Focusing on the resource crowding-out effect, this study aims to examine the relationship between an enterprise’s digital transformation and the internalisation of environmental…
Abstract
Purpose
Focusing on the resource crowding-out effect, this study aims to examine the relationship between an enterprise’s digital transformation and the internalisation of environmental costs.
Design/methodology/approach
This paper manually collects environmental cost data and measures corporate digital transformation constructed through a machine learning word vector (Word2Vec) technology approach based on the text information of annual reports (MD&A) for heavily polluting firms.
Findings
Corporate digital transformation has a significant inhibitory effect on the internalisation of corporate environmental costs. This is because low-level digital transformation has crowded out cash flows, preventing China’s heavily polluting firms from having the extra capacity needed to internalise environmental costs. This crowding-out effect emerges when companies face problems such as capital shortages, short-term profit pressure and intense market competition. These results have the following important implications.
Practical implications
The research highlights the need for enterprises to align digital transformation and sustainability strategies by strengthening resource endowment and optimising internal resource allocation. This requires effective use of digital technology and a long-term sustainability vision for heavily polluting firms facing environmental policy pressures.
Social implications
Enterprises should assume more social responsibility and achieve sustainable socioeconomic development. It will also help mitigate the adverse environmental externalities stemming from their operations.
Originality/value
To the best of the authors’ knowledge, this study considers the impact of enterprise digital transformation on the internalisation level of enterprise environmental costs for the first time and uses enterprises’ financial, management, market characteristics and ownership characteristics to analyse the impact mechanism.