Back to Search Start Over

The effective path of green transformation of heavily polluting enterprises promoted by green merger and acquisition—qualitative comparative analysis based on fuzzy sets.

Authors :
Zhang, Yan
Sun, Ziyuan
Sun, Mengxin
Zhou, Yiqiang
Source :
Environmental Science & Pollution Research; Sep2022, Vol. 29 Issue 42, p63277-63293, 17p
Publication Year :
2022

Abstract

Green merger and acquisition (GMA) is becoming a growing tendency for heavily polluting enterprises in recent years; however, the realization path of green transformation through GMA is still unexplored. Taking 48 Chinese heavily polluting enterprises that had GMA in 2018 as the research object, this paper constructs the "M&A attributes, Organizational characteristics, and External environment" (M-O-E) framework, by using the method of fuzzy-set qualitative comparative analysis (fsQCA) to reveal the configurations of conditions that lead to high levels of green innovation performance. The results show that the high green technology innovation performance after GMA of heavily polluting enterprises is the outcome of multiple antecedents, and no singular antecedent is sufficient for achieving it. Besides, there are three equivalent configurations of conditions to achieve green transformation: professional buyer, internal leading, and internal-external linkage. Among them, the professional buyer configuration highlights that the combination of M&A experience and M&A scale is of great importance, the internal leading configuration emphasizes that the existence of environmental awareness and organizational resources is the core conditions, and the internal-external linkage configuration requires simultaneous efforts of M&A experience and government environmental regulations. Our research contributes to the understanding of green transformation in heavily polluting enterprises from a configurational perspective, and provides a practice-oriented guide to achieve green transformation for the government and heavily polluting enterprises. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09441344
Volume :
29
Issue :
42
Database :
Complementary Index
Journal :
Environmental Science & Pollution Research
Publication Type :
Academic Journal
Accession number :
159141151
Full Text :
https://doi.org/10.1007/s11356-022-20123-2