长三角数字经济网络演化特征及影响因素.

Against the backdrop of digital technology integration and digital transformation, the digital economy has become an important new economic development in China. The digital economy changes and subverts the traditional production and organization modes of industries, breaks regional and spatial barriers, and realizes a highly interconnected network structure. Therefore, it is critical to study the digital economy from a network analysis perspective. In previous studies, the interlocking network model and the headquarters-branch model have been adopted to construct enterprise networks; however, the networks based on these models have some deficiencies in comprehensiveness and authenticity. An enterprise equity network built based on the investment relationships between enterprises can reflect the actual contact network status of the enterprise. Based on the above background, this study analyzed the evolutionary characteristics of the digital economy network in the Yangtze River Delta area through an enterprise equity network and explored its influencing factors and mechanisms. First, we constructed the digital economy networks of the Yangtze River Delta area for 2010, 2015, and 2020 using equity investment data between enterprises and a directed correlation network model. Second, with the indicators of degree centrality, degree centralization, an investment source, and others, the spatial and temporal evolution characteristics of digital economy networks were described from two aspects: network patterns and investment relationships. Furthermore, this study explored the possible factors affecting digital economy networks in the Yangtze River Delta area through a Quadratic Assignment Procedure. This study has three main findings: 1) From 2010 to 2020, various types of digital economy networks in the Yangtze River Delta area showed the characteristics of hierarchical diffusion and node agglomeration. Each industry forms an expansion of the network framework around the core node in the initial stage and then expands to the surrounding areas through secondary nodes. Shanghai and Hangzhou were the most important network nodes in the digital economy. 2) The number of net inflow areas for digital economy investment in the Yangtze River Delta was increasing, whereas the number of net outflow areas was decreasing. Hangzhou was the main net inflow city, while Shanghai and Ningbo were the main net outflow cities. Simultaneously, the source of investment in research units has changed from inside the province to outside, and there are clear interprovincial differences. 3) Cognitive proximity, the difference in the number of digital economy enterprises, the difference in the proportion of secondary industries, the difference in information facilities, and the early network foundation all have significant positive effects on the establishment of digital economy networks. System proximity, the difference in the proportion of tertiary industries, the time difference in the establishment of digital economy enterprises, and the gap in innovation ability restrict the formation and development of digital economy networks. Geographical distance is no longer the main factor influencing the formation of digital economic networks. Based on the above conclusions, this study proposes some suggestions for promoting the development of the digital economy from the perspectives of industrial agglomeration, facility and policy allocation, and path dependence. [ABSTRACT FROM AUTHOR]