might have a positive effect on group identity and are of relevance to organizations. In this instance, groups actually refer to different departments in an organization. The factors that were labeled as antecedents of group identity were the differences of the principles and traditions between functional groups, group reputation, the importance of the out-group, intergroup competition, and the factors traditionally associated with group formation (Ashforth & Mael, 1989).
and comply to the principles and rules in order to maintain uniformity within that group (Ashforth & Mael, 1989).
SIT was further used to illustrate its applications towards organizational socialization, role conflict and intergroup relations in organizations (Ashforth & Mael, 1989). Intergroup relations and their relevance are elaborated upon in this study. Ashforth & Mael (1989) stated that groups are prone to high degrees of conflicts because of the constant comparisons being made between the focal group and other groups with the goal to enhance the focal groups’ self-esteem. This foremost locus of intergroup conflict is stimulated through competition between subunits for scarce resources or rewards, among other reasons (Ashforth & Mael, 1989).
These intergroup comparisons may have a number of possible effects, four of which are elaborated upon by Ashforth & Mael (1989). First, the focal group might create negative stereotypes about other groups and also ‘deindividuate’ and ‘depersonalize’ its members (Ashforth & Mael, 1989). Second, the focal group will warrant to decrease its social interaction and hold down other groups (Ashforth & Mael, 1989). Third, these biases can develop to such an extent that each individual in the focal group shares the same biased view towards other groups and may feel personally attacked if other members of the focal group are ‘attacked’ (Ashforth & Mael, 1989). Lastly, the above effects may be strengthened due to competition because it may threaten the focal group and its identity (Ashforth & Mael, 1989).
Initially it seems that social identity by groups, in this case departments, may be detrimental to the overall performance of an organization. This problem might be especially troublesome for cross-functional teams. To mitigate these biases and conflicts between different departments, companies may need to foster superordinate identity in cross-functional teams in order to positively influence overall performance (Sethi, 2000b). This is elaborated upon below.
New product performance. New product performance is seen as the overall success or failure
of products after it has been released in the market (Schleimer & Faems, 2016; Troy et al., 2008). Troy et al. (2008) summarized several dimensions of product success that are widely used in literature, namely marketing performance, product effectiveness and production outcome (Troy, et al., 2008). Furthermore, these successes can be measured through objective and subjective means (Troy et al., 2008). The former relates to documents with, for example, market shares and profits, and the latter is measured through the perception by managers on how well the product performed in comparison to their expectations (Troy, et al., 2008). In this research, new product performance is evaluated by a subjective measure to examine how performance can be affected by the degree of cross-functionality.
According to information processing theory, there needs to be a “fit between information processing requirements and the capacity to process information” (Galbraith, 1973; Tushman &Nadler, 1977; Zelt et al., 2018, p. 70). Cross-functionality can help maintain this fit in a cross-functional NPD team. Sethi (2000a) argued that when the number of active departments in a team increases, it is predicted that it will increase the amount of critical input from different backgrounds during the NPD process. This can lead to advantages in the development of new products because it leads to improvement of interactions between functions and better information flow (Randolph & Posner, 1992; Troy et al., 2008). Thus, one advantage of cross-functionality is to improve decision making capabilities of NPD teams by adding more information flows.
Related to the information processing theory, there are several technical and market uncertainties involved during the development of new products, which can lead to an overall increase in the uncertainty of the needed resources (Song & Xie, 2000). However, cross-functionality is believed to reduce any uncertainties that may develop during the NPD process by “improving a company’s ability to develop a product that provides a superior technical performance and meets customers’ needs” (Song & Xie, 2000 p. 66). Another advantage of cross-functionality can thus lead to a reduction of uncertainties in the NPD process.
There are many papers that have tested the relationship between cross-functionality and new product performance, and which found a positive effect between the variables (Olson et al. 2001; Engelen et al., 2012; Song & Xie, 2000). The arguments discussed above are in line with the benefit argument presented by Haans et al. (2016), which can be illustrated as a positive linear relationship between cross-functionality and new product performance.
between high levels of cross-functionality and new product performance (Tsai & Hsu, 2014; Lovelace et al., 2001; Griffin, 1997). Thus, at a certain point, the benefits of cross-functionality will be overtaken by the costs of cross-functionality, leading to a negative effect on new product performance. Related to these arguments, Haans et al. (2016) also stated that the costs rise alongside the increasing benefits, and therefore an increase in the independent variable can potentially lead towards rapidly escalating costs. These costs can be illustrated in a convex or exponential cost curve (Haans et al., 2016). As can be seen, cross-functionality seems to have a non-linear relationship with new product performance. The next section elaborates on cross-functionality during the NPD process.
Cross-functionality during the NPD process. The NPD process is highlighted in this section.
There are many papers that have each used different categorization of the NPD process. For example, the process was divided into development and commercialization phases (Brettel et al., 2011), divided into four phases (Kong et al., 2014). In short, there is no consistency in the naming of the stages (Song et al.1998; Avlonitis et al., 2001).
For the purpose of this study, the categorization that was introduced by Avlonitis et al. (2001) will be used, which denotes the 5 stages of the NPD process. These stages are idea generation and screening, business analysis and marketing strategy, technical development, testing and launch (Avlonitis et al., 2001). Idea generation and screening involves the decision regarding whether to proceed with the development of ideas or not, which is based on the screening and checking of different ideas against market and technical criteria (Avlonitis et al. 2001). Business analysis and marketing strategy consist of cost-benefit analysis, using data on several market aspects and on the potential cost or investments involved (Avlonitis et al. 2001). Technical development is defined as “the design and development of process procedures and system design” (Avlonitis et al. 2001, p. 326). Testing includes testing the functionality and marketability of the new product which can be conducted in-house and/or in the market (Avlonitis et al. 2001). Commercialization/launching entails the market-wide release of the product and the assessment of its performance (Avlonitis et al. 2001). Thus, cross-functionality is measured in each of these stages to see their effects on new product performance.
Based on the discussion above, there is thus a possibility that there is a non-linear relationship between cross-functionality and NPD performance. This argument can be strengthened with the cost benefit argument, where the subtraction of the costs from the benefits may lead to an inverted-U relationship (Haans et al., 2016), hence a non-linear relationship may exist between the dependent and independent variable. However, there is no certainty that this relationship can be found at each stage, meaning that the goal is to find out what kind of effect cross-functionality at each stage has on new product performance. The first hypothesis, split up per stages in the NPD process, states:
H1a-e: Cross-functionality has an inverted-U relationship with new product performance, where such a
Superordinate identity. The homogeneity of its members and behavior in groups, which was elaborated on above, can be inferred as the behavior that can be found in the departments of a firm. Sethi (2000b) argued that “strong functional identities of individuals in organizations give rise to interfunctional biases and stereotypes, which can hinder effective joint working between members of various functional areas” (Sethi, 2000b, p. 332). In other words, the effective teamwork in cross-functional groups might be negatively affected when there is a strong functional identity present. An answer to this is to foster a superordinate identity in cross-functional teams.
The degree of association with, and the noted involvement in the accomplishments of a project team can be referred to as superordinate identity (Sethi, 2000b). This focuses on the mental aspects of a member’s affiliation with the team, and this contrasts with the social attachment, which explains the emotional part of the member-team relationship as presented by Ashford & Mael (1989) (Sethi, 2000b). This construct is based on social identity theory.
The basic premise of superordinate identity is that when teams in the NPD process exhibit a high amount of superordinate identity, inter-functional boundaries will diminish and make place for a superordinate feeling for its members (Sethi, 2000b; Brewer & Miller, 1984). In other words, the inherited inter-functional biases in the minds of members of different backgrounds may be diminished when a superordinate identity is formed in a team. Members of a team who have a high degree of superordinate identity may view themselves as idiosyncratic to the team, instead of simply adding value to the team based solely on their functional background (Sethi, 2000b; Mackie & Goethals, 1987). Members will see themselves completely as part of their team, rather than as a representative of a particular department or function. This feeling of being part of the team by an individual can lead to acceptance by the overall members of the team, which will further lead to learning and obeying the principles and rules in order to maintain uniformity within that team (Sethi, 2000b; Ashforth & Mael, 1989). Practically the same antecedents and consequences of social identification in organizations also arise in the team setting (Ashforth & Mael, 1989). However, in contrast to inter-functional groups, social identification in teams or superordinate identity may lead to an increase in the performance of a new product team.
The increase in connection in the teams will lead its members to be more active in sharing information and be more open to discussions with other members (Sethi, 2000b). This may lead to an increase in effective merging of functional resources and competencies during the NPD process and can eventually lead to increased product success (Sethi, 2000a). Lastly, members in high superordinate identity teams may exhibit higher interest towards the success of the project by sharing the same goal as the team instead of following separate functional goals, which can lead to a higher probability for radical innovations (Sethi,2000b).
Based on the arguments presented above, there is a probability that superordinate identity might have a positive moderating effect on the main relationship between cross-functionality and new product performance. This is in line with the arguments presented by Haans et al. (2016) which state that a moderator may have either a turning point shift or steepening effect on the predicted inverted-U relationship. By using the logic by Haans et al. (2016), it can be inferred that this positive moderating relationship will strengthen the linear mechanism which may lead to a shift in the turning point to the right. This linear mechanism is in line with the benefit argument presented in the previous section (Haans et al., 2016). However, these arguments also indicate that the cost mechanism proposed by Haans et al. (2016) might be negatively affected. Therefore, the cost argument presented above might be diminished by superordinate identity (Haans et al., 2016). In other words, it can be expected that the cost mechanism might have less of an effect on the benefits mechanism, which means a potential steepening of the inverted-U relationship. Thus, superordinate identity may probably lead to a firm’s ability to have a higher degree of cross-functionality, which can lead to high new product performance and an increase in the overall new product performance of the hypothesized model. The following hypotheses will explain the positive interaction effects of superordinate identity on the relationship between cross-functionality and new product performance per stage:
H2a-e: Superordinate identity will shift the turning point of the inverted-U relationship between
cross-functionality with new product performance to the right and will steepen this relationship where such effects are found in the idea generation and screening stage, the business analysis and marketing strategy, the technical development, the testing, and the launch stages.
Figure 1
Graphical representation of the conceptual model
H2e
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H2a Cross-functionality in the Idea Generation and Screening StageCross-functionality in the Business Analysis and Marketing Strategy Stage
3 METHODS
A quantitative empirical approach was implemented, where the hypotheses were tested in order to find out whether or not cross-functionality has an effect on new product performance and if superordinate identity moderates this relationship (Blumberg, Cooper & Schindler, 2011). This method is in accordance with the proposed research questions presented above.
Data Collection
This research makes use of an existing database with data from about 120 different SME’s. This type of company was chosen because it can represent a significant portion of the population. SMEs are categorized by the amount of people that they employ. In the Netherlands these ranges from up to 10 persons in small firms and from 10 to about 150 persons in medium companies (Nooteboom, 1994). SMEs in the Netherlands are responsible for about 43,02% of new products that are released on the market (based on percentage of R&D expenditures for firms with 0 till 250 employees)1. Furthermore,
SMEs make up a considerable percentage of the total amount of firms in the market. For example, the statistics for the first quarter of 2019 of all the firms in the Netherlands reveals that about 99,81% of all firms can be categorized as SMEs2. Therefore, it has been decided to use data from Small and Medium
sized enterprises exclusively.
The researcher was tasked with acquiring data from 10 companies. Furthermore, the ORBIS database was used in order to find potential Dutch SME’s. Two participants were needed per company, one project leader or team member and a manager or a supervisor. In order to add new data to the database, participants were recruited via telephone and email, and were asked to fill an online questionnaire. However, only 5 companies completed the survey and this data was added to the database by the researcher, leading to a database consisting of 120 companies.
The project leaders or team members were asked questions related to cross-functionality and identity during a new product development project. The managers or supervisors were asked about connectedness, turbulence, and performance of innovation projects.
Descriptive statistics of the companies. The database contains data from 120 companies. The average duration of the innovation projects lasted 13.73 months (SD=12.18) and the average budget is €297,605.17 (SD=€672,894.21). Moreover, about 60.83% of the companies reported that their owner participated in the project development team, whereas 39.17% reported no participation. Next, 72.50% of the companies had a separate department for marketing, 75.83% had a separate department for R&D, 90% had such a department for production, and 81.67% had one for purchasing. The average turnover is €53,028,903.52 (SD= €147,272,337.66). The average product newness is 1.87 (SD=.96) meaning that the average project is new to the team. In addition, average spending in development activities is
€623,567.06 (SD= €1,127,262.06). Lastly, technological turbulence averages at 4.99 (SD=1.14) meaning that the technology is relatively turbulent for the companies.
Additional descriptive. The average age of these companies is 57 (SD = 46.10). Next, 73.73%
of the companies sell products, 16.95% provide services and 9.32% provide both (N=118). About 13.56% of the companies are active in the consumer market, whereas 80.51% are in the business-to-business market and 5.93% do business-to-business in both markets (N=118). Furthermore, the average number of employees is 119 (SD=302.25), and 47.37% are a family business.
Measurements
The measures used in this research can be seen as valid due to the fact that they were previously used in the literature.
Cross-functionality. Cross-functionality was measured on a multi-item scale where project leader or team members must check which combination of departments or people with a particular background were actively working together per activity during the NPD process. This measure was adapted from Avlonitis et al., (2001) and Song & Montoya-Weiss (1998), where the activities during the NPD process were divided into 5 stages, namely idea generations and screening, business analysis and marketing strategy, technical development, testing, and launch. This research used this 5-stage format in order to get detailed data on the effects of cross-functionality per stage on new product performance. Several examples of activities are: “Expanding the idea into a full product concept”, “Identifying the target market”, and “Determining the final product design and specifications”. Per activity, participants can choose a combination of 7 different departments or check ‘NONE’ if no departments were active. All checked functions were registered as 1 in the database, whereas the functions that did not participate were denoted with a 0. If the option ‘NONE’ was checked, all the functions will be 0. The data then had to be rearranged by looking at whether a function participated in a stage during the NPD process or not. This was done by listing all activities that a particular function was active in, in one stage and denoting that as 1 when the frequency of participation is above 0. Likewise, a score of 0 will be given to the functions that did not participate at all in one stage. All the functions that had a 1 in a particular stage were then summed up to form the degree of cross-functionality of that stage. For example, 1 will indicate that only 1 function participated in a certain stage and 7 will mean that all functions that were used in this research were active in a particular stage. All the items were then grouped together into 5 variables. Lastly, the variables were binary and were then summed up together. It was therefore not necessary to perform an exploratory factor analysis and a subsequent reliability analysis for cross-functionality (Yong & Pearce, 2013).
score of 1 meant “significantly worse than initial expectations” whereas a score of 7 “significantly better than expectations”. Example items include: “Product quality”, “Market share”, and “overall commercial success of the product”.
Superordinate identity. This measure was adapted from Sethi (2000b), where 6 items were measured using a 7-point Likert scale. A score of 1 means “strongly disagree” and a score of 7 “strongly agree”. Example items were: “Members behaved like a unified team”, “Members were committed to common project objectives”, and “Members valued their membership in the team”.
Control variables. The following variables were chosen to control for the main relationships, because there is reason to believe that they are of influence on the main variables. Project duration may have an influence of the eventual performance of the product. Nowadays, it is required that new products need to be developed at an increasingly rapid pace (Wu & Lai, 2019). Hence, it is required that the development time cannot be very long. Therefore, it is predicted that a short project duration may have a positive influence on the success of the new product and a long duration time will have a negative influence.
Project budget can be crucial for the eventual success or failure of the new product. The budget of a project practically dictates how successful the final product will be. There is an increased risk for project failure when the budget for said project is not quite as high, making it impossible to develop a successful product (de Wit, 1988). Thus, it is predicted that project budget may also have an effect on the performance of a new product.
Marketing department is believed to be a crucial element for the development of a new product. According to Olson et al. (2001), the task of the marketing department is to research the users’ needs and obtain information about competing products, amongst others. The availability of a marketing department may therefore lead to a successful new product.
A company’s turnover can explain how a product performed during a certain period of time (Hart, 1993). The turnover can therefore be used to predict the performance of a new product.
A company’s spending in developing projects is seen as an accumulation of all the money that was spent in developing of several projects. A projects’ budget forms a part of the total spending of a company. Therefore, this variable can be seen as an important predictor on the eventual success of a new product.
The involvement of the owner of the company can have an effect on the functioning of a cross-functional team. The owner may decide to exert his or her influence and try to make a new product according to his or her wishes, disregarding suggestions from others in the team. This behavior may lead to an eventual success or failure of the product (Bubshait, 1994). Therefore, an owner’s influence may have an effect on the performance of the new product.
is not that new to the company may lead to a more successful product. Thus, the newness of a project can have an influence on the performance of a new product.
Lastly, technological turbulence may have an influence on the products that the company offers (Chavez et al., 2015), in particular the speed in which the technology can change can lead to the success or failure of a new product. This is in line with the duration of the project where, in a highly turbulent market, projects are required to have a relatively short duration. The opposite might be true for a less turbulent market. Thus, technological turbulence is predicted to have an influence on the performance of the new product.
4 RESULTS Preliminary Results
TABLE 1
Results of exploratory factor analysis
Factor loading
Item 1 2
Factor 1: Superordinate Identity (α= .84)
ID-6 .78 .03
ID-4 .78 -.02
ID-5 .77 -.08
ID-1 .76 .10
ID-2 .76 .05
Factor 2: New Product Performance (α= .78)
M-Perf-6 .07 .88
M-Perf-7 .10 .87
M-Perf-5 .06 .79
M-Perf-3 -.07 .61
M-Perf-1 -.02 .43
Exploratory Factor Analysis. Table 1 shows the results of the exploratory factor analysis for the variables superordinate identity and new product performance. Kaiser- Meyer- Olkin measure of sampling adequacy was .70, which is above the recommended .60 (Neil, 2008). The Bartlett’s test of sphericity was significant (χ2 (45) = 403.12, p < .05). A varimax rotation was applied and the results
Descriptive Statistics. The descriptive statistics and intercorrelations of all the variables are shown in table 2. Unfortunately, none of the cross-functionality variables (presented as CFIGS, CFBM, CFTD, CFTE and CFLA from this point on) nor the superordinate identity variable appear to have a significant correlation with new product performance.
Several control variables, however, did appear to have a significant correlation with new product performance. The availability of a separate marketing department was found to have a significant positive correlation with new product performance (R=.20, p=.04). Moreover, company’s turnover appears to have a significant positive correlation with new product performance (R=.22, p=.04). Thus, these variables will be included in the main analysis to observe their effects on new product performance.
Lastly, a remarkable number of control variables had a significant correlation with the cross-functionality variables or superordinate identity. Both project budget and availability of a marketing department have a significant positive correlation with CFIGS (R=.23, p=.03; R=.27, p=.00). Availability of a separate marketing department also has a positive significant correlation with CFBM (R=.26, p=.00). CFTD is correlated with three control variables, namely the project’s duration, the project’s budget, and the company’s developmental spending, all of which are positive and significant, as well as with product newness which is negative and significant (R=.20, p=.03; R=.19, p=.08; R=.22, p=.05; R=-.22, p=.01). Project duration is also significantly correlated with CFTE (R=.19, p=.04). CFLA is positively and significantly correlated with the availability of a separate marketing department (R=.18, p=.06). Moreover, owner’s participation and product newness correlate significantly and positively with superordinate identity (R=.28, p=.00; R=.18, p=.06).
The control variables appear to have an effect on most of the main variables, especially after it was found that the main variables do not correlate with each other. This means that the control variables are crucial in this research and therefore must be included in the main analysis.
Main Analysis
This section involved the testing of the two hypotheses that were presented above. The first hypothesis argued that cross-functionality has an inverted-U relationship with new product performance, and this was split up into 5 sub-hypotheses to account for the 5 stages in the new product development process. The second hypothesis entails that superordinate identity will affect the main relationship by shifting the tipping point to the right and steepening the relationship. A regression analysis was done in order to test these hypotheses.
Prior to the regression analysis, the data needed to be adjusted in order to accurately measure the hypotheses. First, CFIGS, CFBM, CFTD, CFTE, and CFLA were squared to create 5 new variables that, together with the non-squared variables, were used to measure the proposed inverted-U relationship. Lastly, to account for the moderating or interacting effect, the variables cross-functionality and superordinate identity were mean-centered in order to minimize any multicollinearity (Aiken & West, 1991). The mean-centered cross-functionality variable was then squared to form the variable cross-functionality squared. The variance inflation factors of all the regression results were calculated in order to check for multicollinearity. According to Neter, Wasserman & Kutner (1985), the VIF should not be higher than 10 (Schroeder, Lander & Levine-Silverman, 1990). All the variables except for the interaction of superordinate identity and cross-functionality in the testing stage (VIF=14.73) had adequate VIF scores.
The results of the regression analysis are highlighted in Table 3. A total of 5 models were created in order to test the hypotheses. Model 1 is the baseline model with the control variables. Model 2 added the first 5 cross-functionality variables. Model 3 measured the first hypothesis by also adding the squared cross-functionality variables. Model 4 looked at the interaction effects of the moderating variables with the non-squared cross-functionality variables. And model 5 looked at the complete data by adding the squared cross-functionality variables and their interaction effects with superordinate identity the which were used to measure the interaction hypotheses.
Cross-functionality and new product performance. The following section highlights the findings for the first hypothesis. Model 3 is used here to check if the sub-hypotheses of hypothesis 1 are supported or not.
Cross-functionality in the idea generation and screening stage. The results of the regression
analysis indicate that CFIGS has a positive effect on new product performance. However, this effect is not significant (B=.19, SE=.12, p=.14). Furthermore, CFIGS2 has a positive effect on new product
performance and this effect is significant (B=.11, SE=.06, p=.07). These results suggest that cross-functionality IGS is more likely to have a U-shaped effect instead of the proposed inverted-U relationship. In other words, a small number of active functions in a project group has a negative effect on performance, and this effect will become less negative and also can even become positive as the number of active functions increase. Thus, hypothesis 1a cannot be supported.
Cross-functionality in the business analysis and marketing strategy stage. The results indicate
that CFBM has a positive effect on new products’ performance. However, this relationship is not significant (B=-.02, SE=.13, p=.88). Next, CFBM2 is negatively related with new product performance
TABLE 3
Regression results for effects on new product performance New product performance
Model 1 Model 2 Model 3 Model 4 Model 5
Constant 4.07** 5.06** 3.81** 3.91** 2.02
Cross-functionality in the idea generation and screening stage (CF_IGS)
.19 .19 .23+ .24
Cross-functionality in the business analysis and marketing strategy stage (CF_BM)
-.12 -.02 -.10 -.09
Cross-functionality in the technical development stage (CF_TD)
-.07 -.08 -.18 -.23
Cross-functionality in the testing stage (CF_TE) -.23+ -.40* -.18 -.33+
Cross-functionality in the launch stage (CF_LA) .07 .07 .08 .10
CF_IGS2 .11+ .07
CF_BM2 -.02 0
CF_TD2 -.04 .03
CF_TE2 .14+ .13
CF_LA2 -.11+ -.05
Superordinate identity (ID) -.19 -.09 -.01 .30
TABLE 3 (CONTINUED) CF_TD2 x ID -.20 CF_TE2 x ID -.21 CF_LA2 x ID -.02 Project duration -.03+ -.02 -.04* -.02 -.03 Project budget 0 0 0 0 0+ Owner’s participation .48+ .69* 1.10** .54+ .91*
Separate marketing department .47+ .46+ .54* .59* .87**
Company’s turnover 0+ 0 0* 0 0*
Product newness .22+ .30* .41** .20 .30+
Company’s developmental spending 0 0 0+ 0 0*
Technological turbulence -.13 -.13 -.15 -.12 -.23*
F 2.03+ 1.97* 2.02* 1.68+ 1.87*
R2 .25 .39 .50 .45 .65
Adjusted R2 .12 .19 .25 .18 .30
Notes. N=59. +p < .10, *p < .05, **p < .01
Cross-functionality in the technical development stage. The results suggest that CFTD is
positively related to new product performance, but that this relationship is not significant (B=-.08, SE=.13, p=.56). The CFTD2 appears to be negatively associated with new product performance and this
association is not significant (B=-.04, SE=.09, p=.67). Hypothesis 1c is therefore not supported.
Cross-functionality in the testing stage. Results indicate that CFTE is negatively related to new
product performance and that this relationship is significant (B=-.40, SE=.17, p=.02). Furthermore, CFTE2 is positively related to new product performance and this relationship is significant (B=.14,
Cross-functionality in the launch stage. Results suggest that CFLA is positively related to new
product performance and that this relationship is not significant (B=.07, SE=.12, p=.60). Furthermore, results indicate that CFLA2 has a negative effect on new product performance and that this effect is
significant (B=-.11, SE=.06, p=.06). It seems that cross-functionality in the launch stage has an inverted-U relationship with new product performance, as was proposed. inverted-Up to a certain point, a small number of active functions in a group have a positive influence on new product performance, but after that point this effect becomes negative. Thus, hypothesis 1e is supported.
Superordinate identity. The next section highlights the findings for the second hypothesis. Model 5 is used to interpret whether the proposed sub-hypotheses in the second hypothesis can be supported or rejected.
Interaction effect of superordinate identity with CFIGS Results indicate that the moderating
effect of superordinate identity decreases the negative effect of CFIGS on new product performance. However, this relationship is not significant (B=-.12, SE=.26, p=.66). Furthermore, superordinate identity increased the positive effect between CFIGS2 and new product performance, but this
relationship is significant (B=.20, SE=.08, p=.02). The results found a U-shaped relationship. Therefore, hypothesis 2a is not supported.
Interaction effect of superordinate identity with CFBM. The results indicate that the
moderating effect of superordinate identity on the relationship of CFBM towards new product performance is negative and not significant (B=-.04, SE=.25, p=.87). The results suggest that the moderating effect of superordinate identity on the relationship of CF BM2 on new product performance
is also negative and not significant (B=-.08, SE=.11, p=.48). Thus, hypothesis 2b is not supported. Interaction effect of superordinate identity with CFTD. The results show that the moderating
effect of superordinate identity on the relationship between CFTD and new product performance is positive and not significant (B=.42, SE=.40, p=.30). Furthermore, the moderating effect of superordinate identity on the relationship of CFTD2 with new product performance is negative and also not significant
(B=-.20, SE=.15, p=.19). Therefore, hypothesis 2c cannot be supported.
Interaction effect of superordinate identity with CFTE. Results reveal that superordinate
identity has a negative moderating effect on the relationship of CFTE on new product performance. This relationship, however, is not significant (B=-.01, SE=.34, p=.97). Next, superordinate identity has a negative moderating effect on the relationship of CFTE2 with new product performance. However, the
found effect is not significant (B=-.20, SE=.17, p=.24). Thus, hypothesis 2d cannot be supported. Interaction effect of superordinate identity with CFLA. Superordinate identity has a negative
moderating effect on the relationship of CFLA on new product performance, but this effect is not significant (B=-.28, SE=.32, p=.97). Furthermore, superordinate identity has a negative moderating effect on the relationship between CFLA2 and new product performance and this effect is not significant
Only one sub-hypothesis was supported after the regression analysis. Cross-functionality in the launch stage appears to have an inverted-U relationship with new product performance. The tipping point of the inverted-U relationship was calculated using the data from the regression analysis and was found to be present in the range of the data with a x-value of .32 with a y-value of 3.82. The x-value of the tipping point is quite low because the variables were mean-centered. Next, the mean was added to the x-value of the tipping point, turning it to 3.63. This means that the optimal amount of cross-functionality on new product performance lies between 3 to 4 different participating functions. Also, the mean was also added to both points where the y-value is 0, making them x=-2.65 and x=9.13. With this data, a chart can be made to illustrate the inverted-U relationship, which is presented in figure 2.
FIGURE 2
Furthermore, none of the cross-functionality in the other stages had a significant inverted-U relationship with new product performance. However, several stages appeared to have had the opposite effect to what was predicted. Also, it appears that a handful of control variables were found to have a significant effect on new product performance. Lastly, the lack of data and the presence of several outliers may have had an influence on the results, because only 59 of the available 120 data points were used in the analysis. These results are further explained in the discussion section.
5 DISCUSSION
The goal of this study was to find out if cross-functionality in all stages of the new product development process has an inverted-U relationship with new product performance and whether this relationship is moderated by superordinate identity. A survey was sent to 10 companies where both a manager or supervisor and a project leader or team member were asked to fill out this survey. Only 5 companies returned complete answers, and these were added to an existing database where the total number of companies sampled became 120. The complete database was used in the correlation analysis. However, with the combination of the control variables, the population went from 120 to 59 companies during the regression analysis. 0 0,5 1 1,5 2 2,5 3 3,5 4 4,5 -4 -2 0 2 4 6 8 10
The regression analysis revealed that only cross-functionality in the launch stage had a significant inverted-U relationship with new product performance. It showed that the optimal degree of cross-functionality lies between 3 to 4 different participating functions. All the other proposed hypotheses could not be supported. However, there were several results that are worth elaborating more on. CFIGS2 revealed to have a significant positive effect on new product performance, suggesting the
existence of a U-shaped relationship. Furthermore, CFTE showed a significant negative effect on new product performance and CFTE2 showed a significant positive effect, which also suggests a U-shaped
relation. All the stages in the NPD process should have revealed an inverted-U relationship with new product performance. However, these stages appear to differ with what was proposed above. Therefore, it can be assumed that the stages in the NPD process are not governed by the same mechanisms (Haans et al., 2016).
An explanation for this can be found in the resource dependency theory which involves “the degree of interrelationship and the nature of interactions among functional specialists in an organization are influenced by the collective task being accomplished” (Pfeffer & Salancik, 1978; Olson et al.,1995; Song & Swink, 2002, p.3). Furthermore, this theory suggests that the contents of the uncertainty an organization faces influence the corresponding gravity of each professional’s role in fixing that uncertainty as well (Olson et al., 2001). Furthermore, the data contained only information from SME’s, and these organizations are known to be resource constrained, which means that they need to be effectively managed (Desouza & Awazu, 2006). Therefore, it can be argued that the requirements of cross-functionality per stage in the NPD process may be heterogenous due to limited available resources in SMEs and the presence of high levels of uncertainties (Pfeffer & Salancik, 1978; Olson et al., 2001; Dean, Brown & Bamford, 1998).
Several control variables did provide some interesting results. Project duration had a significant negative effect towards new product performance in accordance to what was proposed above. Furthermore, in accordance with Bubshait (1994), the presence of the company’s owner in the project team had a significant positive effect on new product performance. Next, the presence of a separate marketing department appeared to have a significant positive effect on new product performance, which is in accordance with the ideas presented by Olson et al. (2001). Last, product newness had a positive significant effect on new product performance, which is in accordance with what was proposed above (Tatikonda & Rosenthal, 2000).
Theoretical Implications
which will lead to an inverted-U relationship. Thus, the degree of cross-functionality in the launch stage can either be beneficial or detrimental for the eventual performance of the new product.
Superordinate identity did appear to have an influence on the relationship between cross-functionality and new product performance in the idea generation and screening stage. An explanation for this may be that SMEs are argued to be highly connected organizations due to the limited amount of resources available to them (Desouza & Awazu, 2006; Sethi, 2000b). Therefore, superordinate identity can be seen as an additional measure to implement in order to increase the degree of connectedness in SMEs. Thus, superordinate identity can provide interesting insights when looking for cross-functionality and new product performance in SMEs.
Lastly, the results showed no significant results of cross-functionality towards new product performance in the first four stages of the NPD process. One explanation for this might be that unlike the launch stage, these other stages might not have a direct effect on product performance but rather an indirect effect. On the other hand, several control variables were revealed to have a direct effect on new product performance, and perhaps these variables might provide interesting insights if they were included in the main analysis as a mediator or moderator.
Practical Implications
The amount of participating functions in a project group during the launch stage of the development of a new product was proven to have an effect on the performance of that product. Practitioners need to be aware that adding as many functions as possible together in a project group, especially at the last stage, might lead to many delays, information overload from many functions, and coordination issues (Wu & Lai, 2019; Galbraith,1973; Dwivedi et al., 2012). These all may have a negative influence on the performance of the new product. Therefore, practitioners need to constantly look for the right balance in participating functions in order to maximize the positive effect of teams of different functions working together on the eventual performance of the new product.
Limitations and Future Research
and willing to effectively share information between its members. Taken together, a more comprehensive definition about functionality can be made. A more wholesome definition of cross-functionality can be defined as the amount of different functional teams that are active in a project and their propensity to effectively share information with their team members. However, there is an issue with feasibility that may arise when it comes to involving a large number of functions and looking at whether these functions display the propensity to share information with each other. The amount of combinations of information sharing parties may become extremely high and can be difficult to completely measure through surveys. Therefore, future research should look at cross-functional integration instead of cross-functionality to get a more comprehensive explanation of its effects on new product performance. However, the optimal amount of functions to involve in the study in order to avoid potential feasibility issues must first be decided upon.
Next, the available data proved to be limiting to the research. The main reason for this is the extensive amount of missing data and outliers present in the database. This led to a regression analysis with a sample size of only 59 instead of the available 120. A larger sample size would have provided more interesting results.
Lastly, almost all of the independent variables and the moderating variable did not produce any significant association with new product performance. An explanation for these independent variables might be that there might be one or several intermediate variables that might have a more direct connection with new product performance. The moderating variable might perhaps have a direct relationship with new product performance as was found by Sethi (2000a) instead of being a moderator. The proposed existence of a mediating variable for most of the cross-functionality variables may be explained through the control variables. The control variables that had a significant relationship with new product performance were project duration, the presence of the company’s owner in the project team, the presence of a separate marketing department, and product newness. Thus, these variables may be used in future research as a mediator between cross-functionality and new product performance due to their direct influence on the dependent variable.
Conclusion
The aim of the study was to look at the effects of cross-functionality on new product performance at each stage of the NPD process and the moderating effects of superordinate identity on this relationship. Also, it was suggested that cross-functionality in all stages of the NPD process has an inverted-U relationship with new product performance.
revealed that superordinate identity has a moderating effect on the main relationship in the idea generation and screening stage, which was contrary to what was hypothesized. Notwithstanding this interesting result, it does partially answer the second research question. When a team establishes a superordinate identity, it can increase the amount of different functions that participate in a project that can still provide positive results.
This study presented a different perspective on how to measure cross-functionality and its effect on new product performance. Moreover, adding superordinate identity as a moderator adds an extra dimension by looking at how employees identify themselves in a cross-functional team. Furthermore, some of the control variables can be used in the future as mediators to strengthen the proposed associations between cross-functionality, superordinate identity, and new product performance. Therefore, there is still much potential for future research to help practitioners understand and create the most optimal cross-functional teams that can create and release new products effectively and in a timely manner in order to become successful.
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APPENDIX
Excerpt from The Survey (cross-functionality, superordinate identity and new product performance)
De volgende vragen gaan over welke mensen bij het innovatie project betrokken waren in de verschillende fasen. Het gaat om de achtergrond van de mensen. We maken onderscheid tussen:
- mensen van de R&D afdeling of met een R&D achtergrond (R&D)
- mensen van de productie afdeling of met een productie achtergrond (PROD) - mensen van de inkoop afdeling of met een inkoop achtergrond (INK) - leveranciers van het bedrijf (LEV)
- distributeurs (DISTR)
- de uiteindelijke klant (KLANT).
Als u een hokje aankruist betekent dat dat iemand van die afdeling of met die achtergrond betrokken
was bij een bepaalde fase van het project.
A. Ideegeneratie en –screening
MAR R&D PROD INK LEV DISTR KLANT GEEN
1. Het verzamelen van ideeën voor een nieuw product
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
2. De eerste screening van het productidee (wat zijn de kansen en risico’s)
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
3. De ontwikkeling van het idee tot een compleet productconcept
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
4. Het ontwikkelen van
commerciële en
financiële aspecten van het concept
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
5. Het vaststellen van de gevolgen voor de andere producten van het bedrijf
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
6. Het bepalen van implicaties voor productie/ distributie
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
C. Bedrijfsanalyse en marketingstrategie
MAR R&D PROD INK LEV DISTR KLANT GEEN
1. Het (laten) uitvoeren
van een
marktonderzoek
(marktpotentie, klantvoorkeuren, aankoopproces) 2. Het identificeren van
de doelmarkt ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
3. Het in kaart brengen van de concurrentie en hun producten
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
4. Het vaststellen van
de gewenste
productkenmerken en hun haalbaarheid
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
5. Het maken van een geïntegreerd
marketingplan
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
D. Technische ontwikkeling
MAR R&D PROD INK LEV DISTR KLANT GEEN
1. Het bouwen van het
product of prototype ¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
2. Het testen van het product tijdens de ontwikkeling
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
3. Het ontwerpen en testen van de productie faciliteiten
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
4. Het bepalen van het definitieve
productontwerp en de specificaties
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
5. Het uitwerken van een plan voor grootschalige
productie
¨ ¨ ¨ ¨ ¨ ¨ ¨ ¨
