Developing new products has received much attention within the last decades. This issue can be highlighted for strategic innovations, in particular. Recently, knowledge-based networks have been introduced in order to facilitate the affair of transforming knowledge into commercial products which can be regarded as a set of research centers, universities, knowledge intermediaries, customers, and so forth. However, there is a wide range of risk factors that are liable to affect the chain performance. Hence, this paper aims to consider the most influencing criteria that can play a more significant role in achievements of such networks. To do so, DEMATEL has been applied to take the relationships between the risk factors into account. Moreover, fuzzy set theory has been utilized in order to deal with the linguistic variables. Finally, the most important factors are identified and their relations are determined. 1. Introduction Over the last years, companies have extensively concentrated on developing high quality products and services which can be justified with respect to the rise of consumer demands and severe competition amongst the companies. The competition is more highlighted about the case of introducing novel products, in particular [1]. It is commonly observed that many companies are hesitant to endure the risks of experiencing innovations or adopting leading-edge technologies, particularly “strategic” innovations. The strategic innovations are expensive with a noticeable proportion of ambiguity, which make the associated research and development take longer. The risks can be facilitated by the application of collaboration strategies. However, the cooperation may be hindered when the companies look for collaborating with technology partners that are reluctant to have serious working relations. Technological innovations may be followed by another shortcoming: the intrinsic risks with science-based innovations which are often hard to express, define, and quantify. The organizations may encounter significant financial and opportunity losses if the development or launch of their new product is deferred. For instance, Kurawarwala and Matsuo [2] showed that a six-eight-month delay in launch of products such as computers and cellular phones by a computer manufacturer results in a 50–75% loss in revenue. In a more recent study, McGrath and MacMillan [3] indicated that a six-month delay in the introduction of the product leads to a $2 million decrease in the project’s net present value. These instances can prove the importance of enhancing new product
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