The impact of information sharing on ordering policies to improve supply chain performances Francesco Costantino a , Giulio Di Gravio a , Ahmed Shaban a,b,⇑ , Massimo Tronci a a Department of Mechanical and Aerospace Engineering, University of Rome ‘‘La Sapienza’’, Via Eudossiana, 18, 00184 Rome, Italy b Department of Industrial Engineering, Faculty of Engineering, Fayoum University, 63514 Fayoum, Egypt article info Article history: Received 30 May 2013 Received in revised form 19 January 2015 Accepted 21 January 2015 Available online 2 February 2015 Keywords: Supply chain Ordering policy Information sharing Bullwhip effect Simulation abstract Bullwhip effect represents the amplification and distortion of demand variability as moving upstream in a supply chain, causing excessive inventories, insufficient capacities and high operational costs. A grow- ing body of literature recognizes ordering policies and the lack of coordination as two main causes of the bullwhip effect, suggesting different techniques of intervention. This paper investigates the impact of information sharing on ordering policies through a comparison between a traditional (R, S) policy and a coordination mechanism based on ordering policy (a combination of (R, D) and (R, S) policies). This pol- icy relies on a slow, easy to implement, information sharing to overcome drawbacks of the effect, in which replenishment orders are divided into two parts; the first is to inform the upstream echelons about the actual customer demand and the second is to inform about the adjustment of the inventory position, smoothing at the same time the orders of the different levels of the supply chain. A simulation model for a multi-echelon supply chain quantifies the supply chain dynamics under these different policies, identify- ing how information sharing succeeds to achieve an acceptable performance in terms of both bullwhip effect and inventory variance. Ó 2015 Elsevier Ltd. All rights reserved. 1. Introduction A supply chain is a system of suppliers, manufacturers, distrib- utors, retailers and customers where raw material, financial and information flows connect participants in both upstream and downstream directions. The lack of coordination and the search for local optimization by each partner, without considering the consequences on the other partners, reduces the performances of the whole supply chain. The main symptom of such inefficiency is the bullwhip effect, a misalignment between the demand and order signal (Fig. 1). Starting from any change in the demand, the order variability tends to transmit and increase at the upstream suppliers, generating and amplifying instability. This leads to stock-outs, large and expensive swings of capacity utilization, lower quality of products and a considerable increase of production and transport costs as deliveries continuously ramp up and down (Towill et al., 2007; Disney and Lamrecht, 2008). Many real cases described this phenomenon and its negative effects on various industries, as for Campbell Soup’s (Fisher, Hammond, Obermeyer, & Raman, 1997), HP and Proctor & Gamble (Lee, Padmanabhan, & Whang, 1997a), a clothing supply chain (Disney & Towill, 2003), Glosuch (McCullen & Towill, 2000), fast moving consumer goods (Zotteri, 2012) and car manufacturing (Klug, 2013). Among its behavioral and operational causes, inventory control is one of the main areas of intervention. If supply chains partners take inventory decisions basing only on the incoming orders and the local information, without knowing the actual customer demand or the inventory position of the other members, replenish- ment orders tends to amplify to cover uncertainty. Many research- ers have attempted to improve the performances of the inventory control process by adopting actions to increase coordination. Sharing local and global information improves forecasting and inventory control processes in order to gain inventory stability, assuming that all the supply chain partners have a real-time access on information (Dejonckheere, Disney, Lambrecht, & Towill, 2004; Ciancimino, Cannella, Bruccoleri, & Framinan, 2012; Cho & Lee, 2013). The integration of traditional ordering policies with a collaborative approach proved its success in different configura- tions as for Information-Enriched Supply Chain, Vendor Managed http://dx.doi.org/10.1016/j.cie.2015.01.024 0360-8352/Ó 2015 Elsevier Ltd. All rights reserved. ⇑ Corresponding author at: Department of Mechanical and Aerospace Engineer- ing, University of Rome ‘‘La Sapienza’’, Via Eudossiana, 18, 00184 Rome, Italy. Tel.: +39 0644585260; fax: +39 0644585746. E-mail addresses: francesco.costantino@uniroma1.it (F. Costantino), giulio. digravio@uniroma1.it (G. Di Gravio), ahmed.shaban@uniroma1.it, ahmed. shaban@fayoum.edu.eg (A. Shaban), massimo.tronci@uniroma1.it (M. Tronci). Computers & Industrial Engineering 82 (2015) 127–142 Contents lists available at ScienceDirect Computers & Industrial Engineering journal homepage: www.elsevier.com/locate/caie