Quantity flexibility contracts under bayesian updating

quantity flexibility contracts under bayesian updating-17
Jianghua Wu, Aiqiu Huang and Xianguo Li, Outsourcing Decisions of Competing Firms with Alternative Products Under the Scale Effect, Operations Research and Management Science, August 2017, Accepted; Jianghua Wu and Xianguo Li, Reverse Auction Model of Procurement Contract Under Uncertain Demand, Journal of Systems Engineering, February 2016, Accepted; Jianghua Wu and Zelin Zhang, Research on Non-transparent Sales Strategy Based on Price Randomization, Operations Research and Management Science, No.Cases: 2016 Practice of Clinical Path Management in People's Liberation Army General Hospital 2012 Research on Traditional Printing Enterprise - Strategic Transformation of Keelung Hyde 2011 Construction of National Drug Administration Network Key community services Member, Production and Operations Management Society (POMS); Member, INFORMS; External Referee of following academic journals: Manufacturing & Service Operations Management, Production and Operations Management; Naval Research Logistics, Omega-International Journal of Management Science; International Journal of Production Economics, Asia-Pacific Journal of Operational Research.

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In this paper we consider a two-stage ordering problem with a buyer’s minimum commitment quantity contract. Under the contract the buyer is required to give a minimum-commitment quantity. Yano, “Supplier Commitment and Production Decisions under a Forecast- Commitment Contract,” Management Science, Vol. Then the manufacturer has the obligations to supply the minimum-commitment quantity and to provide a shortage compensation policy to the buyer. Donohue, “Efficient Supply Contract for Fashion Goods with Forecast Updating and Two Production Modes,” Management Science, Vol. Chen, “A Coordination Mechanism for a Supply Chain with Demand Information Updating,” International Journal of Production Economics, Vol. Through a two-period dynamic programming model formulation and the simulations based on design of experiments, we analyzed the effects of factors such as penalty cost, backup ratio, purchasing cost ratio, and demand correlation coefficient on retailer’s ordering policy and expected profit.Detailed sensitivity analysis is further conducted based on combinations of penalty cost and backup ratio.The contract considers stochastic and price-dependent demand.We present an analytical model and then use numerical methods with the Stackelberg game to identify the contract properties.We numerically show that a returns policy indeed improves supply chain performance.However, the benefits earned from the returns policy, under price-sensitive and variable demand, are different for different supply chain partners.

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