Business Location Choices Research Articles

A Two-Layer Location Choice Model Reveals What’s New in the “New Retail”

The New Retail is an emerging e-commerce model in recent years. It claims innovation in creating competitive advantages through intensive Internet-based data to promote online-to-offline interactions. Whether this self-claimed innovation would cause a different rationale in the choice of store locations is a subject worthy of investigation. In this article, taking Beijing’s Starbucks and Luckin coffee stores as cases, we build a two-layer business location choice model to examine the problem. The model consists of a macroscale (city-wide) submodel and a microscale (street block) submodel. Results show that the macroscale store location choice logics for the two are consistent, with differences predicted by economic geographical laws, thus rejecting the hypothesis of the big-data-driven location choice advantage for the New Retail. Results from the microscale model, however, suggest that the difference between the two brands is better explained with cognition and behavioral theories, where the delivery agents, rather than the customers’ environmental cognition characteristics, shape the New Retail’s peculiar store location preference over less “fancy” urban locales. We argue this unique location preference is indeed something new in the New Retail. We conclude the article with discussions on the relevance of the cognitive and behavioral perspectives in the business location choice problem, and suggest incorporating the microscale layer that explicitly considers these aspects in addressing the problem in real-world settings.

Place niche and its regional variability: Measuring spatial context patterns for points of interest with representation learning

In the built environment, places such as retail outlets and public sites are embedded in the spatial context formed by neighboring places. We define the sets of these symbiotic places in the proximity of a focal place as the place's “place niche”, which conceptually represents the features of the local environment. While current literature has focused on pairwise spatial colocation patterns, we represent the niche as an integrated feature for each type of place, and quantify the niches' variation across cities. Here, with point of interest (POI) data as an approximation of places in cities, we propose representation learning models to explore place niche patterns. The models generate two main outputs: first, distributed representations for place niche by POI category (e.g. Restaurant, Museum, Park) in a latent vector space, where close vectors represent similar niches; and second, conditional probabilities of POI appearance of each place type in the proximity of a focal POI. With a case study using Yelp data in four U.S. cities, we reveal spatial context patterns and find that some POI categories have more unique surroundings than others. We also demonstrate that niche patterns are strong indicators of the function of POI categories in Phoenix and Las Vegas, but not in Pittsburgh and Cleveland. Moreover, we find that niche patterns of more commercialized categories tend to have less regional variation than others, and the city-level niche-pattern changes for POI categories are generally similar only between certain city pairs. By exploring patterns for place niche, we not only produce geographical knowledge for business location choice and urban policymaking, but also demonstrate the potential and limitations of using spatial context patterns for GIScience tasks such as information retrieval and place recommendation.

Does rural entrepreneurship pay?

This paper investigates entrepreneurship and location choices among college-educated individuals in the USA and the role of location-specific human capital in these choices. We model the location and entrepreneurship decisions jointly, demonstrating that individuals who choose a rural residence are more likely to become entrepreneurs when compared to their urban peers. We then explore whether, all else equal, the entrepreneurship choice of rural alumni lowers earnings, consistent with the story of business location choice being motivated by the entrepreneurs’ preference for a rural lifestyle, whether there is evidence that the location choice is productive, or whether rural residents are pushed to start a business due to thin labor markets. After controlling for selection, rural entrepreneurs earn significantly more than rural workers but still less than urban entrepreneurs, lending support to the notion that rural entrepreneurs’ location choices are productive and rural entrepreneurs have stronger location preference. An Oaxaca decomposition of the earnings gap across subsamples reveals the returns to entrepreneurial skills are much lower in rural areas; however, the earnings gap between rural and urban entrepreneurs is at least partially offset by positive self-selection into a rural area. This finding lends support to “grow your own” business development strategies for rural regions.

Behavioural location theory – evolution, tools and future

The behavioural location theory emphasises high importance of the limited rationality and the subjective perception of space in selecting of the location for a business activity. The article discusses key competencies from the scope of behavioural location theory. Ac-cording to the Authors, the behavioural location theory is rather complementary than competitive in relation to the neoclassical or modern approach, as it allows to explain the deviations of the decision-makers from the optimisation behaviour.

Factors affecting post-disaster location choices of businesses: an analysis of the 1999 earthquake

ABSTRACTDespite global policies advocating risk reduction and community level recovery, post-disaster implementations usually focus on households, but fail to focus on businesses in spatial terms. Due to the lack of appropriate policy and tools, businesses often make their own location choices as part of their recovery strategy. In view of this, this study aims to establish the factors affecting the location choices of businesses challenged by disasters in the absence of any specific spatial strategies designed for them. In order to determine these factors, empirical research was conducted in Adapazari, Turkey on 232 firms selected as a result of a stratified random sampling procedure. According to the analysis of the results, the most notable impacts on business location choices after a disaster shock are associated with occupancy status, education level, and extent of damage. In line with these findings, the impacts of business location choices are discussed to highlight the role of businesses in spatial decisions.

Discrete choice with spatial correlation: A spatial autoregressive binary probit model with endogenous weight matrix (SARBP-EWM)

Discrete choice modeling is widely applied in transportation studies. However, the need to consider correlation between observations creates a challenge. In spatial econometrics, a spatial lag term with a pre-defined weight matrix is often used to capture such a correlation. In most previous studies, the weight matrix is assumed to be exogenous. However, this assumption is invalid in many cases, leading to biased and inconsistent parameter estimates. Although some attempts have been made to address the endogenous weight matrix issue, none has focused on discrete choice modeling. This paper fills an existing gap by developing a Spatial Autoregressive Binary Probit Model with Endogenous Weight Matrix (SARBP-EWM). The SARBP-EWM model explicitly considers the endogeneity by using two equations whose error terms are correlated. Markov Chain Monte Carlo (MCMC) method is used to estimate the model. Model validation with simulated data shows that the model parameters can converge to their true values and the endogenous weight matrix can be reliably recovered. The model is then applied to a simplified firm relocation choice problem, assuming that similar size firms influence one another. The model quantifies the peer effect, and takes into consideration other independent variables including industry type and population density. The estimation results suggest that peer influence among firms indeed affect their relocation choices. The application results offer important insights into business location choice and can inform future policy making. The sample size for applying the model is currently limited to hundreds of observations. This paper contributes to the existing literature on discrete choice modeling and spatial econometrics. It provides a new tool to discover spatial correlations that are hidden in a wide range of transportation issues, such as land development, location choice, and various travel behavior. Those hidden spatial correlations are otherwise difficult to identify and estimation results may be biased. Establishing a new model that explicitly considers endogenous weight matrix and applying the model to a real life transportation issue represent a significant contribution to the body of literature.

Are state\u2013local government expenditures converging? New evidence based on sequential unit root tests

Large and persistent gaps in subnational public expenditure have important implications regarding growth, equity, and migration. In this context, we revisit the question of expenditure convergence across the American states to provide more nuanced evidence than found by a small number of previous studies. We employ a methodology due to Smeekes (Bootstrap sequential tests to determine the stationary units in a panel, 2011) that sequentially tests for unit roots in pairwise (real per capita) expenditure gaps based on user specified fractions. In a panel of 48 combined state–local government units (1957–2008), we found that expenditures on highways, sanitation, utility, and education were far more convergent than expenditures on health and hospitals, police and fire protection, and public welfare. There was little evidence of “club convergence” based on the proportion of intraregional convergent pairs. Several historically high-grant receiving states showed relatively strong evidence of convergence. Our results bode well for future output convergence and opportunities for Tiebout-type migration across jurisdictions. They also imply a diminished role for public infrastructure and education spending in business location choices over time and a mixed role for federal grants in inducing convergence.

Welfare Measures to Reflect Home Location Options When Transportation Systems are Modified

Transportation system improvements do not provide simply travel time savings, for a fixed trip table; they affect trip destinations, modes, times of day, and, ultimately, home and business location choices. This paper examines the welfare (or willingness-to-pay) impacts of system changes by bringing residential location choice into a three-layer nested logit model to more holistically anticipate the regional welfare impacts of various system shifts using logsum differences (which quantify changes in consumer surplus). Here, home value is a function of home price, size, and accessibility; and accessibility is a function of travel times and costs, vis-à-vis all mode and destination options. The model is applied to a sample of 60 Austin, Texas, zones to estimate home buyers’ welfare impacts across various scenarios, with different transit fares, automobile operating costs, travel times, and home prices. Results suggest that new locators’ choice probabilities for rural and suburban zones are more sensitive to changing regional access, while urban and central business zone choice probabilities are more impacted by home price shifts. Automobile costs play a more important role in residential location choices in these simulations than those of transit, as expected in a typical U.S. setting (where automobile travel dominates). When generalized costs of automobile travel are simulated to rise 20%, 40%, and 60% (throughout the region), estimated welfare impacts (using normalized differences in logit logsum measures) for the typical new home buying household (with $70,000 in annual income and 2.4 household members) are estimated to be quite negative, at -$56,000, -$99,000, and -$132,000, respectively. In contrast, when auto’s generalized costs fall everywhere (by 20%, 40%, and then 60%), welfare impacts are very positive (+$74,000, $172,500, and $320,000, respectively). Such findings are meaningful for policymakers, planners, and others when anticipating the economic impacts of evolving transportation systems, in the face of new investments, rising travel demands, distance-based tolls, self-driving vehicles, and other changes.

The effect of urban quality improvements on economic activity

This paper is concerned with the link between urban quality improvements and economic activity. A key question is whether improvements in the urban environment which might be achieved, for instance, through pedestrianisation, will affect business location choices - for example, are office or retail businesses particularly keen to locate in more pleasant urban places? The paper outlines the current state of development of the literature with respect to the influence of urban quality on economic activity, and proposes a framework for forecasting economic impacts based on three communities of reference: customers, employees, and the businesses themselves. The results from original modelling of a case study area in Manchester, England are reported and suggest that the positive uplifts that may be expected from environmental improvement programmes may well be on a scale which is significant. The research is obviously important for the urban regeneration and renaissance agendas which posit attractive and well-designed environments as a way to create the right conditions for promoting economic growth.

Business Environment, Clustering, and Industry Location: Evidence from Indian Cities

How do differences in the local business environment influence location of industry within countries? How do the benefits of a good business environment compare with those from good market access and agglomeration economies from industry clustering? The authors examine these questions by analyzing location decisions of individual firms. Using data from a recently completed survey of manufacturing firms in India, they find that both the local business environment and agglomeration economies significantly influence business location choices across cities. In particular, excessive regulation of labor and of other industrial activities reduces the probability of a business locating in a city. The authors'findings imply that in order to attract industrial activity, smaller or remoter cities need to offer even more attractive policy concessions or reforms to offset the effects of their relatively adverse (economic) geography. Their methodology pays special attention to the identification of agglomeration economies in the presence of unobserved sources of natural advantage.

Empirical Examination of Relationship Between Firm Location and Transportation Facilities

The locations and profiles of firms in the six-county Chicago, Illinois, region were used to compare the businesses’ proximities to freeway ramps and transit stations for two time periods: 1981 and 1999. A series of regression models was constructed to assess whether the location patterns with respect to transportation facilities have changed over the last two decades. The data suggest that, controlling for exogenous factors, businesses have moved closer to freeway ramps in the last two decades. Meanwhile, the distance to transit stations has not changed except in the city of Chicago, where it has decreased. These findings suggest shifts in location choice behaviors in the urban core and the suburbs. Specifically, firms in the urban core areas are valuing access to rail stations to a greater degree, whereas those in the suburbs are placing more importance on proximity to freeway ramps. The concentration of businesses near expressway ramps in the inner and middle suburbs suggests the emergence of a pattern in those areas that corresponds to a polycentric development, with freeway ramps as the focal points. Finally, the findings indicate a shift, not a decrease, in the importance of transportation access for business location choice.

Firm Location in the MEPLAN Model of Sacramento

MEPLAN land use and transportation-interaction models traditionally include models of business-location choice. The mechanisms in the model that allow for realistic aggregate assignment of firms to zones, and the resulting impact that firm location has on the entire modeling system, are described. The models use a form of logit function to allocate production activities to zones. Interdependencies in the Social Accounting Matrix, together with trip- and land-cost data and usage rates, generate a utility function for the attractiveness of purchasing a given sector’s output from a given zone. The alternative specific constants and the dispersion parameter are estimated in calibration, based primarily on cost data, trip-length distributions, and arrangement of activity in a calibration year. Results from a model of Sacramento show the various features and strengths of the model, while pointing out some weaknesses and potential pitfalls. The strengths include the realistic representation of current and continuing patterns, the close linkages between different industry and household types, and the market-based nature of the model. The weaknesses include the aggregate nature of the model and the possibility of difficulties in establishing realistic, alternative, specific constants.

Mesurer l'influence de la fiscalité sur la localisation des entreprises

Measuring the Influence of Taxation on Business Location Choices by Michel Houdebine and Jean-Luc Schneider The paper attempts to model business location choices and the choice of tax rates by local authorities. Methods for estimating the sensitivity of business location choices to taxation are derived and then applied to the 36,000 local business tax rates observed in French communes and the actual location of businesses. The various estimators of sensitivity to taxation derived all provide the same relatively small order of magnitude. The results may be used to assess the cost effectiveness of local tax incentives.