Research on innovation customer resource selection and evaluation based on wavelet network

Product innovation capability is becoming the core competence of manufacturing enterprises, and many researches show that the knowledge and innovation ability of customers are the most important resources of enterprises´ innovation capability. How to identify innovation customers and evaluate them becomes a hot issue. Firstly, according to the characteristics of customer collaborative product innovation, the problems in resources selection and evaluation methods in traditional manufacturing enterprises were analyzed in this paper. Secondly, innovation customer evaluation index and fuzzy number were put forward. Then, based on the theory of wavelet neural network, a new collaborative innovation customer resources selection model was proposed, where conjugate grades algorithm was used to decide the parameters of wavelet neural network. Finally, a numerical example was given, and it was shown that the evaluation of innovation customer was comparatively accurate. This model is useful and meaningful for manufacturers to select innovation customer resources. It also provides a scientific basis of decision-making for customer collaborative innovation design and paves a solid basis for the optimization of customer innovation process.