Research on the influence of the characteristics of cross-border R&D cooperation network on its disruptive innovation performance

doi:10.19571/j.cnki.1000-2995.2024.12.013

Abstract

Abstract: Cross-border R&D cooperation is a new type of cooperation model that achieves breakthroughs in core technologies, and plays an important role in improving disruptive innovation performance and ensuring high-quality economic development. Based on social network theory, this article takes 290 cross-border R&D cooperation networks identified from joint patent application information in the field of drones as the research object. K-Means clustering algorithm and decision tree CART algorithm are used to analyze the basic characteristics of these networks, distinguish network types, and explore the impact of feature variable combinations of different types of networks on their disruptive innovation performance. Research has shown that there are three types of crossborder R&D cooperation networks: binary R&D cooperation networks, mesh R&D cooperation networks, and complex R&D cooperation networks, which exhibit different network characteristics; Moreover, the main types of crossborder R&D cooperation networks are binary R&D cooperation networks. (2) There are differences in the disruptive innovation performance of three different types of crossborder R&D cooperation networks; In terms of the proportion of highly disruptive innovation performance, the network type R&D cooperation network has the highest proportion, followed by the complex type R&D cooperation network, and the binary type R&D cooperation network has the lowest proportion. (3) The intensity of cooperation is the core factor that affects the performance of disruptive innovation; In a binary R&D cooperation network, the intensity of cooperation will positively affect its disruptive innovation performance; For mesh R&D cooperation networks with high cooperation intensity, maintaining a lower average path length helps to improve their disruptive innovation performance; The disruptive innovation performance of complex R&D cooperation networks is jointly influenced by cooperation intensity, clustering coefficient, and network centrality. This article enriches and expands the research on disruptive innovation performance from the perspective of social network theory, and provides useful guidance for various innovative entities to improve disruptive innovation performance through cross-border research and development cooperation.

Key words: disruptive innovation performance, crossborder R&D cooperation, network characteristics, decision rule, cluster analysis

Zhu Xiaoyan, Lin Chunpei, Yu Chuanpeng, Liao Yangyue, Li Hailin. Research on the influence of the characteristics of cross-border R&D cooperation network on its disruptive innovation performance[J]. Science Research Management, 2024, 45(12): 122-132.

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Research on the influence of the characteristics of cross-border R&D cooperation network on its disruptive innovation performance

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