Abstract
This study, based on supply chain-linked panel data of U.S. listed manufacturing firms from 1991 to 2018, examines how customers with environmental and social (ES) commitments affect the operational efficiency of dependent suppliers. An overlooked aspect in the literature is how operational concessions—such as extended trade credit terms and excess inventory holding—naturally emerge as a way for suppliers to balance power asymmetries in relationships with major customers. These concessions act as equilibrium outcomes that sustain partnerships but burden suppliers. Addressing this gap, we explore how ES commitments from major customers shift this equilibrium, reducing the need for suppliers to offer long trade credit and hold excess inventory, thereby improving efficiency through a shorter operating cycle. Our results show that suppliers working with ES-committed customers achieve shorter operating cycles, driven by reductions in both inventory days and receivable days. Additionally, suppliers leverage ES performance to signal credibility, reducing their reliance on long credit terms as assurance. During the 2008 financial crisis and its aftermath, suppliers reciprocated the goodwill of ES-committed customers by offering longer credit terms, fostering resilience and mutual support within the supply chain during financial stress. These findings contribute to the literature on sustainable supply chain management by showing how ES commitments foster trust-based partnerships that enhance long-term supply chain resilience across both stable and crisis periods.
| Original language | English |
|---|---|
| Article number | 109640 |
| Journal | International Journal of Production Economics |
| Volume | 285 |
| DOIs | |
| Publication status | Published - Jul 2025 |
Keywords
- Customer-supplier power asymmetry
- Inventory
- Operational efficiency
- Sustainable supply chain finance
- Sustainable supply chain management
- Trade credit
ASJC Scopus subject areas
- General Business,Management and Accounting
- Economics and Econometrics
- Management Science and Operations Research
- Industrial and Manufacturing Engineering