ESG introduction mechanism of construction firms based on Bayesian network coupled with machine learning: Evidence from Zhengzhou

Jinzhao Tian; Yisheng Liu; Lincoln Wood; Yulin Sun

doi:10.1016/j.jenvman.2025.124185

ESG introduction mechanism of construction firms based on Bayesian network coupled with machine learning: Evidence from Zhengzhou

J Environ Manage. 2025 Jan 25:375:124185. doi: 10.1016/j.jenvman.2025.124185. Online ahead of print.

Authors

Jinzhao Tian¹, Yisheng Liu², Lincoln Wood³, Yulin Sun⁴

Affiliations

¹ School of Economics and Management, Beijing Jiaotong University, 100091, Beijing, China. Electronic address: 21113057@bjtu.edu.cn.
² School of Economics and Management, Beijing Jiaotong University, 100091, Beijing, China. Electronic address: yshliu1@bjtu.edu.cn.
³ Otago Business School, University of Otago, Dunedin, 9054, Otago, New Zealand. Electronic address: lincoln.wood@otago.ac.nz.
⁴ School of Economics and Management, Beijing Jiaotong University, 100091, Beijing, China. Electronic address: l24125595@bjtu.edu.cn.

PMID: 39864153
DOI: 10.1016/j.jenvman.2025.124185

Abstract

Chinese construction enterprises are at a pivotal point in their transition to sustainable development, with Environmental, Social, and Governance (ESG) emerging as a key driver. However, limited understanding of ESG mechanisms hampers effective management strategies. To address this challenge, this study constructs an ESG introduction mechanism framework based on Bayesian networks and machine learning algorithms. Using Zhengzhou, a major city in China, as a case study, the research employs quantitative methods to identify key factors influencing ESG introduction. The findings reveal that attitudes towards ESG-related construction products, the establishment of corporate brand image, and ESG readiness are the three primary factors driving ESG introduction among construction enterprises. Further scenario simulation analyses indicate that a positive attitude towards ESG significantly enhances the likelihood of successful ESG introduction. Additionally, fostering and expanding local ESG consulting and service agencies and strengthening regulatory measures markedly improve the success rate of ESG introduction. This framework provides construction enterprise managers with a practical tool to analyze ESG introduction mechanisms and offers critical decision-making support for policymakers in designing policies to promote ESG introduction.

Keywords: Bayesian network; Chinese construction firms; ESG introduction; Machine learning; Sustainable development.