Residential Location Choice Research Articles

Changing travel behaviour and attitudes following a residential relocation

A considerable amount of studies have indicated that people to some extent select themselves in specific neighbourhoods allowing them to travel in their desired way. Although a lot of studies analysed the degree to which travel preferences affect the residential location choice, few studies looked at the effect of a residential relocation on people's travel behaviour and attitudes. A new residential context has the potential to disrupt previous travel choices and could potentially change people's attitudes. This study – using 1539 recently relocated residents in the city of Ghent (Belgium) – analyses self-reported changes in mode frequency and travel attitudes after a relocation, and uses a cohort approach to look at mode frequency and attitudes at different times after the relocation took place. Results suggest that (i) travel attitudes often influence the residential location choice, and (ii) both travel attitudes and travel mode choice change after a relocation, albeit in different ways depending on the current (urban versus suburban) and previous residential neighbourhood (more/equally/less urbanised). This study also suggests that a (possible) dissonance between travel attitudes and the residential neighbourhood is partly a temporal situation, as attitudes can gradually change in accordance with the new residential environment.

How Vehicle Access Enables Low-Income Households to Live in Better Neighborhoods

ABSTRACTTransportation influences residential location choices generally, but low-income households often face unique constraints because of a lack of access to automobiles. This article examines how vehicle access influences the type of neighborhoods in which low-income households are able to secure housing following a move to a new neighborhood. We rely on data from the Moving to Opportunity program to estimate locational attainment models, including a wide range of variables capturing various dimensions of neighborhood opportunity. Our findings suggest that auto access enables low-income households to secure housing in neighborhoods that exhibit a wide range of positive neighborhood attributes, including lower poverty rates, lower housing vacancy rates, higher median household income, higher labor-force participation, and higher adult high school graduation rates.

Place attachment and challenges of historic cities

PurposeThe effect of heritage on place attachment is assessed by understanding how people “value” their heritage environment. In addition, the purpose of this paper is to assess the effects of place attachment on residential and investment trends according to two different social groups: local inhabitants and foreign immigrants.Design/methodology/approachA single case study design for Santa Ana de los Ríos de Cuenca including an open-ended survey, combined with Likert-scale analysis. The survey protocol and questions for the respondent groups were structured according to place identity, place dependency and sense of place.FindingsThe analysis bridges the gap between theory and practice and demonstrates interesting similarities as well as differences between both foreign and local respondent groups in terms of the attributes they consider as cultural heritage and their preferences in terms of residential or investment location choice. The research demonstrates that an increased understanding of place attachment as the link between place dependency and sense of place in a specific location can assist in defining effective built heritage policies in favour of local sustainability.Originality/valueThe analysis of place attachment in relation to the origin of respondents revealed different perceptions on the role that a heritage environment might play on attracting or influencing displacement of local inhabitants and foreign immigrants. Based on original empirical data collection in Cuenca, Ecuador, this study identified research lines and actions which should be prioritised for improving management of this World Heritage Site.

What Shapes Uneven Access to Urban Amenities? Thick Injustice and the Legacy of Racial Discrimination in Denver’s Parks

Like other urban amenities, parks are unevenly distributed throughout cities, with advantaged groups enjoying better access to better parks than more disadvantaged residents. Although such inequities are well documented, we know less about the mechanisms that shape them. We conduct a case study in Denver that includes a GIS analysis and interviews with local planners and historians. We find that while park funding systems have tended to steer investments into richer neighborhoods, racially discriminatory land use and housing policies that shape where low-income people of color can live have produced some of the deepest and most persistent inequities in access to parks. Recent improvements in park access for low-income people of color are based less on equity-oriented efforts by public agencies and more on residential location choices of affluent white residents.

Towards incorporating location choice into integrated land use and transport planning and policy: A multi-scale analysis of residential and job location choice behaviour

Residential and job location decisions have lasting impacts on the emergent structure of cities, which in turn, determines travel patterns, energy use and travel-related greenhouse gas emissions. The ability to understand and predict these choice processes are therefore crucial to long-term sustainable urban land use and transport strategies. Understanding housing-job location choice processes requires unpacking the interplay among heterogeneous attributes of decision-makers on the one hand, and various location-defining attributes observable at multiple spatial scales on the other hand. Also, to better understand the interdependence between these location choice sets, empirical examination of how the home and work locations respond to each other over time is necessary. This study responds to these empirical imperatives by exploring residential-job location choice behaviour of households and individuals in a metropolitan context in Ghana, West Africa. The study utilizes data from a cross-sectional survey of 665 households and their 1158 individual workers in the Kumasi metropolis, Ghana’s second largest metropolis. Results show variations in preferences among households and individuals for macro-scale location-defining factors as well as discrete spatial choice alternatives specified as urban-zones, dwelling types and tenancy arrangements. Retrospective analysis of the residential-job choice interdependence shows that in most cases, residential location decisions are taken first, implying a sequential choice process where job location decisions are subsequently anchored on the initial home locations. Besides the in-depth empirical contributions, the paper outlines how the findings could ultimately inform the development of planning support systems to integrate location choice into sustainable urban development and transport management policies.

Are Millennials Coming to Town? Residential Location Choice of Young Adults

How widespread is the downtown resurgence among the current generation of young adults 25 to 34 years old, often referred to as the Millennials? Answering the question, this article provides a detailed analysis of the past, current, and future geographic population distribution, focusing on the young adults. It first documents the demographic shifts from 1990 to 2015 by distance from the central business districts (CBDs) of the 50 largest U.S. metros. The results of the intrametropolitan analysis reconcile the back-to-the-city thesis with sustained suburban growth, explaining how the two sides have reached different conclusions. Then this article empirically examines the generational residential patterns using a multinomial logistic regression, suggesting the generational characteristics of the Millennials, at least partially, explain their inclination to choose city center over suburbs. The simulations based on the model estimates indicate that ongoing demographic shifts might contribute to more population growth in urban centers over the next two decades.

Mode choice and railway subsidy in a congested monocentric city with endogenous population distribution

The objective of this paper is to provide new insights into commuters’ mode choice behavior in a monocentric closed city with endogenous population distribution, where a congested highway and a crowded railway provide commuting services for residents on a linear urban corridor. We first explore the typical equilibrium mode-choice patterns with exogenous city boundary and population distribution, and then incorporate the residents’ mode choice into an urban spatial equilibrium model, in which the residents’ household consumption, the residential location choice and the property developers’ housing production are also explicitly modeled. Using comparative static analysis, we find that the urban corridor expands with the increase of railway fare if there is no congestion in the bimodal transportation system, but it’s not necessarily the case if highway congestion and transit crowding cannot be ignored. We provide numerical evidence to show that the urban corridor possibly shrinks with the increase of railway fare once congestion effects are considered. We also discuss the changes of urban form, utility level of residents and social welfare with different railway fare and subsidy policies. Numerical results show that the distance-based fare policy with low subsidy should be preferred because it can realize the Pareto-improved social welfare and utility level of residents.

Residential Location Choice in the Era of Shared Autonomous Vehicles

This study examines the potential changes in residential location choice in a scenario where shared autonomous vehicles (SAVs) are a popular mode of travel in the Atlanta metropolitan area. This hypothetical study is based on an agent-based simulation approach, which integrates residential location choice models with a SAV simulation model. The coupled model simulates future home location choices given current home location preferences and real estate development patterns. The results indicate that commuters may relocate to neighborhoods with better public schools and more amenities due to reductions in commute costs.

Agent-based modelling of purchasing, renting and investing behaviour in dynamic housing markets

Residential Location Choice (RLC) and Real Estate Price(REP) have been considered as highly correlated and therefore have been jointly studied. This paper develops an agent-based RLC-REP joint model as a key component of an integrated land use-transport model, SelfSim. RLC-REP is capable of simultaneously simulating purchasing, renting and investing behaviour, considering the interactions and competitions between different agent types in the housing market, including renter, landlord, purchaser, seller and investor agents, resulting in new residential locations and real estate prices. In addition, the demographic evolution model in SelfSim that is directly linked to the RLC-REP model is also introduced. Next, both global and local sensitivity analyses (SAs), which employ the Elementary Effect Method (EEM) and Once-At-A-Time (OAT) Method, respectively, are carried out to fully test RLC-REP in a numerical example set up based on a Chinese medium-sized city, Baoding. The EEM-based global SAs identify four influential parameters (among the thirty-four) that could significantly influence the outputs of interests. The OAT-based local SAs further explore how these four important parameters influence the outputs, suggesting that the interactions between parameters could heavily influence the model sensitivity. Finally, the potential applications of the SA results to calibrate the model and to set up “what-if” scenarios are discussed.

Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach

Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict activity-travel choices, with those downstream in the decision-making chain influenced by those upstream in the sequence. The adoption of a singular sequential causal structure to depict relationships among activity-travel choices in travel demand model systems ignores the possibility that some choices are made jointly as a bundle as well as the possible presence of structural heterogeneity in the population with respect to decision-making processes. As different segments in the population may adopt and follow different causal decision-making mechanisms when making selected choices jointly, it would be of value to develop simultaneous equations model systems relating multiple endogenous choice variables that are able to identify population subgroups following alternative causal decision structures. Because the segments are not known a priori, they are considered latent and determined endogenously within a joint modeling framework proposed in this paper. The methodology is applied to a national mobility survey data set to identify population segments that follow different causal structures relating residential location choice, vehicle ownership, and car-share and mobility service usage. It is found that the model revealing three distinct latent segments best describes the data, confirming the efficacy of the modeling approach and the existence of structural heterogeneity in decision-making in the population. Future versions of activity-travel model systems should strive to incorporate such structural heterogeneity to better reflect varying decision processes across population subgroups.

The usefulness of past crime data as an attractiveness index for residential burglars

AbstractThis study examines the effects of neighbourhood attractiveness on the residential burglar's crime location choice process using a discrete choice model. We show that past crime data are an important index of a neighbourhood's attractiveness and can be combined with other attractiveness indices adapted from previous studies. We used data from 369 solved cases committed by 70 offenders and related these data to 1,134 areas (500 m grid cells) in Sendai City, Japan. The results showed that residential burglars were attracted to the following potential locations for crimes: (a) areas in proximity to his or her own residence; (b) areas having many or at least a higher proportion of residential burglaries in the past; (c) areas having many residential units; and (d) areas having a higher proportion of single‐family dwellings. The results confirm the validity of past crime data as an index of a neighbourhood's attractiveness for residential burglary.

Quantifying the relative contribution of factors to household vehicle miles of travel

Household vehicle miles of travel (VMT) has been exhibiting a steady growth in post-recession years in the United States and has reached record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are increasingly seeking ways to curb vehicular travel to advance sustainable, vibrant, and healthy communities. Although there is considerable understanding of the various factors that influence household vehicular travel, there is little knowledge of their relative contribution to explaining variance in household VMT. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes, residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT generation. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 33 percent, density (as a key measure of built environment attributes) explaining 12 percent, and self-selection effects explaining 11 percent of the total variance in the logarithm of household VMT. The remaining 44 percent remains unexplained and attributable to omitted variables and unobserved idiosyncratic factors, calling for further research in this domain to better understand the relative contribution of various drivers of household VMT.

The role of subjective risk perceptions in shaping coastal development dynamics

Social and economic costs in coastal zones resulting from natural hazard events, such as hurricanes, are increasing. Household residential location decisions and adaptive behaviors (i.e., purchasing insurance) are influenced by perceived risk of storms events, and can have long-term consequences for development patterns and regional resilience. Perceived risks may be capitalized into housing prices in hazardous areas, but the attraction of coastal amenities may dampen market responses to risk information. Empirical studies provide contradictory conclusions about the effect of storm events on housing market dynamics, and thus the decision-making processes leading to post-storm residential location and insurance purchase choices remain unclear. Here, an economic agent-based model (ABM) of coupled housing and land markets (CHALMS), adapted to a coastal setting, or C-CHALMS, is used to investigate alternative decision-making models and associated behavioral mechanisms driving post-storm responses. A pattern-oriented modeling (POM) and abductive reasoning approach is used to compare the ability of alternative decision-making models to explain empirical patterns of housing and insurance market dynamics. By explicitly modeling individual decision-making, results demonstrate that post-storm location and insurance purchasing decisions vary greatly within a coastal landscape. Coastal amenities dampen the effects of storm events on housing price dynamics for properties immediately adjacent to the coast, while areas with the lowest risk of damages (and lowest coastal amenities) are most responsive to storm events. Further, psychological factors, such as the perceived salience of positive and negative consequences, explain dynamics of insurance policy uptake after storms better than rational economic decision-making alone.

Racial Residential Segregation: Measuring Location Choice Attributes of Environmental Quality and Self-Segregation

Both sorting on public goods and tastes for segregation contribute to the persistence of segregation in America. Incorporating Schelling’s (1969, 1971) concept of “neighborhood tipping” into a two-stage equilibrium sorting model, in which both neighborhood demographic composition and public goods (e.g., environmental quality) affect households’ residential location choice, this study investigates how preferences for neighborhood demographic composition could obscure the role of exogenous public goods on segregation. The results reveal that non-white households face higher level of exposure to air pollution, suggesting the presence of environmental injustice in Franklin County, OH. Using a counterfactual scenario of switching off heterogeneous taste for environmental quality, this study identifies that sorting on Toxic Release Inventory (TRI) emissions drives little correlations between emissions and demographics. However, when taste parameters of the interactions between neighborhood demographic composition and household race are eliminated, segregation (as measured by over-exposure to households of the same race) of black and white households decreases by 7.63% and 16.36%, respectively, and own-race neighbor preferences contribute to segregation differently according to household income. These results may help explain some recent puzzles in the relationship between environmental quality and demographics.

Relationship between Urban Transport and Residential Location Choice

AbstractThis paper presents a fuzzy three-objective optimization model to study the relationship between residential location choice and urban transport in a city. In the proposed model, the fuzzy ...

The effect of residential housing policy on car ownership and trip chaining behaviour in Hangzhou, China

China has recently initialised affordable housing policies to provide low rent housings for medium and low income households aiming to satisfy the growing demand in the housing market. The travel behaviour of residents in these two different types of housing is likely to differ, since public housing tenants have a limited choice of residential location, as the location of low-rent housing is fixed, while residents in commodity housing are able to take their travel patterns into account in choosing their housing location. Therefore, this paper investigates the differences in car ownership and trip chaining behaviour arising from living in different types of residential housing. The self-selection bias caused by the differences in the observed individual and household characteristics is partially controlled by a propensity score matching approach. The study further considers the endogenous effect of car ownership on travel chaining behaviour, thus controlling for the self-selection bias at car ownership level. The results show that residents in private commodity housing are more likely to own a car than those in low-rent housing with similar individual and household characteristics. Different life cycle stages play a vital role in car ownership after self-selection in residential housing has been taken into account. Living in private commodity housing has a direct negative effect on trip chaining complexity, after controlling for endogenous car ownership, although this effect is offset by the tendency for private commodity housing owners to do complex trip chaining because they have one or more cars.

Univariate or multivariate analysis for better prediction accuracy? A case study of heterogeneity in vehicle ownership

ABSTRACTWe contrast different modeling frameworks that offer alternative ways of capturing observed/unobserved heterogeneity. The model systems compared are: ordered logit, residential location cluster-based ordered logit model (exogenous segmentation), mixed ordered logit, latent segmentation-based ordered logit model, and a joint copula-based self-selection clustering model. While the comparison across single dependent variable models is straight forward, the comparison with the copula-based model requires post-processing to generate marginal distribution for the choice of interest. The comparison exercise is conducted in the vehicle ownership context using O–D survey data of Greater Montreal Area, Canada. The superior performance of the ordered part of the joint copula-based model in the context of model estimation and validation indicates that employing information from an additional dependent variable (such as residential location choice in our case) allows us to better understand and predict the main dimension of interest (vehicle ownership).

Qualified Labors' Residential Location Choice and Residential Satisfaction

Qualified Labors' Residential Location Choice and Residential Satisfaction

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

This study explored the residential choice of households based on the discrete choice model. Although, many authors in Africa cities have commented on this choice behavioural process. Notwithstanding, empirical study in this area is still lacking. There is a need to provide understanding on the household choice and decisions that influences the structure of urban landscape. A sector-wise model was formulated and used to estimate the choice behaviour of 1100 households in the area. However, the model shows that there exists somewhat complex household sorting pattern which is initiated by sociocultural, socioeconomic, accessibility and neighbourhood composition. Among these, sociocultural factors show robust influence. Such factors support that African households tend to develop strong ties to their origin. Generally, the model shows that the pattern of household choices in the region is distinct across sectors.

Examining factors that keep residents with high transit preference away from transit-rich zones and associated behavior outcomes

Many studies on travel-induced residential self-selection assume that travel attitudes are strong enough to influence people's residential decisions. Using quantitative and qualitative methods, this article investigates the impacts of preference for transit and other residential preferences on residential location choice. Employing preference ranking, logistic regression and ANOVA tests on survey data from the Oslo metropolitan area, we find that individuals with simultaneously high preference for transit and low preference for attributes related to households with children are likely to reside in transit-friendly neighborhoods. Transit preference, while important in residential choice, is more so as second tier after other more important preferences related to lifecycle/demographics are satisfied. Individuals who prefer transit but live in transit-poor zones tend to have higher preference for private garden, a larger number of children, lower income, and are older. Variations in access to transit and transit preference have significant influences on transit use. The results of qualitative interviews are also consistent with these findings and substantiate the mechanism by which the built environment and travel preference affect residential and travel choices.