Supply Chain Network Analytics Guiding Food Regulatory Operational Policy

52 Pages Posted: 17 May 2019 Last revised: 9 Dec 2020

See all articles by Retsef Levi

Retsef Levi

MIT Sloan School of Management - Operations Research Center

Nicholas Renegar

Massachusetts Institute of Technology (MIT), Operations Research Center

Stacy Springs

Massachusetts Institute of Technology (MIT)

Tauhid Zaman

affiliation not provided to SSRN

Date Written: April 14, 2019

Abstract

Food adulteration poses a serious threat to public health. The U.S. Food and Drug Administration (FDA) has a major role in maintaining food safety in the U.S. through various activities including sampling of imported shipments and site inspections. However, resource constraints limit the number of these interventions, making risk-based allocation essential to ensure effectiveness. This paper aims to develops a data-driven, risk analytics approach to identify high-risk firms importing food (consignees). Leveraging supply chain analytics, based on shipment history and other data sources, network features are constructed to model risk, specifically predicting which consignees are likely to fail FDA site inspections. The approach is applied to consignees of shrimp, a product with frequent food safety problems. The main findings are that supply chain network complexity, and website network engagement, are predictive of risk. For instance, firms that import a more unusual portfolio of products, as measured through subgraph modularity on a product network graph, are more likely to fail site inspections. The results suggest that network-based risk analytics could significantly improve the effectiveness of regulatory activities related to food supply chains, and substantially increase the number of failed site inspections and imported shipment samples.

Keywords: food safety, risk management, supply chains, networks, statistics

Suggested Citation

Levi, Retsef and Renegar, Nicholas and Springs, Stacy and Zaman, Tauhid, Supply Chain Network Analytics Guiding Food Regulatory Operational Policy (April 14, 2019). Available at SSRN: https://ssrn.com/abstract=3374620 or http://dx.doi.org/10.2139/ssrn.3374620

Retsef Levi

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

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

Nicholas Renegar (Contact Author)

Massachusetts Institute of Technology (MIT), Operations Research Center ( email )

77 Massachusetts Avenue
Bldg. E 40-149
Cambridge, MA 02139
United States

HOME PAGE: http://www.mit.edu/~renegar

Stacy Springs

Massachusetts Institute of Technology (MIT) ( email )

77 Massachusetts Avenue
50 Memorial Drive
Cambridge, MA 02139-4307
United States

Tauhid Zaman

affiliation not provided to SSRN

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
212
Abstract Views
1,145
rank
198,400
PlumX Metrics