Good neighbors but bad employers? How corporate digital transformation affects incongruence between external and internal corporate social responsibility

Yuting Zhang, Tachia Chin and Ragwa Al-Wazer

Technological Forecasting and Social Change, 2025, vol. 210, issue C

Abstract: Extant research provides compelling conceptual and empirical arguments on how digital transformation shapes corporate social responsibility (CSR). This paper constructs a theoretical model to explain the impact of digital transformation on inconsistent CSR. Based on the panel data of 1695 Chinese A-share listed companies from 2010 to 2020, this article identifies the direct impact, underlying mechanism, and heterogeneous impact of digital transformation on inconsistent CSR. The results indicate that digital transformation decreases inconsistent CSR. The mechanism analysis shows that digital transformation reduces inconsistent CSR by increasing the attention to internal stakeholders and the attention to internal and external stakeholders. Further tests of the moderating effect reveal that media coverage mitigates the impact of digital transformation on the attention to internal stakeholders. The heterogeneity analysis suggests that the impact of digital transformation is more pronounced in firms with Party organizations. This article contributes new empirical evidence regarding CSR-enhancing effects of digital transformation and extends practical implications for firms to better balance internal and external CSR so that employees can share in corporate growth. Additionally, it outlines directions for future research that can possibly explore the relationship between digital transformation and inconsistent CSR through alternative theoretical perspectives and more rigorous mathematical models.

Keywords: Corporate digital transformation; Inconsistent CSR; Attention-based view; Media coverage (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:210:y:2025:i:c:s0040162524006565

DOI: 10.1016/j.techfore.2024.123858

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