Flexibility & turbulence: The effects on NPD performance
How are the flexibility factors gate conditionality, the product freeze point and centralization moderated by the degree of market- and technological turbulence in their effect on New
Product Development performance?
Julia Maria Frielink S2769042
j.m.frielink@student.rug.nl
University of Groningen Faculty of Economics and Business MSc BA Strategic Innovation Management
Supervisors: Dr. Van Der Bij Co-assessor: Dr. Biemans
2 ABSTRACT
New Product Development can create competitive advantage for firms (Rothwell, 1995). The amount of flexibility in NPD processes can be of influence on the NPD performance, and thereby on the competitive advantage that can be created. Therefore, it is important for scholars and managers to get a clear view this relationship. Market- and technological turbulence are important moderators in this relationship, because turbulence requires flexibility in NPD processes (Kamoche & Cunha, 2001). This study researches this by combining measures from the flexibility framework by Biazzo (2009); centralization, gate conditionality and the product freeze point, and access their effect on NPD performance. The moderating effects of turbulence were also taken into account. There was a positive relationship found between the delay of the product freeze point and the NPD product profitability. Furthermore, concluded was that the different measures of flexibility had different effects on each performance measure. These different effects should be taken into account, when discussing the effects of flexibility and turbulence on NPD performance.
INTRODUCTION
Firms need innovation, since innovation is an essential source of competitiveness and corporate success. It is important for managers to understand how to achieve positive performance out of innovation activities (Rothwell, 1995). Thereby, New Product Development (NPD) can be an asset to firms and their competitive advantage.
Dominant NPD approaches in literature are built on the idea of a structured process and are fit to operate in stable environments (Kamoche & Cunha, 2001). These approaches to control NPD processes fit in the major trend for firms regarding the improvement of efficiency and the lowering costs in their processes, through process management and control initiatives (Sethi & Iqbal, 2008).
3 Therefore, Biazzo (2009) tried to create a contingent approach on the design of New Product Development processes. Since otherwise, there is risk of ‘Simply accepting a normative perspective that leads to the identification and diffusion of decontextualized ‘’best practices’’’ (Biazzo, 2009).
From the current literature, Biazzo (2009) concluded that there are three important dimensions of flexibility, namely; structural flexibility, informational flexibility and temporal flexibility. In current literature, there is no clear distinction been made in literature between these different aspects of flexibility, while they are likely to have different effects on NPD performance (Biazzo, 2009). Adding to this, the conflict between the approaches that opt for structure and efficiency stand opposed to the approaches that opt for room for flexibility (Kamoche & Cunha, 2001).
The conflictual nature of the literature regarding this subject has proven to be a significant problem to both academics and practitioners (Biazzo, 2009). Source of this is the lack of knowledge on flexibility and the effect of turbulence that can result in an NPD management style that has a negative impact on the NPD performance (Biazzo, 2009). Therefore, it is of importance to increase clarity on this topic in order to get an insight in the optimal flexibility factors for NPD success, taking in account the turbulence in NPD environments.
4 The research question for this study will therefore be:
How are the flexibility factors gate conditionality, the product freeze point and centralization moderated by the degree of market- and technological turbulence in their effect on New Product Development performance?
LITERATURE REVIEW
Different interpretations of a phenomenon are from an academic point of view a symptom of the need of improvement of theory (Biazzo, 2009). This is the case for flexibility in New Product Development, since literature has no consistent formula for success, regarding this subject (Biazzo, 2009). Therefore, it is of academic importance to shed a light on the issue of flexibility in NPD processes.
Furthermore, innovations currently face turbulent environments (Iansiti, 2005). These can be hard to adapt to, especially with the lack of knowledge on the effects of flexibility, since uncertainty demands more flexibility in processes. If however, the right procedure for NPD is found and implemented, firms can innovate more successful. This can lead to the desired optimal innovative success for NPD projects (Sethi & Iqbal, 2008).
New Product Development
On one hand, high speed environments that NPD projects face demand flexible and fast reactions, which can be created with a flexible approach to the NPD process (Reinertsen, 1998; Kamoche & Cunha, 2001). Flexibility can also be a powerful tool to control development risk (Thomke & Reinertsen, 1998), because the design can be adapted in a less expensive or harmful way when there is room for flexibility. On the other hand, the use of structured management approaches to NPD can lead to superior product innovations (Cooper, 1993; Kamoche & Cunha, 2001) and can avoid the risks created by the acceleration of lead times (Kamoche & Cunha, 2001; Crawford, 1992). This shows that there is no consistent ‘right move’ for NPD teams, when deciding on flexibility in NPD processes, in order to create the maximum NPD performance.
New Product Development Performance
5 time to market of the newly developed product (Brown & Eisenhardt, 1995). The process that takes product development activities from idea generation to market launch is an important factor that can influence the innovative performance of a firm (Biazzo, 2009; Griffin, 1997). Keeping time in mind can create the greatest productivity and shorter lead times (Biazzo, 2009). That is why reducing the time to market for NPD is the competitive challenge that organizations across industries are facing (Feng, Sun, Zhu & Sohal, 2012). Greater customer involvement can improve NPD project success on the market, but has a negative effect on the time to market of the product (Feng, Sun, Zhu & Sohal, 2012). Therefore, this is a conflict regarding the effect of the time to market of the product and the adaptability to market demands.
Flexibility
Flexible processes are differently managed and organized than rigid processes (Biazzo, 2009; Iansiti, 1995a; Iansiti 1995b). Flexibility of a NPD process can be described as a function of the incremental economic cost of adjusting a product as a response to changes that are ex- or internal to the NPD project (Thomke & Reinertsen, 1998). Research has shown, that the later in the development process, the less flexible the process is. Less changes are being made, since the a greater part of the process has already been decided and therefore changes are more costly (Thomke & Reinertsen, 1998).
6 markets and technologies. Firms can be able to pursue a better development strategy, to make changes that create better design solutions, whereas the market and the used technology are concerned, and to avoid the need for large, late changes, because the commitments can be made later (Thomke & Reinertsen, 1998).
Concluded was that the use of structure and control as opposed to flexibility is much discussed in literature, but so far there is no clear outcome or conclusion. Biazzo (2009) conducted a meta-analysis on the effects of flexibility on performance. They found different sorts of flexibility in literature, and addressed them separately. This enables to investigate the relationships between process structuration (structural dimension), process flexibility in terms of the level of intersection between problem formulation and problem solving (informational dimension), and simultaneity in task execution (temporal dimension) (Biazzo, 2009). This study builds on this framework. There will also be attention for the effects of the different sorts of flexibility on each other and the NPD performance effects that occur from that. The aim in the former structures was to create a better understanding of the complex effects of flexibility in NPD projects. The three-dimensional framework can create better understanding of the complex relationships between the different forms of flexibility and the effects on NPD performance resulting from that (Biazzo, 2009). Therefore, the details on the different dimensions will now be discussed.
Structural flexibility
Structural flexibility, or organizational flexibility, discusses the ‘formal segmentation of the temporal progression in stages and the definition of the activities that should be occurring in each stage’ (Biazzo, 2009). There are two forms of structural flexibility that have an influence on NPD management (Biazzo, 2009). First, the structuration of the workflow, regarding formalization and centralization. Second, the process orientation, which refers to the progression structure of activities in the NPD process (Veryzer, 1998, 2005).
7 benefit to the NPD team and their firm. So there are two sides to formalization, regarding its possible effect on NPD performance.
Centralization is the extent to which project related power, decision making and power are concentrated (Monneart et al 1994). Centralization of control in a team, can negatively influence the NPD processes. It reduces the ability to solve problems in their projects and unit members also become less likely to seek to be innovative (Atuahene-Gima, 2003; Jansen, van den Bosch, Volberda, 2006). This shows that for this workflow structuration variable, a negative effect towards NPD performance can be expected.
Process orientation is the degree to which the NPD process follows a defined, standardized path (Biazzo, 2009). The NPD performance is effected by the ‘choice of the number and nature of the gates in the NPD process path’ (Anthony, 1996; Biazzo, 2009). While strict gates and paths are beneficial to NPD projects to a certain level because of the process speed that they can provide (Milosevic & Patanakul, 2005), they can have a restricting effect on the possibility of NPD project success because of learning failure. When there is no room to change direction, opportunities for growth and new projects can be missed. Therefore, this can possibly hurt the performance of novel products (Sethi & Iqbal, 2008). So, this part of structural flexibility is two-sided as well.
Informational flexibility
The informational flexibility regards the ‘level of intersections between problem formulation and problem solving’ in the NPD process (Biazzo, 2009). Firms often have a model of development wherein every requirement of the development is set in stone, before the actual design phase can begin (Thomke & Reinertsen, 1998). Because of this, they can get stuck in a pattern in which they have to make decisions, without having the proper knowledge to make such choices regarding the NPD process. That is why informational flexibility is needed. Although, the higher the cost and time of modifying a NPD design, the lower the informational flexibility in the NPD process will be (Biazzo, 2009; Thomke, 1997).
8 to focus on trying to find ways to production with a more cost effective and informationally flexible approach. Flexibility in this matter can reduce costs of NPD (Thomke & Reinertsen, 1998). Especially in turbulent environments, prone to fast and radical changes, having a flexible product development process is critical as a source of advantage for NPD success (Iansiti, 1995).
Therefore, the focus on iterations in the product development process should be facilitated, since it can bring prospect upon the process. Iterations entail that ‘product requirements and specifications are modified throughout the project starting from an initial hypothesis’. The product is defined late in the process, which creates an opportunity to easily adapt the product’s design, if need be (MacCormack, Verganti & Iansiti, 2001; Biazzo, 2009). A high degree of ‘modularity’ in the product, facilitates a product creation organization that is ‘loosely coupled’, wherein the components can function autonomously and concurrently (Sanchez and Mahoney, 1996; Biazzo, 2009), which adds to the iteration possibilities of the NPD project.
When iterations cannot be made anymore, the product is ‘frozen’. When the product design is frozen early in the process, no more changes to the design can be done. The lack of adjustment capabilities, possibly leading to a favorable product, can turn out to be a drawback. Although, it can have a positive effect to the time to market of the product, as the development of the product can be completed faster, due to the clear, but rigid goal (Zirger & Hartley, 1994). Temporal Flexibility
Biazzo (2009) found the importance of ‘temporal flexibility’ as well. Temporal flexibility discusses flexibility to the time scheduling and the simultaneity in task execution. Kamoche & Cunha (2001) Flexibility in time is also discussed as the ‘variation followed by fast convergence and overlapping procedures’, while the opposite, a sequential approach, is seen as ‘structured, with discrete phases carried out sequentially’.
9 Flexibility to time scheduling, or the time between the formal project review points (Eisenhardt & Tabrizi, 1995) increases flexibility in the NPD process (Sethi & Iqbal, 2008). It can also lead to increased performance, because of the control, teams are more likely to find and overcome shortcomings, when reviewing the project process (Sethi & Iqbal, 2008).
Overlap, or simultaneity in tasks, entails that project phases can be carried out sequentially (Kamoche & Cunha, 2001). This approach can create high uncertainty, resulting in counterproductivity, possible delays and difficulties coordinating the NPD process. All of the above can have a negative impact on NPD performance. Although, it cuts ‘project review preparation, presentation and resulting engineering changes, because the functionally related issues have been addressed and resolved within the team, during the NPD process (Zirger & Hartley, 1996). Overlap in the activities in the NPD process also facilitates the fast development of the products, as the tasks can be done simultaneously (Zirger & Hartley, 1996). These are positive effects on NPD performance, compared to sequential approaches. Sequential approaches can be rigid, too formal and time-consuming, which can create difficulties in the NPD process as well (Biazzo, 2009; MacCormack et al, 2001). So, overlap in design phases can have both positive and negative consequences for NPD performance.
The effect of Market- and Technological Turbulence
Market- and technological turbulence need to be taken into account when it comes to the flexibility of the NPD project. It requires motivation to change and cognitive flexibility for the project team (Canas, Fajardo, and Salmeron 2006; Duncan and Weiss 1979; Sethi & Iqbal, 2008). Since in uncertain environments, NPD teams need more ability to adapt to the sudden changes. Flexibility can help them do so. Otherwise, learning failure can occur, which has negative effects on the market performance and on novel products (Sethi & Iqbal, 2008). The teams risk the chance of ending up with less than ideal NPD processes and products.
10 If new information on technology occurs suddenly, there is technological turbulence for firms and their NPD projects. Technological turbulence is often defined as the degree to which technology changes over time within an industry and the degree to which such changes affect the industry (Jaworski and Kohli 1993; Sethi & Iqbal, 2008). Technical breakthroughs in the environment therefore are a reason for managers to act opportunistic, since they need to adjust to the changes fast to keep up (Veryzer, 1998). They need flexibility in their NPD processes to be able to do so. Therefore, expected can be that flexibility therefore has a positive influence on the performance of NPD processes in a technological environment.
In conclusion, flexibility seems to have a positive effect on NPD processes in turbulent environments, on either the level of their market or their technologies. But, this effect is not researched yet, in combination with the dimensions and measures by Biazzo (2009). The turbulence factors do seem to thrive on flexible processes. However, Biazzo (2009) does not vote for a complete dismantling of Stage-gate processes. This paper will therefore look into the effects of the market- and technological turbulence on several flexibility measures in the framework of Biazzo (2009).
Organizational Information Processing theory
This study can be approached from the perspective of Organizational Information Processing Theory. This theory (OIPT) was first introduced by Tushman & Nadler (1978). The thought behind this theory is that there has to be a ‘fit’ between the information processing requirements and the information processing capabilities (Song, Van der Bij & Weggeman, 2005). The effectiveness of the OIPT is the function of the matching of these requirements and capabilities. In our case, this can be translated in the need to fit the flexibility in the project to the turbulence and their fit to create maximum NPD performance. The requirements in OIPT evolve out of the uncertainty of a unit or team. This depends on the complexity and the interdependence of the task, the environment that the task or project is in, and the inter-unit task interdependence. The information processing capabilities in OIPT emerge from the organic or mechanistic design of the unit and the set of coordination and control mechanisms on the task (Tushman & Nadler, 1978).
11 Hypotheses
In this paper, focus is on one factor of flexibility of each dimension of Biazzo (2009). Tested will be what their effects towards NPD performance will be, and how market- and technological turbulence might moderate this effect.
The first factor that is researched is centralization. The flexibility measure centralization is mostly related to the information processing capabilities in the OIPT, since it involves the mechanisms of coordination and control in NPD projects (Tushman & Nadler, 1978). The capability to work with dispersed power in the NPD process, can be an asset to NPD teams, because there is a negative effect of centralization towards the performance of such innovative endeavours, such as NPD projects (Damanpour, 1991). Dispersion of power is facilitating for innovation and its success, according to Thompson (1965). It creates involvement and commitment for team members, which can lead to higher performance (Damanpour, 1991). From this information, we can conclude, that centralization will probably have a negative effect on the NPD performance. Therefore, argued is that
H1a: A higher degree of centralization decreases NPD performance.
Adding to this, argued is that the amount of uncertainty in the environment of the innovation and the differences between industries is of vital importance for the effect of centralization (Cardinal, 2001; Jansen, van de Bosch and Volberda, 2006). Decentralization creates more flexibility, and increased flexibility thrives in turbulent environments (Sethi & Iqbal, 2008). The more turbulent the environment, the more dispersion of power has a positive impact on the NPD performance. Therefore, turbulence can negatively moderate the relationship between centralization and NPD performance. Thus
H1b: Market turbulence increases the negative effect of increased degree of centralization on NPD performance.
H1c: Technological turbulence increases the negative effect of increased degree of centralization on NPD performance.
12 criteria for improved control makes projects more inflexible’ (Sethi & Iqbal, 2008). This inflexibility can lead to worse performance, because the rigid outcome restricts learning possibilities (Sethi & Iqbal, 2008). Therefore, gate-conditionality can be of positive influence to NPD performance. Adding to this, criteria that lower gate conditionality are often made on the top of the hierarchy, and therefore, high gate conditionality is not likely to appear in combination with centralization (Sethi & Iqbal, 2008). Taking this information in mind, the next hypotheses are conducted.
H2a: High gate conditionality has a positive impact on NPD performance.
H2b: High gate conditionality has a less positive impact on NPD performance, when combined with a high degree of centralization.
Rigorous gate criteria and controls are not appropriate, when there is turbulence in the technological environment of the project. Actually, turbulence can be seen as an information processing requirement in the OIPT. Because the unit task environment, in our case the NPD team environment, is an influencing factor of the information processing requirement (Tushman & Nadler, 1978). It influences the possibilities for gathering information that can be used in the NPD project, as turbulence causes for information changes and new information. Gates should therefore be made flexible, and fitting to the state and nature of the project, so they can be adapted to the requirements of the changing environments (Sethi & Iqbal, 2008). Therefore, proposed is that
H2c: Market turbulence increases the positive effect of high gate conditionality on NPD performance.
H2d: Technological turbulence increases the positive effect of high gate conditionality on NPD performance.
13 early has its drawbacks, when taking into account turbulence. If the market or technology in the environment of the firm and the product change fast, the new product will not match expectations and standards when frozen too early. With changing as the environment changes, firms have a larger chance of matching the demand of their external environment, and therefore a greater chance of a commercial success (Zirger & Hartley, 1994; Susman, 1992). Therefore, hypothesized is that
H3a: An early freeze point has a positive effect on NPD performance in case of low market turbulence.
H3b: An early freeze point has a positive effect on NPD performance in case of low technological turbulence.
H3c: An early freeze point has a negative effect on NPD performance in case of high market turbulence.
H3d: An early freeze point has a negative effect on NPD performance in case of high technological turbulence.
Conceptual Model
14 METHODS
Fit of the study
This study builds on the framework that Biazzo (2009) created. From the data that were collected, a quantitative, theory testing research has been done. This fits the current state of literature on the subject, since this paper tests the literature grounded framework by gaining information out of practice. This was not done with the framework of Biazzo (2009) yet, while it has the potential of creating uniformity regarding the view on flexibility in NPD processes. Data collection procedures
15 The interviewed firms all had to fit the following criteria. First, the survey regarding the NPD project characteristics had to be filled out by a NPD team member of a firm, consisting more than 30 employees. Teams of this size tend to be the most successful in NPD development (Dayan, 2010). By using teams that all fit to this requirement, the research will be able to create a more unbiased view on the topic of flexibility. Second, a survey regarding firm data and performance has been filled out by a general or innovation manager, to overcome the common method bias of team members reviewing their own projects. The interviewees all are working in Dutch firms, as this creates more unity in the sample and rules out country-related culture differences in NPD management (Souder & Jenssen, 1999).
In order to carry out the interviews, the students received a template from their supervisors, that was created from earlier research. This interview template (Appendix 1) has been improved and translated to Dutch, in order to fit the research and the Dutch interviewees. The interviewers also were all Dutch, this way, a possible language barrier is avoided, to get the interviewees to respond as precise as possible. Interviews were mostly distributed via Qualtrics. A few interviews were done on paper or over the phone. All the interview results are collected in Excel, so the students got the ability to work with each other’s results.
Measures
Independent variables
For centralization, the team members were asked to react on five different quotes, on a seven-point Likert scale, ranging from 1- fully disagree to 7-fully agree. The same scale was used for the questions on gate conditionality, using four statements, adopted from earlier research (Jansen, van den Bosch and Volberda, 2006, Sethi and Iqbal, 2008). To address the freezing of the NPD project, the interviewees were asked to write down what percentage of the project that was already done, when the project definition was determined. To address the moderating variables in this paper, regarding the turbulence, the interviewees from the group of managers were asked to range their market- and technological turbulence on a similar Likert scale (1-fully disagree, 7- fully agree) in four statements addressing technological turbulence and in five statements regarding market turbulence (Jaworski and Kohli, 1993).
Dependent variables
16 to review the performance of their NPD process on a 1-7 Likert scale, from 1-considerabily worse to 7- considerably better (than expected at the start of the process). Seven performance statements, adopted from the research by Schleimer & Faems (2016) and Ahmad, Mallick, & Schroeder (2012), were used for this . The seven measures are product development costs, product quality, technological performance regarding product specifications, time to market, market share, profitability, and commercial success of the product.
Control variables
To check the reliability of the outcome of the research, several control variables were used. The ‘firm age’ was used as one of these control variables. Since, as a firm matures, their innovation activities and focus changes. Their view and methods on innovation changes, as well as the outcome of these activities. (Utterback & Abernathy, 1975; Veryzer, 1998). The duration of the project was also taken into consideration. Development time is of critical importance for NPD projects. Time of development needs to be taken into account since NPD projects have to avoid missing their window of opportunity (Zirger & Hartley, 1994). Also, the R&D expenses are taken into account, since this tells something about the focus that the firm of the NPD project lays on innovation activities (Andras & Srinivasan, 2003). All these control variables were asked after in such a way, that interviewees could answer with the exact amount of time or budget involved.
Validity & reliability issues
17 ANALYSIS & RESULTS
With the 49 gathered data sets (including a few missing data points), a factor analysis was conducted before testing the hypotheses. Thereby, addressed could be if the multi-item scales on the different factors could be taken together, so new variables could be computed. The factors needed to load into the correct factor and have the right loading; greater than 0,5 and lower than 0,4 on more than one factor. They also needed to have appropriate Chronbach’s Aplhas. Table 1 shows the results of the factor analysis. It turned out that all five questions regarding centralization could be computed into a new variable, as well as all seven performance measures. For gate conditionality and technological turbulence, three measures could be used to compute a new variable. For market turbulence, two measures were included. Therefore, the follow-up tests were done with new, computed variables, related to the factor analysis results (table 1).
TABLE 1
Loadings of Factor Analysis - Rescaled Components
18 With these new constructs, the correlation between the measures was conducted, as shown in table 4. However, this showed not much correlation between the measures so far. Only gate conditionality showed significant correlation with the time until freeze point (r=-0,341, p<0,05) and the firm age (r=0,342*, p<0,05).
TABLE 2 Correlations Mean (Standard Deviation) Perfor- mance Techno- logical Turbu-lence Market Turbu- lence Centrali-zation Gate Conditio- nality Time until Freeze Point Firm Age R&D Expenses Project Duration Performance 4,425 (0,840) 0,099 0,061 0,013 0,145 0,198 0,066 0,123 -0,149 Technological Turbulence 5,305 (1,110) 0,143 -0,187 -0,069 -0,072 -0,194 0,154 0,088 Market Turbulence 4,802 (1,161) 0,254 -0,055 0,068 -0,021 -0,213 -0,111 Centralization 2,535 (1,205) 0,044 0,079 0,043 -0,283 -0,077 Gate Conditionality 2,905 (0,908) -0,341* 0,342* 0,190 -0,145 Time until Freeze Point 41,933 (31,184) -0,202 -0,162 0,246 Firm Age 71,54 (94,094) 0,316 -0,126 R&D Expenses 21,573mljn (80,003mljn) 0,020 Project Duration 17,51 (21,484) *P<0,05
19 The regression analysis with the conducted performance measure (C) turned out to not have significant results for technological turbulence. So, no conclusions can be drawn regarding the effect of the independent variables nor on the effect of the moderating effects on NPD performance and the hypotheses regarding this statement. Therefore, the performance measures (1) to (7) were also reviewed separately, which did result in some significant results (tables 3 & 4). The results show that only the regression analysis on the sixth performance measure, the profitability of the project, creates significant results. R&D expenses and firm age showed significant (p<0,05) and positive effect in models 2 and 3. The time until freeze point (model 2: p<0,01 and model 3: p<0,05) also showed positive and significant effects. Centralization (p<0,1) showed a significant but negative effect towards the profitability of the project. In model 3, the technological turbulence had a positive effect to the profitability (p<0,05), whereas the added interaction term of the time until freeze point and technological turbulence had a slightly negative influence (p<0,1). So in combination with technological turbulence, the effect becomes less positive. The higher the technological turbulence, the lower the positive effect of a late freeze point to the profitability of the NPD project.
TABLE 3
Model 2 Regression Analysis Results: Technological Turbulence
20 TABLE 4
Model 3 Regression Analysis Results: Technological Turbulence
Performance (C) (1) (2) (3) (4) (5) (6) (7) B(f) B(f) B(f) B(f) B(f) B(f) B(f) B(f) Control Variables Project Duration -0,00 -0,01 0,00 -0,00 -0,02 0,01 0,01 0,00 R&D Expenses 0,00 0,00 0,00 0,00 0,00 0,00 0,00** 0,00 Firm Age 0,01* 0,00 0,00 0,00 0,01 0,01* 0,01** 0,01* Independent variables Time to Freeze Point 0,01 0,00 0,02 0,11 0,01 0,01 0,02** 0,01 Gate Conditionality -0,13 0,11 0,01 0,05 -0,23 -0,55* 0,15 -0,45 Centralization 0,27 0,36 -0,14 0,09 0,65 0,58* -0,02* 0,36 Moderator Technological Turbulence 0,07 -0,11 0,07 0,12 -0,03 0,30 4,50** 0,06 Interaction Terms Freeze point X Tech Turbulence -0,01 -0,01 0,01 -0,01 -0,01 -0,02* -0,01* -0,01 Centralization X Tech Turbulence 0,18 0,32 0,01 0,01 0,13 0,30 0,18 `0,31 Gate Conditionality X Tech Turbulence 0,05 0,12 0,24 -0,12 0,48 -0,03 -0,02 -0,32 F value 1,63 1,70 0,67 0,60 1,63 1,75 2,79 1,39 ANOVA Sig. 0,18 0,31 0,74 0,80 0,18 0,15 0,03** 0,27 Highest VIF 2,92 2,92 2,92 2,92 2,92 2,92 2,92 2,92 *= P<0,1, **=P<0,05
The regression analyses for the variables in combination with market turbulence were also conducted. In these analyses, the models using the conducted NPD performance measure were significant (p<0,1). In model 2 of this analysis (table 5), firm age and the time until freeze point were positive and significant (p<0,05). Firm age stayed positively significant in model 3 (p<0,05) (table 6), whereas the time until freeze point was not significant anymore when the interaction effects were added. So, argued can be that time until freeze point has a positive effect on NPD performance in model 2 (table 5), which it had not in the same model, where technological turbulence was a factor of influence (table 3). Given these findings, we cannot prove our hypotheses regarding the NPD performance and the influence of market turbulence on these findings.
21 (profitability of the project) was significant (p<0,01). R&D expenses (p<0,05), firm age (p<0,01), time until freeze point (p<0,01) and centralization (p<0,05) were the significant measures in this analysis. Time until freeze point was also significant in the regression analyses that involved the technological turbulence. Therefore, stated can be that a late product freeze point has a positive effect on profitability of NPD projects, without taking into account the moderating influence of turbulence. .
In model 3, including the interaction effects of market turbulence (table 6), the regression analysis was also performed for all the separate performance measures. This showed that the analysis had a significant result for three performance measures; market share, profitability and commercial success of the product. For commercial success, the market turbulence stood out as significant and positive effect (p<0,001). Firm age was also positive and significant in this case (p<0,05). For market share and profitability, the interaction variable of market turbulence and centralization had a positive and significant effect (p<0,1). Therefore, we can assume that market turbulence has a positive moderating influence on these performance measures. For the performance measure profitability of the project, time until freeze point also showed a positive and significant result (p<0,1). However, these findings cannot be attached to any hypotheses that was made.
TABLE 5
Model 2 Regression Analysis Results: Market Turbulence
22 TABLE 6
Model 3 Regression Analysis Results: Market Turbulence
Performance (C) (1) (2) (3) (4) (5) (6) (7) B(f) B(f) B(f) B(f) B(f) B(f) B(f) B(f) Control Variables Project Duration -0,00 -0,02* 0,00 0,00 -0,03** 0,00 0,00 0,01 R&D Expenses 0,00 0,00 0,00 0,00 0,00 0,00 0,00*** 0,00 Firm Age 0,01** 0,00 0,01* 0,00 0,00 0,01* 0,01*** 0,01** Independent variables Time to Freeze Point 0,01 0,00 0,01 0,01 0,01 0,00 0,02* 0,01 Gate Conditionality -0,07 0,30 -0,129 0,04 -0,14 -0,36 0,26 -0,31 Centralization 0,05 0,17 -0,15 0,06 0,56 0,14 -0,23 -0,25 Moderator Market Turbulence 0,213 -0,09 0,21 0,17 -0,24 0,38 0,24 0,71*** Interaction Terms Freeze point X Market Turbulence 0,01 -0,01 0,01 0,01 -0,00 0,00 -0,02 0,01 Centralization X Market Turbulence 0,21 0,25 -0,01 0,06 0,29 0,51* 0,37* 0,12 Gate Conditionality X Market Turbulence 0,07 -0,01 0,27 0,22 0,30 -0,21 -0,06 -0,18 F value 2,10 1,71 1.38 1.10 1.71 2,05 3,47 2,54 ANOVA Sig. 0,09* 0,37 0,27 0,41 0,16 0,09* 0,01** 0,04** Highest VIF 3,20 2,88 2,88 2,88 2,88 3,20 2,88 2,88 *= P<0,1, **=P<0,05, ***P<0,01 DISCUSSION
23 How are the flexibility factors gate conditionality, the product freeze point and centralization moderated by the degree of market- and technological turbulence in their effect on New Product Development performance?
There were no significant results to answer this question on the model with the computed NPD performance variable, which covered all the performance measures. Therefore, no claims regarding this matter can be done, even if the regression results in the models were significant. There were no results related to the hypotheses, that could be considered significant, taking into account that the analyses for market- and technological turbulence were conducted separately. But there were some other significant results.
When the performance measure was split, there were some significant models found regarding the separate performance measures. Since this research tested technological turbulence and market turbulence separately, because of collinearity, the results were separate. In the model that tested on profitability of the project, we found that R&D expenses and firm age had significant influence on this matter. Time until freeze point also has positive influence on this performance measure, but was negatively moderated by technological turbulence. Without this turbulence, an earlier freeze point can have a positive influence on the profitability of an NPD project, which is in line with the research by Zirger and Hartley (1994). Centralization has a negative influence on profitability in this analysis. An explanation for this could be that centralization reduces the ability to solve problems and seek innovation, since teams lack control of their own ideas (Atuahene-Gima, 2003; Jansen, van de Bosch, Volberda, 3006). However, market turbulence is not involved in this claim, and probably should be.
24 Theoretical implications
This research tried to create clarity in the ongoing debate of flexibility in NPD project and the effect on NPD performance. Taking into account the increasing uncertainty in markets and technologies (Kamoche & Cunha, 2001), which generally asks for more flexibility, we did not find evidence for the effects of the three different flexibility measures that were discussed in this paper. No significant results were found for centralization, the time until freeze point and the gate conditionality in the NPD performance outcome, when the turbulence measures were added. A level of significance was found for the time until freeze point in the second regression model including market turbulence, which implicates a positive influence of a late freeze point. This relationship however does not keep up, when the moderation of market turbulence is added. On other hypotheses, there can be no conclusion drawn. Therefore, no further implications on the proposed effects can be added to literature.
Managerial implications
Based on this research, there are no implications when it comes to the effect of turbulence and flexibility. However, concluded can be, that a later product freeze point has a positive effect towards the project profitability (Zirger and Hartley, 1994). This is therefore recommendable, if managers want to enhance their project profitability. However, its effect on other performance measurements could not be proven, and can therefore also be negative. This is the case for most findings in this research. A positive influence on one parameter of performance, does not promise a positive influence on other measures. Managers have to take in mind that the effects on all the performance measures and flexibility choices together create the final NPD performance (Biazzo, 2009).
Limitations & further Research
25 of the NPD projects was not taken into account. The flexibility of the management in the project is of influence to the NPD performance (Biazzo, 2009), but one should note, that the nature of the project and firm itself also has an influence (Sahay & Riley, 2003). The place in market of the firm and their NPD product does matter, no matter how ideal the flexibility and turbulence in the NPD project.
So, there is still no clarity on all the effects of flexibility on all the different performance measures. Because of the inconsistency regarding this subject, it would still be relevant to access and create a theory on this issue. After all, it can be of importance to managers. Since managers desire optimal performance of their NPD projects, and every insight that can be found, can be another chance for success.
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APPENDICES
Appendix 1: Survey questions related to this paper from the template
Questions to the NPD team leader/project participant What is the name of the project/product?
What was your role in the project (e.g., project leader, project member)? Project duration in months:
How far was the project completed when the project definition fixed? (% completion =) The next 5 questions have to do with the centralization in and around the project. - There could be taken little action in the project until a supervisor approved the decision
- A person wanting to make his own decision during the project would have been quickly discouraged
- Even small matters had to be referred to someone higher up for a final decision - Project members needed to ask their supervisor before they did almost
everything
- Most decisions project members made had to have their supervisor’s approval
Anchor: 1=completely disagree, 2=disagree, 3=somewhat disagree, 4=neutral, 5=somewhat agree, 6=agree, 7=fully agree.
The following 4 questions have to do with gate conditionality
29 - The review criteria recognized that the project followed a different development
sequence and allowed the project to proceed further even when it only met criteria partially
- The review criteria recognized that various development activities needed to be approved out of sequence and allowed for that to happen
- At every stage, all project criteria had to be met before the project was allowed to proceed further
Anchor: 1=completely disagree, 2=disagree, 3=somewhat disagree, 4=neutral, 5=somewhat agree, 6=agree, 7=fully agree
Questions to the managers
What is the name of the project/product? What is the age of your firm?
What were the R&D expenses of your firm in the year the project was launched? What is the success of the project with respect to the initial expectations in terms of:
- Product development costs - Product Quality
- Technical performance with respect to specifications - Time to market
- Market share
- Overall profitability of the product
- Overall commercial success of the product
Anchor: 1=significantly worse than initial expectations, 2=worse, 3=somewhat worse, 4=about the same, 5=somewhat better, 6=better, 7=significantly better
The next questions will discuss the degree of technological turbulence in the environment - The technology in our industry is changing rapidly
- Technological changes provide big opportunities in our industry
- A large number of new product ideas have been made possible through technological breakthroughs in our industry
30 Anchor: 1=completely disagree, 2=disagree, 3=somewhat disagree, 4=neutral, 5=somewhat agree, 6=agree, 7=fully agree.
The next questions will discuss the degree of market turbulence in the environment - In our kind of business customers’ product preferences change quite a bit over time
- Our customers tend to look for new products all the time
- We are witnessing demand for our products from customers who never bought them before
- New customers tend to have product-related needs that are different from those of our existing customers
- We cater to many of the same customers that we used in the past
