Household Residential Location Research Articles

In search of causality in the relationship between the built environment and travel behaviour. On the challenges of planning and realising an ambitious mixed-methods panel travel survey among relocating households in Germany

Household residential location changes have become an important life event to study changes in travel behaviour. However, most related studies suffer from the shortcomings of collecting retrospective pre-move data, i.e. recall errors and ex-post rationalisation of change. What is more, the overwhelming majority of research in the field relies on quantitative data that do not adequately reflect the subjective perspective of the households or individuals under study, and that are prone to causality issues. Based on a solid theoretical discussion of causality between the built environment (on two interconnected scales) and travel behaviour, the paper reports on a mixed-methods (qualitative/quantitative) panel survey among movers and a control group of non-movers in Germany. Substantial effort was required to conduct the survey due to the dependence on collaboration partners who provided access to households planning to move in the near future. Therefore the paper focuses on the sampling and recruitment process, for which various channels were used. Results pertaining to representativeness and the costs and effectiveness of recruitment channels are presented, and implications for data analysis are briefly discussed. Conclusions are drawn with respect to the relevance of the approach for researchers and practitioners.

Differential impacts of autonomous and connected-autonomous vehicles on household residential location

High market penetration of autonomous vehicles (AVs) and connected-autonomous vehicles (CAVs) is expected to impact transportation network performance, which is an important determinant of residential location decisions, especially for households who commute to work by personal vehicle. This study examines and compares the impacts of privately owned AVs and CAVs on the location and commute characteristics as well as the spatial distribution of households within the Triangle Region in North Carolina. A Mixed Multinomial Logit model is developed using recent household survey data to capture household preferences. In addition, the region’s travel demand model, the Triangle Regional Model, is used to predict the network-level impacts of AV and CAV adoption, and cluster analysis is conducted to explore how network performance changes vary with transportation demand and supply zone characteristics at a local and regional level. Residential location patterns are predicted for a number of AV and CAV scenarios for the year 2045 using the outputs of the econometric analysis and the Triangle Regional Model. We find that extensive adoption of private CAVs improves network conditions and encourages households to live farther from work, leading up to a 5.6% increase in suburban and rural households that commute to work by personal vehicles. A high market share of AVs is associated with deteriorated transportation network performance and up to a 2.8% increase in urban households. Results vary by market penetration rate of each technology, mix of AVs, CAVs, and human driven vehicles in the traffic stream, and fuel type (conventional-fuel versus electric vehicles).

Household Residential Location Choices Under Uncertainty: Evidence from Auckland

Household Residential Location Choices Under Uncertainty: Evidence from Auckland

Determinants of household residential location choice among informal settlers in Port Harcourt

Informal settlements, sometimes called slums, are sites of significant environmental risk in developing cities. Despite its environmental challenges, residents prefer to live in informal settlements rather than planned allocated plots. This paper assesses the determinants of households’ residential location decision in an informal settlement in Port Harcourt in order to gain understanding on what makes individuals consider a particular location in an informal settlement. The study employs a case study approach and uses both indepth face-to-face interviews and structured questionnaires on waterfront households using Cluster sampling to group the settlements into seven (7) zones based on their location in order to capture information on residential location choice decisions of respondents in the informal settlements. In each settlement, we interviewed two households, thereafter questionnaires were administered on 55 respondents’ household by trained graduate students who worked as enumerators. In all a total of 14 interviews were conducted and 385 questionnaires administered. Out of the 385 questionnaires administered, 315 were completed and returned. The results of the survey corroborated by an indebth interview revealed that the growing informality are not limited to income level, but household uses social networks (living close to family or friends), livelihood opportunities, proximity to work, and commuting cost to find accommodation, land for building and support for everyday life in an informal settlement.

Assessing the Efficiency of Household Residential Location Choices

As part of strategic plans, we often see car dependency reduction vision along with strategies to reduce car use and vehicle-kilometers traveled while promoting alternatives such as transit and active modes. It is less common to see strategies to generate more structural changes, even if such change can have much more important and sustainable impacts. Whereas it is well known that home location is one of the key drivers of travel behaviors, it is much less frequent to have planners put forward strategies to encourage people to move and choose their locations more wisely with respect to their needs. This research aims to assess the potential collective gain of an optimal allocation of households to available dwellings. It aims to estimate how inefficient the current distribution is of households among the dwellings with respect to where all household members need to travel. Results show that the household relocations reduce the distances for work and study by 37.9%. This reduction saves an average of 13.8 km per household per day or 4.9 km per work or study trip. If the mode choice remains constant despite the new trip conditions following the household relocations, the total mileage for work and study trips would decrease by 42.8% for car drivers, by 35.2% for car passenger, by 13.3% for school bus, and 34.2% for public transport. As a result of the household relocations, walking and cycling latent trips increased, respectively, from 2.6% to 15.5% and 26.1% to 39.9% of motorized trips.

Residential Location, Mobility, and Travel Time: A Pilot Study in a Small-Size Italian Metropolitan Area

This research concerns the topic of Land Use and Transport Interaction (LUTI) models. In particular, the patterns between residential households’ location and mobility choices are analyzed and simulated. The attributes that influence household residential location choices belong to four categories: socioeconomic and mobility attributes of households and/or of their components; land use; real-estate market; transport system. The paper presents the results of a pilot study on households’ location and mobility patterns in the metropolitan area of Reggio Calabria (Southern Italy). The pilot study is divided into two stages. In the first stage, a survey allowed to collect information and identify existing patterns about residential and mobility choices of a sample of households. In the second stage, a residential location model is proposed and some preliminary calibrations are presented in a prototypal way. The pilot study could be extended and improved in terms of spatial extension and sample dimension in order to allow a complete specification-calibration-validation process of the model. The model development can support the land use-transport planning process in the Metropolitan City of Reggio Calabria.

Household residential location choice in retirement: The role of climate amenities

The paper examines the relationship between climate amenities and locational choices in retirement. Using data from 2017 release of the American Community Survey, I construct a household residential location choice model and value climate amenities from the trade-offs among housing cost, climate amenities, and other locational attributes in a metropolitan statistical area (MSA). On average, a retired household is willing to pay $1209 for a 1 °C drop in average summer temperature, $1114 for a 1 °C increase in average winter temperature, and $486 for a 1 °C decrease in temperature variability. The values of climate amenities vary with household demographic characteristics, and older households with a higher retirement income and disability have a higher marginal willingness to pay for a favorable climate. Moreover, among the retired population, there exists a positive preference-based sorting across MSAs, where those favoring the preferred temperatures more than the average live in places with a more friendly climate. Using the estimated preference parameters, I compute the values of projected climate amenities and find that retired households would be willing to pay nearly 3.3% of their annual income to avoid a standard future projected climate scenario. Simulation results suggest that over 2% of retired households would relocate in response to this level of climate change, resulting in an overall northbound shift in the retired population.

Lifestyles, residential location, and transport mode use: A hierarchical latent class choice model

This study develops a hierarchical latent class choice model that captures the concurrent influence of lifestyles on household residential neighbourhood location and individual transport mode use decisions. The model is empirically evaluated using data from the 2010–12 California Household Travel Survey. The model identifies six household-level classes that differ in terms of their preferences for different neighbourhood attributes when deciding where to live and their household characteristics. Coincidentally, the model also identifies six individual-level classes that differ in terms of the travel modes that they consider when deciding how to travel, their sensitivity to different level-of-service attributes, and their individual characteristics. Household preferences for neighbourhood types and individual preferences for travel modes show expected patterns of correlation. In general, households that prefer to live in suburban neighbourhoods are more likely to consist of individuals that are car-dependent, and households that prefer to live in inner-city neighbourhoods are more likely to consist of individuals that are multimodal. However, our analysis also reveals interesting patterns of deviation. For example, high-income migrant households and median-income white households display strong preferences for suburban neighbourhoods, but individuals belonging to these households also have a high likelihood of being multimodal, with a strong preference for bicycling. We discuss how these patterns of correlation can be used to inform transport and land use policy in novel ways.

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.

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.

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.

Analysis of vehicle ownership evolution in Montreal, Canada using pseudo panel analysis

This paper employs a pseudo-panel approach to study vehicle ownership evolution in Montreal region, Canada using cross-sectional origin–destination survey datasets of 1998, 2003 and 2008. Econometric modeling approaches that simultaneously accommodate the influence of observed and unobserved attributes on the vehicle ownership decision framework are implemented. Specifically, we estimate generalized versions of the ordered response model—including the generalized, scaled- and mixed-generalized ordered logit models. Socio-demographic variables that impact household’s decision to own multiple cars include number of full and part-time working adults, license holders, middle aged adults, retirees, male householders, and presence of children. Increased number of bus stops, longer bus and metro lengths within the household residential location buffer area decrease vehicle fleet size of households. The observed results also varied across years as manifested by the significance of the interaction terms of some of the variables with the time elapsed since 1998 variable. Moreover, variation due to unobserved factors are captured for part-time working adults, number of bus stops, and length of metro lines. In terms of the effect of location of households, we found that some neighborhoods exhibited distinct car ownership temporal dynamics over the years.

Optimal time for implementing cordon toll pricing scheme in a monocentric city

AbstractThis paper proposes an analytical model to address the timing issue of cordon toll pricing in a monocentric city. The proposed model allows an explicit consideration of the interactions among three types of agents in the urban system: (i) the local authority who aims to jointly determine the optimal time for introducing cordon toll pricing scheme, cordon toll location and toll level to maximize social welfare of the urban system; (ii) property developers who seek to determine the intensity of their capital investment in the land market to maximize their own net profit generated from the housing supply; and (iii) households who choose residential locations that maximize their own utility within a budget constraint. The effects of the cordon toll pricing scheme on household's residential location choice and housing market structure in terms of housing price and space are explicitly considered. A comparison of the toll pricing schemes with a fixed and a mobile cordon location over time and the no toll case is carried out. The proposed model is also illustrated in several Chinese cities. Insightful findings are reported on the interactions among cordon toll pricing scheme, urban population size, household income level, toll collection cost, and urban development.

More Than Meets the Market? Landlord Agency in the Illinois Housing Choice Voucher Program

The federal Housing Choice Voucher Program currently serves as one of the nation's predominant strategies for providing affordable rental housing for low-income households. The program is designed around two goals: first, to uphold the U.S. Department of Housing and Urban Development's mission to provide safe, decent, and affordable housing; and second, to facilitate household residential location choices, with the idea that such choices can leverage other types of nonhousing opportunities for assisted households. While scholarly research has described a range of positive and negative household outcomes associated with the voucher subsidy, less is known about how those outcomes are produced on the ground. This research describes findings from 72 in-depth interviews with Illinois landlords and other voucher program stakeholders regarding their experiences with the program, with the goal of linking landlord practices to tenant outcomes. Findings of this research underscore the substantial influence that landlords have on assisted-household residential location choice and tenure, and show the potential for voucher program design to more actively engage with landlords as providers of supports that extend beyond the housing unit.

The Importance of Community Attributes in Household Residential Location Decisions

This study identifies how community attributes affect household residential location decisions in Medellin, Colombia. The empirical model applies the revealed preference principle: each household is assumed to have made an optimal location decision given a set of alternatives. Using household data, we estimate a conditional logit choice model for residential communities by controlling for both individual and neighborhood characteristics, including environmental attributes. The set of alternatives for each household are defined using the applicable neighborhood’s socioeconomic and geographic characteristics. The results provide an estimate of household preferences for the many characteristics of the potential choices in the choice set. In the case of Medellin, we found positive and significant preferences for public provided goods such as public schools and security but relatively low preferences for recreational and cultural spaces; households prefer that the latter be provided by the private sector.

Influences of current neighbourhood characteristics on Hanoian’s actual residential choices and subjective expectations

Bearing in mind that people may have rational expectations conditional on current information, this paper provides additional insights about the influences of current neighborhood characteristics on household residential location choice behavior from such a perspective by comparing actual choices and subjective expectations. Using data in Hanoi, Vietnam in 2005 and multinomial logit models, it is found that current neighborhood characteristics surely influence subjective expectations for the future residential location, but the influences are different from those on actual choices in the sense that signs and/or magnitudes of parameters of some specific neighborhood characteristics change significantly. With the above results, it is concluded that subjective expectations in the research of residential location choice behavior should be paid more attention.

Modeling Household Residential Location Choice and Travel Behavior and Its Relationship with Public Transport Accessibility

Cities are seeking to reduce the growth of car-based travel by developing public transport networks. Much research asserts that the correct arrangement of built environment will result in the enhancement of public transport utilization. There is, however, debate that this approach results only in ‘self-selection’, that is that only residents willing to travel by public transport will locate in these places with resultant minimal impact on car -user households. If policy solutions towards public transport are to be effective, it is necessary to understand the multi-dimensional relationship between location behavior and travel patterns of residents living in proximity to public transport. This research seeks to model the relationship between residential location and mode choice within a behavioral analysis framework. At this early stage of in the research this paper focuses on the methodological framework.

Modeling interdependencies between vehicle transaction, residential relocation and job change

This paper introduces a vehicle transaction timing model which is conditional on household residential and job relocation timings. Further, the household residential location and members’ job relocation timing decisions are jointly estimated. Some researchers have modeled the household vehicle ownership decision jointly with other household decisions like vehicle type choice or VMT; however, these models were basically static and changes in household taste over time has been ignored in nearly all of these models. The proposed model is a dynamic joint model in which the effects of land-use, economy and disaggregate travel activity attributes on the major household decisions; residential location and members’ job relocation timing decisions for wife and husband of the household, are estimated. Each of these models is estimated using both the Weibull and log-logistic baseline hazard functions to assess the usefulness of a non-monotonic rather than monotonic baseline hazard function. The last three waves of the Puget Sound Panel Survey data and land-use, transportation, and built environment variables from the Seattle Metropolitan Area are used in this study as these waves include useful explanatory variables like household tenure that were not included in the previous waves.

Household travel attributes transferability analysis: application of a hierarchical rule based approach

This paper presents a system of hierarchical rule-based models of trip generation and modal split. Travel attributes, like trip counts for different transportation modes and commute distance, are among the modeled variables. The proposed framework could be considered as an alternative for several modules of the traditional travel demand modeling approach, while providing travel attributes at the highly disaggregate level that can be also used in activity-based micro-simulation modeling systems. Nonetheless, the modeling framework of this study is not considered as a substitute for activity-based models. The explanatory variables set ranges from socio-economic and demographic attributes of the household to the built environment characteristics of the household residential location. Another important contribution of the study is a framework in which travel attributes are modeled in conjunction with each other and the interdependencies among them are postulated through a hierarchical system of models. All the models are developed using rule-based decision tree method. Moreover, the models developed in this study present a useful improvement in increasing the practicality and accuracy of the rule-based travel data simulation models.

Influence of Race on Household Residential Utility

Residential location choice models are an important tool employed by urban geographers, planners, and transportation engineers for understanding household residential location behavior and for predicting future residential location activity. Racial segregation and residential racial preferences have been studied extensively using a variety of analysis techniques in social science research, but racial preferences have generally not been adequately incorporated into residential location choice models. This research develops residential location choice model specifications with a variety of alternative methods of addressing racial preferences in residential location decisions. The research tests whether social class, family structure, and in-group racial preferences are sufficient to explain household sensitivity to neighborhood racial composition. The importance of the interaction between the proportion of in-group race neighbors and other-race neighbors is also evaluated. Models for the San Francisco Bay metropolitan area are estimated and evidence of significant avoidance behavior by households of all races is found. The results suggest that social class differences, family structure differences, and in-group racial preferences alone are not sufficient to explain household residential racial preference and that households of all races practice racial avoidance behavior. Particularly pronounced avoidance of black neighbors by Asian households, Hispanic neighbors by black households, and Asian neighbors by white households are found. Evidence of a decrease in household racial avoidance intensity in neighborhoods with large numbers of own-race neighbors is also found.