4.6 Article

Economic properties of multi-product supply chains

Journal

COMPUTERS & CHEMICAL ENGINEERING
Volume 145, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compchemeng.2020.107157

Keywords

Supply chains; Coordinated markets; Multi-product; Waste management; Incentives

Funding

  1. U.S. Department of Agriculture [2017-67003-26055]
  2. National Science Foundation [CBET-1604374]
  3. NIFA [914491, 2017-67003-26055] Funding Source: Federal RePORTER

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This study interprets multi-product supply chains as coordinated markets and uses duality theory to explain resource allocation and price determination. It highlights the artificial price behavior and economic losses that can result from forcing stakeholder participation in markets, and proposes market incentive mechanisms using bids. Illustrated with an urban waste management problem, the results provide guidelines for properly remunerating stakeholders and fostering market transactions.
We interpret multi-product supply chains (SCs) as coordinated markets, casting SC optimization problems as market clearing problems that allocate resources to stakeholders and determine market prices. The market interpretation allows us to establish fundamental properties that explain how physical resources (primal variables) and associated economic values (dual variables) flow in SCs. We use duality theory to explain why incentivizing markets by forcing stakeholder participation (e.g., by imposing demand or service provision constraints) yields artificial price behavior and economic losses. To overcome these issues, we explore market incentive mechanisms that use bids. Here, we introduce a product-based representation for SCs, and show that this representation allows us to determine minimum bids that activate markets. These results provide guidelines for SC formulations that properly remunerate stakeholders and for policy that fosters market transactions. The results are illustrated using an urban waste management problem for a city of 100,0 00 residents. (C) 2020 Elsevier Ltd. All rights reserved.

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