Lead users: a source of novel product concepts
Management Science
Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation
Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Shifting Innovation to Users via Toolkits
Management Science
International Journal of Intelligent Systems
A two phase multi-attribute decision-making approach for new product introduction
Information Sciences: an International Journal
User involvement competence for radical innovation
Journal of Engineering and Technology Management
Organizational determinants of innovation capacity in software companies
Computers and Industrial Engineering
Computers and Industrial Engineering
Expert Systems with Applications: An International Journal
An overlapping process model to assess schedule risk for new product development
Computers and Industrial Engineering
Risk analysis models and risk degree determination in new product development: A case study
Journal of Engineering and Technology Management
Journal of Engineering and Technology Management
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This study mainly focuses on the risk evaluation of customer integration in new product development. Customer integration in product innovation projects has been widely recognized a best practice to enhance innovation success rate and reduces the development cycle time, but it also has many potential risks including loss of know-how, much dependence on customer, and limitation to incremental innovations, etc. Unfortunately, there are few researches about risk evaluation for customer integration which is important to the risk management of the co-innovation process. Further, evaluating customer integration risk involves much subjectivity and vagueness. To manipulate this problem, a novel evaluation approach for assessing customer integration risk under uncertainty is proposed. The novel approach integrates the merit of rough set theory in handling vagueness and the strength of group analytic hierarchy process (GAHP) in modeling hierarchy evaluation. Finally, an application in a project of mobile phone development is provided to demonstrate the application and potential of the methodology.