JOURNAL ARTICLE
Does financial distress suppress CSR gap? The moderating effect of state ownership and market competition.
Published In: Business Ethics, the Environment & Responsibility, 2025, v. 34, n. 3. P. 989 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Long, Xianyi; Cao, Qinwei 3 of 3
Abstract
Companies will prioritize external corporate social responsibility (CSR) practices over internal ones, a phenomenon known as the corporate social responsibility gap (CSR gap). Previous studies have mostly focused on its consequences, little is known about its antecedents. We argue that such practice is illegitimate because it goes against stakeholder expectation that primary stakeholders' interests should be prioritized, but it also has potential to gain differentiation benefit for intense investment on external CSR. Drawing on compensatory orchestration logic and the three types of firm legitimacy, we argue that firms that have gained high pragmatic legitimacy are more likely to engage in morally illegitimate but differentiation gaining activities such as CSR gap. Using financial distress to indicate low pragmatic legitimacy, we predict that distressed firms are inclined to practice low CSR gap. Considering the competing logics in China, we further argue that this negative relationship will be less pronounced if firms are state‐owned or operating in a competitive industry. Using Chinese listed firms from 2010 to 2019 as an empirical sample, the results provide support for our arguments. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Business Ethics, the Environment & Responsibility. 2025/07, Vol. 34, Issue 3, p989
- Document Type:Article
- Subject Area:Religion and Philosophy
- Publication Date:2025
- ISSN:2694-6416
- DOI:10.1111/beer.12693
- Accession Number:185963597
- Copyright Statement:Copyright of Business Ethics, the Environment & Responsibility is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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