Implications of risk-sharing strategies on supply chains with multiple retailers and under random yield

• Main Authors: Esmaeili, M. (Author), He, Y. (Author), Zare, M. (Author)
• Format: Article
• Language: English
• Published: Elsevier B.V. 2019
• Subjects: Cost reduction; Game; Government agencies; Production decisions; Random yield; Risk management; Risk perception; Risk-sharing; Risk-sharing contracts; Sales; Supply chain management; Supply chain performance; Technology advancement
• Online Access: View Fulltext in Publisher

 Nowadays, supply chain management cannot be overlooked with the existence of uncertainties caused by both the random demand and the random production yield. This paper considers a supply chain which includes a supplier facing random yield and multiple downstream retailers dealing with random demands. Under a Stackelberg game structure, several analytical models are presented in order to investigate the supply risk sharing mechanism within the supply chains. Under the first scenario, the same contracts (either risk-sharing contract (RS) or no risk-sharing contract (NRS)) are non-discriminatively used for all involving retailers. Then, both RS and NRS contracts are offered to the retailers (namely as a non-identical strategy), which results in the segmentation of the retailer groups. Under both scenarios, the analytical solutions to the retailers' optimal order decisions and the supplier's production decisions are obtained. The random yield impact of the supplier is investigated especially on supply chain performances. The effects of demand uncertainty, production costs' sharing, and wholesale price reduction approaches are explored. The key findings include, first, RS contract may significantly reduce supplier's holding costs; second, RS contract benefit both the supplier and the retailers in comparison with NRS contract; third, by process improvement and technology advancement, if the supplier may reduce the supply random yield effect, supply chain performances can be improved. Numerical examples and managerial insights are presented to illustrate the presented models. The findings may benefit both private companies and government agencies regarding decision making and policy setting in industries with high supply risks such as agriculture and farming related industries. © 2019 Elsevier B.V.