The Nexus between Artificial Intelligence and ESG Performance: A Case from Manufacturing Firms of China
Improving manufacturing organizations' ESG (Environmental, Social, and Governance) performance is becoming more and more important in the global pursuit of green and sustainable development. AI (Artificial intelligence) has become a vital instrument for manufacturing companies to obtain a driven advantage in sustainability as a result of the growing digital revolution and urgent environmental issues. There is little academic research on the precise effects of artificial intelligence (AI) on the performance of ESG of manufacturing companies. The role of digital technologies in promoting ESG developments has been not extensively explored. The sample consists of Chinese-listed manufacturing companies from 2013–2022. This research study fills the research gap by developing a theoretical framework of how AI affects manufacturing organizations ESG pillars. Regression analysis, a correlation matrix, and descriptive statistics were used by the researcher to examine the data. The results show that the use of AI technology successfully encourages enhancements in manufacturing companies' ESG performance. This research adds to the body of knowledge on improving ESG performance, clarifies the theoretical basis for AI-enabled companies' non-economic performance, and expands the use of organizational dualism theory in novel settings.
Authors
- Muhammad Ali (ORCID: https://orcid.org/0000-0002-3176-4746)
- Zara Rafique
- Ayaz Qaiser
- Muhammad Fahad
- Waseema Batool
Institutions
- Shaheed Benazir Bhutto University (PK)
- Asian University (TH)
- University of Management and Technology (PK)
- University of Faisalabad (PK)
- University of Agriculture Faisalabad (PK)
- International Institute of Social History (NL)
Publication Details
- Journal
- The critical review of social sciences studies
- Published
- 2025-02-15
- DOI
- https://doi.org/10.59075/74h8qc65
- Citations
- 1
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 1.24