The role of location in residential location choice models: a review of literature

Abstract

Geospatial data available to researchers has increased tremendously over the last several decades, opening up opportunities to define residential location in multiple ways. is has led to a myriad of variables to define "location" in residential location choice models. In this paper, we propose a common classification for location variables and categorize findings from a wide range of studies. We find similar preferences but different measurement methods and market segments for locations across different study regions. Recent studies consider the residential unit as choice alternative, making it possible to include a detailed description of the built environment. However, these studies are still limited in number and the inclusion of socioeconomic environment is more common. Transport land-use models can benefit from the inclusion of points of interest, such as schools, network distances, and the distance to previous locations. For the results of location choice models to be transferable to different disciplines, and avoid multi-collinearity, it is necessary to present different model specifications, including variables of interest in different disciplines.

A multiscale classification of urban morphology

“…e representation of the urban environment using independent variables in location choice models has mainly been simplified to the socioeconomic distributions available in census data (Schirmer et al 2014). Reasons for this included the unavailability of spatial data, limited computational power, or limited geoprocessing capabilities in these research fields.…”

Microsimulation of Residential Activity for Alternative Urban Development Scenarios: A Case Study on Brussels and Flemish Brabant

“…This map constitutes one of the key inputs in the scenario definition. To address the socio-economic realities faced by households relating to housing costs and social housing [63][64][65], use was made of data provided by Statistics Belgium, the Brussels Institute for Statistics and Analysis and the Flemish Society for Social Housing. To define urban development scenarios in a spatially explicit fashion, a spatial analysis of zoning, parcel and building data proved essential to quantify feasable evolutions of housing stock distributions.…”

“…The 12 location features used to construct utility models are displayed in Table 3. Similar location features are often used in residential location choice research [63][64][65]. Location features were defined on a statistical ward level, with the exception of % social housing and average house selling price, which were defined on a municipality level due to the lack of spatially more detailed data.…”

Sector-Wise Exploratory Analysis of Household Residential Location Choice in the African Context: Empirical Evidence from Benin City, Nigeria

“…It impacts employment, economic advancement, social structure, spatial segregation and the transport system (Schirmer et al, 2014 use-transport modeling systems, as they predict the dynamics in the urban environment and help to determine how the urban landscape is shaped over time.…”