What is the value of real-time shipment tracking information?

This paper presents a stochastic model for evaluating the value of real-time shipment tracking information in a supply system with a manufacturer that fulfills demand from a retailer for a single product using a periodic review, order-up-to-level inventory control policy. Products shipped by the manufacturer can move through multiple stages before they reach the retailer, where each stage represents a physical location or a step in the replenishment process. The lead time for an order placed by the retailer depends on the distribution of all the shipments, or outstanding orders, across the different stages. Hence, it is desirable to track the location of shipments to determine the ordering policy that minimizes the long-run average cost for the retailer. The long-run average cost is modeled under different scenarios: with real-time tracking information, with lagged tracking information, with no tracking information and with historical information on lead times for past orders. Under optimal myopic ordering policies, it is shown that the long-run average cost for the retailer increases when the shipment tracking information is lagged. Numerical examples are used to demonstrate the savings in long-run average cost with real-time tracking information. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for the following free supplemental resource: Appendix]