Residential Location Decisions Research Articles

Back to the suburbs? Millennial residential locations from the Great Recession to the pandemic

In the past decade, there has been a great deal of attention paid to and speculation about the residential mobility and location decisions of millennials. Academics and practitioners alike have been trying to determine where millennials are moving and why, including whether they are leading a ‘back to the city’ movement or whether they are moving to the suburbs as previous generations did at their age. Using US Census data, this article examines the geographical population distribution of young adults in the USA in recent decades. Categorising neighbourhoods by their urban or suburban character and by their central or peripheral location, we find that millennials lived in urban areas on the heels of the Great Recession at higher rates than previous generations. However, over the decade, the millennial population gradually shifted towards suburban areas: central urban and peripheral urban neighbourhoods largely lost millennial residents from 2011 to 2021, while peripheral suburban neighbourhoods experienced substantial gains. When it comes to neighbourhood amenities (e.g. restaurants and parks), millennials largely left amenity-rich areas for neighbourhoods with fewer amenities, though these amenities grew faster in the neighbourhoods that gained millennials the most. Millennial suburbanisation seems to be associated with housing affordability and demand for larger homes, as the population shift was more pronounced in the metros that have lower housing affordability and a lower share of larger homes in their central urban neighbourhoods. The results indicate the importance of affordable and right-sized housing, complemented with neighbourhood amenities, in attracting and retaining this population group.

Determining Residential Location Choice along the Coastline in Victoria Island, Nigeria Using a Factor Analytical Approach

This paper evaluates how households consider environmental attributes alongside other housing attributes in their residential location decisions along the coastline in Victoria Island, Nigeria. The data were obtained from tenants’ revealed preference surveys where 204 respondents rated 15 identified and most common key factors in the order by which they influence their residential location choices. The factor analytical approach was then applied to understand how these factors influence such decisions. Thus, this study also gives bearing to the factors considered in making policy and/or investment decisions around residential location choice (RLC). The results revealed the presence of four key components with a total variance of 70.76%. Among the components, neighbourhood, critical dwelling cum socio-economic attributes are found to have a significant influence in explaining 39.78% of the variation in the factors influencing the study area’s selection as the residential location choice (RLC) for households. The findings have implications for households’ residential location choices. For residential locations to be equally attractive to tenants, policymakers and urban planners should pay attention to addressing the menace of the neighbourhoods including crime and traffic congestion. Moreover, property owners should respond to tenants’ needs by paying attention to the provision of utility facilities such as portable water and an appropriate mix of toilet/bathrooms to available bedrooms.

Macro-Level Factors Shaping Residential Location Choices: Examining the Impacts of Density and Land-Use Mix

Many published papers have delved into the factors affecting the residential location choices of households using various logit models. Nonetheless, only a few pieces of literature have attempted to examine those associative attributes from a macroscopic view. Thus, this article investigates the factors that influence households’ preference to reside in densely populated locations or regions with a wide variety of land-use types using ordered choice models (ORM). This study proposes three indicators that are reflective of residential areas, namely population density, housing density, and land-use mix index, based on prior research. Population density and housing density are modeled at census block and tract levels to explore households’ sensitivity to different geographical scales. Regarding land use, this research classifies the diversity index into four categories: uniform, moderately diverse, more diverse, and the most diverse. Similarly, the study is predicated on 0.25-mile and 0.5-mile buffer zones. The findings are consistent with earlier research and highlight macro-level issues that influence residential location decisions. As for the residential preference for housing density, significant factors are the structure of households, the number of vehicles per household, and household income. Regarding the residential choices of population density, significant attributes refer to demographic characteristics, household income, and housing types. Concerning the residential choices based on land-use mix, the most influential factors turn out to be the interacting terms between demographics and housing-related index, household income, and housing-related indexes.

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).

Residential location and the male-female gap in labor market outcomes—a lesson from newcomers to israel

We estimated two dynamic programing models, one for men and one for women, on a sample of immigrants who arrived in Israel from the Former Soviet Union (FSU) between 1989 and 1995. Following the literature, we assume that the household maximizes its expected utility based only on the husband’ s human capital. Therefore, the family’s residential location decision is based on the husband’s labor market opportunities. We study the potential effect of this assumed behavior on the labor market’ s gender gaps. In the model estimated for men, we endogenize the decisions regarding residential location, employment location, and occupational choices. In contrast, in the model estimated for women the family’s residential location is taken as given. Using the estimated parameters from the two models and a number of counterfactual simulations, we are able to decompose the observed gender wage gap into two parts–one based on behavioral differences and the other based on the lower labor market returns for women. The simulations indicate that if women had the same labor market returns and the same preferences as men, their outcomes would have been similar to those of men. Moreover, the simulations show that even without any changes in their labor market conditions, women would have gained in terms of both job quality and wages if the family’s residential location was based on their human capital.

Impact of telecommuting on Japanese Citizen's travel, activities, and residential locations: Experiences and future expectations under COVID-19 pandemic

In the past few years, telecommuting has diffused on a large scale across many developed countries; however, its popularity in Japan is low due to various factors and cultural differences. The outbreak of COVID-19 has made the adoption of telecommuting indispensable, reaching an unprecedented level in Japan, bringing dramatic changes in the lifestyles and behaviors of citizens. This study investigates how and to what extent this pandemic-induced telecommuting affected employees’ travel, activities, and residence locations and explores their expectations of post-pandemic life. The data were collected through the online questionnaire survey across three major metropolitan areas in Japan that incorporates a comprehensive set of questions regarding telecommuting implementation and feasibility, lifestyles before and during the pandemic, and expected way of life after the pandemic, and the total of 2045 respondents were collected. The analysis has been done based on revealed preference data considering two time periods i.e., before COVID-19, during COVID-19, and for the post-COVID 19 scenario where stated preferences are considered. In the first step, telecommuting behavior, telecommuting preferences and plans, and activity patterns are estimated based on aggregate sample data. Next, by using the stated preference survey conducted, ordered probit model and mixed logit model are applied to identify factors influencing post-pandemic telecommuting frequency and residential location preference, respectively. The analysis revealed two major findings: telecommuting brought significant changes in multiple aspects of people’s lifestyles and activities that might persist after the pandemic; although determinants that govern telecommuting frequency and residential location choice after COVID-19 may differ across metropolitan areas, commuting/telecommuting frequency is the prime factor influencing residential location decisions. The findings of this research can guide transportation and urban planners in establishing effective travel demand management tools and sustainable urban networks for the new-normal era.

The role of residential choice on the travel behavior of young adults

Several studies have shown that the travel behavior of young adults in the United States in the past two decades differed from that of prior generations. On average, recent young adults drove fewer miles, owned fewer vehicles and made use of public transit more often. A higher share of young adults also chose to live in cities. This study examines the relationship between the location decision of young adults and their travel behavior. We examine how being a young adult and other socioeconomic variables are associated with residential location decisions, and how these in turn affect vehicle ownership, mode choice and travel distance. Our analysis uses household travel survey data from the Seattle regions collected in 2006 and 2017 and employs a recursive structural equation model to examine these questions. We find that young adult households were more likely to live closer to the city center and to have fewer vehicles than older ones. Fewer young adults also chose to own vehicles in 2017 than in 2006. While young adults made more use of non-automobile modes and had fewer person miles traveled, we find that these effects were more due to their residential location and vehicle ownership decisions than due to direct preferences about mode or distance traveled. These findings suggest that significant changes would be expected in the mode use and miles traveled among young adults if their residential location or vehicle ownership preferences change significantly due to life cycle or other factors.

Tense Housing Markets: Displacement and Residential Location Decisions in Berlin

Given the tense situation in many metropolitan housing markets, concerns have arisen about tenants being displaced from their homes. The debate not only focuses on the number of people obliged to move, but also on the challenges and burdens it entails and, above all, where it leads them. Empirical, notably quantitative, findings on these questions, however, are rare. This article presents such findings for the German capital. These are based on a representative survey on moves between 2013 and 2015 and show that the majority of displaced tenants strive to find a new flat near their old one and for the most part succeed. It also shows that they have to make a much greater effort to find a new flat than those who have not been displaced. A detailed, spatially explicit analysis of where respondents moved to also indicates that some displaced tenants feel forced to move to locations not of their preference, including the outskirts of the city. That said, this only affected a comparatively small proportionof displaced tenants, at least in the period under review. It can be assumed, nonetheless, that with the further tightening of Berlin’s housing market in recent years, the problem of displacement to specific areas of the city is gaining substantial significance. In addition, there is evidence of exclusionary displacement, although this phenomenon was not the focus of the study: Low-income households in search of housing are excluded from certain urban areas in Berlin due to high asking rents.

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.

Toward Accessibility-Based Planning

Problem, research strategy, and findings A growing consensus has formed among planners, especially planning scholars, that promoting accessibility is a major policy goal. However, efforts to promote accessibility-based planning face a conceptual impediment: a common assumption that equates the benefits of accessibility to travel cost savings (TCS). Starting from this assumption, many researchers have interpreted the absence of TCS (e.g., savings in commuting costs and reductions in vehicle miles traveled [VMT]) as evidence undermining the rationale for accessibility-promoting strategies such as jobs–housing balance and transit-oriented development (TOD). In this study I challenge these interpretations by suggesting that accessibility improvements can result in not only TCS but also destination utility gains, which means the individual satisfaction from interacting with or choosing desirable destinations. The absence of TCS from accessibility-promoting policies can be explained by accessibility gains manifesting as destination utility gains. To analyze the importance of destination utility gains, I engage with literatures in economic geography and travel behavior and examine some recent urban trends (e.g., the rise of city-to-suburb commuting). I further estimate residential location choice models to test whether households value accessibility beyond the benefit of TCS. Results from the Puget Sound (WA) and Southeast Michigan regions support the hypothesis, demonstrating that destination utility gains shape residential location decisions. Takeaway for practice Planners should not automatically interpret the absence of TCS as evidence that accessibility-promoting strategies are not working. To advance accessibility-based planning, planners should start to explore and measure the various forms of destination utility gains. The evaluation framework for land use and transportation policies should shift from being centered on TCS alone to being accessibility based.

Efficiency and Equity Impacts of Urban Transportation Policies with Equilibrium Sorting

We estimate an equilibrium model of residential sorting with endogenous traffic congestion to evaluate the efficiency and equity impacts of urban transportation policies. Leveraging fine-scale data on household travel diaries and housing transactions with home and work locations in Beijing, we jointly estimate travel mode and residential location decisions. The estimation highlights the importance of incorporating work commute in housing decisions and features preference heterogeneity for the ease of work commute by gender. Counterfactual simulations show that while different policies can attain the same level of congestion reduction, their impacts on residential sorting and social welfare are drastically different. First, a driving restriction intensifies income-stratified urban structure where high-income households live closer to subway and work. Distance-based congestion pricing reduces the spatial separation between residence and workplace across income levels, while subway expansion does the opposite. Second, residential sorting strengthens the effectiveness of congestion pricing in improving traffic conditions but undermines that of the driving restriction and subway expansion. Third, the driving restriction is welfare reducing as it leads to large distortions on travel choices. Congestion pricing improves welfare but is regressive, highlighting the need to recycle revenue to address the associated equity concern. Finally, congestion pricing and subway expansion when combined deliver the largest congestion relief and efficiency gain and at the same time achieve self-financing, with revenue from congestion pricing fully covering the cost of subway expansion.

İZMİR KENT BÖLGESİNDE İZBAN’IN MAHALLE NÜFUS DEĞİŞİMİNE ETKİSİ

Recently, metropolitan public transit sector in Turkey has witnessed a surge in urban rail projects. Accordingly, suburban railways, metro or light railways have become the main focus of investment in public transit. Enactment of Law No. 6360, which expands powers and responsibilities of metropolitan municipality to its provincial boundaries, has increased the prospects of rail transit to suburban rail systems. In fact, suburban rail lines, especially in Istanbul, Ankara and Izmir, had long been providing regional services in Turkey. However, slow speeds, infrequent arrival, and a generally low service level with outdated technology make these trains less appealing than private car in early 2000s. Lately, suburban lines, such as Marmaray in Istanbul, Baskentray and IZBAN, in Ankara and Izmir, respectively, have been upgraded and put to service. IZBAN, extending to the provincial boundaries, is the longest of all suburban lines in Turkey. Currently, providing access between Aliaga, an important industial district in the north, and Selcuk, southernmost district of Izmir, IZBAN is planned to extend to Bergama, the northernmost district of Izmir. Started by a joint venture between metropolitan municipality and state railways, IZBAN is the only project of its size initiated by local collaboration and innovative entrepreneurship. The line connects a significant number of destinations in daily trips, which makes IZBAN an important commuting trip mode. The current study has the aim to find out the effects of a suburban railway investment on population mobility. Based on this quest, we firstly hypotesize that reliable and fast rail public service, which connects main destinations in a region like IZBAN, has a significant role in residential location decisions. Accordingly, population changes in the neighborhoods where IZBAN provides direct access are examined in relation to other neighborhoods by Analysis of Covariance (ANCOVA) statistical models. Significant relative increase in the populations of neighbourhoods, served by IZBAN stations, is found. Moreover, these population increases are higher in the northern and southern segments, pointing to IZBAN induced decentralization in the metropolitan area and exemplifying a self-organized transit-oriented development in Turkey.

Latent class analysis of residential and work location choices

ABSTRACT This paper developed a two-stage modeling framework for analyzing residential and work location choices with probabilistic choice sets. In the first stage, a household (or a worker) was assumed to select a neighborhood (such as central business district, urban, suburban etc.) to live (or work). In the second stage, the household (or worker) was assumed to choose a specific zone conditional on the selected neighborhood. The neighborhood choice model component takes the form of Manski model with latent choice sets. The model was used to analyze residential and work location decisions in Nashville, Tennessee. The model results indicate significant heterogeneity in the consideration probability of different neighborhood alternatives both in the residential and work location choices. The latent class neighborhood models were found to outperform standard MNL models that assume all decision-makers consider the universal choice set in their decision-making.

Ranking residential locations based on neighborhood sustainability and family profile

ABSTRACT Neighborhood characteristics increase human well-being and happiness and is becoming a key criterion for residential location decisions nowadays. This paper proposes a tool to measure neighborhood characteristics, especially those that increase its sustainability, and to rank neighborhoods based on different residents’ profiles. The proposed ranking procedure, based on multiple decision criteria, combines the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with a method that assigns preference weights to different Analytic Hierarchy Process (AHP) profiles. In order to illustrate the suitability and properties of the proposed framework, the case of a medium-sized city in northern Spain is presented. Five different resident or family profiles are defined and the different residential locations are ranked taking into account different sustainability neighborhood criteria. The obtained relative proximity index can be interpreted as an adequacy index in terms of neighborhood quality of live and sustainability. The proposed procedure can be a very valuable tool for real estate agents, construction companies or urban planners. All of them can make different uses of the tool, either to provide a service better adapted to the client or, in the case of urban planners and managers, to make projections and evaluate alternatives or ex-ante policies.

A study of car and home ownership decisions in the face of increasing commuting expenses (CHOICE) in the Greater Toronto Area (GTA)

This paper presents a study of Car and Home Ownership decisions in the face of Increasing Commuting Expenses (CHOICE) within the Greater Toronto Area (GTA) of Canada. The CHOICE study uses a web-based survey tool to collect data from a sample of households with cross-regional commuters. The survey uses stated preference experiments pivoted on the retrospective revealed preference information of commuting trips, car ownership, and home ownership of participating households. Data collected through the survey are then used to estimate econometric choice models of households’ reactions to increasing commuting costs by either changing the car fleet or changing the home location and dwelling type. The study reveals that, with increasing commuting expenses, households are willing to change their usual travel behavior, but such adaptation is not straight-forward. Choosing a more efficient car is a more favorable solution than switching to transit, while choosing a different home location to reduce commuting costs is less common. Currently, suburban households prefer moving to another suburban region instead of moving into the city. This study provides evidence that vehicle ownership and residential location decisions follow complex and interrelated processes, and it clearly shows that home-related decisions are not necessarily adapted in response to increased commuting costs.

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.

Are movers irrational? On travel patterns, housing characteristics, social interactions, and happiness before and after a move

Auto use in the United States is too high, and land uses are too spread out, due to market failures in transportation along with municipal restrictions on density that make residential choices suboptimal. Residential choices may also be suboptimal if households make irrational decisions when deciding where to live and how to get around—failing to account for time spent commuting, overvaluing privacy and material goods like housing, or undervaluing time spent on social activities. Such hypotheses from the behavioral economics literature have rarely been empirically explored with regard to residential location decisions. We surveyed 84 individuals, primarily university students, at two points in time: about six months apart, before and after moving. The questions included measures of self-reported well-being, travel patterns, social connections, housing characteristics, and neighborhoods, along with socioeconomic and personality measures. In controlled statistical models we found that changes in the number of close friends, time spent bicycling, and the number of visits carried out on foot to visit friends and family were positively associated with changes in well-being. These influences were stronger than the influence of housing characteristics in almost all cases. Changes in the time spent commuting by auto were not significantly correlated with changes in well-being. When choosing a residence, movers prioritized housing characteristics over social factors despite the fact that social factors and active transport were generally more correlated with well-being. However, the results do suggest people may improve their residential location decisions as they get older.

Weekday trip patterns of students in Obafemi Awolowo University, Ile-Ife, Nigeria

Data used were obtained from Obafemi Awolowo University Annual Report publication, questionnaire administration and interview on socioeconomic characteristics of off-campus resident students; travel characteristics and mobility pattern; perception on the availability of transport infrastructure as well as factors that determine the decision to reside off-campus. Results showed two main types of mobility patterns, viz: unidirectional (89.8%) and bidirectional (10.2%) movements. An average student spends between ₦31 and ₦175 (US$ 0.09 and US$ 0.48); and between 15 and 30 minutes, daily from their residence to the university. Gender, amount paid on house rent, family house ownership, and source of income were the main factors determining the choice of residential location among students. Proximity to bus stops and/or junctions, quick and easy access to motorcycles and buses, and nearness to park or garage were the most important factors that influence accommodation location choices among the off-campus resident students. The study concluded that transport infrastructure influenced the residential location decisions among off-campus resident students in the study area.

Explaining Spatial Distribution of the Middle Class: A Multiple Indicator Approach with Multiple Explanatory Dimensions

This study attempts to investigate the pattern of the middle class in the Seoul Metropolitan Region and to explain why such a pattern occurs from spatial perspectives. For this purpose, the middle class are first defined based on four indicators: income, education, occupation and housing. Then, the spatial concentration of the middle class are explored by each indicator for 2010. The explanation of the pattern is pursued based on four dimensions often considered as critical factors in residential location decisions of the middle class: neighborhood, employment, consumption and educational environment. The findings suggest that the spatial distribution of the middle class generally shows a combination of concentric and sector models as we go farther from Seoul. The results of the global and the local regression analyses suggest that employment (producer service jobs) and educational environment (private after-school educational institutes) are important dimensions in explaining the residential location of the middle class in the Seoul Metropolitan Region.

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.