Towards a low-carbon digital future: AI affordance and digital-green synergistic transformation of manufacturing firms
Description
This dataset comprises an unbalanced panel of 13,298 firm-year observations across 2,334 Chinese A-share listed manufacturing firms spanning the period from 2015 to 2024. Data were comprehensively sourced from the CNRDS, CSMAR, Wind, and DIB databases, alongside corporate annual reports. Utilizing this dataset, a double machine learning (DML) model is employed to confirm that AI affordance (AIA) significantly promotes digital-green synergistic transformation (DGST). Furthermore, technological innovation diversification (TID), internal control quality (ICQ), and market competitive position (MCP) mediate this impact. Additionally, the positive impact is more pronounced in firms with lower levels of industrial chain integration (ICI), analyst coverage (AC), and policy intensity (PI). Further analysis reveals that the impact of AIA on DGST exhibits a single threshold effect, becoming positive and significant if and only if AIA surpasses a certain threshold.
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Institutions
- Beijing Technology and Business UniversityBeijing, Beijing