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Prioritization and operations NPD mix in a network with strategic partners under uncertainty
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Prioritization and operations NPD mix in a network with strategic partners under uncertainty

Hsing Hung Chen, Amy H.I. Lee 和 Yunhuan Tong
Expert systems with applications, 卷.33(2), 頁碼.337-346
01/08/2007
Web of Science ID: WOS:000244344000009

摘要

Fuzzy analytic hierarchy process (FAHP) New product development (NPD) NPD mix selection and operations Technological conglomerate network (TCN)
In response to dynamic and individual customer needs and increasing complexity in product design along with rapidly changing technologies, new product development (NPD) is always a focus to companies. NPD process contains a tremendous degree of complexity and uncertainty, and multiple NPD are usually selected to increase the possibility of having more successful products. This, however, leads to an even more complicated problem of designing an appropriate portfolio of NPD in a program. Additionally, since a firm is difficult to survive independently in industry, flexible strategies to collaborate with or to compete with firms when selecting and operating NPD inside the network are essential. This topic, which has not been discussed a lot, is becoming more and more important in the near future. This paper first discusses the critical success factors (CSF) of NPD based on technological conglomerate networks (TCN), and then simplifies 37 CSFs into three criteria, 10 sub-criteria and their detailed judgment factors by factor analysis. Analytic hierarchy process (AHP) is employed to prioritize the relative importance of multiple evaluation criteria and the preferences of NPD mixes by generalizing experts’ opinions. To compensate the uncertainty and vagueness in the environment and human judgment, a fuzzy AHP model considering of confidence level ( α) and risk index ( β) is proposed. A home appliances firm in China is used as an example, and the results show that the firm can lead to a more operational excellence in NPD mix practice and core competence by applying the proposed model.

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