Resilience Characteristics and Driving Mechanism of Urban Collaborative Innovation Network—A Case Study of China’s New Energy Vehicle Industry

Author:

Guan Yuyue1,Li Longfei23ORCID,Liu Chao1

Affiliation:

1. School of Business, Shandong University, Weihai 264209, China

2. Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China

3. School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China

Abstract

The innovation ecosystem of the new energy vehicle industry is highly complex and spans several sectors; it is important to increase the resistance of the new energy vehicle industry network. This paper explores regional resilience in the context of China’s new energy vehicle industry. Using patent cooperation data from 2011 to 2021, we construct a three-stage urban collaborative innovation network and analyze its structural characteristics. We also develop a resilience evaluation index system to measure the resilience of the network and its nodes. Furthermore, we propose a framework for resilience analysis that operates at the network, community, and node levels. Through our analysis of the network’s resilience characteristics and evolution, we investigate the driving mechanisms behind its formation using the exponential random graph model (ERGM). Empirical results demonstrate that the urban collaborative innovation network is expanding and strengthening, with increased resilience and the ability to withstand uncertainty. Notably, the distribution of node resilience exhibits spatial heterogeneity, with cities in the eastern and central regions demonstrating higher resilience than those in other areas. Furthermore, the study finds that economic development and investment in education and technology can enhance network connections and resilience. Additionally, this paper reveals a strong dependence of inter-city cooperation on geographical proximity.

Funder

National Social Science Foundation of China

Publisher

MDPI AG

Subject

Information Systems and Management,Computer Networks and Communications,Modeling and Simulation,Control and Systems Engineering,Software

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