Impact of demand correlation and information sharing in a capacity constrained supply chain with multiple-retailers

Authors:
Chanel Marchèi Helper;Lauren B. Davis;Wenbin Wei
Affiliations:
Department of Industrial and Systems Engineering, North Carolina A&T State University, Greensboro, NC 27411, USA;Department of Industrial and Systems Engineering, North Carolina A&T State University, Greensboro, NC 27411, USA;Bank of America, Calabasas, CA 91302, USA
Venue:
Computers and Industrial Engineering
Year:
2010

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Abstract

This paper considers a single product, two-echelon capacity constrained supply chain consisting of a supplier and two retailers facing correlated end-item demand. We use a decentralized Markov decision process with restricted observations to represent this system and conduct a numerical study to quantify the benefits of information sharing to the retailers under varying levels of supplier capacity and supply allocation mechanisms. Our results show an inverse relationship between capacity and information and indicate the retailers can achieve significant benefits as a result of the information sharing partnership.