 A closed-loop supply chain with stochastic product returns and worker experience under learning and forgettingB.C. Giri and Christoph H. Glock International Journal of Production Research, 2017, vol. 55, issue 22, 6760-6778 Abstract: This paper addresses a single-manufacturer single-retailer closed-loop supply chain with stochastic product returns considering worker experience under learning and forgetting in production and inspection of returned items at the manufacturer. Customer demand is assumed to be dependent linearly on the retail price, and it is fulfilled by using both manufactured and remanufactured products. The manufacturer delivers the buyer’s order quantity in a number of equal-sized batches. The optimal number of shipments, the shipment size and the retail price are determined by maximising the average expected profit of the closed-loop supply chain. It is observed from the numerical study that high learning effects in production and inspection lead to high recovery rates of used products, which, besides an economic advantage, may have a positive effect on the environment. Even though forgetting has an adverse effect, the average expected profit of the closed-loop supply chain is much higher than that of the basic model which ignores worker learning. Date: 2017 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:55:y:2017:i:22:p:6760-6778 Ordering information: This journal article can be ordered from DOI: 10.1080/00207543.2017.1347301 Access Statistics for this article International Journal of Production Research is currently edited by Professor A. Dolgui More articles in International Journal of Production Research from Taylor & Francis Journals |
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