Store Categories Research Articles

A class-oriented architecture for designing learning apps

ABSTRACT In the age of Apps, where almost everyone is fast becoming accustomed to using apps in almost every walk of life. Such widespread production, consumption, and burgeoning proliferation of Apps are also frequently seen in the various educational pitches and we call them “Learning Apps” (LAs). Now, approximately everyone is believing in and engaging through these apps as the mandatory future of our educational-organizations. However, their overwhelming nature surprised everyone including learners, parents, and other stockholders. Every day, a thousand apps get published, and continuously adding in educational categories of various app stores. Significantly, most LA developers are targeting preschoolers. And, who knows if they contain true educational values or not? Nevertheless, this scenario seems elusive. We observe the emergence of several de facto design paradigms, having no or little theoretical basis. Moreover, their design features do not scientifically connect with evidence-based teaching practices. Despite the expansion of enterprises and the development of new tools and technology, there is a lack of a sound app design strategy grounded in established didactics. Realizing this, we developed A Class-oriented Architecture of LAs to facilitate the content experts’ design.

Identification of waste composition in Shopping Centre X in Central Jakarta City

Waste is an unavoidable by-product of most human activities. Central Jakarta City is one of the administrative cities in the centre of the Special Capital Region of Jakarta, where Shopping Centre X is situated, a place relied on by the local community to serve their needs and to facilitate community activities. Shopping Center X has ±4,478 active shops which occupy all of its 9 floors, built on an area of 47,760 m2 and the waste generated varies. The purpose of this study was to identify sources of waste, before analysing the waste generation and composition in Shopping Centre X. The waste composition is an illustration of each component contained in the waste produced, and it can be used as a basis for determining a proper waste management in Shopping Centre X. Sampling was carried out using the SNI 19-3694-1994 method, where the waste measurement was made using a sampling box for eight consecutive days. The results of field research showed that, the waste composition in Shopping Centre X consists of 77.42% nonorganic and 22.58% organic waste components. The average rate of waste generation in Shopping Centre X is 3.58 kg/shop/day. The primary data collection was done directly, through field surveys and sampling. Waste samples taken were based on store category grouping on all the 9 (nine) floors, representing the number of samples in Shopping Centre X.

THE INFLUENCE OF STORE RATING, DELIVERY SERVICE, AND STORE CATEGORY TOWARD SALES LEVEL IN TOKOPEDIA

This study aims to find out what variables are significant related to the level of sales on one of the e-commerce platforms in Indonesia, Tokopedia, by using the variables Store Rating, Delivery Service and Store categories as independent variables. This study uses quantitative research by taking data directly from Tokopedia, a total of 160 stores with 80 data from official stores and 80 from non-official stores, and processed using statistical data processing software. This research data were obtained using quantitative methods, with secondary quantitative data from the results of data collection on the first page of the seller/store and the info of the store/merchant/seller Tokopedia based data from 2022. The results of this study are that of the four hypotheses proposed, there are two hypotheses which are stated to have no effect, while the other two hypotheses are stated to have an effect on the dependent variable. The first independent variable has no influence on the dependent variable, so that the H01 hypothesis is partially accepted. The hypothesis that H02 is accepted while Ha2 is rejected is in variable X2 the same as variable X1. Meanwhile, variable X3 has a partial effect on variable Y so that the Ha3 hypothesis is accepted and H03 is rejected. The last hypothesis has been confirmed by Ha4 and H04 is rejected because variable Y is simultaneously influenced by these three factors.

Determinants of Online Food Delivery(OFD) Sales during COVID-19

Purpose: The outbreak of COVID-19 in early 2020 compelled consumers to abstain from dining out and instead use online food delivery (OFD) services. This study aims to examine the determinants of OFD sales in a restaurant during the COVID-19 crisis.
 Design/methodology/approach: We analyzed 139,812 restaurant-level credit card OFD transaction data from January 2019 to June 2020 in Seoul, South Korea.
 Findings: During COVID-19, many restaurants participated and experienced sales growth through the OFD platforms. On the demand side, the composition of customers using OFD services has changed, replacing the demand for dining out. Our estimation results show that the food category, customer composition ratio, and past performance significantly affected restaurants’ OFD revenue during the pandemic.
 Research limitations/implications: The results suggest implications for the restaurant industry responding to changing customer needs on OFD platforms. Restaurants with high-performing OFDs before the pandemic experienced higher sales during the pandemic period. The results imply that experiences to fit customers’ needs toward OFD are likely to help restaurants overcome the losses incurred due to the COVID-19 outbreak.
 Originality/value: This study empirically revealed the effect of store category, past performance, demographic, and geographical customer profile on OFD demand for external shocks such as COVID-19.

A forecasting method of multi-category product sales: analysis and application

To solve the problems of high prediction costs and difficult practices in multi-category product classification in the retail industry, optimize the inventory, and improve resilience, this work introduces a forecasting method for multi-category product sales. The forecasting method divides the data into a category set and a numerical set, uses the stacking strategy, and combines it with catboost, decision tree, and extreme gradient boosting. During the feature engineering process, the ratio and classification features are added to the category feature set; the sales at t are used for training to obtain the prediction at (t + 1); and the features used in the prediction at time (t + 1) are generated by the prediction results at t. The update processes of the two sets are combined to form a joint feature update mechanism, and multiple features of k categories are jointly updated. Using this method, data of all categories of retail stores can be linked so that historical data of different categories of goods can provide support for the prediction of each category of goods and solve the problem of insufficient product data and features. The method is verified on the retail sales data obtained from the Kaggle platform, and the mean absolute error and weighted mean absolute percentage error are adopted to analyze the performance of the model. The results reveal that the forecasting method can provide a useful reference to decision-makers.

LITERATURE STUDY OF FREE APPLICATIONS OF THE ISLAMIC ECONOMY IN THE PLAY STORE

Every Android phone registered with a Gmail account will usually automatically be installed with the Google Play or Play Store application. Play store is an online store that provides various kinds of applications. Applications can be obtained via download for free or paid. Applications in the play store have many categories, including applications in the Books and Reference category and Education category applications. This study aims to find free Islamic economic applications in the play store. The sample in this study is a free Islamic economics application in the play store category of education and the category of books & references. This research methodology is qualitative research using literature study techniques (documentation) on the play store. The study results show six free Islamic economic applications in the play store. Each application has its advantages and disadvantages. But overall, all of these Islamic economics applications provide short, concise and explicit Islamic economics material.

Food environment near schools in the largest Brazilian metropolis: analyses and contributions based on census data.

We aimed to investigate and compare the distribution of establishments that sell food near municipal, state, and private schools in the municipality of São Paulo, Brazil. This cross-sectional, exploratory, and census study was conducted in 3,121 schools. Circular buffers were traced around schools and concentrations or dispersions of food stores (in absolute numbers and densities) were analyzed. A p-trend was calculated to analyze how food stores density behaved as the buffer radius distance increased. Stratified regression models were built to analyze the characteristics of the food environment. Snack bars and street vendors are the most common types of establishments surrounding schools. Some categories of food stores are concentrated (such as candy stores around municipal and private schools, mini markets around municipal schools, and snack bars around private schools), whereas others (such as super and hypermarkets and fruit and vegetable stores) are dispersed around public schools. The food environment around schools shows differences regarding the instance that administers them and private schools have more food stores around them. Poor-quality food environment around schools exposes students to risk factors regarding excessive unhealthy food consumption.

Understanding Food Access in Flint: An Analysis of Racial and Socioeconomic Disparities

The primary objective of this study was to describe the food landscape of Flint, Michigan, and the surrounding townships. We investigated the relationship between the location of food outlets and the racial composition of census tracts. We collected data from multiple sources; however, Data Axle, a repository of information on the U.S. and Canadian businesses, was our primary data source. Data were collected and verified between September 2020 and December 2021. The final fact-checking was completed in June 2022. We used ArcGIS 10.8.1 and SPSS Version 28 to map and analyze the data. We conducted negative binomial regression analyses to identify the difference in the likelihood of finding food retailers in census tracts where the percentage of Black residents was low and those where the percentage of Blacks was high. The article examines 1,137 food retailers in the study area: 407 were in Flint, and the remainder in the surrounding townships. Restaurants—especially fast food and take-out establishments—dominated the food environment. In addition, small groceries and convenience stores proliferated in the grocery store category. The racial composition of the census tracts mattered. Census tracts in which more than 40% of the residents are Black have a mean of 7.6 food outlets. In comparison, census tracts in which 40% or less of the residents are Black have a mean of 11.3 food outlets; the difference is significant. Census tracts with a high percentage of Blacks also had significantly fewer restaurants. The results of this study show Flint’s food landscape to be more complex and robust than described in earlier studies. It underscores the point that researchers should not rely solely on documenting the presence of supermarkets or traditional grocery stores when addressing food insecurity and food access. In the case of Flint, such food outlets comprise only 2.2% of the food landscape. Focusing exclusively on these food retailers misses several important types of food venues that residents rely on to secure food. This siloed approach also ignores the resilience and ingenuity of residents to respond to limited access to traditional food retailers.

Occurrence of methylsiloxanes in indoor store dust in China and potential human exposure

Methylsiloxanes are synthetic molecules with versatile and extensive applications. Because of their volatile properties, they are easily released from manufactured products and contaminate indoor environments, causing high human exposure. However, available information on their presence in specific microenvironments, and on the related potential risks for human health, is limited. We conducted a survey of sixteen methylsiloxanes species, including three cyclic (D4–D6) and thirteen linear (L4–L16) chemicals, in indoor dust samples from twenty-eight stores representative of six store categories in Beijing, China. Total methylsiloxane concentrations in store dust were 176–54,825 ng/g, depending on the store, with a median of 2196 ng/g. Linear chemicals represented a median proportion of 90.8% of total methylsiloxanes. The measured methylsiloxane concentrations in this study were marginally higher than those reported previously for standard living and working environments. The highest linear and total methylsiloxane concentrations were measured in electronic stores, while the highest cyclic methylsiloxane concentrations were measured in department stores. The presence of methylsiloxanes in the store dust samples was attributed mainly to their release from chemical additives in marketed products. Estimated median total exposure doses under normal and worst-case exposure scenarios were 0.237 and 0.888 ng/kg bw/d, respectively. Further investigation is needed to characterize methylsiloxane distribution in other microenvironments and to evaluate the associated health risks.

Relationship Between Neighborhood Food Environment and Diet Variety in Japanese Rural Community-dwelling Elderly: A Cross-sectional Study.

BackgroundFood access is an important aspect of health promotion for the elderly. The aim of this study was to investigate the relationship between distance to the nearest food store and diet variety in rural community-dwelling elderly Japanese.MethodsThis cross-sectional study analyzed data from 1,103 elderly participants surveyed by mail in rural areas of Japan. Diversity of food intake was assessed using the diet variety score (DVS). Street network distance from home to food store was calculated and categorized by quartile using a geographic information system and analyzed in relation to diet using multivariable regression with the primary outcome as low DVS. Sub-analysis of the association with DVS was conducted for each food store category (convenience store, supermarket, and small food store). The association between intake frequency of each food group and distance was also analyzed.ResultsParticipants in the fourth quartile of distance to food store had significantly higher prevalence ratio (1.15; 95% CI, 1.01–1.32) for low DVS than those in the first quartile. There was a significant tendency between greater distance to food store and lower DVS (P for trend = 0.033). Supermarkets and convenience stores, in particular, showed significant associations. Greater distance was significantly associated with lower frequency of meat and fruit intake.ConclusionThere was significant association between distance to nearest food store and diet variety in rural Japanese elderly. These findings suggest the importance of interventions for areas at high risk of low diet variety, such as places far away from food stores.

Availability of food stores around Brazilian schools.

The aim of this study was to analyze the availability of food stores in the territory of schools. Ecological study conducted in Viçosa, Minas Gerais, Brazil, with all schools (N=42) and food stores (N=656). Data were collected through the objective evaluation of the environment, and the stores were categorized into healthy, unhealthy, mixed and supermarkets. Bivariate Ripley´s K function assessed the existence of clustering of categories of stores in the territory of schools. All the schools had at least one food store in their territory. Unhealthy stores were the most common and closest to the schools. There were more stores around private schools, offering high school education, located in the central region and in the highest per capita income tercile. The bivariate Ripley´s K function showed evidence of clustering of stores at all analyzed distances (400 to 1.5 km) with up to 3 times more establishments than would be expected if they were randomly distributed. Therefore, schoolchildren were likely exposed to unhealthy food environments, regardless of neighborhood income and location, which may contribute to inadequate food choices.

Association of tobacco retailer count with smoking population versus vaping population in California (2019)

BackgroundAccess to tobacco products, including vape products, from local brick-and-mortar stores influences the exposure, uptake, and use of these products in local communities.MethodsLicensed tobacco retailers in California were classified as specialized tobacco/vape stores or non-specialized stores by obtaining categories published on Yelp. California smoking and vaping prevalence data were obtained from the 500 cities project and ESRI community analyst tool respectively. A series of simple linear regression tests were performed, at the zip code level, between the retailer count in each store category and smoking/vaping population. The Getis-Ord Gi* and Anselin Local Moran’s I statistics were used for characterization of tobacco retail density hotspots and cold spots.ResultsThe association between CA smoking/vaping population and number of tobacco retailers was statistically significant for all store categories. Variability in smoking population was best explained by variability in non-specialized storefronts(R2=0.84). Spatial variability in tobacco-only storefronts explained the least proportion of variability in the overall smoking population. Similar results were obtained specific to vaping population, although the proportion of population explained by variability in the number of non-specialized storefronts was comparatively lower(R2=0.80).ConclusionsLocalities with greater numbers of non-specialized tobacco retailers had higher rates of smoking/vaping populations, and this association was much stronger for localities with greater numbers of specialized retailers. Non-specialized storefronts may represent convenient access points for nicotine products, while specialized storefronts may represent critical access points for initiation. Hence, regulations that address the entirety of the tobacco/vaping retail environment by limiting widespread access from non-specialized stores and reducing appeal generated by specialized retailers should be incorporated in future tobacco regulatory science and policymaking.

Landscape Analysis of Oncology Mobile Health Applications.

More than 325,000 mobile health (mhealth) applications (apps) have been developed. We sought to describe the state of oncology-specific apps and to highlight areas of strength and opportunities for future development. We searched for oncology apps in the Apple iOS and Google Play app stores in January 2020. Apps were classified by English language support, date of last update, downloads, intended audience, intended purpose, and developer type. We identified 794 oncology-specific, English language applications; only 257 (32%) met basic recency standards and were considered evaluable. Of evaluable apps, almost half (47%) were found in the Medical Store Category and the majority were free (88%). The most common intended audience was health care professionals (45%), with 28% being geared toward the general public and 27% being intended for patients. The intended function was education for 36%, clinical decision support for 19.5%, and patient support for 18%. Only 23% of education apps and 40% of clinical decision support apps reported any formal app content review process. Web developers created 61.5% of apps, scientific societies created 10%, and hospitals or health care organizations created just 6%. Of 54 studies that used mobile apps in oncology identified by a recent meta-analysis, only two could be matched to commercially available apps from our study, suggesting a substantial divide between investigation and product dissemination. Relatively few oncology-related apps exist in the commercial marketplace, up-to-date apps are uncommon, and there is a notable absence of key oncology stakeholders in app development. Meaningful development opportunities exist.

Street pedestrianization in urban districts: Economic impacts in Spanish cities

This study analyzes the influence of pedestrianization of urban space on the revenues of surrounding retail stores. Pedestrianization refers to the conversion of street use from vehicles to a walkable environment. We compiled a unique transaction dataset containing the estimates of sales volumes for stores across Spain and combine it with data from Open Street Map to provide the history of land-use changes at the street-level. Based on these high-granular datasets, we apply a difference-in-differences empirical method to measure the economic impact of pedestrian intervention. The results show that stores located in pedestrian environments tend to record higher sales volumes than stores located in non-pedestrian environments. We further analyze the mechanisms underlying this revenue-boosting effect and find that a key factor is the store density of the pedestrianized place, while geographic location is insignificant. This finding suggests that there are no differentiation impacts on stores' revenue based on whether pedestrianization occurs in the city center or periphery. Store category also acts as an important moderator for revenue impacts, with positive effects observed mostly for the café or restaurant category. Our results provide suggestive evidence that people prefer a pedestrian-friendly environment to a vehicle-oriented one for non-tradable, local consumption activities. This research provides evidence-based policy implications for urban planners interested in making smart, sustainable cities.

A geospatial analysis of age disparities in resolute localities of tobacco and vaping-specific storefronts in California.

INTRODUCTIONConcomitant with the popularization of vaping, vape shops have dramatically proliferated over the past years. This study assesses whether vape storefronts in California are significantly associated with density of different age groups, and whether this differs between tobacco storefronts or non-specific tobacco retailers.METHODSAddresses for licensed tobacco retailers were obtained from the California Department of Tax and Fee Administration. Business names and addresses were used to obtain store categories cross-referenced from Yelp. Using a cross-sectional ecological design, stores categorized as ‘Vape Shop’ or ‘Tobacco Shop’ were geolocated and compared with age-related variables from the American Community Survey. Regression was conducted in R to determine relationships between age group concentration, in ventiles, and proportion of tracts with tobacco-specific or vape-specific stores. Geospatial visualization was conducted using ArcGIS.RESULTSWe found 848 vape shops, 820 tobacco shops, 419 categorized as both, and 20320 retailers with neither category. Overall, 1800 tobacco and/or vape shops were categorized in 1557 of California’s 23194 census tracts. A positive linear association was found between ventiles of two age categories, 20–24 and 25–34 years, and proportion of tracts with vape-specific or tobacco-specific shops separately.CONCLUSIONSPositive associations were found for ages 20–34 years but not for other ages, suggesting vape shops are strategically located in areas populated by young adults. Location-based targeting increases access, thereby increasing proportion of tobacco users, and could be a critical factor in e-cigarette uptake and use. Further study to identify additional age-related demographic characteristics among clientele of tobacco storefronts is warranted.

Patterns of Location and Other Determinants of Retail Stores in Urban Commercial Districts in Changchun, China

Knowledge of the patterns of location of retail stores in urban areas supports the development of effective urban planning and the reasonable allocation of commercial facilities. Using point of interest data and consumer survey data in three main commercial districts in Changchun, China, this study investigates the spatial structures of commercial districts and the patterns of distribution of retail stores to assess the determinants of the development of retail stores in commercial districts. Kernel density estimation, nearest neighbor index, and Pearson’s correlation analysis were used for this study. The following conclusions are drawn. (1) The spatial distribution of retail stores in Changchun commercial districts generates the coexistence of a concentration in the core area and diffusion in the peripheral area. The emergence of shopping malls has challenged the traditional single-center structure, resulting in the transformation of commercial districts from single-center to multicenter layouts, while also producing a hierarchical trend in development. (2) The Chongqing Road and Hongqi Street commercial districts have a relatively high spatial concentration of retail stores. Retail stores in Guilin Road exhibit distinct characteristics, namely, stores selling textiles, clothing, and daily necessities show the highest concentration, and food, beverage, and tobacco outlets as well as integrated stores show the lowest concentration. (3) The selected locations of the differing categories of stores on Chongqing Road strongly correlate, and textile, clothing, and daily necessity stores show a high correlation with other retail categories. (4) Four main factors affect the development and spatial layout of retail in the commercial districts. First, the interaction between consumer behavior and location choice in retail stores promotes the evolution of retail formats and trends in the development of comprehensive, specialized, and hierarchical retail commercial spaces. Second, the retail format determines the spatial layouts and the historical inheritance of the format. Third, governmental planning and policies lead to the agglomeration and diffusion of commercial activities in different areas. Fourth, such spatial clustering effects are an external driving factor for integration and aggregation among retail formats.

Antitrust & Privacy: It's Complicated

It has become almost an article of faith that large, zero-price platforms, such as Facebook and Google, exercise market power by offering lower levels of privacy. Yet, a rigorous examination of the assumptions underlying this data-price analogy is seriously lacking. Even more important, almost no empirical work has been done in this area. This Article contributes to the debate by filling these important gaps in the literature. After presenting a theoretical examination of the relationship between privacy and competition, we provide empirical evidence on the relationship between market power and privacy. First, using data from PrivacyGrade.org, we find no relationship between privacy grades and our proxies for market concentration—the Herfindahl-Hirschman Index (HHI) and market shares based on Google Play Store categories. Second, we collected website traffic data from SimilarWeb and matched it to DuckDuckGo’s privacy ratings for sites in thirty-seven website categories. Again, the data suggest a lack of a reliable relationship between privacy ratings and market concentration. Our theoretical analysis and empirical results cast serious doubt on the notion that firms exercise market power by reducing privacy levels. Challenging conventional wisdom, our results suggest that antitrust is a poor tool to address perceived privacy problems. Instead, if markets produce less than optimal levels of privacy, it is likely due to informational problems that have no relationship with competition. Accordingly, we conclude that privacy regulation and competition policy might be complementary, but only in one direction: consumer protection designed to increase consumer access to information about firms’ privacy practices—and firms’ ability to credibly commit to these promises—could help foster competition over privacy, but the converse is not true.

Debunking the High Cost of Healthy Diets: Consumer Behavior Predicts Dietary Energy Density in a Nationally Representative Sample of US Adults

Dietary energy density (ED; kcal/g) is an established marker for diet quality and a risk factor for obesity. Previous studies have suggested that low-ED diets cost more than high-ED diets, adding an economic contribution to the obesity epidemic. This study evaluated the relationship between consumer behavior (money spent on food) and dietary energy density in a nationally representative sample of US adults. Data from 10,622 adult participants in the 2013-2016 NHANES were used for this study. The NHANES is a large cross-sectional survey conducted by the CDC and NCHS. Consumer behavior was evaluated by examining total dollars spent on food, as well as dollars spent at various categories of food stores & restaurants. Dietary ED was calculated using multiple methods. Multivariate regression models were then used to evaluate the relationship between consumer behavior, defined as money spent in four categories (groceries, take-out, dining out, other food purchases) and dietary energy density. Low-ED diets did not cost more than high-ED diets overall, though low-ED diets contained more servings of fruits (1.6 vs 0.4), vegetables (2.2 vs 0.9) and fiber (21 vs 13g), and fewer added sugars (15 vs. 18 tsp), solid fats (28 vs 39g), all p's < 0.01. Differences in spending patterns were identified. A positive linear trend between money spent on fast food/takeout and dietary energy density (p < 0.001) was observed. Additionally, individuals in the lowest quartile of ED spent more at grocery stores per person than individuals in the highest quartile of ED ($182 vs. $150 p = 0.04). Spending pattern and consumer choices are associated with dietary ED in this cross-sectional analysis of a nationally representative population sample. Identifying eating behaviors associated with diets high in energy density may inform future investigations that intervene on dietary habit for promotion of healthy eating and prevention of weight gain.

Spatial clustering: Influence of urban street networks on retail sales volumes

As is often believed that the more centrally located a shop, the higher its sales volume, this paper analyzed relationships between the spatial clustering of retail stores, their respective transaction volumes, and the urban street networks to determine whether, and to what extent, the accessibility and density of a store’s location was correlated with its transaction volume. While this hypothesis is widely accepted, its veracity is underexplored and rarely validated using large-scale empirical datasets, possibly owing to the lack of access. Therefore, transaction datasets and accessibility indicators were first examined; a clear, positive correlation between density and revenue was found for specialty stores wherein people do “comparison shopping,” and for stores that complemented each other for activities such as “one-trip shopping,” the revenues were positively correlated when the stores were clustered. Generally, daily-use stores’ revenues were more sensitive to local access and those of non-daily-use stores were more sensitive to global access. In conclusion, these findings would not have been found using conventional methodology focused on the retail sector as a whole, because aggregate market mechanisms would have hidden the observed effects on specific store categories. Therefore, upon disaggregating the data, we found a distinct heterogeneity across the different store types for what concerns the relationship between revenue and location.

Supplemental Nutrition Assistance Program (SNAP)-Authorized Grocery, Convenience, Dollar, and Restaurant or Delivery Service Settings Are Associated With Increased Obesity Prevalence in Virginia.

United States Department of Agriculture Supplemental Nutrition Assistance Program (SNAP) participants use SNAP-authorized stores for dietary purchases. Relationships between obesity prevalence and access to grocery and varied nontraditional (eg, dollar, drug, and convenience) SNAP settings are underexplored. This research aimed to determine the association of a full range of SNAP-authorized stores with obesity prevalence in Virginia. The SNAP Retailer Locator was used to cross-sectionally identify authorized stores, and county health ranking information was applied based on store location. Virginia, United States. The SNAP-authorized stores, classified among store categories: grocery or supermarket; drug; mass merchandiser; supercenter; convenience; dollar; club; other; nonfood store; farmers markets; and independent grocery stores. County-level obesity prevalence with income and rurality as potential confounders. Multiple linear regression was used to determine associations between county-level adult obesity prevalence and available SNAP-authorized store formats (P < .05 a priori). Store format was a predictor of obesity prevalence in Virginia in simple and adjusted models (R2 = 0.035, P < .0001 and R2 = 0.434, P < .0001, respectively). Grocery store or supermarket access was associated with obesity. The SNAP-authorized convenience, dollar, and nonfood stores were associated with a 0.3, 0.5, and 1.3 increase in county obesity prevalence, respectively (P < .05). Research, practice, and health policy approaches to improve grocery, convenience, dollar, and restaurant or delivery service settings may favorably influence community obesity prevalence in Virginia.