Optimizing a Sustainable Inventory Model Under Limited Recovery Rates and Demand Sensitivity to Price, Carbon Emissions, and Stock Conditions
The recovery, rework, or remanufacturing of returned products has received significant attention, leading to considerable advancements in green supply chain management. However, the impact of recovery mechanisms under demand sensitivity remains understudied. This study develops a sustainability model that incorporates limited recovery rates and demand sensitivity to price, carbon emissions, and stock conditions. The analysis investigates the difference in profit when considering recovery and proposes a procedure for deriving optimal solutions using two key decision variables: unit sales price and cycle time, within a nonlinear profit model. The findings show that (i) the increase in total profit is significant and (ii) both sellers and consumers benefit from this mechanism. In addition, total profit is 15% higher, while the total cost is 22% lower than in the case without recovery. Consumers can purchase products at lower prices (−12%), and sellers can sell more products (+4%), thereby earning higher profit (+15%). Such a win–win policy aligns with environmental, social, and governance (ESG) regulations and supports a healthy, long-term supply chain relationship. Numerical examples and sensitivity analysis illustrate the characteristics of the proposed model. The results also provide managerial insights into enterprises’ limited recovery capacity.
Authors
- Xi-Bin Lin (ORCID: https://orcid.org/0009-0002-5075-038X)
- Jonas C.P. Yu (ORCID: https://orcid.org/0000-0002-1157-2245)
- Jen Ming Chen
Institutions
- National Central University (TW)
- Takming University of Science and Technology (TW)
Publication Details
- Journal
- Mathematics
- Published
- 2025-09-09
- DOI
- https://doi.org/10.3390/math13182916
- Citations
- 1
- Primary Topic
- Sustainable Supply Chain Management
- Type
- article
- Field-Weighted Citation Impact
- 2.23
Funders
- National Science and Technology Council