Search Results (16)

Carsharing has long supported trip purposes typically made by private vehicles, with grocery shopping especially benefiting from the carrying capacity of a personal vehicle. BlueLA is a one-way, station-based electric vehicle (EV) carsharing service in Los Angeles aimed at improving access in low-income neighborhoods. We hypothesize that BlueLA improves grocery access for underserved households by increasing their spatial-temporal reach to diverse grocery store types. We test two hypotheses: (1) accessibility from BlueLA stations to grocery stores varies by store type, traffic conditions, and departure times; and (2) Standard (general population) and Community (low-income) members differ in perceived grocery access and station usage. Using a mixed-methods approach, we integrate walking and driving isochrones, store data (n = 5888), trip activity data (n = 59,112), and survey responses (n = 215). Grocery shopping was a key trip purpose, with 69% of Community and 61% of Standard members reporting this use. Late-night grocery access is mostly limited to convenience stores, while roundtrips to full-service stores range from 55 to 100 min and cost USD 12 to USD 20. Survey data show that 84% of Community and 71% of Standard members reported improved grocery access. The findings highlight the importance of trip timing and the potential for carsharing and retail strategies to improve food access. Full article

The rapid growth of the e-commerce market in the retail sector has led to a greater demand for home delivery services in recent years. In order to develop policies to address the issues related to delivery demand, it is critical to understand the demand mechanism of online shopping. Furthermore, the relationship between proximity to mass rapid transit and shopping mode choice mechanisms has not been studied, although, in the field of urban design, accessibility to mass rapid transit is known to affect travel behaviors. We focus on the relationship between proximity to mass rapid transit stations and the shopping mode choice mechanism and estimate structural equation models, considering in-person and online shopping propensities as the latent variables. We use the two datasets. One is from a web-based survey of online shoppers in Japan. The other is the 2019 NYC Citywide Mobility Survey data. The results based on Japanese survey data indicate a clear difference in shopping mode choice mechanisms between MRT-dependent neighborhoods and non-MRT-dependent neighborhoods, while such a difference is limited in NYC. Furthermore, the study reveals how individual and household characteristics and accessibility indicators affect online shopping propensity based on the type of neighborhood and city/country. Full article

The visibility of retail frontages is critical for earning profits from spontaneous traffic visits to retail shops located along a street. The urban tree canopy plays a crucial role in enhancing the street-side environment, yet more is not always better when considering the placement of retail shops behind trees with big canopies. Related evidence in the literature is rarely provided, and an unclear relationship has been reported to exist between the number of shops for a specific retail type and the quantified ratio of the canopy shade in a street view. In this study, both big data crawling and deep learning were employed to unravel this relationship for retail shops in Changchun, Northeast China. The entire study area was divided into 6037 grid cells with a side length of ~0.6 km, wherein the number of shops of five retail types (food and beverage, shopping, life services, entertainment, and hotel) were quantified by computer counting their points of interest (POIs). The canopy shade was evaluated using the green view index (GVI) quantified through the ratio of canopy pixels divided by all the pixels in a street view image obtained through an online map API. A neighboring road network was categorized into four classes: class I road density mainly reduced the number of retail shops, and the road densities of classes III and IV accounted for more retail shops. The relationship between the number of retail shops and the GVI could be fitted with positive skewness curves for class II roads, where the critical peak of the GVI was estimated to be about 3.27%. The optimization scheme indicated that more retail shops should be placed along class I and II roads. In conclusion, more retail shops for food and beverage, shopping, and life services should be placed in the landscape neighboring big canopies. Full article

This study examines the impact of spatial characteristics on gendered retail consumption in Seoul, South Korea, providing empirical evidence for gender-sensitive urban planning. Gender-sensitive urban planning integrates gender perspectives into all stages of urban development, aiming to address the diverse needs and experiences of all genders spatially. While existing research has predominantly focused on gender differences in labor participation, this study shifts the focus to retail consumption, which is a critical aspect of daily life. Our research analyzes the spatial attributes of urban spaces at the neighborhood scale and their influence on aggregated retail consumption by gender. The aggregated retail sales by census output area (jipgyegu) represent the aggregated retail consumption. Utilizing spatial regression methods, this study identifies significant spatial autocorrelations and clustering patterns in retail sales data. The findings reveal that traditional markets, less-developed commercial areas, and specific retail sector (retailing, medical, and educational services) densities positively impact SMW (subtraction of men’s retail sales from women’s retail sales), while city center areas, developed commercial districts, special tourism zones, and specific retail sector (restaurants and entertainment) densities have negative impacts. Full article

Community revitalization is a complex, multifaceted process, studied conceptually and empirically in the vast multidisciplinary literature. Among the cited elements of community revitalization are housing; school, civic, and retail spaces; street networks; parks; and green spaces. However, the elements are commonly studied in isolation, not considering their interrelated qualities as all-of-a-piece of the community revitalization process. In this paper, we draw on the concept of the neighborhood unit that facilities a holistic approach to community revitalization. We show how the neighborhood unit is metamorphosed and thereby endured from the classic to the contemporary. We argue that the neighborhood unit informs, as well as being challenged by, community revitalization. Furthermore, inadequate attention is given to how urban revitalization challenges the efficacy of the neighborhood unit itself. The inner-city blight provides an impetus to look beyond the neighborhood to the metropolitan region as a whole. The neighborhood unit’s fundamental limitation is posed by its cellular autonomy, in favor of alternatives that connect the neighborhood to the metropolitan region’s jobs–housing–services–mobility opportunity holistically. Our literature review of the impactful elements of community revitalization is aided by AI (ChatGPT) as an expeditious search engine. It is found that the AI-aided search of the universal poses anew the significance of the particular—the site- and context-specific. We conclude with universal “performance dimensions” of Good City Form that are calibrated locally, reflecting the goodness of the city form, of which the neighborhood is a building block. Full article

We aimed to determine whether neighborhood socioeconomic characteristics are associated with the coronavirus disease 2019 (COVID-19) incidence in elementary school children and, if so, the associated characteristics. We obtained data on the number of infected children from 282 public elementary schools and the socioeconomic characteristics of each school district in Osaka City, Japan. We examined associations between these variables through negative binomial regression analyses. The proportion of employment in the wholesale and retail trade industry and the college graduation rate were significantly positively and negatively associated, respectively, with the total number of COVID-19-infected children. It was discovered that percentages of employment in the accommodation and food service industries in Wave 2, wholesale and retail trade industries after Wave 3, and healthcare and social assistance industries in Wave 5 were significantly positively associated with the number of infected children; likewise, the college graduation rate in Wave 5 was significantly negatively associated with the number of infected children. Our findings provide insight into the relevant and important areas of focus for public health policymakers and practitioners to ensure reduced disparities in COVID-19 infection rates. Full article

Walking, as a major mode of travel or activity among older adults, deserves more attention in research on travel behavior related to the neighborhood built environment. However, most previous research has examined global relationships or assumed that all spatial scales are identical rather than focusing on the intensity of spatial scale differences between explanatory variables and travel behavior. Therefore, this paper employs a multi-scale, geographically weighted regression model to analyze the effect of the neighborhood built environment on the walking activities of 863 older adults in Taiyuan, China, using survey data. The results indicate that the influence intensity of the explanatory variables is determined, in descending order, by the number of retail establishments, the number of pedestrian crossings, the number of restaurants, the residential density, the land use combination, the number of recreation facilities, and the location and the number of bus stops. Moreover, the spatial scales of the number of recreation and public service facilities are greater than those of the other explanatory variables. This research can contribute to a better understanding of the relationships between the built environment of a neighborhood and walking activities and provide case support for the sustainable development of age-friendly transportation services. Full article

In contemporary urban logistics, drones will become a preferred transportation mode for last-mile deliveries, as they have shown commercial potential and triple-bottom-line performance. Drones, in fact, address many challenges related to congestion and emissions and can streamline the last leg of the supply chain, while maintaining economic performance. Despite the common conviction that drones will reshape the future of deliveries, numerous hurdles prevent practical implementation of this futuristic vision. The sharing economy, referred to as a collaborative business model that foster sharing, exchanging and renting resources, could lead to operational improvements and enhance the cost control ability and the flexibility of companies using drones. For instance, the Amazon patent for drone beehives, which are fulfilment centers where drones can be restocked before flying out again for another delivery, could be established as a shared delivery systems where different freight carriers jointly deliver goods to customers. Only a few studies have addressed the problem of operating such facilities providing services to retail companies. In this paper, we formulate the problem as a deterministic location-routing model and derive its robust counterpart under the travel time uncertainty. To tackle the computational complexity of the model caused by the non-linear energy consumption rates in drone battery, we propose a tailored matheuristic combining variable neighborhood descent with a cut generation approach. The computational experiments show the efficiency of the solution approach especially compared to the Gurobi solver. Full article

Utilizing local brick-and-mortar stores for same-day order fulfillment is becoming prominent in omni-channel retailing. Efficient in-store order picking is critical to providing timely value-added omni-channel delivery services. Despite numerous studies on order picking in traditional logistics warehouses and distribution centers, there is scant research focusing on in-store order fulfillment with the multi-skilled workforce in omni-channel retail stores. We studied the integrated Order Picking and Heterogeneous Picker Scheduling Problem (OPPSP-Het) in omni-channel retail stores. We characterized the OPPSP-Het in a mixed-integer linear optimization model with the objective of the minimization of total tardiness of all customer orders. A hybrid heuristic combining the genetic algorithm and variable neighborhood descent was designed to obtain effective solutions. Extensive experiments were conducted to validate the performance of the proposed approach relative to existing algorithms in recent literature. We further numerically showed the effects of order size and heterogeneous workforce on order fulfillment performance. We lastly emphasized the importance of workforce flexibility as a cost-effective approach to improving in-store order fulfillment performance. Full article

Creating a sustainable urban space should allow everyone to benefit from urbanization regardless of their ability. Spatial equity is one of the significant factors of sustainability. Several studies have explored pedestrian accessibility and spatial equity, but few researchers have addressed daily retail activities. This study aimed to examine the equity of pedestrian accessibility to neighborhood retail and service (NRS) establishments in Seoul, Korea. Accessibility of NRSs was measured by pedestrian direction API and spatially clustered by local indicators of spatial association (LISA). Equity was examined using the Mann–Whitney U test to test the difference between socioeconomic and built environment variables between high and low accessibility areas. We found that vulnerable groups favored access to the NRSs over more affluent groups. This study’s results suggest that urban planners and designers should contemplate ways to enhance the walkability of the residents and continually monitor accessibility to prevent urban problems, such as food deserts and retail deserts. Additionally, the results provide empirical evidence for achieving equity in urban development and urban retail systems to further enhance sustainability. Full article

The paper tests whether low-income workers suffer a greater commuting cost burden compared with a typical commuter within the context of decreasing economic opportunity. The paper adds to the spatial mismatch research by studying the metropolitan area in the U.S. South, which experienced “some of the largest decreases” in job proximity in 2012. Memphis, Tennessee, saw the disproportionately steep declines in the average employment opportunities within a typical commute distance experienced by low-income and minority residents. The paper first delineates low-income neighborhoods across the study area, then identifies commuting patterns within the three-state study area including the greater Memphis, and lastly, it compares average commute lengths by a typical and a low-income commuter, as well as the shares of resident workers with a long commute by earning category. The paper offers insight into the ways in which the changes in spatial location of employment and population within the metropolitan area may impact commuting distance for disadvantaged low-income travelers. We show low-income workers commute statistically significantly shorter distances to their places of work compared with a typical commuter. Our other results find that disadvantaged workers in Shelby County, TN, are disproportionately concentrated in lower-wage industries, such as hospitality and retail service industries, compared to overall workers. Finally, a significantly greater proportion of disadvantaged workers travel long distances of over 50 miles compared with higher-earning workers, indicating the disparity in commuting patterns between a typical resident and a low-income worker. Full article

Considering the association between the neighborhood food environment and individual eating behaviors, this study aimed to assess the association between parents’ reported use of food facilities by their children, and parental perceived travel time to food facilities, with their children’s dietary patterns. Parents reported the use of supermarkets, full-service and fast-food restaurants, and perceived travel time to these food retailers. To assess school children’s food consumption, a previous day dietary recall was applied. Factor analysis was conducted to identify dietary patterns. To test the association between reported use and perceived travel time to food retailers and school children’s dietary patterns, we performed multilevel linear regression analyses. Parents’ reported use of supermarkets was associated with children’s higher score in the “Morning/Evening Meal” pattern. The use of full-service and fast-food restaurants was associated with children’s higher score in the “Fast Food” pattern. Higher parental perceived travel time to full-service and fast-food restaurants was associated with children’s lower score in the “Fast Food” pattern. Although the use of full-service and fast-food restaurants was associated with a less healthy dietary pattern, the perception of living further away from these food retailers may pose a barrier for the use of these facilities. Full article

Person re-identification is an important topic in retail, scene monitoring, human-computer interaction, people counting, ambient assisted living and many other application fields. A dataset for person re-identification TVPR (Top View Person Re-Identification) based on a number of significant features derived from both depth and color images has been previously built. This dataset uses an RGB-D camera in a top-view configuration to extract anthropometric features for the recognition of people in view of the camera, reducing the problem of occlusions while being privacy preserving. In this paper, we introduce a machine learning method for person re-identification using the TVPR dataset. In particular, we propose the combination of multiple k-nearest neighbor classifiers based on different distance functions and feature subsets derived from depth and color images. Moreover, the neighborhood component feature selection is used to learn the depth features’ weighting vector by minimizing the leave-one-out regularized training error. The classification process is performed by selecting the first passage under the camera for training and using the others as the testing set. Experimental results show that the proposed methodology outperforms standard supervised classifiers widely used for the re-identification task. This improvement encourages the application of this approach in the retail context in order to improve retail analytics, customer service and shopping space management. Full article

This paper investigates the effect of food environments, characterized as food swamps, on adult obesity rates. Food swamps have been described as areas with a high-density of establishments selling high-calorie fast food and junk food, relative to healthier food options. This study examines multiple ways of categorizing food environments as food swamps and food deserts, including alternate versions of the Retail Food Environment Index. We merged food outlet, sociodemographic and obesity data from the United States Department of Agriculture (USDA) Food Environment Atlas, the American Community Survey, and a commercial street reference dataset. We employed an instrumental variables (IV) strategy to correct for the endogeneity of food environments (i.e., that individuals self-select into neighborhoods and may consider food availability in their decision). Our results suggest that the presence of a food swamp is a stronger predictor of obesity rates than the absence of full-service grocery stores. We found, even after controlling for food desert effects, food swamps have a positive, statistically significant effect on adult obesity rates. All three food swamp measures indicated the same positive association, but reflected different magnitudes of the food swamp effect on rates of adult obesity (p values ranged from 0.00 to 0.16). Our adjustment for reverse causality, using an IV approach, revealed a stronger effect of food swamps than would have been obtained by naïve ordinary least squares (OLS) estimates. The food swamp effect was stronger in counties with greater income inequality (p < 0.05) and where residents are less mobile (p < 0.01). Based on these findings, local government policies such as zoning laws simultaneously restricting access to unhealthy food outlets and incentivizing healthy food retailers to locate in underserved neighborhoods warrant consideration as strategies to increase health equity. Full article

Information on grocery shopping patterns is one key to understanding dietary changes in recent years in Spain. This report presents an overview of Spanish food shopping patterns in the adult population. A cross-sectional, nationally representative telephone survey was conducted in Spain. Individuals were asked about food shopping responsibility roles, types of visited food stores, time spent, additional behaviors while shopping, the influence of marketing/advertising and, in particular, fresh produce shopping profile. Binary logistic regression models were developed. The final random sample included 2026 respondents aged ≥18 years, of which 1223 were women and 803 were men. Women reported being in charge of most of the food shopping activities. Looking for best prices, more than looking for healthy or sustainable foods, seemed to be a general behavior. Supermarkets were the preferred retail spaces for food price consideration, convenience, variety and availability. Fresh produce shopping was associated with traditional markets and neighborhood stores in terms of reliance and personalized service. It is essential to highlight the importance of the role played by women. They are the main supporters concerned in preserving adequate dietary habits. Economic factors, more than health or food sustainability, are commonly considered by the population. Traditional markets may play an important role in preserving some healthy dietary habits of the Mediterranean food culture in Spain. Full article