Empirical Study on Influencing Factors of Knowledge Product Remixing in OIC

Abstract

Remixing of knowledge products has become one of the mainstream innovation models for the online innovation community (OIC). It is of great significance to explore the influencing factors of knowledge product remixing in OIC for better stimulating the open innovation. We first propose an analytical model for influencing factors of knowledge product remixing, then come up with a method for identifying false product attributes based on deep learning, and finally sum up the influencing factors of knowledge product remixing after analyzing the knowledge product attributes. The study results show that attention degree and user interaction have a positive impact on remixing of knowledge products, and there exists an inversely U-shaped relationship between knowledge complexity and product remixing. Continuous innovation has no significant positive incentive effect on product remixing.