Publications
Published in Transportation Research Part E: Logistics and Transportation Review, 2024
Abstract: The food transportation and distribution industry has been radically disrupted over the last few years, especially amid the COVID-19 pandemic. Food prices, for example, have been seen to increase considerably in the wave of economic inflation. As two main driving factors in the context of food transportation, (1) the rising diesel prices and (2) the prevailing shortage of truck drivers have posed threatening challenges, leading to a substantial surge in transportation costs and subsequently contributing to higher food market prices. Based on collected data consolidated from multiple sources, this study conducts a comprehensive analysis to elucidate the impact of diesel prices and driver availability on food prices. To this end, we have curated a panel dataset encompassing key variables such as diesel prices, truck driver availability, and food prices for the most popular food commodities (i.e., apples, potatoes, onions, and tomatoes) pre-, amid, and post-pandemic of COVID-19. Employing fixed effects regression, this paper specifically investigates the extent to which the surge in fuel prices and truck-driver availability has contributed to the overall increase in food prices in the United States fresh food market. With high statistical significance, the experiment results show that the rising diesel prices and the shortage of truck drivers’ availability have a significant positive impact on food price margin, ceteris paribus. The contributions of this study are multifold. First, our study enriches the food price literature by specifically considering the two fundamental root factors: truck-driver availability and diesel price. Second, this study provides data-driven empirical analysis to unveil how diesel prices, driver availability, and the significant impact of the pandemic drive food prices. Third, considering the impact of COVID-19, the food price sensitivity to diesel prices and driver availability obtained from this study renders practical guidelines for policy implications, especially in the age of a devastating pandemic.
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Published in Finance Research Letters, 2024
Abstract: This study investigates the impact of state-level Economic Policy Uncertainty (EPU) on FinTech lending marketplace. Leveraging two large-scale Peer-to-Peer (P2P) datasets of LendingClub and Prosper from 2010 to 2019 alongside the news-based EPU index, we unveil a causal relationship between the EPU and both the interest rates and loan amounts. Economically, a one-standard-deviation increase in EPU causes 4.49 and 8.90 basis points change in P2P loan rates, and 1.56% and 1.28% variation in loan amounts, for LendingClub and Prosper, respectively. Furthermore, the national-sourced EPU has a relatively stronger effect on LendingClub, while the state-sourced EPU imposes more impacts on Prosper.
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Working papers
Food on Road: A Novel County-Level Analysis of Road Density and its Impact on Food Prices in the U.S. Market, with Dr. Jasmine (Aichih) Chang, Dr. Jim Shi
Abstract: Food crisis has been prevailing for decades. Recently, the world-wide economic inflation, especially in food price, has exacerbated the food crisis dramatically. This study examines how transportation infrastructure, e.g., road density, influences food price through the lens of food access and mobility. Using 2010 and 2020 U.S. county-level datasets in conjunction with other data sources, empirically we reveal that, in the U.S. market, higher road density significantly reduces cost per meal by enhancing local and regional food mobility. In particular, ceteris paribus, one mile per square mile increase in road density reduces the cost per meal by 1.3%. We further reveal that road density helps narrow price disparities tied to store availability, while such price dampening effect diminishes or vanishes in or near densely populated areas. These findings shed light on how infrastructure influences food mobility and price equity, and offer evidence-based implications for urban planners, transportation policymakers, and local governments. This study makes several salient contributions to the extant literature. First, it documents empirical evidence from the U.S. market on how infrastructure affects food prices, along with other geographic, demographic, and temporal factors. Second, the study offers a nuanced and deep understanding of how transportation networks interact with local food market, spatially and temporally. Last but not least, this study enriches the food-transportation literature with novel empirical evidence by curating a county-level road density dataset.
Work in progress
Ripple Effects of Tariff Shocks: Estimating Supply Chain Disruptions and Transportation Cost Spillovers in the U.S. Tomato Market, with Dr. Jasmine (Aichih) Chang, Dr. Jim Shi
Abstract: This study investigates the indirect effects of import tariffs on food prices, with a focus on the U.S. tomato market. Specifically, it examines how policy-induced tariff shocks affect prices through the transportation channel. Employing a Difference-in-Differences (DiD) approach, the analysis identifies the causal relationship between tariff changes and food prices. Furthermore, the study develops a U.S. tomato transportation network model to estimate the resulting shifts in transportation costs, providing insights into the broader economic consequences of trade policy.
Integrating AI-Powered XR Wearables for Real-Time Shelf-Life Estimation and Pricing Optimization, with Dr. Jasmine (Aichih) Chang
Abstract: Fresh food retailers operate in a highly uncertain environment where product perishability and fluctuating consumer demand make pricing and inventory management especially challenging. This project proposes an AI-enabled dynamic pricing system using XR wearables to track freshness and adjust prices in real time. By linking fixed purchase costs with prices shaped by perishability and fluctuating demand, retailers can optimize product selection, ordering, and pricing. The approach aims to boost profitability, reduce waste, and improve decision-making in fresh food retail.
The Impact and Implications of Bag Tax Policies on Sustainable Operations: A Systems Dynamics Approach, with Dr. nNesreen El-Rayes, Dr. Jasmine (Aichih) Chang, Dr. Jim Shi
Abstract: This study investigates the impact of bag tax policy in the United States. By leveraging 71k historical dataset and Vensim modeling, we simulate the interactions and feedback loops to demonstrate and forecast policy impacts, providing evidence-based recommendations for optimizing tax structures and accompanying measures to maximize environmental and social benefits.
