A closed-loop supply chain model with learning effect, random return and imperfect inspection under price- and quality-dependent demand

• Published in: Opsearch Vol. 59; no. 3; pp. 1094 - 1115
• Main Authors: Masanta, M., Giri, B. C.
• Format: Journal Article
• Language: English
• Published: New Delhi Springer India 2022; Springer Nature B.V
• Subjects: Business and Management; Demand; Inspection; Learning; Management; Mathematical models; Mathematics; Operations research; Operations Research/Decision Theory; Raw materials; Sensitivity analysis; Supply chains; Theoretical Article; Supply chain; Price and quality dependent demand; Learning; Inspection error; Random return; Remanufacturing
• ISSN: 0030-3887; 0975-0320
• DOI: 10.1007/s12597-021-00558-w

This paper addresses a closed-loop supply chain consisting of a manufacturer and a retailer. While producing a single item, the manufacturer executes a perfect production process influenced by learning effect. Production process is supported by raw materials as well as used materials. Collected used items follow an inspection process which is subject to learning and incurs Type I and Type II errors. Return of used items is random. The demand of the end-product is in a linear relationship with retail price and product quality. The proposed model is developed and optimal results are analysed with a numerical example. Sensitivity analysis is carried out to investigate the effects of various parameters on optimal decisions. It is observed from the numerical study that higher learning in production and inspection results in achieving a higher system profit, and the price sensitivity factor in demand has a significant impact on the retail price. Some important managerial insights of the proposed model are also discussed.