Work

Enterprise Digitalization and ESG Performance: Evidence from Interpretable AI Large Language Models

Year: 2025

Type: article

Abstract: In recent years, enterprise digitalization has garnered significant attention in business practices, yet its impact on environmental, social, and governance (ESG) performance remains underexplored. This study focuses on two core questions: (1) How can enterprise digitalization be measured more effectively? (2) How does digitalization affect the three dimensions of ESG, and through what mechanisms? Based on annual reports of A-share-listed companies in Shanghai and Shenzhen from 2013 to 2022, we construct an innovative measurement of digitalization using an interpretable AI large language model. Panel regression and mechanism analysis reveal that digitalization significantly enhances ESG performance, primarily through three mechanisms: improving energy efficiency, increasing social concern, and strengthening internal controls. Heterogeneity analysis shows that this effect is more pronounced among large and state-owned enterprises. This study proposes a replicable and transferable approach to measuring digitalization, offering empirical evidence and practical insights for firms and policymakers.

Source: Systems

DOI: 10.3390/systems13090832

Authors: Hongbo Kou, Rui Tang, Na Chen

Institutions: Renmin University of China, Sun Yat-sen University

Language: English

Topic: Digital Economy and Transformation

Subfield: Strategy and Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDGs: Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $2,896