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Controlling the Risk for an Agricultural Harvest


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  • Stuart J. Allen

    (Penn State University)

  • Edmund W. Schuster

    (MIT Auto-ID Labs, 23 Valencia Drive, Nashua, New Hampshire 03062)

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    Gathering the harvest represents a complex managerial problem for agricultural cooperatives involved in harvesting and processing operations: balancing the risk of overinvestment with the risk of underproduction. The rate to harvest crops and the corresponding capital investment are critical strategic decisions in situations where poor weather conditions present a risk of crop loss. In this article, we discuss a case study of the Concord grape harvest and develop a mathematical model to control harvest risk. The model involves differentiation of a joint probability distribution that represents risks associated with the length of the harvest season and the size of the crop. This approach is becoming popular as a means of dealing with complex problems involving operational and supply chain risk. Significant cost avoidance, in the millions of dollars, results from practical implementation of the Harvest Model. Using real data, we found that the Harvest Model provides lower-cost solutions in situations involving moderate variability in both the length of season and the crop size as compared to solutions based on imposed risk policies determined by management.

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    Bibliographic Info

    Article provided by INFORMS in its journal Manufacturing & Service Operations Management.

    Volume (Year): 6 (2004)
    Issue (Month): 3 (July)
    Pages: 225-236

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    Handle: RePEc:inm:ormsom:v:6:y:2004:i:3:p:225-236

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    Related research

    Keywords: harvest risk; agriculture;


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    Cited by:
    1. Ahumada, Omar & Villalobos, J. Rene, 2009. "Application of planning models in the agri-food supply chain: A review," European Journal of Operational Research, Elsevier, vol. 196(1), pages 1-20, July.
    2. Jean-Pierre Aubin & Luxi Chen & Marie-Hélène Durand, 2013. "Dynamic decentralization of harvesting constraints in the management of tychastic evolution of renewable resources," Computational Management Science, Springer, vol. 10(4), pages 281-298, December.
    3. Ahumada, Omar & Villalobos, J. Rene, 2011. "Operational model for planning the harvest and distribution of perishable agricultural products," International Journal of Production Economics, Elsevier, vol. 133(2), pages 677-687, October.
    4. Rosa, Franco, 2012. "Planning the Sustainable Agro-fuel Supply Chain," Congress Papers 124130, Italian Association of Agricultural and Applied Economics (AIEAA).
    5. Ferrer, Juan-Carlos & Mac Cawley, Alejandro & Maturana, Sergio & Toloza, Sergio & Vera, Jorge, 2008. "An optimization approach for scheduling wine grape harvest operations," International Journal of Production Economics, Elsevier, vol. 112(2), pages 985-999, April.


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