Coordinating The Cloud Computing Service Supply Chain under Asymmetric Demand Information with Quantity Discount Contract

The article mainly examines coordinated strategies in a cloud computing service supply chain that faces random demand of a single product, and consists of one application infrastructure provider (AIP), one application platform provider (APP) and one application service provider (ASP). We consider a setting that the ASP has accurate demand information while the APP and AIP don't because they are relatively far away from the consumer market. In this paper, we examine the supply chain's performance mainly through discussing three situations: basic model (decentralized control) under asymmetric information, reference model (centralized control) and experimental model (quantity discount contract) under sharing demand information. We provide numerical results to compare the supply chain profits and conduct sensitivity analysis under three models. We find that using quantity discount contract can attain Pareto improvement. We also find that the ASP doesn't have motivation to transfer false demand information. Moreover, the numerical analysis and sensitivity analysis show that reducing the delay cost can improve the profits of the cloud computing service supply chain and its members. What is more, on the same level of delay cost, the impact of quantity discount on the expected profits improvement of upstream members is more than the downstream members.