Revisiting the value of information sharing in two-stage supply chains

• Published in: European journal of operational research Vol. 270; no. 3; pp. 1044 - 1052
• Main Authors: Teunter, Ruud H., Babai, M. Zied, Bokhorst, Jos A.C., Syntetos, Aris A.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.11.2018; Elsevier
• Subjects: Bullwhip effect; Forecasting; Humanities and Social Sciences; Information sharing; Supply chain; Supply chain; Bullwhip effect; Forecasting; Information sharing
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2018.04.040

•We analyse the value of information sharing in a two stage supply-chain.•We consider two demand processes: stationary or random walk.•The retailer and manufacturer forecast demand using a moving average.•The value of information sharing is shown to be negative in the case of random walk. There is a substantive amount of literature showing that demand information sharing can lead to considerable reduction of the bullwhip effect/inventory costs. The core argument/analysis underlying these results is that the downstream supply-chain member (the retailer) quickly adapts its inventory position to an updated end-customer demand forecast. However, in many real-life situations, retailers adapt slowly rather than quickly to changes in customer demand as they cannot be sure that any change is structural. In this paper, we show that the adaption speed and underlying (unknown) demand process crucially affect the value of information sharing. For the situation with a single upstream supply-chain member (manufacturer) and a single retailer, we consider two demand processes: stationary or random walk. These represent two extremes where a change in customer demand is never or always structural, respectively. The retailer and manufacturer both forecast demand using a moving average, where the manufacturer bases its forecast on retailer demand without information sharing, but on end-customer demand with information sharing. In line with existing results, the value of information turns out to be positive under stationary demand. One contribution, though, is showing that some of the existing papers have overestimated this value by making an unfair comparison. Our most striking and insightful finding is that the value of information is negative when demand follows a random walk and the retailer is slow to react. Slow adaptation is the norm in real-life situations and deserves more attention in future research – exploring when information sharing indeed pays off.