This paper takes 728 heavily polluting enterprises in A-share listed companies from 2013 to 2021 as the research sample, and takes provincial research as the scale.On the basis of a comprehensive measurement of its carbon total factor productivity, this paper uses social network analysis and QAP method.To explore the spatial correlation network and driving factors of carbon total factor productivity of heavy polluting enterprises in China. The results showed that (1) from 2013 to 2021,The carbon total factor productivity of heavy polluting enterprises in China has experienced three stages of fluctuation, which first increased, then decreased and then decreased.On the whole, there is still much room for improvement.(2) The spatial correlation network of carbon total factor productivity of heavy polluting enterprises in China has broken through the constraints of geographical proximity.The carbon total factor productivity of heavy polluting enterprises among provinces shows significant spatial correlation and spillover effect.However, the overall relevance of the network is low, but the stability is high.(3) Each region shows different status and function in the spatial correlation network.Shandong, Henan, Hubei, Anhui and other provinces have higher degree centrality, closeness centrality and intermediary centrality.It belongs to the "leader" and "middleman" in the network. (4)The spatial correlation network of carbon total factor productivity in heavily polluting enterprises can be divided into four sectors: net spillover, net beneficiary, two-way spillover and broker. There are significant spillover effects both within each sector and between different sectors, and the spillover effects between sectors possess obvious transmission characteristics.(5) There are differences in the effects of the factors affecting the spatial correlation network of carbon total factor productivity of heavy pollution enterprises in different years.Economic development level, informatization level, transportation level, innovation level and spatial adjacency relationship are all carbon factors for heavy pollution enterprises.Productivity has a significant impact on the formation of spatial correlation network.

Fuyun Zhu, Yan Gao. Spatial Correlation Network and Driving Factors of Carbon Total Factor Productivity of Heavily Polluting Enterprises in China. Academic Journal of Business & Management (2024) Vol. 6, Issue 11: 176-185. https://doi.org/10.25236/AJBM.2024.061126.

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