Residential Location Choice Research Articles

Do people live in urban neighbourhoods because they do not like to travel? Analysing an alternative residential self-selection hypothesis

Previous research has indicated that mode-specific attitudes can affect travel mode choice through the residential location choice. According to the principle of residential self-selection, people will try to choose a residential neighbourhood that enables them to travel with as high a share as possible of their amount of travel with their preferred mode. In this study, however, we will analyse whether differences in travel distance, travel time and travel satisfaction in urban versus suburban neighbourhoods are due to travel-liking attitudes, the residential location or a combination of both. Results of this study − analysing leisure trips within the city of Ghent (Belgium) − indicate that suburban respondents are, compared to urban respondents, more satisfied with their trips, which are also longer in time and distance. Suburban respondents also have a more positive stance towards travelling, suggesting a possible residential self-selection process. Travel lovers might prefer a residential neighbourhood where travel distances and travel time are relatively high, while people who do not like to travel might prefer to live in a neighbourhood that enables more short-distance and less travel-time intensive trips. This study suggests that especially people who do not like to travel self-select themselves in urban neighbourhoods in order to limit travel distance and travel time. In contrast, respondents with a more positive stance towards travelling are equally distributed in urban and suburban neighbourhoods. Results also indicate that travel distance and travel time are mainly affected by respondents’ residential neighbourhood, while travel satisfaction is mainly affected by travel-liking attitudes.

NaWo - a Tool for More Sustainable Residential Location Choice

Urban sprawl is a major problem in many metropolitan areas. Especially in cities with high housing prices people are looking for residential locations in suburban or remote areas where residential costs are lower. Still, these decisions are often made without being fully aware of the consequences on mobility patterns and transport costs. Furthermore, residential location shapes social, economic and environmental issues and thereby the sustainability of human life.To foster sustainable residential location choice a decision-making aid which is focused on the effects of residential location on daily mobility has been developed as part of the project “Sustainable choice of residential locations” and made available in the greater Munich area as well as the Austrian province of Tyrol. Using this web-based calculator (“NaWo”), property seekers are given an initial insight into the distances to be covered at the desired location considering their personal mobility behavior. With this awareness-raising measure, it is possible to take the sustainability aspect into greater consideration in residential location choice with regard to the costs, impact on the environment and the opportunities for social inclusion.

Results of a New Approach in Making Survey on P.T. – New Bus Rapid Transit Service in Nantes

It has been 30 years since Greater Nantes reprioritized its transport policies based on a radial public transport network and constructed a Tramway. Today, Greater Nantes is developing a new BRT system, called ‘Chronobus’. Chronobus enables Nantes’ public transport network to function across a new mesh network with a controlled investment (70 M€). Until now, household travel and operator surveys have not provided comprehensive information about the public's local transport needs and perceptions. With this in mind, Greater Nantes conducted a large-scale innovative survey in 2014 to determine how users make their travel choices considering a wide range of social factors. The survey was targeted at small geographic areas to determine the effectiveness for residents on a fine scale. The objectives of this article are: (1) to describe the innovative survey carried out within Greater Nantes and to outline the diversity of the results; (2) to outline the potential use for local authorities to conduct similar surveys in order to better understand the dynamics of urban mobility in their jurisdictions. The survey includes both quantitative (around 8,000 answers) and qualitative features (30 semi-structured interviews; two focus groups) and are aimed at both Chronobus users and non-users. This article emphasizes four main topics: the willingness to walk to a Chronobus service (rather than to a classic bus service); the consideration of Chronobus and other transport criteria in choice of residential dwelling location; the use of Chronobus as a tool for urban renewal and for opening up isolated and disadvantaged areas; and the perception of Chronobus users and non-users of its impacts on the other transport modes and local life. This innovative study is not only an evaluation tool, but a social barometer that provides useful information to local authorities to supplement other current household and operator surveys. The article shows that similar surveys can be seen as a useful tool for opening up dialogue with local populations on mobility topics.

Choice Set Imputation in Atomistic Spatial Choice Models

Constructing the universal choice set in spatial choice models developed at the level of elemental alternatives (atomistic models) is challenging because disaggregate data on the attributes of nonchosen alternatives are often not available. Even when the disaggregate data on nonchosen alternatives are available, matching two data sources will inevitably be error prone given that they might be collected at different times and they might have different coding for categorical variables. An important practical question in the estimation of such atomistic models, therefore, is how to construct the universal choice set in the absence of disaggregate data on the attributes of the nonchosen alternatives. This paper presents a novel approach for spatial imputation of attributes of nonchosen alternatives for estimation and application of atomistic spatial choice models in the absence of disaggregate data. The proposed approach uses the iterative proportional fitting algorithm to impute the attributes of nonchosen alternatives from aggregated data on elemental alternatives. The proposed method is validated with a Monte Carlo experiment and applied to real data in the London residential location choice context.

Local variation in hedonic house pricing in Hanoi, Vietnam: a spatial analysis of status quality trade-off (SQTO) theory

GIScience 2016 Short Paper Proceedings Local variation in hedonic house price, Hanoi: a spatial analysis of SQTO theory A. J. Comber 1 , P. Harris 2 , T. Q. Nguyen 3 , P. K. Chi 4 , H. Tran 4 and H. H. Phe 5 School of Geography, University of Leeds, LS2 9JT, UK Email: a.comber@leeds.ac.uk Rothamsted Research, North Wyke, Okehampton, EX20 2SB, UK Email: paul.harris@rothamsted.ac.uk National University of Civil Engineering, Hanoi, Vietnam Email: quannt@nuce.edu.vn GeoViet Consulting Co. Ltd, Hanoi, Vietnam Email: chi.geoviet@gmail.com Vinaconex RD Fujita, 1989). In these, access to place of work to minimise commuting costs, for example, is one of the main factors explaining residential location choices for lower- income households and higher-income households choose larger properties in the suburbs

Walking Distance of Commuters after Modal Shift to Rail Transit in Bangkok

This paper investigates the walking distance of commuters in Bangkok who changed transport modes to rail transit, and examines the factors that may determine the degree of change in walking distance. The authors hypothesize that people walk a longer distance after the modal shift and that socioeconomic, trip characteristics, residential and job location choice affect the change in walking distance. The authors test the hypotheses by analyzing 1,020 commuter surveys, conducted at 34 stations of the Bangkok Mass Transit System, using regression techniques. The results suggest that people walk farther, averaging a 750-m increase, after modal shift. The regression results imply that socioeconomic characteristics, including gender, age, income and occupation, and trip characteristics, such as type of origin stations, significantly affect the degree of change in walking distance, while residential and job locations choice have a more limited impact on the change.

Social and cultural factors that influence residential location choice of urban senior citizens in China – The case of Chengdu city

With the graying of Chinese society increasing, elderly people who do not live with their family's younger generations has become common. Social and cultural factors have powerful psychological implications for elders in residential location choice making, with the premise of affordability. This preliminary study, is one of the first to examine systematic social and cultural factors of residential location choice, and classifies senior citizens by pre-retirement occupation. Survey data were obtained via three in-depth interviews from 2013 to 2015, and a large-scale questionnaire survey from August 15 to September 16 in 2015. Structural equation modeling results show that perception of comfort, perception of presence, and perception of convenience have marked effects, and perception of affection is not conspicuous on decision-making. Moreover, there are differences in social and cultural factors of elders according to different age periods and pre-retirement occupations. These findings highlight social and cultural demands by elders in residential location choices, and provides a basis for subsequent study on elderly dwelling location choice.

Flood Risk, Flood Mitigation, and Location Choice: Evaluating the National Flood Insurance Program's Community Rating System.

Climate change is expected to worsen the negative effects of natural disasters like floods. The negative impacts, however, can be mitigated by individuals' adjustments through migration and relocation behaviors. Previous literature has identified flood risk as one significant driver in relocation decisions, but no prior study examines the effect of the National Flood Insurance Program's voluntary program-the Community Rating System (CRS)-on residential location choice. This article fills this gap and tests the hypothesis that flood risk and the CRS-creditable flood control activities affect residential location choices. We employ a two-stage sorting model to empirically estimate the effects. In the first stage, individuals' risk perception and preference heterogeneity for the CRS activities are considered, while mean effects of flood risk and the CRS activities are estimated in the second stage. We then estimate heterogeneous marginal willingness to pay (WTP) for the CRS activities by category. Results show that age, ethnicity and race, educational attainment, and prior exposure to risk explain risk perception. We find significant values for the CRS-creditable mitigation activities, which provides empirical evidence for the benefits associated with the program. The marginal WTP for an additional credit point earned for public information activities, including hazard disclosure, is found to be the highest. Results also suggest that water amenities dominate flood risk. Thus, high amenity values may increase exposure to flood risk, and flood mitigation projects should be strategized in coastal regions accordingly.

Interdependences between current choices and future expectations in the context of Hanoians’ residential location choices

ABSTRACTBased on the theory of backward-looking and forward-looking behaviour, a residential location choice model is established to represent interdependences between current choices and future expectations (FE). The interdependences might be observed not only with respect to a particular alternative in a choice set (within-alternative interdependences), but also between different alternatives (between-alternative interdependences), which are jointly incorporated by using a paired combinatorial logit model. Analysis results using data collected from 13,712 individuals in Hanoi in 2005 confirmed that 26.42–55.28% of the total variance of current residential location choice utility can be explained by FE, while 40.81–99.37% of FE can be captured by current choices (i.e. state dependence). The influence of within-alternative interdependences regarding urban core (UC) residence for low-income individuals is almost double that for medium-to-high-income individuals. For between-alternative interdependences, similar results are observed for both low- and medium-to-high-income groups: it can explain 37.37–58.55% of total variance for suburban residence, but only marginal influence (0.00–0.89%) is confirmed for UC residence. These findings suggest that FE cannot be ignored in the analysis of residential location choice behaviour.

Simulating Transport and Land Use Interdependencies for Strategic Urban Planning—An Agent Based Modelling Approach

Agent based modelling has been widely accepted as a promising tool for urban planning purposes thanks to its capability to provide sophisticated insights into the social behaviours and the interdependencies that characterise urban systems. In this paper, we report on an agent based model, called TransMob, which explicitly simulates the mutual dynamics between demographic evolution, transport demands, housing needs and the eventual change in the average satisfaction of the residents of an urban area. The ability to reproduce such dynamics is a unique feature that has not been found in many of the like agent based models in the literature. TransMob, is constituted by six major modules: synthetic population, perceived liveability, travel diary assignment, traffic micro-simulator, residential location choice, and travel mode choice. TransMob is used to simulate the dynamics of a metropolitan area in South East of Sydney, Australia, in 2006 and 2011, with demographic evolution. The results are favourably compared against survey data for the area in 2011, therefore validating the capability of TransMob to reproduce the observed complexity of an urban area. We also report on the application of TransMob to simulate various hypothetical scenarios of urban planning policies. We conclude with discussions on current limitations of TransMob, which serve as suggestions for future developments.

A joint best–worst scaling and stated choice model considering observed and unobserved heterogeneity: An application to residential location choice

Traditional stated choice (SC) experiments are the most widely used method for measuring individual preferences. Notwithstanding, the issue of differentiating between the impacts of the attributes per se vs. the impact of the attribute levels shown in the experiment has been something of a challenge for researchers. Recent studies suggest that Best–Worst scaling (B–W) experiments would allow for the possibility of making this discrimination. In this study we combine B–W data with more traditional SC data to model the choice of residential location; we also allow for observed and unobserved heterogeneity in the combined models. To the best of our knowledge, this type of data fusion has not been used before in this context. Our dataset is fairly unique and corresponds to a sample of individuals interested in acquiring a flat in the centre of Santiago, Chile, from whom both types of responses were elicited. In addition, we have available a larger independent validation sample that responded to a second SC exercise in the same location and time period. We found that the best-fit model corresponded to pooling the ‘best’ and SC responses (i.e., ignoring the ‘worst’ data), while accounting for systematic taste variations (observable heterogeneity) and allowing for a correct treatment of the pseudo-panel nature of the data through error components (unobserved heterogeneity). Our results imply that analysts could get valuable additional information to increase their understanding on individuals’ behaviour when considering the joint use of B–W Scaling and SC data incorporating heterogeneity.

Social interactions in transportation: analyzing groups and spatial networks

Travel demand is derived from activities that people have to or want to engage in. Work trips have been a primary concern for transportation researchers and an early focus of transportation modeling was on commuting behavior (Ben-Akiva and Lerman 1974; Train 1980). Subsequently, non-work activities, such as shopping or doctor visits, increasingly caught the attention of transportation analysts, and interest shifted from a trip-purpose approach (i.e. work trips) towards scheduled-based travel analysis (Bhat and Koppelman 1999). However, these activity trips all have in common that they still could be modeled without considering social context. The analysis approach of choice behavior was rooted in neoclassical economics assuming methodological individualism of isolated, utility-maximizing agents (Small and Winston 1999). While using the traditional neoclassical tool box, much has been learned about journeys to work and trip scheduling for non-work activities. Early research in intra-household interactions in travel demand modeling focused on coordination of individual daily activity patterns, joint participation in activities and travel, mechanisms for allocation of maintenance activities, and activity location and residential location choice behavior (Scott and

Why live far? — Insights from modeling residential location choice in Bangladesh

Increasing commute distances often lead to increased auto-dependency and is a major problem in many developed as well as developing countries. While in developed countries, the propensity to commute long distances generally originates from the preference to work in the core of the city and live in the suburb or periphery, in developing countries, the trend is often quite the opposite. For example, in Bangladesh, people generally have a strong preference to live at the heart of the major cities even if they work at the peripheral areas of the city, in another city or in a rural area. Further, it is also not uncommon to maintain split-families where the earning member of the family lives near the workplace while the rest of the family is based in a big city (subject to affordability). These phenomena lead to substantial increase in Vehicle Miles Traveled (VMT) and add burden to the transport infrastructure.The focus of the research is to explore the key factors that induce middle and upper-middle class commuters in Bangladesh to live away from their workplace and/or maintain split-families. A case study is conducted using Stated Preference (SP) surveys conducted among the faculty members of two universities: one located at the periphery of the capital city and the other quite far away. Discrete Choice Models are developed using the collected data. Results reveal that albeit some differences, for both cases, the choices are strongly driven by quality of the education institutes and the house rent. Factors like gender, income and car-ownership, which traditionally play a strong role in the context of developed countries, are found to be of less significance.The models, though estimated with limited data, provide useful insights about the factors that drive residential location choices in the context of a developing country and can help in formulating policies for encouraging people to live closer to their workplaces and thereby reduce commuter VMT.

Determinants of residential location in the Adenta Municipality, Ghana

This paper assesses the determinants of households’ residential location decision in the Adenta Municipality. Using a total sample of 194 respondents selected from the 18 communities in the Municipality, a multi-stage sampling procedure and google-earth images; the paper concludes that neighbourhood welfare, accessibility attributes, comfort levels of the households and the overall housing conditions are the major determinants which influence household residential location choices in the study area. The paper recommends among others that neighbourhood characteristics such as security of vicinity, proximity to access road, house types, proximity to work and noise levels should be given the necessary attention in the development of urban communities such as Adenta in Ghana.

An Agent‐Based Simulation of Residential Location Choice of Tenants in Tehran, Iran

AbstractResidential location choice modeling is one of the substantial components of land use and transportation models. While numerous aggregated mathematical and statistical approaches have been developed to model the residence choice behavior of households, disaggregated approaches such as the agent‐based modeling have shown interesting capabilities. In this article, a novel agent‐based approach is developed to simulate the residential location choice of tenants in Tehran, the capital of Iran. Tenants are considered as agents who select their desired residential alternatives according to their characteristics and preferences for various criteria such as the rent, accessibility to different services and facilities, environmental pollution, and distance from their workplace and former residence. The choice set of agents is limited to their desired residential alternatives by applying a constrained NSGA‐II algorithm. Then, agents compete with each other to select their final residence among their alternatives. Results of the proposed approach are validated by comparing simulated and actual residences of a sample of tenants. Results show that the proposed approach is able to accurately simulate the residence of 59.3% of tenants at the traffic analysis zone level.

A new generalized heterogeneous data model (GHDM) to jointly model mixed types of dependent variables

This paper formulates a generalized heterogeneous data model (GHDM) that jointly handles mixed types of dependent variables—including multiple nominal outcomes, multiple ordinal variables, and multiple count variables, as well as multiple continuous variables—by representing the covariance relationships among them through a reduced number of latent factors. Sufficiency conditions for identification of the GHDM parameters are presented. The maximum approximate composite marginal likelihood (MACML) method is proposed to estimate this jointly mixed model system. This estimation method provides computational time advantages since the dimensionality of integration in the likelihood function is independent of the number of latent factors. The study undertakes a simulation experiment within the virtual context of integrating residential location choice and travel behavior to evaluate the ability of the MACML approach to recover parameters. The simulation results show that the MACML approach effectively recovers underlying parameters, and also that ignoring the multi-dimensional nature of the relationship among mixed types of dependent variables can lead not only to inconsistent parameter estimation, but also have important implications for policy analysis.

Transit technology investment and selection under urban population volatility: A real option perspective

This paper addresses transit technology investment issues under urban population volatility using a real option approach. Two important problems are investigated: which transit technology should be selected and when should it be introduced. A real option model is proposed to incorporate explicitly the effects of transit technology investment on urban spatial structure in terms of households’ residential location choices and housing market. The trigger population thresholds for investing in a transit technology project and for shifting from a transit technology to another are explored analytically. Comparative static analyses of the urban system and transit technology investment are also carried out. It was found that (i) transit technology investment can induce urban sprawl; (ii) ignoring the effects of transit technology investment on urban spatial equilibrium can lead to a late investment; and (iii) there is a significant difference in the trigger population thresholds for transit technology shift estimated by the net present value approach and the real option approach.

Cordon tolls and competition between cities with symmetric and asymmetric interactions

The aim of this paper is to model the impacts of competition between cities on both the optimal welfare generating tolls and upon longer-term decisions such as business and residential location choices. The research uses a dynamic land use transport interaction model of two neighbouring cities and analyses the impacts by setting up a game between the two cities to maximise the welfare of their own residents. The work builds on our earlier research which studied competition in a small network using a static equilibrium approach for private car traffic without accounting for the land use responses to the change in accessibility. This paper extends the earlier work by setting up a dynamic model which includes active modes of travel and the more usual car and public transport in a realistic twin city setting and assesses the longer term relocation responses. This paper firstly sets out the competition between two hypothetical identical cities i.e. the symmetric case; and then sets out the real world asymmetric case in which the cities are of different size representative of Leeds and Bradford in the UK but equally applicable elsewhere too. We found that the level of interaction between the two cities is a key determinant to the optimal tolls and welfare gains. Our findings show that the competition between cities could lead to a Nash Trap at which both cities are worse off in terms of welfare gains. On the other hand, we found that cities, if regulated, would gain in terms of welfare and yet charge only half the toll compared with tolls under competition. We then show that the effect of competition increases with increased interaction between cities. In terms of residential location, cities with higher charges benefit from an increase in residents, though as with other studies, the relative change in population in response to cordon charging is small. The policy implications are threefold—(i) while there is an incentive to cooperate at local authority level, this is not achieved due to competition; (ii) where cities compete they may fall into a Nash Trap where both cities will be worse off compared to the regulated solution; and (iii) regulation is recommended when there is a strong interaction between the cities but that the benefits of regulation decrease as interaction between cities decreases and the impact of competition is lessened.

Correlated environmental impacts of wastewater management in a spatial context

In this paper we analyze how wastewater management affects water quality and urban spread, through agents' residential location choice between sewer-serviced suburbia, and septic dependent exurbia. We adopt an urban economics model of monocentric city, then a polycentric city, with two different residential areas: suburbia, where there is access to a sewer system and the residential lot size is small, and exurbia, where there is no access to sewerage and the residential lot size is larger to accommodate the sanitary arrangements to meet the regulation on individual septic systems. According to the abatement efficiency gap between wastewater treatment technologies, improving water quality may be achieved at the expense of higher or lower urban spread. We also conduct an analysis of a polycentric city to highlight how asymmetric decision making between primary and secondary cities may have beneficial consequences at the local level, but be detrimental to aggregate environmental performance of the polycentric city. Our conclusions illustrate the unexpected impacts, positive and negative, that managing an environmental issue can have on another issue on the same scale or the same issue on a larger scale.

Spatial variations in residential property development in Birnin-Kebbi, Nigeria

Shelter is a basic necessity of man. The location and spatial distribution of residential accommodation across towns and cities are however subject to a variety of factors. This study aimed at analysing spatial variations in residential property development across BirninKebbi. The relevant population comprised housing units in three (3) major areas. Primary data were obtained through interactions and interviews conducted with residents of the study area as well as questionnaire administered. A comprehensive survey of the area was also carried out and observations were noted. Analysis of data was done using simple descriptive statistics. The study revealed that household level of income is the most prominent factor considered by 53% of residents of Patrick Aziza when choosing areas for residential property development, while proximity to work place is the most influential factor for 50% of Gesse residents. In Badariya, residential location choices are most influenced by religious and ethnic affiliations (30%), security of neighbourhood (29%), and cost of land (27%). The study further revealed varied intensities in residential property development across the three sampled areas and explained reasons for these variations. In addition, the implications of residential expansion in the study area was thoroughly examined, while emphasizing the need for appropriate measures to ensure that the health, safety and wellbeing of inhabitants are not compromised in an attempt to fulfill the housing needs of the people.