Economically Motivated Adulteration in Farming Supply Chains

Forthcoming in Management Science

42 Pages Posted: 27 Oct 2017 Last revised: 4 Oct 2018

See all articles by Retsef Levi

Retsef Levi

MIT Sloan School of Management - Operations Research Center

Somya Singhvi

USC Marshall School of Business

Yanchong Zheng

Massachusetts Institute of Technology (MIT) - Sloan School of Management

Date Written: September 17, 2018

Abstract

Economically motivated adulteration (EMA) is a serious threat to public health. In this paper, we develop a modeling framework to examine farms' strategic adulteration behavior and the resulting EMA risk in farming supply chains. We study both "preemptive EMA," where farms engage in adulteration to decrease the likelihood of producing low-quality output, and "reactive EMA," where adulteration is done to increase the perceived quality of the output. We fully characterize the farms' equilibrium adulteration behavior in both types of EMA and analyze how quality uncertainty, supply chain dispersion, traceability, and testing sensitivity (in detecting adulteration) jointly impact the equilibrium adulteration behavior. We determine when greater supply chain dispersion leads to a higher EMA risk and how this result depends on traceability and testing sensitivity. Furthermore, we caution that investing in quality without also enhancing testing capabilities may inadvertently increase EMA risk. Our results highlight the limitation of only relying on end product inspection to deter EMA. We leverage our analyses to offer tangible insights that can help companies and regulators to more proactively address EMA risk in food products.

Keywords: Economically motivated adulteration, farming supply chains, supply chain dispersion, traceability, testing sensitivity, quality risk, food safety, socially responsible operations

Suggested Citation

Levi, Retsef and Singhvi, Somya and Zheng, Yanchong, Economically Motivated Adulteration in Farming Supply Chains (September 17, 2018). Forthcoming in Management Science, Available at SSRN: https://ssrn.com/abstract=3060078 or http://dx.doi.org/10.2139/ssrn.3060078

Retsef Levi

MIT Sloan School of Management - Operations Research Center ( email )

100 Main Street
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Somya Singhvi

USC Marshall School of Business ( email )

701 Exposition Blvd
Los Angeles, CA
United States

Yanchong Zheng (Contact Author)

Massachusetts Institute of Technology (MIT) - Sloan School of Management ( email )

100 Main Street
E62-416
Cambridge, MA 02142
United States

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