Coupling Coordination between Corporate Digitalization and Green Efficiency under the Data Elements × Action Plan
DOI:
https://doi.org/10.54097/qsrfxb06Keywords:
Data Elements × Action Plan, corporate digital transformation, green efficiency, coupling coordination degree, super efficiency SBM model.Abstract
The release of the Data Elements × Three Year Action Plan (2024 to 2026) provides an important real world setting for studying the coordinated development of corporate digital transformation and green efficiency. Using panel data of Chinese A share listed manufacturing firms from 2014 to 2023, this paper constructs a composite corporate digitalization index covering five dimensions (artificial intelligence, big data, cloud computing, blockchain, and digital technology applications) based on annual report text analysis. Corporate green efficiency is measured by a super efficiency SBM model that incorporates undesirable outputs. On this basis, a coupling coordination degree model quantifies the dynamic synergy between the two subsystems, and a panel Tobit regression identifies key drivers of the coupling coordination degree. The empirical sample covers 2,683 listed firms and 21,328 firm year observations, with a complete pipeline of indicator standardization, entropy weighting, and coupling coordination grading. The main findings are as follows. First, the mean digitalization index rises from 0.142 to 0.387 over the sample period, with an annual growth rate of 10.5 percent. Second, mean green efficiency rises from 0.524 to 0.681, indicating steady improvement. Third, the mean coupling coordination degree rises from 0.412 to 0.586, moving the sample from the verge of disorder to the transition between barely coordinated and primary coordinated stages. Fourth, government R&D subsidy intensity, environmental regulation intensity, and firm human capital exhibit significantly positive effects on the coupling coordination degree. The paper provides a quantitative framework and policy implications for advancing the synergy between the Data Elements × Action Plan and green low carbon transformation of manufacturing.
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