Optimizing Inventory for Imperfect and Gradually Deteriorating Items Under Multi-Level Trade Credit in a Sustainable Supply Chain

Abhay Bansal, Aastha Panwar, Bhuvan Unhelkar and Mandeep Mittal ()
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Abhay Bansal: School of Computer Science Engineering and Technology, Bennett University, Greater Noida 201310, India
Aastha Panwar: School of Basic Sciences, Galgotias University, Greater Noida 203201, India
Bhuvan Unhelkar: Muma College of Business, University of South Florida, N. Tamiami Trail, Sarasota, FL 34243, USA
Mandeep Mittal: School of Computer Science Engineering and Technology, Bennett University, Greater Noida 201310, India

Mathematics, 2025, vol. 13, issue 5, 1-29

Abstract: Reducing carbon emissions is of immense interest to most modern organizations striving for sustainability. Effective inventory management is crucial for achieving resource optimization and minimizing environmental impact. Very little work has been conducted up to this point on slowly declining, low-quality products with multi-level trade credit rules under the influence of carbon emissions. In this study, an inventory model is tailored specifically for imperfect and gradually deteriorating products with a multi-level trade credit policy. Further, the impact of carbon emissions on the retailer’s ordering strategies is also considered. To determine the optimal policy for supply chain partners, three trade credit instances with seven subcases are taken into consideration. To choose the best scenario out of ten cases, an algorithm is also developed. The model’s validity is illustrated through a numerical experiment and sensitivity analysis. This study is an innovative approach to balancing economic trade credit policy in sustainable supply chain management.

Keywords: sustainable supply chain; carbon emission reduction; inventory optimization; non-instantaneous deterioration; trade credit policies; defective product management introduction (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2025
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