A one-sample t-test was conducted to determine whether there is a statistically significant difference between the mean perceptions of team members from technological functions and team members from other functions. Team members from technological background gave more importance to both probability and impact of technological rapidity risk, the probability of marketing rapidity risk and the probability of financial unpredictability risk. In contrast, risk factors such as the probability of technological capability risk, the probability of marketing capability risk, the probability of competition risk, the probability of planning risk, the probability of lack of funding and probability of supply chain risk were given more importance by team members from other functions. For the remaining risk factors, there were no statistical differences in the perceptions of team members with the varying background.
Another one-sample t-test was conducted to determine whether there is a statistically significant difference between the mean perceptions of top management and team members from middle or low-level management. Top management gave more importance to the probability of technological rapidity risk, the probability of technological capability risk, the probability of financial unpredictability risk, the probability of financial unpredictability risk and impact of macroeconomic risk. In relation to their perceptions, middle level or low-level management gave more
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importance to risk factors such as the impact of technological capability risk, the impact of marketing capability risk, the impact of resource risk, the impact of human resource risk, the impact of planning risk, the impact of control risk and the probability of lack of funding risk. For the remaining risk factors, there was not any significant difference in the perceptions of top management and middle or low-level management. In other words, they viewed remaining risk factors equally important or unimportant.
With the help of mode values and independent sample t test, I tried to determine whether there was significant statistical difference in the mean perception of team members from technological functions associated with SMEs and large firms. According to the result, there was a clear difference of perceptions about certain risk factors by R&D respondents from both SMEs and large firms. For example, R&D respondents from SMEs emphasized their worries for the high likelihood of marketing capability and potential negative impact of lack of funding. In contrast, R&D respondents from large firms were more inclined towards the negative impact of competition risk and resource risks.
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8 Discussion
The purpose of this chapter is to build on the findings from the empirical elements of the study reported previously. The section begins with the synthesis of the findings presented in the descriptive statistics section. Next, the findings related to the research question (RQ1), research question (RQ2) and research question 3(RQ3) are discussed and synthesised. By doing so, this work aimed to empirically identify and confirm the risks prevalent to NPD projects and identify how perceptions of risk changes according to different contingency factors. Finally, a summary is presented to conclude the chapter.
8.1 Introduction
New product development (NPD) is a key aspect of innovation and is one of the most important strategic and operational tools; an organization can use to sustain growth and profitability (Kok and Lightart, 2014). Firms increasingly develop new products to respond to market change, develop competitive advantages, and increase their chances of survival (Kok and Lightart, 2014). Market changes require firms to develop not just incremental products, but also radical products that they can commercialize (Kok and Lightart, 2014; O‟Connor et al., 2008). While radical NPD requires new knowledge based on new competencies and practices, incremental NPD, in contrast, builds on existing competencies and practices (Christensen, 1997; O'Connor, 2008).
There are several significant incentives for firms to continuously introduce new products (increment or radical) to the markets. First, the financial return from successful NPD can help firms overcome the slowing growth and profitability of existing products that are approaching the maturity stages of their life cycles (Ahmad et al., 2013). For example, according to a study by the Marketing Science Institute (USA), 25% of successful firms‟ current sales were derived from new products introduced in the last three years (Dahan and Hauser, 2002). Second, the reputation of the firm and its brands is heavily influenced by the number of successful NPD projects it conduct (Dahan and Hauser, 2002). For example, Nike has enhanced its overall brand reputation, well
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beyond athletic footwear by introducing golf equipment and supplies, swimwear, soccer equipment and apparel (Dahan and Hauser, 2002). Third, NPD can be a potential source of significant economies of scale for the firm (Beverland et al., 2016). New products may be able to use many of the same raw material inputs as the firm‟s existing products and may be able to be sold by the firm‟s existing sales force resulting in substantially lower unit costs (and in turn higher margins) for the firm.
Although NPD creates value for firms, each NPD project involves some degree of uncertainty and risk (Cui and Wu, 2016; Keizer et al., 2005). Yet, many firms assume that their entire portfolio of NPD projects will succeed, and fail to identify and analyse the risks associated with each NPD project. This orientation will lead to the failure of NPD projects (Raz et al., 2002). There is considerable evidence that NPD projects suffer from risks and are prone to serious cost and schedule overrun and decline in targeted technical performance of the product. For example, according to a report published in 2013 by the Product Development and Management Association (Markham and Lee, 2013), only 61% of launched products succeeded in the market. Given the high ratio of NPD project failures, firms cannot continue to carry NPD projects which are prone to risks. They need to be prepared for NPD project risks and be ready to manage these risks effectively (Raz et al., 2002). Consequently, the awareness of NPD project risks has gained considerable attention among both academics and practitioners.
While existing academic literature provides an extensive discussion of risk management tools and methods, it was found that no classification of NPD project risks existed despite regular calls for its development (Schmidt et al., 2001; Wallace et al., 2004) that would allow comprehensive insight into NPD project risks and permit comparisons of NPD project risks for different NPD types (incremental or radical), different firm sizes (i.e. SMEs vs. Large firms) and for different industries. This is considered to be a major omission because, without a clear overview of risks and a proper understanding of the interaction between risks and different contingency factors (e.g. different NPD types and firms sizes), the policy makers may fail to devise an effective risk management strategy (Wallace et al., 2004). Therefore, the purpose of this research was to fill in this significant gap in the literature by developing inductively
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from the existing studies, a classification of main risk types, each with a number of sub- categories, providing definitions and supporting evidence for each and empirically validating the proposed taxonomy of risks.
Because, NPD literature also suggests that NPD projects differ from each other in several characteristics such as size, duration, product type, industry (Raz et al., 2002) and that NPD practices depend on these project‟s characteristics (Griffin, 1997). Therefore, any NPD related construct which needs to be investigated should be analyzed in the context of these project characteristics. The same applies to NPD project risks. One cannot expect that a single universal list of risk factors would apply to all types of NPD projects. Just as there are different types of projects, there can be different types of risks (Raz et al., 2002). Because the interactions between NPD project risks and different project characteristics were not studied extensively, I decided to analyze this interaction between risks and different contingency factors that may influence NPD projects? Particularly, I focused on three characteristics: NPD project type i.e. radical vs. incremental, firms‟ size (SMEs and large firms) and industry type.
To achieve the objectives, I first adopted an inductive approach mentioned by Armstrong et al. (2012), Pittaway and Cope (2007) and Pittaway et al. (2004) to produce an extensive list of risk factors. In this approach, each article was coded using an emergent coding scheme which allowed the key themes to emerge from the data. This process led to the emergence of 18 risk types which were organized into six main categories: technological risk, marketing risk, operations risk, supply chain risk, finance risk and environmental risk. The research first empirically examined the extent to which this proposed list of risk factors was associated with UK firms conducting NPD operations. Then I analyzed their interactions with three different contingency factors by employing large-scale survey of 263 respondents. In the following sections, I will provide a synthesis of the findings in the light of past literature and provide extensive discussion on each risk type. I will start with the discussion of the key points of the descriptive findings.
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