State-owned Capital and Green M&A: A Machine Learning Analysis of Private Firms

This study examines the impact of state-owned capital participation on private enterprises’ green mergers and acquisitions (M&A) in China, using the data on green M&A events of Chinese listed organization between 2010 and 2023. An empirical analysis is conducted to investigate the moderating role of media attention in this relationship. Machine learning model such as Random Forest (RF) and Logistic Regression (LR) are used to validate the results. The results show that state-owned capital participation in private enterprises significantly facilitates green M&A by improving internal and external supervision and providing resource synergies. RF received (85.7%) accuracy followed by LR with (83.1&) in predicting the success of green M&A success. Results also reveal that the media attention plays a positive and moderating role in the relationship between state-owned capital participation and green M&A of private enterprises. This study contributes to a deeper understanding of the impact of state-owned capital participation on private enterprises’ green M&A, empowering high-quality economic development and supporting the achievement of the national “dual carbon” goals.