Title: Information sharing policies based on tokens to improve supply chain performances

Authors: Francesco Costantino; Giulio Di Gravio; Ahmed Shaban; Massimo Tronci

Addresses: Department of Mechanical and Aerospace Engineering, University of Rome 'La Sapienza', Via Eudossiana, 18, 00184, Rome, Italy ' Department of Mechanical and Aerospace Engineering, University of Rome 'La Sapienza', Via Eudossiana, 18, 00184, Rome, Italy ' Department of Mechanical and Aerospace Engineering, University of Rome 'La Sapienza', Via Eudossiana, 18, 00184, Rome, Italy ' Department of Mechanical and Aerospace Engineering, University of Rome 'La Sapienza', Via Eudossiana, 18, 00184, Rome, Italy

Abstract: One of the most studied dynamics of supply chains is a phenomenon that has been named 'the bullwhip effect'. What happens is that variations in customer demand are translated into wider and wider variations in orders issued by companies along the supply chain, affecting performances and increasing the level of complexity in transactions and relationships among partners. This paper introduces the opportunity of measuring the performance of a supply chain in case of disruption, proposing a progressive information sharing technique (token approach) in order to control bullwhip effect. This technique relies on dividing orders into two streams: the first stream transmits the value of the demand to the whole supply chain echelons whereas the second one includes the adjustments needed to keep a stable inventory for each partner of the network. To investigate the token approach, a simulation model is developed for a four-echelon supply chain where it is assumed that lead times for transferring information or materials are deterministic and suppliers have unlimited production and inventory capacities. Four different ordering policies are evaluated and the results analysed to identify general findings.

Keywords: supply chain management; SCM; supply chain dynamics; BWE; bullwhip effect; supply chain performance; information sharing; ordering policy; order variance; inventory level; inventory variation; simulation; tokens.

DOI: 10.1504/IJLSM.2013.051336

International Journal of Logistics Systems and Management, 2013 Vol.14 No.2, pp.133 - 160

Published online: 28 Jun 2013 *

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