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Salamirad, Amirhossein

University of British Columbia

Digital marketplace platforms are important because they provide low prices, easy accessibility, and global reach, which enable suppliers to create value and offer novel business models in e-commerce. Typically, large platforms engage in two types of contracts with their suppliers, wholesale and agency contracts, which define the terms of their business relationship and influence product distribution and pricing. In order to ensure a high level of service and maximize profitability and supply chain resilience, an optimal inventory management system is necessary. In this study, we present a robust optimization (RO) framework to determine the optimal inventory and ordering policy for each contract type based on the uncertain nature of demand and supply. Supposedly, RO is over-conservative. Hence, we propose an alternative framework, namely the maximum regret minimization (MRM), which is less conservative than the RO. The column-and-constraint generation method is used to test the proposed models under various scenarios with different demand correlation levels. As a method of solving these computationally intensive model, we propose a linear decision rule (LDR) for the wholesale-based MRM problem. Our LDR is shown to be a superior decision rule to existing ones through numerical results with which we are able to demonstrate encouraging managerial insights.

Text

2024-01-04

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/87078

Mathematics

University of British Columbia

UBCO

http://creativecommons.org/licenses/by-nc-nd/4.0/