Remedying food policy invisibility with spatial intersectionality: A case study in the Detroit Metropolitan Area

This study examines the intersectionality of race/ethnicity and poverty in terms of geographic access to 2,635 food stores of three types (supermarkets, grocery stores, and convenience stores) in the tricounty Detroit metropolitan area (DMA). Prior research not only lacks an intersectional view of sociodemographic categories in explicating food store access, but it also fails to provide place-based policies to remedy food policy invisibility. The authors explore whether spatial dependencies among food stores exist and whether these are linked to sociodemographic heterogeneity in the DMA. Food stores are clustered across suburban and rural areas surrounding urban boundaries but are less clustered in the inner city. Poor neighborhoods have varying access to different types of food stores depending on the predominant racial/ethnic composition of the neighborhood. This research can assist policy makers in implementing place-based food interventions and policies, especially attracting new supermarkets and grocery stores to the urban DMA

Tourism Industry Specialization, Overtourism, and Community Resilience: A Spatial Path Analysis Approach

Despite the positive and negative impacts of tourism, prior studies have rarely focused on addressing how each tourism sector differently affects community resilience, and which factor significantly influences their mixed relationships across communities. This study addresses previous limitations by exploring spatially heterogeneous mixed effects of tourism industry specialization on community resilience and identifying a key moderator that affects their mixed relationships. Geographically weighted regression combined with spatial path analysis was applied to case studies of 3,108 counties in the United States and 67 counties in Florida. The findings show that tourism industry specialization has spatially heterogeneous mixed effects on community resilience, and these effects are strongly affected by the degree of environmental pollution. Specifically, environmental pollution negatively affects the relationships between community resilience and (a) arts/entertainment/recreation tourism sectors in the United States and (b) accommodation/food service tourism sectors in Florida. Theoretical and practical implications of the findings are also discussed

Congestion Costs and Scheduling Preferences of Car Commuters in California: Estimates Using Big Data

On average, California car commuters waste 4–5 minutes per morning commute due to congestion. Multiplied across all California car commuters, those few minutes entail a yearly total of approximately 2.3 billion hours of time wasted, costing 6 billion dollars. The objective of this study is to quantify congestion costs and determine how commuters adapt to the level of congestion they face (i.e., commuters’ scheduling utility functions). To that end, this research developed a model of trip scheduling under congestion to construct California commuters’ travel-time profiles, i.e., the menu of travel times that each individual would likely face according to alternate trip timing choices. The results show that commuters facing higher levels of congestion tend to avoid delays by arriving at an inconvenient edge time rather than commuting during the peak. Further, commuters are willing to accept about 0.5 additional minutes of schedule delay to reduce travel time by 1 minute. We found that for most commuters in our data, the travel time profile is much flatter than the estimated schedule utility, which implies that commuters tend to arrive around their own ideal arrival times, although the estimated utility function exhibits a moderate schedule inflexibility. This finding ultimately calls into question the existing bottleneck model’s quantification of the economic cost of congestion as well as the optimal toll to ameliorate congestion

The importance of tourism clusters and community resilience for remedying Airbnb COVID-19 disruption

Peer-to-peer accommodation markets have been disrupted by the COVID-19 pandemic. However, little attention is paid to how to remedy the disruption in terms of Airbnb business performance. This study empirically investigates the spatially varying COVID-19 disruptions in the Airbnb business and offer place-based remedying strategies through local resources, including tourism clusters and community resilience. Using real data of Airbnb operating performance, COVID-19, and local resources in Florida, we apply geographically weighted regression to estimate the spatial effects in the Airbnb performance model. The results show that Airbnb listings in rural areas that specialized in leisure businesses were more disrupted by COVID-19 than those in urban areas that specialized in hospitality businesses. Furthermore, community resilience attenuated the negative impact of COVID-19 across locations, more in rural areas than in urban areas. These findings enable Airbnb hosts and policymakers to adopt localized resource-based remedying strategies to cope with the pandemic

Financial Repression and Housing Investment: An Analysis of the Korean Chonsei

South Korea has a unique kind of rental contract, called chonsei. The tenant pays an upfront deposit, typically from 40% to 70% of the property value, to the landlord, and the landlord repays the deposit to the tenant upon contract termination. The tenant is not required to make any periodic monthly rental payments. The main goal of this paper is to show why such a unique rental contract exists and has been popular in Korea. The model shows that chonsei is an ingenious market response in the era of "financial repression" in Korea (Renaud (1989)), allowing landlords to accumulate sufficient funds for housing investment without major reliance on a mortgage. The model also shows that the tenant, who suffers from insufficient mortgage borrowings, can access cheaper rental housing via chonsei than when only monthly rental housing is available. The model predicts that the chonsei system should fade out when arbitrage gains from housing investment disappear. An implication of the model is that the chonsei renter may save while the landlord and the owner-occupier put all their assets into housing and thus have no financial savings. This hypothesis is empirically tested and confirmed

Vehicle Fuel-Efficiency Choices, Emission Externalities, and Urban Sprawl

This paper shows that a city where both a congestion externality and an externality from greenhouse gas emissions are corrected by efficient policies is more compact than the laissez-faire equilibrium city. Motivated by recent empirical studies showing a positive relationship between population density and vehicle fuel-efficiency, the consumer is assumed to choose vehicle fuel-efficiency jointly with housing consumption and residential location. By incorporating the consumer's vehicle choice into the urban spatial model, we can represent the total amount of vehicle emissions released by the city residents. We first establish the well-known result that the congestion externality as a source of market failure is associated with excessive urban sprawl. We then show that vehicle emissions are an additional source of market failure, which also leads to excessive urban sprawl. The source of excessive sprawl arising from the emission externality is the use of larger and less-fuel efficient vehicles in more sprawled cities, which is different from that of the congestion externality. We also analyze the effect of the Corporate Average Fuel Economy (CAFE) standards on urban spatial structure and its efficacy as a second-best tool for correcting the emission externality

Exploring museum visitors’ virtual reality experiences: An online user-generated content approach

Despite the emerging virtual reality (VR), little is known about museum visitors’ VR experiences. Particularly, empirical studies through online user-generated content have been rarely attempted. This research note seeks to explore VR experiences through user-generated content in the museum setting. Using 1,891 reviews and attribute data from TripAdvisor, multiple analytical techniques were conducted in spatial, temporal, satisfaction, perceptional (bigram co-occurrence network graph), and sentimental (Russel’s Circumplex Model of Affect) aspects to explore the current marketing landscape of museum visitors’ VR experience. The findings showed that VR experiences were dominantly distributed in North America, Europe, and Oceania; the experiences were mainly focused during 2017 and 2018; museums of highly ranked satisfactions showed characteristics of historical war and military; functional elements of VR indicated predominantly in users’ perceptions; high arousal and pleasure was the most dominant emotional sector. These findings can help practitioners comprehend the VR market in a museum context