Model Estimation Results.

There is continued interest in the modernization of food traceability systems because of increased consumer consciousness of food production, processing, and transportation and the desire of the food industry to identify and contain sources of foodborne illness outbreaks and improve their reputations to consumers. Blockchain-based traceability systems promise faster access to more decentralized, tamper-proof records of the movement of a food product and its ingredients through the supply chain. Using data from two discrete choice experiment surveys, we estimate U.S. consumer marginal willingness to pay for access to blockchain-based traceability information via QR codes and for more specific sub-region provenance labeling placed on the packaging of two economically important and outbreak-prone leafy greens: romaine lettuce and spinach. After conducting sensitivity testing using a variety of specifications, we find that unrestricted random parameter logit models allowing for correlation across random parameters provide the best model fit. Simulations of willingness to pay distributions indicate a median marginal willingness to pay of about $1.45 for access to traceability information over no access and an additional $0.33-$0.38 if the information is blockchain verified. We also find that voluntary sub-region provenance labeling may result in consumers discounting imported relative to domestically produced leafy greens. If domestically produced, consumers are not willing to pay more to know the region within a state where the product was grown.