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Risk Mitigating Strategies in the Food Supply Chain

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  • Agiwal, Swati
  • Mohtadi, Hamid

Abstract

Food safety events in the recent past have generated significant media attention and resulted in increased concerns over the food on the plate. A recent study (Degeneffe et al., 2007) on consumer perceptions of bio-terrorism and food safety risks shows increasing concern over food safety and corresponding decreasing confidence in security of the U.S. food supply. While there are some mandated safety and security practices for the firms in the food supply chain the economic incentives for the firms to actively address food safety throughout the supply chain are less clear. Security practices often require significant investments in both within the firm and across the supply chain but do not show tangible returns. Also, higher investments in securing the firms’ processes and products do not necessarily make the food products more safe if the supply chain partners exhibit higher risks. However, a risk that is realized can potentially bankrupt the firm. Some high-profile cases of food safety outbreaks have had substantial economic consequences such as, lost sales, recall and compensation costs, damaged goodwill and hence impact on future markets. Such incidents can lead the firms out of business and the impact is not contained just at the firm level but also felt throughout the food supply chain. The issues of economic incentives and disincentives for risk mitigation strategies and investments, in a highly vulnerable area such as food sector, are an emerging area of concern both in private and public sector management as well as academic research. The research questions of interest that this paper addresses are: How much should the firm invest to address the security and safety risks that it faces? The optimum investment levels, among other things, are a function of the probabilities of contamination levels exceeding the maximum acceptable standards set. We consider a specification for the contamination levels follow gamma distribution as it exhibits the fat tail property which suggests that extreme events are more likely than predicted by the normal Gaussian form. Previous work by Mohtadi and Murshid(2007) has highlighted the fat-tail nature of extreme events for chemical, biological and radionuclear (CBRn) attacks, which are of intentional nature. However, for food safety risks of unintentional nature the fat-tail nature of the distribution though suggested, is not yet established in literature. The present model leaves less scope for analytical solutions but lends itself to numerical methods, which we employ to examine the firm strategies. Our preliminary model and its analysis suggest that infact for very low levels of risk exposure no investment in security is required! However, as the standards loosen and risk increases the optimum amount of investments also increase. Though the result here are intuitively consistent, they are largely dependent on the parametric specification of the model and their sensitivity to the parameter values is yet to be tested.

Suggested Citation

  • Agiwal, Swati & Mohtadi, Hamid, 2008. "Risk Mitigating Strategies in the Food Supply Chain," 2008 Annual Meeting, July 27-29, 2008, Orlando, Florida 6248, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
  • Handle: RePEc:ags:aaea08:6248
    DOI: 10.22004/ag.econ.6248
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    References listed on IDEAS

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    1. Hamid Mohtadi, 2008. "Information Sharing in Food Supply Chains," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 56(2), pages 163-178, June.
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    Cited by:

    1. Hau Chan & Michael Ceyko & Luis Ortiz, 2017. "Interdependent Defense Games with Applications to Internet Security at the Level of Autonomous Systems," Games, MDPI, vol. 8(1), pages 1-60, February.
    2. Behzadi, Golnar & O’Sullivan, Michael Justin & Olsen, Tava Lennon & Zhang, Abraham, 2018. "Agribusiness supply chain risk management: A review of quantitative decision models," Omega, Elsevier, vol. 79(C), pages 21-42.

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    Keywords

    Agribusiness; Risk and Uncertainty;

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