The DOI matches its Crossref record; 88 of the 88 references it cites were found in a registry or an index.
Corporate social responsibility, Green supply chain management and firm performance: The moderating role of big-data analytics capability
Abstract
Abstract Green supply chain management (GSCM) has attracted wide attention from academia and practitioners with the improvement of environmental awareness. Based on stakeholder theory, the purpose of this study is to explore the relationship between corporate social responsibility (CSR), green supply chain management and firm performance, and to consider the context of big-data analytics capability. Based on 260 samples of Chinese manufacturing industry in three measurement periods, hierarchical multiple regression method was used to analyze the data and test our hypotheses. The empirical results show that internal CSR (management practice towards employees) and external CSR (management practice towards external stakeholders) has a positive impact on green supply chain management. Green supply chain management has a positive impact on firm performance, and big-data analytics capability has a positive moderating effect on the relationship between external CSR and green supply chain management. The theoretical contributions and practical implications are also discussed.
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Cited by
Liao, F., Hu, Y., & Ye, S. (2024) · Humanities and Social Sciences Communications · doi:10.1057/s41599-023-02237-1 · Cited by 430
Green supply chain innovation: Emergence, adoption, and challenges
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Lee, I., & Mangalaraj, G. (2022) · Big Data and Cognitive Computing · doi:10.3390/bdcc6010017 · Cited by 176
Identifying the Key Big Data Analytics Capabilities in Bangladesh’s Healthcare Sector
Uddin Murad, M. A., Cetindamar, D., & Chakraborty, S. (2022) · Sustainability · doi:10.3390/su14127077 · Cited by 7
Metadata
- Authors
- Wang, C., Zhang, Q., & Zhang, W.
- Venue
- Research in Transportation Business & Management
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 37
- Pages
- 100557
- ISSN
- 2210-5395 (ISSN-L)
- OpenAlex
- W3086452535
- Cited by
- 293
- References
- 88
- FWCI
- 43.99
- Type
- journal article
- Language
- en
- Open access
- closed
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