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Understanding and projecting the restaurantscape: Influence of neighborhood sociodemographic characteristics on restaurant location
Abstract and Figures
To better understand the location patterns of different types of restaurants across the United States, we investigate the relationship between neighborhood sociodemographic characteristics and restaurant location using a unique data set from 2013 covering 30,772 U.S. zip codes. The estimation results from negative binomial regression models confirm the significant impacts of various sociodemographic factors (e.g., population density, median age, median household income, average household size, educational attainment, gender distribution, housing tenure, neighborhood urbanization) on restaurant location. We also project future restaurant growth potential based on model estimates and projected changes in sociodemographic characteristics by 2020. The results are analyzed, and several metropolitan areas in Texas and Florida are identified as having high potential for growth. Lastly, implications are provided for restaurant real estate practitioners.
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... One of the critical factors to be considered in a location decision is the socio-demographic characteristics of the neighborhood. Yang et al. (2017) emphasized the sociodemographic factors as predictors of future business growth potential. These characteristics include income, size, household composition, work participation, urbanization level, and household manager's gender, age, race, and education level (Wang et al., 2015;Yang et al., 2017;Wu et al., 2021). ...
... Yang et al. (2017) emphasized the sociodemographic factors as predictors of future business growth potential. These characteristics include income, size, household composition, work participation, urbanization level, and household manager's gender, age, race, and education level (Wang et al., 2015;Yang et al., 2017;Wu et al., 2021). In particular, neighborhood socioeconomic status or class defines the purchasing power of the consumers, economic viability, and the probable success of a food establishment (Singleton et al., 2020). ...
... Various studies in the literature (e.g. Yang et al., 2017;Wu et al., 2021) have emphasized the importance of rent in the overall cost of operations of an establishment. Yacoub et al. (2022) highlighted that failure to consider the rent in the initial location planning of a food establishment can lead to failure and no return on their initial investment. ...
... However, studies specifically projecting future growth in the number of takeaways do not currently exist. One study attempted to forecast the number of restaurants in US zip code areas based on sociodemographic projections [13]. However, the applicability of this approach to forecasting takeaway growth is constrained by geographically limited data availability and the forecast range of future demographic trends. ...
... spatial relationships with other types of outlets) and socio-demographic variables (e.g. deprivation), which could enable more accurate forecasting [13]. This presents an area where future studies can contribute valuable insights. ...
Background
Neighbourhood exposure to takeaways can contribute negatively to diet and diet-related health outcomes. Urban planners within local authorities (LAs) in England can modify takeaway exposure through denying planning permission to new outlets in management zones around schools. LAs sometimes refer to these as takeaway “exclusion zones”. Understanding the long-term impacts of this intervention on the takeaway retail environment and health, an important policy question, requires methods to forecast future takeaway growth and subsequent population-level exposure to takeaways. In this paper we describe a novel two-stage method to achieve this.
Methods
We used historic data on locations of takeaways and a time-series auto-regressive integrated moving average (ARIMA) model, to forecast numbers of outlets within management zones to 2031, based on historical trends, in six LAs with different urban/rural characteristics across England. Forecast performance was evaluated based on root mean squared error (RMSE) and mean absolute scaled error (MASE) scores in time-series cross-validation. Using travel-to-work data from the 2011 UK census, we then translated these forecasts of the number of takeaways within management zones into population-level exposures across home, work and commuting domains.
Results
Our ARIMA models outperformed exponential smoothing equivalents according to RMSE and MASE. The model was able to forecast growth in the count of takeaways up to 2031 across all six LAs, with variable growth rates by RUC (min–max: 39.4-79.3%). Manchester (classified as a non-London urban with major conurbation LA) exhibited the highest forecast growth rate (79.3%, 95% CI 61.6, 96.9) and estimated population-level takeaway exposure within management zones, increasing by 65.5 outlets per capita to 148.2 (95% CI 133.6, 162.7) outlets. Overall, urban (vs. rural) LAs were forecast stronger growth and higher population exposures.
Conclusions
Our two-stage forecasting approach provides a novel way to estimate long-term future takeaway growth and population-level takeaway exposure. While Manchester exhibited the strongest growth, all six LAs were forecast marked growth that might be considered a risk to public health. Our methods can be used to model future growth in other types of retail outlets and in other areas.
... As key components of the urban retail sector, the spatial distribution and location choices of MTSs and COSs represent another crucial factor influencing visitation. Variations in transportation accessibility, population distribution, regional economic conditions, service environments, and competition from similar establishments contribute to spatial differences in the manifestation of UV [69,70]. Therefore this study synthesized built environment factors identified in previous research [71], while incorporating population characteristics, locational conditions, competition, and cost considerations based on retail layout principles [72,73]. ...
Urban vitality is a critical driver of sustainable urban development, significantly contributing to the enhancement of human well-being. A thorough and multidimensional comprehension of urban vitality is essential for shaping future urban planning and policy-making. This study, focused on Chengdu, proposes a framework for assessing various dimensions of UV through the distribution of milk tea and coffee shops. Using random forest and multi-scale geographically weighted regression models, this study investigates the factors influencing urban vitality from both mathematical thresholds and spatial heterogeneity, and develops spatial maps of future vitality to inform targeted urban strategies. The results show that (1) the milk tea index is effective in capturing population vitality, while the coffee index is more closely associated with economic vitality and urban renewal; (2) office buildings (13.46%) and commercial complexes (13.70%) have the most significant impact on both economic and population vitality, while the importance of transportation factors has notably decreased; (3) the influence of these factors demonstrates spatial heterogeneity and nonlinear relationships, with subway station density of 0.5–0.8 stations per kilometer being optimal for stimulating both types of vitality. The minimum threshold for economic vitality in a given unit is a housing price exceeding 6000 RMB/m2; (4) the future vitality map suggests that urban planners should pay greater attention to non-central districts with high development potential. Moreover, spontaneous social interactions and consumer behaviors stimulated by various shops are critical components of urban vitality. In designing the physical environment and urban spatial forms, special attention should be given to enhancing the attractiveness of physical spaces and their capacity to accommodate social interaction.
... Penelitian ini turut mengungkapkan karakteristik pola yang unik dalam distribusi rumah makan, khususnya di lokasi-lokasi pariwisata seperti Losari, Makassar, dan Galesong, Takalar. Temuan ini mencerminkan pentingnya faktor geografis dan sosioekonomi dalam menentukan lokasi restoran, sebagaimana dibuktikan dalam literatur terkait tentang ekonomi lokal dan pengembangan wilayah (Wu et al., 2021;Yang et al., 2017). Misalnya, keberadaan restoran-restoran di kawasan pesisir sering kali dipengaruhi oleh aksesibilitas terhadap bahan baku segar dari laut dan daya tarik turis terhadap pengalaman kuliner lokal (Chen et al., 2023). ...
Penelitian ini bertujuan untuk mengeksplorasi karakteristik dan makna pengalaman makan di rumah makan di kawasan pesisir Makassar, Takalar, dan Gowa, dengan fokus pada bagaimana konsumen memandang dan mengevaluasi pengalaman makan mereka. Penelitian ini menggunakan pendekatan fenomenologi, dengan memanfaatkan wawancara mendalam dan observasi langsung di rumah makan yang dipilih. Sebanyak 18 informan, yang mewakili latar belakang kelompok umur dan demografis yang beragam, diwawancarai untuk mengumpulkan data kualitatif. Data tersebut dianalisis menggunakan teknik analisis data kualitatif untuk mengidentifikasi tema dan pola dalam pemaknaan tempat oleh konsumen. Temuan utama mengungkapkan bahwa pengalaman makan di berbagai jenis rumah makan menawarkan karakteristik dan makna yang berbeda. Rumah makan Asia sering dianggap sebagai tempat untuk bersosialisasi, fungsional, dan nostalgia. Rumah makan Western dipandang sebagai tempat untuk bersosialisasi, pertemuan bisnis, simbolis, psiko-emosional, dan romantis. Sebaliknya, rumah makan lokal dipandang sebagai representasi identitas budaya, nostalgia, dan pilihan ekonomis. Kesimpulan utama dari penelitian ini adalah bahwa makna tempat oleh konsumen sangat dipengaruhi oleh jenis rumah makan dan konteks budaya lokal, yang dapat berkontribusi pada peningkatan pariwisata dan pengembangan ekonomi lokal.
The COVID-19 pandemic placed considerable stress on restaurants from restrictions placed on their operations, shifting consumer confidence, rapid expansion of remote work arrangements and aggressive uptake of third-party delivery services. Industry reports suggest that restaurants are experiencing a much higher rate of failure in comparison to other sectors of the economy. Restaurant survival was assessed in the Middlesex–London region of Ontario, Canada as of December 2020 using a novel dataset constructed from public health inspection permits, business listings and social media. Binomial logistic regression models were used to determine the association of operational, demographic and land use factors with restaurant survival during the pandemic. Operations-related factors were considerably more predictive of restaurant survival, though some demographic and land use factors suggest that urban processes continued to play a role in restaurant survival. Restaurants that offered in-house delivery and phone-based ordering methods were considerably less likely to close. Restaurants with a table-based service model, drive-through or an alcohol licence were also less likely to close. Restaurants proximal to a concentration of entertainment land uses were more likely to be closed in December 2020. Closed restaurants were not spatially clustered as compared to open restaurants. The pandemic appears to have disrupted established theoretical relationships between people, place, and restaurant success.
This paper examines purchase intentions and brand loyalty with five dimensions of Quick Service Restaurant. The objectives of the study are to investigate the associations between consumers' perceptions of Quick Service Restaurant and brand loyalty, and whether purchase intentions mediate these relationships. The measures used for the constructs were adapted from past studies and our hypotheses were tested using online survey data. This research was conducted from the perspective of Generation Y consumers in Singapore and we used McDonald's, the market leader in the Singapore fast food industry, as the context for this study. The findings provided support for all the hypotheses, namely, that consumers' perceptions of location, product menu, food quality, service crew and collectibles were positively related to purchase intentions. Moreover, the results indicate that the purchase intention variable played a mediating role in the relationship between location, product menu, food quality and brand loyalty. The findings have some useful managerial implications for the foodservice industry.
Although location is a significant factor in a restaurant’s survival chances, contrary to the commonly held belief, the presence of nearby homes did not help in lowering failure rates between 2000 and 2010 for restaurants in Boulder, Colorado. Instead, having a substantial population of apartment dwellers and transient residents (notably, university students) enhanced the restaurants’ success, as did the presence of people aged eighteen to twenty-four, those with higher educational levels, non-household families, and low- to middle-income families. Larger restaurants and those with chain affiliation had a greater probability of success than small, quick-service operations. Among the factors that had little effect on restaurant success or failure were unemployment rates, the nature of nearby residents’ profession, and the geographical presence of families with children under eighteen. The study’s results also support the long-held industry perception regarding avoiding locations where restaurants have already failed. When a location had experienced three ownership turnovers, the study found that the location generally ceased to host restaurants as tenants. As explained further in this article, this is the fourth in a series of examinations of the elements of restaurant success and failure.
The aim of the present research was to investigate the factors affecting customer loyalty in the restaurant industry. Data was collected using questionnaire distributed in 10 randomly selected branches of Boof Chain Restaurant in Tehran. In each branch, 40 customers were selected for the study. Ultimately, the research sample consisted of 268 customers. Structured equation modeling was used for data analysis and hypothesis testing. The obtained results show that food quality, service quality, restaurant environment, and perception of price fairness had a positive impact on customer satisfaction, but the impact of restaurant location on customer satisfaction was not confirmed. Also, food quality, service quality, and perception of price fairness had a positive effect on customer trust. The results show that food quality is the most important factor affecting customer satisfaction and trust in Boof Chain Restaurants. Customer satisfaction had a positive impact on customer loyalty, but the effect of customer trust on customer loyalty was not confirmed.
Mr. Chen has reported that he has no relationships relevant to the contents of this paper to disclose. Dr. Patel has received research grant support from AstraZeneca, Bayer, Janssen, Heartflow, and the National Heart, Lung, and Blood Institute; and has served on the advisory board for Janssen, Bayer, CSI, and AstraZeneca.
The combination of demographic and geographic information can be applied to identifying locations for restaurant units. By analyzing restaurant-density patterns, an operator can determine the number and types of restaurants in a market area. Next, the operator can acquire computerized street-level maps showing business generators and traffic patterns for existing restaurants. Finally, the operator can identify potential locations for new restaurants. As an example, the analysis of a neighborhood in Boston shows a location that would likely support a new casual-theme restaurant.
The undue importance that professors give to their choice of work location while searching for an academic position is discussed. It is suggested that a perfect job in an imperfect location is better than the reverse. The process of searching for the right job requires flexibility as things do not always go the expected way. The importance of taking advice and support from friends, family, and colleagues is highlighted.
Location selection plays a crucial role in the retail and service industries. A comprehensive location selection model and appropriate analytical technique can improve the quality of location decisions, attracting more customers and substantially impacting market share and profitability. This study developed a data mining framework based on rough set theory (RST) to support location selection decisions. The proposed framework consists of four stages: (1) problem definition and data collection; (2) RST analysis; (3) rule validation; and (4) knowledge extraction and usage. An empirical study focused on a restaurant chain to demonstrate the validity of the proposed approach. Twenty location variables relevant to five location aspects were examined, and the results indicated that latent knowledge can be identified to support location selection decisions.
This paper investigates household expenditures on food away from home by type of facility. A system of expenditures at full-service
restaurants, fast-food restaurants and other facilities are estimated with a multivariate sample selection procedure, for
three types of households by household composition. Statistical significance of error correlations suggests endogeneity of
sample selectivity and justifies estimation of the equations in a system to improve statistical efficiency. Differentiated
effects of economic and demographic factors are found on expenditures at different facilities and across household types.
Findings on the roles of economic and socio-demographic factors can inform marketing strategies and policy deliberations.
This paper explores the role of restaurants, as consumption spaces, in defining the consumptional identity of 243 American cities. Specifically, it is asked whether, and how, US cities can be classified on the basis of the local prevalence of specific types of restaurants—are some cities culinary deserts, while others are gastronomic oases? A two-stage cluster analysis reveals four distinct city types, which fall along two intersecting dimensions: a quantitative dimension of restaurant availability and a qualitative cultural dimension. These four city types are characterised and connected to the existing literature on consumption spaces, with particular attention to a strong parallel between these city types and the communities discussed by Richard Florida. Several directions for future research using the city classification as a conceptual framework are offered. Additionally, these analyses involve the development and application of a new method of measuring a city's number of consumption spaces, which is theoretically superior to traditional per capita measures and which is described in a methodological appendix.