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Synchromodal Supply Chains for Fast-Moving Consumer Goods

Author(s)
Jackson, Ilya; Saenz, Maria Jesus; Li, Yulu; Moreno, Michelle Stephanie Ramirez
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Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/
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Abstract
Synchromodality is an emerging concept in supply chain management. A synchromodal supply chain can be defined as a multimodal transportation planning system, wherein the different agents work in an integrated and flexible way that enables them to dynamically adapt the transport mode based on real-time information from stakeholders, customers, and the logistic network. The potential of synchromodality for the fast-moving consumer goods (FMCG) industry is related to the nature of business. The FMCG market is characterized by relatively low margins and high turnover, which is especially important in export supply chains. However, for a company, it may be challenging to objectively evaluate the costs and benefits, not to mention the design of a synchronized supply chain. In order to facilitate the adoption of the concept and guide the practitioners, our study put forward the following research questions: What should be considered in incorporating synchromodality in the export supply chain for FMCG? How should companies approach tradeoffs among factors affecting the supply chain? To answer these questions, we propose an adaptable framework, which should be considered a primary contribution of our study. The framework incorporates the center of gravity model, mixed integer linear programming, and sensitivity analysis. The framework is validated using a real-world problem from a multinational FMCG company. The problem involves the optimal volume allocation and the selection of the most efficient transportation mode for inland freight. Our study demonstrates that incorporating synchromodality in the export supply chain could reduce the overall cost by 9% and enhance flexibility by allowing multiple modes of transportation.
Date issued
2023-02-28
URI
https://hdl.handle.net/1721.1/148468
Department
Massachusetts Institute of Technology. Center for Transportation & Logistics
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Applied Sciences 13 (5): 3119 (2023)
Version: Final published version

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