Research on the Configuration Paths of Low-Carbon Transformation of Heavily Polluting Enterprises

Author:

Su Xianna1,Ding Shujuan1

Affiliation:

1. Business School, Yangzhou University, Yangzhou 225127, China

Abstract

In the context of escalating environmental and climate concerns, it is imperative for enterprises to embark on carbon emission reduction initiatives. Exploring the driving pathways for corporate low-carbon transformation is crucial for the development of a green economy. In this paper, various configuration pathways that may drive heavily polluting industrial enterprises towards green and low-carbon transformation were investigated based on the Technology–Organization–Environment (TOE) theoretical framework and the fuzzy set qualitative comparative analysis (fsQCA) method. The results indicated the following: (1) the low-carbon transformation of heavily polluting enterprises is the result of the joint action of multiple factors; (2) there are eight pathways that can promote corporate low-carbon transformation, roughly divided into single-factor driving types (including MEA drive, DT drive, and GI drive), dual-factor driving types (DT–ER drive and DT–ESGR drive), and multi-factor driving types (including GI–DT–MEA–ER drive, GI–FS–ER drive, and GI–FS–ESGR drive). It can be concluded that there can be certain substitutions between green technology innovation and digital transformation, and environmental regulations and ESG ratings. (3) GI and DT are crucial to the low-carbon transformation of heavily polluting enterprises, and the latter has a more significant impact on promoting low-carbon transformation. MEA is also worthy of attention. The research conclusions not only provide theoretical support for the low-carbon transformation of heavily polluting industrial enterprises but also have valuable reference significance for other industry enterprises, and even the whole of society, to achieve green sustainable development.

Funder

Yangzhou Soft Science Project

Jiangsu Province Shuangchuang Doctoral Talent Project

Publisher

MDPI AG

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