Information Sharing in Supply Chains

• Activity Number: 256
• Type: Contributed
• Date/Time: Monday, August 1, 2016 : 2:00 PM to 3:50 PM
• Sponsor: Business and Economic Statistics Section
• Author(s): Vladimir Kovtun* and Avi Giloni and Clifford Hurvich
• Companies: Yeshiva University Sy Syms School of Business and Sy Syms School of Business and New York University Stern School of Business
• Keywords: supply chains ; informations sharing ; ARMA ; forecasting ; partial information shocks

Abstract

We introduce a general class of potentially valuable sharing arrangements in a multi-stage supply chain in which the retailer observes stationary autoregressive moving average demand with Gaussian white noise (shocks). Each supply chain player constructs its best linear forecast of leadtime demand and uses it to determine the order quantity via a periodic review myopic order-up-to policy. We demonstrate how a typical firm can create a sequence of partial information shocks based on its available information and share these with an adjacent upstream player. We go on to show how such a sharing arrangement may be beneficial to the upstream player by characterizing the player's information set in such a case and demonstrating when that player would observe a reduction in its mean square forecast error. Further we demonstrate that a partial information shock arrangement has the desirable property of being incentive compatible. We close by showing that sharing arrangements (such as demand sharing) appearing in previous research can be restated equivalently through partial information shock sharing.