The Impact of R&D Intensity on the Innovation Performance of Artificial Intelligence Enterprises-Based on the Moderating Effect of Patent Portfolio

Yuanyuan Dong, Zepeng Wei, Tiansen Liu and Xinpeng Xing
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Yuanyuan Dong: School of Economics and Management, Harbin University of Science and Technology, Harbin 150001, China
Zepeng Wei: School of Economics and Management, Harbin University of Science and Technology, Harbin 150001, China
Tiansen Liu: School of Economics and Management, Harbin Engineering University, Harbin 150001, China
Xinpeng Xing: School of Business, Jiangnan University, Wuxi 214122, China

Sustainability, 2020, vol. 13, issue 1, 1-17

Abstract: The patent portfolio affects the research and development (R&D) decisions of artificial intelligence enterprises, and provides rights protection for the enterprise’s product market, which is of great practical significance for the realization of innovation performance. The aim of this paper is to discover how the patent portfolio of artificial intelligence enterprises affects the relationship between R&D intensity and innovation performance. Based on the panel data of 164 listed enterprises in the A-share artificial intelligence concept sector of China, using the panel fixed effect regression method, the impact of R&D intensity on innovation performance was analyzed, and the moderating effect of the three dimensions of the patent portfolio on the two was examined. Studies have shown that the impact of R&D intensity on innovation performance is in an inverted U-shaped relationship. In addition, the diversity characteristics of the patent portfolio have a moderating effect on the relationship between R&D intensity and innovation performance, and when the enterprise is at a high level of diversity, the two have a U-shaped flip relationship. The size of the patent portfolio has a positive impact on innovation performance. The research results have theoretical and practical significance for the implementation of effective R&D management in artificial intelligence enterprise organizations.

Keywords: R& D intensity; patent portfolio; innovation performance; regression analysis; artificial intelligence enterprise (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (7)

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