Exaggeration or Concealment: Corporate Social Responsibility Strategy in the Blockchain Era
Supplier green washing behaviors in corporate social responsibility (CSR) have become increasingly notable, often involving exaggerated claims about CSR initiatives or diverting resources to conceal violations. We develop a game-theoretic model to investigate the motivation of green washing and its intricate economic and social consequences, and explore whether blockchain technology can effectively enhance CSR efforts. We find that the trade-off between exaggeration and concealment inherent in green washing plays a significant role in CSR strategy selection and corresponding performances. Specifically, if the exaggerating effect dominates green washing, the supplier has an incentive to adopt blockchain for self-certification in CSR activities. Conversely, when the concealment effect prevails, opportunistic behavior is more likely to occur. However, the integrative green washing coefficient has polarized impacts on the optimal CSR effort level, retailer's profit, and consumer surplus. We unveil that block chain implementation achieves the highest social welfare when the exaggeration of green washing plays a more prominent role, particularly when the CSR violation penalty is relatively subtle for both firms. Interestingly, we observe that green washing, despite its negative connotations, can eventually stimulate CSR efforts due to the incremental demand induced by exaggerated disclosures, ultimately leading to the highest social welfare.
Authors
- Qingquan Lai (ORCID: https://orcid.org/0000-0002-7236-1038)
- Ciwei Dong (ORCID: https://orcid.org/0000-0002-9059-8776)
- Siru Chen (ORCID: https://orcid.org/0000-0003-2829-9131)
- Xiutian Shi (ORCID: https://orcid.org/0000-0003-2748-5813)
Institutions
- Zhongnan University of Economics and Law (CN)
- Nanjing University of Science and Technology (CN)
Publication Details
- Journal
- IEEE Transactions on Engineering Management
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tem.2025.3610266
- Citations
- 1
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 2.11