Green mergers and acquisitions and green innovation: an empirical study on heavily polluting enterprises.

Xuedong Liang, Sipan Li, Peng Luo, Ziyang Li
Author Information
  1. Xuedong Liang: School of Business, Sichuan University, Chengdu, 610064, China.
  2. Sipan Li: School of Business, Sichuan University, Chengdu, 610064, China.
  3. Peng Luo: School of Business, Sichuan University, Chengdu, 610064, China.
  4. Ziyang Li: School of Business, Sichuan University, Chengdu, 610064, China. lzy_feng@scu.edu.cn. ORCID

Abstract

The concept of green development has gradually penetrated into the enterprise. Green mergers and acquisitions (M&A) have gradually become a means for heavily polluting enterprises to achieve the goal of energy conservation and emission reduction and embark on the path of green transformation. Heavily polluting enterprises have acquired clean technology and resources through green M&A, and whether they will promote their green innovations after green M&A has not yet been explored. Based on the data of M&As of China's heavy polluting enterprises from 2010 to 2018, this study empirically tests whether the M&As of heavy polluting enterprises can promote green innovation. The results show that M&As by heavily polluting enterprises can promote green innovation, and this impact is promoted with the support of government subsidies. In addition, older or higher paid CEOs negatively moderate this effect. Therefore, our study believes that most of the M&As of heavy polluting enterprises are taking the initiative to take environmental protection responsibilities and embarking on the path of green transformation. The government can issue relevant policies to encourage heavily polluting enterprises to conduct green M&A in order to achieve their goal of green transformation. Our study has enriched the relevant literature on green investment and green innovation, and can be used as a reference for the government to introduce policies for the green transformation of heavily polluting enterprises.

Keywords

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Grants

  1. 71902128/Young Scientists Fund

MeSH Term

China
Conservation of Natural Resources
Empirical Research
Government
Investments

Word Cloud

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