Empirical Study on Influencing Factors of Knowledge Product Remixing in OIC

被引:3
|
作者
Tan, Juan [1 ]
Miao, Dongqing [1 ]
Tan, Qiong [2 ]
机构
[1] Beijing Technol & Business Univ, Business Sch, Beijing 100048, Peoples R China
[2] Cent South Univ Forestry & Technol, Sch Econ, Changsha 410004, Peoples R China
关键词
Technological innovation; Complexity theory; Licenses; Biological system modeling; Analytical models; Creativity; Machine learning; Remixing of knowledge products; deep learning; false data identification; attention degree; user interaction; knowledge complexity; COMMUNITIES; MOTIVATION;
D O I
10.1109/ACCESS.2020.2974693
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
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页码:34215 / 34224
页数:10
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