An empirical taxonomy of corporate social responsibility in China's manufacturing industries

Lau, Antonio K.W.; Lee, Peter K.C.; Cheng, T.C.E.

Abstract

Notwithstanding the availability of a substantial body of literature on corporate social responsibility (CSR), the term has remained controversial and ambiguous in terms of its meaning, use, and usefulness. Specifically, the impact of CSR on tangible and intangible returns to Chinese manufacturers has remained uncertain. Drawing on stakeholder theory and CSR literature, we empirically develop an exploratory taxonomy of CSR practices in China's manufacturing industries. By surveying the manufacturers operating in China's food, pharmaceutical, automotive, and clothing industries, we identify three CSR clusters and examine how they are related to their financial, operational, reputational, and social capital performances. Our findings deepen the understanding of CSR adoption patterns by clarifying the consequences of CSR adoption in China's manufacturing industry.

Citation

Lau, A. K., Lee, P. K., & Cheng, T. (2018). An empirical taxonomy of corporate social responsibility in China's manufacturing industries. Journal of Cleaner Production, 188, 322-338. https://doi.org/10.1016/j.jclepro.2018.04.010

• Journal Article Type: Article
• Acceptance Date: Apr 2, 2018
• Online Publication Date: Apr 3, 2018
• Publication Date: 2018-07
• Deposit Date: May 30, 2023
• Journal: Journal of Cleaner Production
• Print ISSN: 0959-6526
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 188
• Pages: 322-338
• DOI: https://doi.org/10.1016/j.jclepro.2018.04.010
• Keywords: Industrial and Manufacturing Engineering; Strategy and Management; General Environmental Science; Renewable Energy, Sustainability and the Environment
• Additional Information: This article is maintained by: Elsevier; Article Title: An empirical taxonomy of corporate social responsibility in China's manufacturing industries; Journal Title: Journal of Cleaner Production; CrossRef DOI link to publisher maintained version: https://doi.org/10.1016/j.jclepro.2018.04.010; Content Type: article; Copyright: © 2018 Elsevier Ltd. All rights reserved.