International Journal of Machine Learning and Cybernetics | 2019

Proposing a delay in payment contract for coordinating a two-echelon periodic review supply chain with stochastic promotional effort dependent demand

 
 
 

Abstract


In a decentralized supply chain (SC), each member individually makes decisions according to its personal objectives while these decisions impact on the other SC actors. The promotional effort made by retailers is one of the main factors that largely impacts on the market demand of a commodity, which in turn boosts the profitability of the whole SC members. In this paper, we investigate coordination of promotional effort and replenishment decisions in a two-echelon SC including single supplier and single retailer. The investigated SC faces a stochastic demand influenced by the retailer’s promotional effort. To replenish items, the retailer uses a periodic review inventory system and decides on the review period, order-up-to-level and promotional effort. On the other side, the supplier employs a periodic review lot-for-lot strategy and determines its replenishment cycle multiplier. Firstly, we model the SC under the decentralized and centralized decision-making models. Exact solution procedures are presented using mathematical and concavity analysis to obtain the decentralized and centralized optimal solutions. Afterwards, a coordination model based on delay in payment contract is proposed to motivate the retailer to participate in the joint decision-making model. To create a more realistic model, in the proposed models we assume that the SC members’ rates of return on investment are different. The minimum and maximum length of credit period which are acceptable to both members are determined. Finally, numerical examples and sensitivity analysis are conducted to investigate the performance and applicability of the developed models. The results show that the proposed coordination scheme considerably improves the profitability of both SC members and the whole SC in comparison with the decentralized setting.

Volume 10
Pages 1037-1050
DOI 10.1007/s13042-017-0781-6
Language English
Journal International Journal of Machine Learning and Cybernetics

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