Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice

Concerns over transportation energy consumption and emissions have prompted more studies into the impacts of built environment on driving-related behavior, especially on car ownership and travel mode choice. This study contributes to examine the impacts of the built environment on commuter’s driving behavior at both spatial zone and individual levels. The aim of this study is threefold. First, a multilevel integrated multinomial logit (MNL) and structural equation model (SEM) approach was employed to jointly explore the impacts of the built environment on car ownership and travel mode choice. Second, the spatial context in which individuals make the travel decisions was accommodated, and spatial heterogeneities of car ownership and travel mode choice across traffic analysis zones (TAZs) were recognized. Third, the indirect effects of the built environment on travel mode choice through the mediating variable car ownership were calculated, in other words, the intermediary nature of car ownership was considered. Using the Washington metropolitan area as the study case, the built environment measures were calculated for each TAZ, and the commuting trips were drawn from the household travel survey in this area. To estimate the model parameters, the robust maximum likelihood (MLR) method was used. Meanwhile, a comparison among different model structures was conducted. The model results suggest that application of the multilevel integrated MNL and SEM approach obtains significant improvements over other models. This study give transportation planners a better understanding on how the built environment influences car ownership and commuting mode choice, and consequently develop effective and targeted countermeasures.     

The intra-household choices regarding commuting and housing

This paper is an empirical analysis of the relationships between commuting decisions of spouses in dual-income households, where the role of housing and housing tenure is taken into account. The study is based on a large survey of US commuters and actual commuting and housing choices. Household commuting decisions are analyzed together with housing choices using the data from the 2001 American Housing Survey. A sample of dual-career spouses who commute to work by car only is used to explore the inter-relationship between male and female commuting decisions in such households and the effect of housing choices on their commuting. The inter-relationships between spousal commuting decisions are examined separately for the two forms of housing tenure: ownership and renting. In general, men commute further than women and owners commute further than renters.It is shown that for both renters and homeowners, journeys to work by men and women in such dual-earner households appear to be “complements” and not “substitutes”. This means that commute trips are jointly chosen to be longer (or shorter) for both spouses, as part of household selection of preferred housing and neighborhood characteristics. The residuals of equations explaining commute times and commute distances for men are strongly positively correlated with those for women. Many of the explanatory factors affect the men and women in similar ways. In particular, housing value is positively correlated with commute times and distances for both genders. The commute distance for women owners appears more sensitive to housing value than that of men, meaning women adjust their trips to work even more so than men do, as part of obtaining better housing.For both homeowners and renters, longer commute distances were correlated with higher salaries for both spouses. Somewhat surprisingly, it was found that commuting distances for women are similarly or even more sensitive to income increments than are those of men. Household size appears to affect women who own housing in ways opposite from those who rent. Other housing and neighborhood factors also affect the joint commuting decisions of these men and women.     

Influence of the residential and work environment on car use in dual-earner households

This paper analyses whether the decision to commute by car is influenced by built environment characteristics of residential neighbourhoods and, more especially, of work locations, taking into account interdependencies between household partners. It shows that the residential environment only affects car use among single-earners. Conversely, for all commuters, but in particular for dual-earners, characteristics of the work location affect whether they commute by car. Even in dual-earner households with two cars, work environment plays a role. We found that in cases of dual-earners with only one car, the partners with the longest commuting distances and the lowest density work locations are most likely to commute by car. Moreover, in households with young children, men are more inclined to leave the car at home. Other features relating to work also affect car commuting, including work flexibility and, especially, possession of a company car. We conclude that future policies aimed at reducing car use should place greater focus on work factors.     

Volatility of car ownership, commuting mode and time in the UK

This paper has two objectives: to examine the volatility of travel behaviour over time and consider the factors explaining this volatility; and to estimate the factors determining car ownership and commuting by car. The analysis is based on observations of individuals and households over a period of up to 11 years obtained from the British Household Panel Survey (BHPS). Changes in car ownership, commuting mode and commuting time over a period of years for the same individuals/households are examined to determine the extent to which these change from year-to-year. This volatility of individual behaviour is a measure of the ease of change or adaptation. If behaviour changes easily, policy measures are likely to have a stronger and more rapid effect than if there is more resistance to change. The changes are “explained” in terms of factors such as moving house, changing job and employment status. The factors determining car ownership and commuting by car are analysed using a dynamic panel-data models.     

Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city

As Chinese cities continue to grow rapidly and their newly developed suburbs continue to accommodate most of the enormous population increase, rail transit is seen as the key to counter automobile dependence. This paper examines the effects of rail transit-supported urban expansion using travel survey data collected from residents in four Shanghai suburban neighborhoods, including three located near metro stations. Estimated binary logit model of car ownership and nested logit model of commuting mode choice reveal that: (1) proximity to metro stations has a significant positive association with the choice of rail transit as primary commuting mode, but its association with car ownership is insignificant; (2) income, job status, and transportation subsidy are all positively associated with the probabilities of owning car and driving it to work; (3) higher population density in work location relates positively to the likelihood of commuting by the metro, but does not show a significant relationship with car ownership; (4) longer commuting distance is strongly associated with higher probabilities of riding the metro, rather than driving, to work; (5) considerations of money, time, comfort, and safety appear to exert measurable influences on car ownership and mode choice in the expected directions, and the intention to ride the metro for commuting is reflected in its actual use as primary mode for journey to work. These results strongly suggest that rail transit-supported urban expansion can produce important positive outcomes, and that this strategic approach can be effectively facilitated by transportation policies and land use plans, as well as complemented by timely provision of high quality rail transit service to suburban residents.     

Changes in level of household car ownership: the role of life events and spatial context

Recent longitudinal studies of household car ownership have examined factors associated with increases and decreases in car ownership level. The contribution of this panel data analysis is to identify the predictors of different types of car ownership level change (zero to one car, one to two cars and vice versa) and demonstrate that these are quite different in nature. The study develops a large scale data set (n = 19,334), drawing on the first two waves (2009–2011) of the UK Household Longitudinal Study (UKHLS). This has enabled the generation of a comprehensive set of life event and spatial context variables. Changes to composition of households (people arriving and leaving) and to driving licence availability are the strongest predictors of car ownership level changes, followed by employment status and income changes. Households were found to be more likely to relinquish cars in association with an income reduction than they were to acquire cars in association with an income gain. This may be attributed to the economic recession of the time. The effect of having children differs according to car ownership state with it increasing the probability of acquiring a car for non-car owners and increasing the probability of relinquishing a car for two car owners. Sensitivity to spatial context is demonstrated by poorer access to public transport predicting higher probability of a non-car owning household acquiring a car and lower probability of a one-car owning household relinquishing a car. While previous panel studies have had to rely on comparatively small samples, the large scale nature of the UKHLS has provided robust and comprehensive evidence of the factors that determine different car ownership level changes.     

A dynamic analysis of household car ownership

This paper examines the determinants of household car ownership, using Irish longitudinal data for the period 1995–2001. This was a period of rapid economic and social change in Ireland, with the proportion of households with one or more cars growing from 74.6% to 80.8%. Understanding the determinants of household car ownership, a key determinant of household travel behaviour more generally, is particularly important in the context of current policy developments which seek to encourage more sustainable means of travel. In this paper, we use longitudinal data to estimate dynamic models of household car ownership, controlling for unobserved heterogeneity and state dependence. We find income and previous car ownership to be the strongest determinants of differences in household car ownership, with the effect of permanent income having a stronger and more significant effect on the probability of household car ownership than current income. In addition, income elasticities differ by previous car ownership status, with income elasticities higher for those households with no car in the initial period. Other important influences include household composition (in particular, the presence of young children) and lifecycle effects, which create challenges for policymakers in seeking to change travel behaviour.     

A dynamic model system of household car ownership,trip generation,and modal split: model development and simulation experiment

A dynamic model of household car ownership and mode use is developed and applied to demand forecasting. The model system consists of three interrelated components: car ownership, mechanized trip generation, and modal split. The level of household car ownership is represented as a function of household attributes and mobility measures from the preceding observation time point using an ordered-response probit model. The trip generation model predicts the weekly number of trips made by household members using car or public transit, and the modal split model predicts the fraction of trips that are made by public transit. Household car ownership is a major determinant in the latter two model components. A simulation experiment is conducted using sample households from the Dutch National Mobility Panel data set and applying the model system to predict household car ownership and mode use under different scenarios on future household income, employment, and drivers’ license holding. Policy implications of the simulation results are discussed.     

The persevering commuter – Duration of long-distance commuting

A growing number of people are long-distance commuters. For some long-distance commuting is a temporary solution, while as for others it can be a more long-term strategy to promote career and income. This study addresses duration of long-distance commuting – 30 km or more between home and work – in Sweden, and what characterizes individuals who commute for shorter or longer periods. The effects of long-distance commuting in terms of economic outcome for both partners in a commuter household are analysed. The study is based on register data for the years 1995–2005 covering all long-distance commuters in Sweden. One finding is that previous experience of long-distance commuting makes it more likely to have a long duration of long-distance commuting. In addition economic incentives, such as a higher income, are positively correlated for continuing to long-distance commuting more than a few years. Furthermore, the analysis shows that male commuters benefit more in terms of economic outcome of long-distance commuting. It is concluded that the trend with increasing long-distance commuting can sustain not only gender differences on the labour market but also within households. Finally, the paper indicates that long-distance commuting is a strategic mobility choice for households, rather than a short-term solution for a few years.     

Household type and structure, time-use pattern, and trip-chaining behavior

In order to examine time allocation patterns within household-level trip-chaining, simultaneous doubly-censored Tobit models are applied to model time-use behavior within the context of household activity participation. Using the entire sample and a sub-sample of worker households from Tucson’s Household Travel Survey, two sets of models are developed to better understand the phenomena of trip-chaining behavior among five types of households: single non-worker households, single worker households, couple non-worker households, couple one-worker households, and couple two-worker households. Durations of out-of-home subsistence, maintenance, and discretionary activities within trip chains are examined. Factors found to be associated with trip-chaining behavior include intra-household interactions with the household types and their structure and household head attributes.     

A repeated cross-sectional evaluation of car ownership

This paper studies changes in the relationship between household car ownership and income by household type. Ordered response probit models of car ownership are estimated for a sample of households repeatedly at six time points to track the evolution of income elasticities of car ownership over time. Elasticities of car ownership are found to change over time, questioning the existence of a unique equilibrium point between demand and supply that is implicitly assumed in traditional cross-sectional discrete choice car ownership models. Moreover, different household types and households that underwent household type transitions showed differing patterns of change in elasticities. Observed trends in car ownership and income clearly show behavioral asymmetry where the elasticity of procuring an additional car is greater than that of disposing a car. This too shows the inadequacy of traditional cross-sectional models of car ownership which tend to predict symmetry in behavior. The study suggests the importance of incorporating dynamic trends into the forecasting process, which can be accomplished through the use of longitudinal data.     

Neighborhoods,cars, and commuting in New York City: A discrete choice approach

Cities around the world are trying out a multitude of transportation policy and investment alternatives with the aim of reducing car-induced externalities. However, without a solid understanding of how people make their transportation and residential location choices, it is hard to tell which of these policies and investments are really doing the job and which are wasting precious city resources. The focus of this paper is the determinants of car ownership and car use for commuting. Using survey data from 1997 to 1998 collected in New York City, this paper uses discrete choice econometrics to estimate a model of the choices of car ownership and commute mode while also modeling the related choice of residential location.The main story told by this analysis is that New Yorkers are more sensitive to changes in travel time than they are to changes in travel cost. The model predicts that the most effective ways to reduce both auto ownership and car commuting involve changing the relative travel times for cars and transit, making transit trips faster by increasing both the frequency and the speed of service and making auto trips slower – perhaps simply by allowing traffic congestion. Population density also appears to have a substantial effect on car ownership in New York.     

Characterising and predicting car ownership using rough sets

This paper applies the relatively new knowledge discovery technique of Rough set analysis to identify the factors that influence the level of car ownership in a household. The study uses the detailed Great Britain National Travel Survey data set which contains information on both household and individual travel behaviour. The knowledge extraction is done using the theory of Rough sets and is presented in the form of easily understood if-then statements or rules which reveal how each attribute influences car ownership behaviour. These rules can then be used to predict household car ownership from information held about previously unseen households and the classification performance of the rules can be assessed. The performance of this classification task is shown to be on a par with other reported studies in this area.     

Measuring the equity effects of a carbon charge on car commuters: A case study of Manchester Airport

This papers attempts to quantify the equity effect of a hypothesized economic instrument, a carbon charge on car commuters, for reducing carbon dioxide emissions produced by commuters on airport surface access. Manchester Airport is taken as a case study using staff Survey data from 2008 and 2010. Consumer welfare change is analysed for measuring the equity effects of carbon charge by user group, which considers the changes of travel mode choice, the carbon dioxide emissions reduction, the revenue from a carbon charge and how it is distributed. First, the individual carbon footprint in terms of gram passenger kilometre, and the damage cost of carbon by commuters on airport surface access are estimated. Next, the impact of carbon charge on travel behaviour is investigated by the nested logit model. Finally, the net effect of carbon charges is assessed by travel mode user, gender, job type, and age group. The results show some impacts of the carbon charge on car users and carbon reduction, and the positive effects on lower income group and less carbon commuters. The quantified results provide the evidences for the mitigation policies to combine monetary incentives with disincentives for travel behaviour change, and demonstrate the different equity effects among commuter groups.     

Changing household car ownership level and life cycle events: an action in anticipation or an action on occurrence

This paper analyzes households’ decision to change their car ownership level in response to actions/decisions regarding mobility issues and other household events. Following recent literature on the importance of critical events for mobility decisions, it focuses on the relationship between specific events (e.g. childbirth and buying an extra car), rather than trying to explain the status of car ownership from a set of stationary explanatory variables. In particular, it is hypothesized that changes in household car ownership level take place in response to stressors, resulting from changed household needs or aspirations. The study includes a broad range of events. Apart from changes in work status, employer and residential location, it analyzes demographic events such as household formation and childbirth. Also, it scrutinizes the temporal sequence in which chains of related events are most likely to occur. To this end, data from a retrospective survey that records respondents’ car ownership status, as well as residential and household situation over the past 20 years are used. A panel analysis has been carried out to disentangle typical relationships. The results suggest that strong and simultaneous relationships exist between car ownership changes and household formation and dissolution processes. Childbirth and residential relocation invoke car ownership changes. Changes are also made in anticipation of future events such as employer change and childbirth. Childbirth is associated with increasing the number of cars, whereas the effect of employer change goes the opposite way. Job change increases the probability of car ownership change in the following year.     

A causal analysis of car ownership and transit use

The causal structure underlying household mobility is examined in this study using a sample obtained from the Dutch National Mobility Panel survey. The results indicate that car ownership is strongly associated with mode use, but that it has no influence on weekly person trip generation by household members. Characteristics of mode use are examined through a causal analysis of changes in car ownership, number of drivers, number of car trips, and number of transit trips. It is shown that observed changes in mode use cannot be adequately explained by assuming that a change in transit use influences car use. The finding suggests that the increase in car use, which is a consequence of increasing car ownership, may not be suppressed by improving public transit.     

A latent class joint mode and departure time choice model for the Greater Toronto and Hamilton Area

This paper presents a closed-form Latent Class Model (LCM) of joint mode and departure time choices. The proposed LCM offers compound substitution patterns between the two choices. The class-specific choice models are of two opposing nesting structures, each of which provides expected maximum utility feedback to the corresponding class membership model. Such feedback allows switching class membership in response to the changes in choice contexts. The model is used for an empirical investigation of commuting mode and departure time choices in the Greater Toronto and Hamilton Area (GTHA) by using a large sample household travel survey dataset. The empirical model reveals that overall 38% of the commuters in the GTHA are more likely to switch modes than departure times and 62% of them are more likely to do the reverse. The empirical model also reveals that the average Subjective Value of Travel Time Savings (SVTTS) of the commuters in the GTHA can be as low as 3 dollars if a single choice pattern of departure time choices nested within mode choices is considered. It can also be as high as 67 dollars if the opposite nesting structure is assumed. However, the LCM estimates the average SVTTS to be around 27 dollars in the GTHA. An empirical scenario analysis by using the estimated model indicates that a 50% increase in morning peak period car travel time does not sway more than 4% of commuters from the morning peak period.

     

A panel data switching regression model of mobility and car ownership

The objective of this paper is to present a panel data model of car ownership and mobility. Unobserved heterogeneity is controlled for by including correlated random effects in the equations describing car ownership and mobility. A mass-points approach is adopted to control for unobserved heterogeneity. The results show that decisions concerning the first car in the household are difficult to affect; a large number of households are inclined to keep one car. Second car ownership may be more sensitive to changes in the observed contributing factors. This suggests that in The Netherlands policies aimed at changing second car ownership will be more successful than those aimed at influencing decisions concerning the first car in households. A major part of the correlation between the unobservables in the car ownership and the mobility equations is attributable to random effects. The time-variant errors of the mobility equations are not significantly correlated to car ownership decisions. This implies that mobility can only be influenced to a small extent by policy makers without measures aimed at reducing (second) car ownership.     

Patterns of car usage and restraint modelling

Transport demand forecasting procedures have traditionally employed household based modal split models implicitly assuming a selection of mode for each trip based on relative generalised cost. A detailed examination of the trip patterns of a sample of household in West Yorkshire shows that in fact there is little discretionary choice of public transport; public transport trips in car owning households generally being explained in terms of the specific unavailability of the car for such trips. Two versions of a category analysis model for modal split are based on this observation and applied to household data for Glamorgan and Monmouthshire to show that such a procedure is workable and produces results comparing favourably with traditional approaches. The likely implications of three types of restraint policy are examined and it is concluded that the existing interdependence in trip patterns and modal choice within the household is of great significance in determining their effects. In particular it appears that positive attempts to increase vehicle occupancy at the peak are likely to be more favourable to public transport finances than the more negative policies to restrain use of the car for journey to work, or second car ownership.