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The purpose of this research is to explore from a mass appraisal perspective how the effects of location are reflected within valuation models. The paper sets out to detail the various techniques and the efficacy of their application.

The approach adopted is analytical and based upon the development of locational attributes. An extensive literature base is synthesized with methods being evaluated in their application to mass appraisal.

This research has identified that the three main groups interested in residential property valuation, namely, academia, industry and commerce have to a certain extent been unfamiliar with the research developments occurring in the other groups. The impact of this is important, given the need for integration and collaboration in terms of future model development.

The research underpinning this paper will provide a solid basis for further research into this area. The importance of measuring the effect that location has on value is of major significance in the determination of objective estimates of property value.

Those within the assessment community could be described as pragmatists working in a situation that requires feasible and suitable solutions to the problem of measuring location value. It is our contention that the third generation techniques of spatially varying parameter models and spatial autocorrelation models will require greater industry verification before their use becomes more widely accepted.

This paper provides a detailed analysis of methodologies used to reflect the value of location over the last 50 years. The debate is taken forward by describing what will be the contribution to the development of the next generation of location‐specific modeling techniques.

The purpose of this paper is to test the popular perception that the storefront location choices of premium brands are positively related to adjacent rents. Focusing on the case of Starbucks, a popular international coffee chain, the authors examine the association between Starbucks locations and rents in Manhattan, New York.

The authors use a multi-year data set for average rent per square foot for office and multifamily residential properties within 1/10th of a mile of several hundred coffee shop locations in Manhattan, controlling for vacancy, job density, overall amenity density (WalkScore), coffee shop density, transit accessibility, neighborhood and the Starbucks brand. The authors take two different methodological approaches to isolate potential statistical evidence for an association between Starbucks locations and adjacent rents: the authors run a pooled-cross-sectional model and apply propensity-score matching.

The authors find a statistically significant positive relationship between the presence of Starbucks and average office rents when applying the authors’ pooled-cross-sectional model and applying propensity-score matching. This finding is consistent with several potential causal hypotheses: Starbucks may be attributed to higher rent office locations; the “Starbucks effect” may cause higher rents in adjacent locations; or there may be a mutual reinforcing of positive feedback between Starbucks locations and office rents. The authors find no strong association between Starbucks and residential rents (one model indicates an effect of 2.3 percent on residential rent at 10 percent level of significance), which challenges the direct linearity of the consumption theory of gentrification popularly called the “Starbucks effect.”

In the literature, the existence, causality and directionality of a relationship between Starbucks locations and neighborhood change have been largely unstudied. In this paper, the authors test the hypothesis that there is a positive correlation between Starbucks locations and rents.

The purpose of this study is to examine the key factors that influence the housing preferences of young civil servants in Malaysia.

A self-administered questionnaire was distributed to 400 respondents who fulfilled the eligibility criteria of civil servant working in Malaysia aged between 20 and 40 years, and currently renting a house, or staying with friends, immediate family or relatives. Data were analysed via exploratory factor analysis and Pearson correlation.

The results reveal that financial capability is the factor that most strongly influences the housing preferences of young civil servants, followed by neighbourhood and location. Young civil servants are highly inclined to consider the monthly repayment amount as the most important issue when deciding to buy a house. Furthermore, they prefer to buy a house in a neighbourhood that ensures high security and protection against crime.

Housing developers should develop affordable housing in suitable neighbourhoods and locations to match homebuyers’ preferences to avoid a mismatch between housing demand and supply, which is obviously one of the greater risks of unsold homes.

Given the lack of focus on this precise research sample (i.e. young civil servants), the study is justified in terms of its originality, as it examines a specific cohort by focussing on the correlations of location, financial capability and neighbourhood with housing preferences of young civil servants in Malaysia. These insights are invaluable, as this group has not been the specific focus of research.

While the declining rate of urban security and its potential effects have been globally acknowledged, the ways urban neighborhood security shapes real estate markets in African cities remain largely unexplained. The purpose of this paper therefore is to present the findings from a study of the nexus between urban neighborhood security and home rental prices in Lagos, Nigeria.

This paper is based on the hedonic price theory, an objectively derived urban neighborhood security index (UNSI) and property rental price data in Ojo, Lagos, Nigeria. This is a quantitative cross-sectional study that employs multistage sampling survey procedure. Data are analyzed using descriptive statistics, nonparametric correlation and hedonic price function with ordinary least squares (OLS).

Results show that nearly 50% of the study area is prone to insecurity and average rental values in Ojo, Lagos range from N151329.41 ($302.66) to N167333.33 ($334.67) per annum. Correlation analysis shows that home rental prices have high, positive and significant correlations (rs = 0.725 and p < 0) with UNSI. After controlling for neighborhood and structural factors, it is found that urban neighborhood security positively influences home rental values as a unit improvement in security leads to N81000.00 ($162.00) increase in rental value per annum.

Urban neighborhood security risk threatens residential property values, creates unintended residential mobility and destabilizes families. Findings from this study point to the facts that security is a key component of urban housing values and developers, and real estate investors must ensure that this component is well factored into property design, construction and valuation.

This is perhaps the first study that uses an objectively derived UNSI to study home rental price dynamics in Nigeria. The study extends knowledge on urban housing price determinants and contributes to literature on the crucial place of security in property management.

This paper aims to compare the accepted techniques of location analysis in the food sector with the realities of “real world” forecasting in convenience store (c‐store) retailing. To offer a conceptual framework for c‐store operators intending to become more strategic in their small store location planning but currently lacking established expertise or extensive research budgets.

Outlines potential best practice based on industry experience, and contact and discussion with location analysts and retail consultants, as well as a wide ranging examination of the academic literature in this area.

Finds that the traditional techniques of market analysis for large‐scale food stores will become largely redundant; that neighbourhood retailers are likely to manage their location decision‐making by incremental steps; that the requirements of convenience store forecasting inevitably read to a “back to basics” approach to market analysis; that the use of site visits in combination with more quantitative techniques will provide the most effective solutions; and that reconciling human institutions and their environment is key to effective site research decision‐making.

Academic conceptualisations of location planning in the convenience store sector are largely absent from the literature. This paper adopts a practical perspective.

The purpose of the present study is to explore the factors that influence the residential location choice of households in the Indian context.

Two sub-urban towns of Kolkata, i.e. Biddhanagar Municipal Corporation and Rajarhat Newtown, are taken as case studies. In total, 34 variables are considered related to the household's socioeconomic background (10), dwelling (3), travel (2) and level of importance of neighborhood characteristics (19). A revealed preference household survey is conducted, which resulted in the collection of 390 samples. Firstly, 19 level of importance variables are deduced to 3 latent factors using exploratory and confirmatory factor analysis. After that, a utility function is estimated using a multinomial logit regression to identify significant factors.

The results indicate the significance of car ownership, work travel time, work mode, monthly income, proximity to work, proximity to family/relative/friends, proximity to quality schools, quality of physical infrastructure such as water availability, power availability and housing typology among others in the residential location choice of households.

Kolkata, a major metropolitan area in eastern India, has been experiencing space constraints to cater to the housing demand of the ever-increasing population. Although satellite towns are being developed, the infrastructure landscape in such towns is uneven, resulting in more housing demand in one area than another. The study furnishes significant findings to develop more informed policies to attract households in low-demand areas and manage high-demand areas to achieve sustainable planning.

Considering the importance of geographical context, it is the first study on residential location choice, providing a perspective of household behavior from eastern India. It also shows the importance of physical infrastructure attributes in residential location choice for developing countries, which is seldom employed in the current practice. Moreover, previous studies (although few) done in India consider the objective value of location characteristics. The present study focuses on subjective value or the level of importance perceived by respondents.

The purpose of this study is to enhance the estimation of vertical and horizontal inequity within property valuation. Property taxation is a crucial source of finance for local government around the world – based on a presumptive tax base underpinned by estimates of property value, inaccurate real estate valuations used for such ad valorem or value-based property tax calculations potentially lead to a variety of costs, both financial and other, for tax payers and governments alike. More common are increased costs in time, staff and, in some cases, legal fees. Some governments are even bound by acceptability thresholds to promote fairness, equitability and overall government accountability with respect to valuation.

There exist a number of vertical inequity measurements that have undergone academic testing and scrutiny within the property tax industry since the 1970s. While these approaches have proved successful in detecting horizontal and vertical inequity, one recurring disadvantage pertains to measurement error/omitted variable bias, stemming largely from a failure to accurately account for location. A natural progression within property tax research is the application of a more spatially local weighted modelling approach to examine vertical and horizontal inequity. This research, therefore, specifies a geographically weighted regression (GWR) methodology to detect and measure vertical inequity in property valuations.

The findings show the efficacy of using more applied spatial approaches for vertical tax estimation and indeed the limitations of employing conditional mean estimates coupled with delineated boundaries for assessing property tax inequity. The GWR model findings highlight the more fluctuating nature of vertical inequity across the Belfast market for the apartment sector both in a progressive and regressive sense and at different magnitudes. Moreover, the results reveal spatial clustering in the effects and are indicative of systematic inequities related to location inferring that spatial (horizontal) tax inequities are not random. The findings further show increased GWR model predictability overall.

This research adds to the existing literature base for evaluating both vertical and horizontal inequity in value-based property taxation at the intra-neighbourhood level. This is accomplished by modifying the Birch–Sunderman approach by transforming the traditional OLS model architecture to a GWR model, thereby allowing coefficient estimates of inequity to vary not only across a jurisdiction, but also at a more local level, while incorporating property characteristic variables. This arguably allows assessors to identify specific geographical areas of concern, saving them money, time and resources on identifying, addressing and correcting for inequity.

This study aims to adapt analytical hierarchy process (AHP) for choosing the optimal location for sport facilities. The location of a sports facility contributes significantly to its potential success or failure. Therefore, factors affecting such location-related decisions must be carefully studied and prioritized in a systematic fashion.

This study develops a seven-step framework which may be used to decide on a location from among several alternatives. Through an extensive literature review, this study first determines the factors affecting sports facility location selection and then applies AHP steps by asking several sports facility owners and managers to assess importance of the criteria.

This study determined the sport facility location selection factors as “ease of access,” “facility features,” “financial issues,” “neighborhood” and “market,” and further divided each factor into its subfactors. To illustrate the framework of using AHP as a tool to select the right location for sport facilities, we chose three candidate locations and scored them according to the calculated weight scores of the criteria, identifying the strengths and weaknesses of each location.

This study provides several managerial implications that may guide sport facility investors in choosing the right location.

This study presents a method to evaluate different factors for different actors of sport industry in a systematic way. Private investors can use the method for securing sufficient number of potential customers in a well-selected location. Government institutions and public policymakers can use the method, possibly with different sets of factors, to decide on the location of public sports facilities to maximize the number of visitors or to reach disadvantaged or underserved populations.

This framework of AHP method can help private and public investors and policymakers evaluate and make the optimal decision for choosing sports facility locations. This study contributes both to sport management theory and practice as well as to operation management literature. This study also refined the scattered factors in the literature of selecting a sport facility site in a more understandable and adaptable way.

The aim of this paper is to attempt to measure the effect of location on residential house prices and to endeavour to integrate spatial and aspatial data in terms of developing a hybrid predictive model. The research methodology investigates the traditional hedonic approach to modelling location using multiple regression techniques. Alternative approaches are considered which specifically model the spatial distribution of house prices with the objective of developing location adjustment factors. These approaches are based on the development of surface response techniques such as inverse distance weighting and universal kriging. The results generated from the surfaces created are then calibrated within MRA.

There is a general consensus that residential submarkets exist, but the basis upon which these are specified remains the subject of debate. The purpose of this paper is to model data on different residential locations in Ghana to show how the submarkets have performed over the past 16 years.

The paper employs hedonic modelling based on 3,250 sale transactions and 1,130 rental transactions from 1992 to 2007.

The results demonstrate that five residential real estate characteristics – location, detached, landscaping quality, gross internal areas and plot size – predominate in the explanation of both rental and transactions prices across all submarkets. They also highlight points of variation between the submarkets. An understanding of the impact of these features on residential price and rent is important for capital and rental valuation.

This paper analyses historic performance of the residential market, both at the aggregate and disaggregate level to place the housing market in an investment context.