Information Sharing in the Supply Chains of Products With Seasonal Demand

Abstract

This study considers a two-echelon supply chain with one supplier and one retailer for products with seasonal demand. The effects that information sharing has on coordination and benefits of the supply chain are investigated. In order to better forecast the seasonal demand, the supplier initiates the information sharing process by offering incentives to the retailer which are proportional to the degree of information sharing. Since the variance in the supplier's inventory would marginally decrease as the degree of information sharing increases, the benefits gained by the supplier due to information sharing are thus a convex function. This can be used to obtain the optimal degree of information sharing with the aim of maximizing profits, which is a tradeoff between the benefits gained and costs incurred by information sharing. In this study, the seasonal demand is described by a SARMA time series model. Bayesian analysis is employed to investigate the value of information and determine the optimal degree of information sharing. Constructive properties are derived to provide managerial insight for effective decision making. The results of sensitivity analyses show that the correlations of demand for successive periods and estimation errors would both have great effects on the benefits gained by information sharing.

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