Abstract
Corporate social responsibility (CSR) issues in suppliers can affect the reputation of buyers or even result in supply chain disruption. Thus, buyer and supplier firms are urged to comply with CSR codes in a coordinated manner. In other words, multinational buyers are expected to extend CSR practices to their suppliers in emerging countries. This is particularly crucial when suppliers’ CSR performance is screened under a regulatory agency's inspection regime. To this end, this study formulates an analytical model to understand the effects of buying firms’ supportive schemes, i.e., technical assistance programmes, on their partner suppliers’ CSR performance. Specifically, we develop a multi-period behavioural model to simulate a system consisting of multiple buyers and suppliers where the government regularly conducts inspections on suppliers’ CSR performance. The results from the agent-based simulation analysis shed light on (1) how the dyadic risk preferences of suppliers and buyers affect suppliers’ CSR performance; (2) how the gap between the perceived and actual CSR levels in a supplier interacts with the regulatory agency's tactics to influence suppliers’ CSR performance; (3) the extent to which the overall suppliers’ CSR performance improvement is attributable to the buyers’ technical assistance programmes under the regulatory agency's inspection regime. This research contributes to the socially responsible supply chain management literature and provides innovative managerial insights for policy makers (e.g., CSR regulators) to promote CSR practices among suppliers.
Original language | English |
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Pages (from-to) | 59-69 |
Number of pages | 11 |
Journal | International Journal of Production Economics |
Volume | 206 |
DOIs | |
Publication status | Published - Dec 2018 |
Keywords
- Behavioural
- Buyer-supplier relationship
- Corporate social responsibility
- Inspection
- Multi-period
- Technical assistance
ASJC Scopus subject areas
- Business, Management and Accounting(all)
- Economics and Econometrics
- Management Science and Operations Research
- Industrial and Manufacturing Engineering