Jin-Ho Jeong

The shortages of baby formula in the US resulting from the voluntary recall of contaminated products and shutdown of manufacturing facility in February led to increases in the national out-of-stock rate of the baby formula from 18 to 70% over the summer of 2022. This study utilizes social media listening and data analysis to examine how online media reactions to the physical shortage changed over time and how the reaction to the shortage differed from to the initial recall announcements. Improve

In light of extended stay-at-home periods during the coronavirus disease 2019 pandemic, recent societal trends have revealed an increased use of online media to remain connected. Simultaneously, interests in at-home cooking and baking, particularly of “comfort foods” have increased. Because flour is a crucial component in many of these products, we analyze how the U.S. public, in social and online media spaces, references “flour” and its use. We also quantify the share of media mentions about fl

Background: Interest in local food has been growing, driven by increased attention from consumers, supporting policies, and interest in offering supply by local producers. Nonetheless, a definition of "local food" remains elusive, varying with purposes, geographies, and perceptions. This study quantifies online media mentioning local food in 2018-2021 using online and social media listening and analytics. In addition, a sub-search devoted to local food security and access was conducted due to a

Abstract We estimate the degree of spatial differentiation–primarily driven by transportation costs–among downstream firms that buy corn from upstream farmers and examine whether such differentiation softens competition enabling buyers to exert market power (defined as the ability to pay a price for corn that is below its marginal value product net of processing cost). We estimate a structural model of spatial competition using corn procurement data from the U.S. state of Indiana from 2004 to 20

Abstract Attention to big data analytics is ubiquitous and growing given the online shopping revolution and its potential to generate individual-specific actionable datasets which were previously unavailable or cumbersome to cultivate. However, the food industry has not drawn much attention to discussions of individualized pricing strategies using online grocery datasets. Considering growth of the online grocery market and consumers data abundance to grocers, this brief viewpoint article focuses

Abstract Food delivery applications have grown rapidly in recent years, fueled by increasing consumer demand for convenience and prepared foods. Previous studies on what factors encourage consumers to use delivery platforms rely largely on survey data, likely due to the lack of availability of restaurant or industry level data. Utilizing web-scraping techniques to collect restaurant level data from one of the biggest delivery applications in South Korea, Yogiyo, this study conducts an analysis o

Solar energy is expanding in the US and globally recently in part because of policies encouraging its adoption such as net metering, financing tax benefits, or federal tax credits. Indiana is also expanding solar energy with other renewables to protect its environment because 95% of electricity is generated from coal (U.S. Energy Information Administration (U.S. EIA), 2014). Much of the attention to date on the expansion of solar energy has been on adopting solar PV systems in residential sector

We estimate the cost of transporting corn and the resulting degree of spatial differentiation among downstream firms that buy corn from upstream farmers and examine whether such differentiation softens competition enabling buyers to exert market power (defined as the ability to pay a price for corn that is below its marginal value product net of processing cost). We estimate a structural model of spatial competition using corn procurement data from the U.S. state of Indiana from 2004 to 2014. We

First Essay: We study the effect of entry of ethanol plants on the spatial pattern of corn prices. We use pre- and post-entry data from corn elevators to implement a clean identification strategy that allows us to quantify how price effects vary with the size of the entrant (relative to local corn production) and with distance from the elevator to the entrant. We estimate Difference-In-Difference (DID) and DID-matching models with linear and non-linear distance specifications. We find that the a