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Demand Shocks and Supply Chain Resilience: An Agent Based Modelling Approach and Application to the Potato Supply Chain

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  • Liang Lu
  • Ruby Nguyen
  • Md Mamunur Rahman
  • Jason Winfree

Abstract

The food supply chain has experienced major disruptions from both demand and supply sides during the Covid-19 pandemic. While some consequences such as food waste are directly caused by the disruption due to supply chain inefficiency, others are indirectly caused by a change in consumer’s preferences. As a result, evaluating food supply chain resilience is a difficult task. With an attempt to understand impacts of demand on the food supply chain, we developed an agent-based model based on the case of Idaho’s potato supply chain. Results showed that not only the magnitude but also the timing of the demand shock will have different impacts on various stakeholders of the supply chain. Our contribution to the literature is two-fold. First, the model helps explain why food waste and shortages may occur with dramatic shifts in consumer demand. Second, this paper provides a new angle on evaluating the various mitigation strategies and policy responses to disruptions beyond Covid-19.

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  • Liang Lu & Ruby Nguyen & Md Mamunur Rahman & Jason Winfree, 2021. "Demand Shocks and Supply Chain Resilience: An Agent Based Modelling Approach and Application to the Potato Supply Chain," NBER Working Papers 29166, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:29166
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    Cited by:

    1. Guang Tian & Xiaoxue Du & Fangbin Qiao & Andres Trujillo-Barrera, 2021. "Technology Adoption and Learning-by-Doing: The Case of Bt Cotton Adoption in China," JRFM, MDPI, vol. 14(11), pages 1-13, November.
    2. Xiaoxue Du & Levan Elbakidze & Liang Lu & R. Garth Taylor, 2022. "Climate Smart Pest Management," Sustainability, MDPI, vol. 14(16), pages 1-19, August.
    3. Rahman, Md Mamunur & Nguyen, Ruby & Lu, Liang, 2022. "Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach," Agricultural Systems, Elsevier, vol. 201(C).
    4. Rebecca Sarku & Ulfia A. Clemen & Thomas Clemen, 2023. "The Application of Artificial Intelligence Models for Food Security: A Review," Agriculture, MDPI, vol. 13(10), pages 1-28, October.
    5. Zhengliang Yang & Xiaoxue Du & Liang Lu & Hernan Tejeda, 2022. "Price and Volatility Transmissions among Natural Gas, Fertilizer, and Corn Markets: A Revisit," JRFM, MDPI, vol. 15(2), pages 1-14, February.

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    More about this item

    JEL classification:

    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
    • Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices

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