Development and Application of Predictive Models for Survival, Growth, and Death of Enteric Pathogens in Leafy Greens Supply Chain

Leafy greens are essential part of a healthy diet. Because of their health benefits, production and consumption of leafy greens has increased considerably in the U.S. in the last few decades. However, leafy greens are also associated with a large number of foodborne disease outbreaks in the last few years. The overall goal of this dissertation was to use the current knowledge of predictive models and available data to understand the growth, survival, and death of enteric pathogens in leafy greens at pre- and post-harvest levels. Temperature plays a major role in the growth and death of bacteria in foods. A growth-death model was developed for Salmonella and Listeria monocytogenes in leafy greens for varying temperature conditions typically encountered during supply chain. The developed growth-death models were validated using experimental dynamic time-temperature profiles available in the literature. Furthermore, these growth-death models for Salmonella and Listeria monocytogenes and a similar model for E. coli O157:H7 were used to predict the growth of these pathogens in leafy greens during transportation without temperature control. Refrigeration of leafy greens meets the purposes of increasing their shelf-life and mitigating the bacterial growth, but at the same time, storage of foods at lower temperature increases the storage cost. Nonlinear programming was used to optimize the storage temperature of leafy greens during supply chain while minimizing the storage cost and maintaining the desired levels of sensory quality and microbial safety. Most of the outbreaks associated with consumption of leafy greens contaminated with E. coli O157:H7 have occurred during July-November in the U.S. A dynamic system model consisting of subsystems and inputs (soil, irrigation, cattle, wildlife, and rainfall) simulating a farm in a major leafy greens producing area in California was developed. The model was simulated incorporating the events of planting, irrigation, harvesting, ground preparation for the new crop, contamination of soil and plants, and survival of E. coli O157:H7. The predictions of this system model are in agreement with the seasonality of outbreaks. This dissertation utilized the growth, survival, and death models of enteric pathogens in leafy greens during production and supply chain.

Essays on Supply Chain Finance

I study how a larger party within a supply chain could use its superior knowledge about its partner, who is considered to be financially constrained, to help its partner gain access to cheap finance. In particular, I consider two scenarios: (i) Retailer intermediation in supplier finance and (ii) The Effectiveness of Supplier Buy Back Finance. In the fist chapter, I study how a large buyer could help small suppliers obtain financing for their operations. Especially in developing economies, traditional financing methods can be very costly or unavailable to such suppliers. In order to reduce channel costs, in recent years large buyers started to implement their own financing methods that intermediate between suppliers and financing institutions. In this paper, I analyze the role and efficiency of buyer intermediation in supplier financing. Building a game-theoretical model, I show that buyer intermediated financing can significantly improve supply chain performance. Using data from a large Chinese online retailer and through structural regression estimation based on the theoretical analysis, I demonstrate that buyer intermediation induces lower interest rates and wholesale prices, increases order quantities, and boosts supplier borrowing. The analysis also shows that the retailer systematically overestimates the consumer demand. Based on counterfactual analysis, I predict that the implementation of buyer intermediated financing for the online retailer in 2013 improved channel profits by 18.3%, yielding more than $68M projected savings. In the second chapter, I study a novel buy-back financing scheme employed by large manufacturers in some emerging markets. A large manufacturer can secure financing for its budget-constrained downstream partners by assuming a part of the risk for their inventory by committing to buy back some unsold units. Buy back commitment could help a small downstream party secure a bank loan and further induce a higher order quantity through better allocation of risk in the supply chain. However, such a commitment may undermine the supply chain performance as it imposes extra costs on the supplier incurred by the return of large or costly-to-handle items. I first theoretically analyze the buy-back financing contract employed by a leading Chinese automative manufacturer and some variants of this contracting scheme. In order to measure the effectiveness of buy-back financing contracts, I utilize contract and sales data from the company and structurally estimate the theoretical model. Through counterfactual analysis, I study the efficiency of various buy-back financing schemes and compare them to traditional financing methods. I find that buy-back contract agreements can improve channel efficiency significantly compared to simple contracts with no buy-back, whether the downstream retailer can secure financing on its own or not.

Improving cold chain technologies through the use of phase change material

Gemstone Team FRESH