The indirect effect of the built environment on travel mode choice: A focus on recent movers

Many studies have demonstrated that the built environment has a strong impact on people's travel mode choice. However, the built environment also influences elements such as travel distance and car ownership, which might be the true predictors of which travel modes are chosen. In this study, we analyse the effects of changes in residential neighbourhood on changes in travel mode (for commute trips and leisure trips), both directly and indirectly through changes in car ownership, travel distances and travel attitudes. This study applies a structural equation modelling approach using quasi-longitudinal data from 1650 recently relocated residents in the city of Ghent, Belgium. Results indicate that the built environment has strong direct effects on active leisure trips and car use. However, distance (for car use) and attitudes (for active travel) were found to be important mediating variables. In sum, the effect of the built environment on travel mode choice might be more complex than commonly assumed as it partly seems mediated by travel distance and travel attitudes.     

Built environment diversities and activity–travel behaviour variations in Beijing, China

The association between built environment and travel behaviour has received considerable research attention in recent years. In an attempt to contribute to this growing literature, this paper investigates the connections between urban built environments and activity–travel patterns in Beijing, the capital city of China. We characterize the built environment in Beijing and establish associations between built environment and activity–travel behaviour in terms of car ownership, time spent for out-of-home activities, and daily trip frequencies and travel time. Activity diaries from 1119 respondents living in ten different neighbourhoods were collected by face-to-face interviews. A household-level structure equations model incorporating intra-household interactions is developed to analyse this data. The empirical results show that residents of different types of neighbourhoods in Beijing demonstrate significant differences in car ownership, time spent for out-of-home activities, trip rate, and travel time. Further, the characteristics of the built environment are found to have more significant impacts on the activity–travel behaviour of the male head than that of the female head.     

Causes and effects between attitudes,the built environment and car kilometres: A longitudinal analysis

Travel-related attitudes are believed to affect the connections between the built environment and travel behaviour. Previous studies found supporting evidence for the residential self-selection hypothesis which suggests that the impact of the built environment on travel behaviour could be overestimated when attitudes are not accounted for. However, this hypothesis is under scrutiny as the reverse causality hypothesis, which implies a reverse direction of influence from the built environment towards attitudes, is receiving increased attention in recent research. This study tests both directions of influence by means of cross-sectional and longitudinal structural equation models. GPS tracking is used to assess changes in travel behaviour in terms of car kilometres travelled. The outcomes show stronger reverse causality effects than residential self-selection effects and that land-use policies significantly reduce car kilometres travelled. Moreover, the longitudinal models show that the built environment characteristics provide a better explanation for changes in car kilometres travelled than the travel-related attitudes. This contradicts the cross-sectional analysis where associations between car kilometres travelled and travel-related attitudes were stronger. This highlights the need for more longitudinal studies in this field.     

Nonlinear effects of residential and workplace built environment on car dependence

The relationships between the built environment (BE) and car dependence have been thoroughly evaluated, with a primary focus on the residential BE; however, the effects of the BE at workplaces have remained largely unexplored. Little is known about the potential nonlinear effects of the BE at both locations. Using data from a household travel survey in Changchun, China, we aimed to reveal the nonlinear effects of the residential and workplace BE on car dependence by building a gradient boosting decision trees model. The results show that the BE at both locations has strong explanatory power for car ownership and car purchasing intention. With relative contributions values of 17.90% and 18.13%, respectively, the BE at workplaces contributes less to explaining the two dependent variables than the BE at residences. All BE attributes show nonlinear effects on car ownership, and car purchasing intention and the effects differ between residential and workplace locations.     

The built environment and vehicle ownership modeling: Evidence from 32 diverse regions in the U.S.

Vehicle ownership is an important determinant of the travel demand forecasting process. Vehicle ownership models are used by policy makers to identify factors that affect vehicle miles traveled, and therefore address problems related to energy consumption, air pollution, and traffic congestion. For the conventional travel demand forecasting, it logically follows land use forecasting, before trip generation, which is commonly treated as step one. The most critical limitation of the vehicle ownership models, especially in the conventional process, is that they are often related mainly to sociodemographic variables, not so much to built environmental variables. In this study, by pooling regional household travel survey data from 32 diverse regions (almost 92,000 households) of the U.S., and by controlling for socio-demographic and the built environmental variables, we estimated a vehicle ownership model that contributes to the understanding of vehicle ownership and improves the accuracy of travel demand forecasts. Two main findings of this research are: 1) The number of vehicles owned by a household increases with socio-demographic variables and decreases with almost all of the built environmental variables. For the urban planning and design practices, this finding suggests that car shedding occurs as built environments become more dense, mixed, connected, and transit-served. 2) We used both count regression and discrete choice models, and the results suggest that count regression models have better predictive accuracy. The model developed in this study can be directly used for travel demand modeling and forecasting by metropolitan planning organizations.     

Built for active travel? Investigating the contextual effects of the built environment on transportation mode choice

The study investigates the role of the built environment attributes and their contextual effects on travel behaviour. The study utilized a dataset of 4739 respondents elicited from an online survey distributed in Hamilton City, Canada. A Nested Logit (NL) model and a quadratic polynomial trend surface are employed to spatially investigate the determinants influencing mode choice behaviour. The study contributes to our understanding of how geography moderates the impact of built environment attributes on mode choice behaviour. Socioeconomic demographics are found to play a pivotal role in explaining Hamiltonians' mode choice behaviour. For built environment attributes, sidewalk density is positively associated with walking and public transit use. Moreover, bike lane density is positively associated with biking and negatively associated with public transit use. Regarding land-use entropy (mix), the results show that high land-use entropy is negatively associated with choosing the car as a passenger travel mode. From a contextual perspective, the results affirmed that the influence of built environment attributes is not equally efficacious across the city. Improving the built environment attributes across the city reveals a substantial increase in walking and biking while decreasing the probability of choosing other modes. However, it is noteworthy to mention that the influence of improving the built environment is not homogeneous over geography.     

Exploring the effects of the rural built environment on household car ownership after controlling for preference and attitude: Evidence from Sichuan,China

With the rapid infrastructure development and economic growth in China, household car ownership in the country's rural areas has changed dramatically in the past 16 years. The total number of cars owned by households in rural areas is currently 12 times higher than it was 16 years ago. The exploration of the effects of the built environment on household car ownership in China's rural areas is worthwhile. However, few studies have investigated this topic. To fill in the research gap, this work collected 374 household data from rural areas in China to examine the effects of the built environment in Sichuan's rural areas on the number of cars in a household. It considered family structure, socioeconomic characteristics, and individual's perceptions of the built environment, preferences towards the built environment and attitudes towards car ownership (shortened to perceptions, preferences and attitudes from now on). Geographic information system (GIS) technology, combined with on-site measurement, was used for data collection. The multinomial logit model was applied for estimation. Household structure and the built environment (including the perceived built environment and the objective built environment) significantly influence the number of cars in a household. By contrast, preference and attitude attributes have less influence on car ownership. Most of the findings are in line with the literature in the context of Chinese cities. Nevertheless, new results are also found. For example, rural hukou, and building density have significant positive impacts on household car ownership in China's rural areas, which is in contrast with their effects on cities. As the first study on rural areas in China, this research provides some insights for rural planners and policymakers to understand better the relationship between built environment and household car ownership.     

An exploratory analysis of relationships between socioeconomic,land use,activity participation variables and travel patterns

This paper aims to find relations between the socioeconomic characteristics, activity participation, land use patterns and travel behavior of the residents in the São Paulo Metropolitan Area (SPMA) by using Exploratory Multivariate Data Analysis (EMDA) techniques. The variables influencing travel pattern choices are investigated using: (a) Cluster Analysis (CA), grouping and characterizing the Traffic Zones (TZ), proposing the independent variable called Origin Cluster and, (b) Decision Tree (DT) to find a priori unknown relations among socioeconomic characteristics, land use attributes of the origin TZ and destination choices. The analysis was based on the origin–destination home-interview survey carried out in SPMA in 1997. The DT application revealed the variables of greatest influence on the travel pattern choice. The most important independent variable considered by DT is car ownership, followed by the Use of Transportation “credits” for Transit tariff, and, finally, activity participation variables and Origin Cluster. With these results, it was possible to analyze the influence of a family income, car ownership, position of the individual in the family, use of transportation “credits” for transit tariff (mainly for travel mode sequence choice), activities participation (activity sequence choice) and Origin Cluster (destination/travel distance choice).     

Interdependences between household residential and car ownership behavior: a life history analysis

Once a transportation system is built or a land-use policy is carried out, it influences people’s travel behavior and their lives for a long time period. It is therefore important for policy makers to understand people’s decisions on travel behavior and lives over a longer time period. However, little has been known about the interdependences between life domains, especially over the life course (i.e., biographical interdependences) in the context of residential and car ownership behavior. To fill this gap, this study aims to clarify households’ biographical interdependences relating to residential and car ownership biographies by explicitly incorporating the influence of household structure and employment/education biographies. Biography is defined based on a general concept of mobility that indicates a change occurring in a life domain. For this purpose, a Web-based life history survey was conducted in November 2010 and 1000 households living in major Japanese cities provided valid data. Aggregate analysis and exhaustive CHAID analysis were carried out, focusing on the occurrence times of mobilities in each biography. Results confirm obvious two-way cause–effect relationships over the life course between residential and car ownership biographies that are further influenced by household structure and employment/education biographies. Especially, not only short-term but also long-term state dependence and future expectations within and across life domains are clarified. Household structure and employment/education biographies are found to be more influential on residential biography than car ownership biography. Though residential biography is seen to be more influential on car ownership biography, the other two biographies also play an important role in explaining the car ownership mobility decision. All these findings suggest the necessity of developing intra-domain and inter-domain biographical interdependence models with flexible structures that capture the influences of state dependence and future expectations over different time scales in the life course in a unified framework.     

Structures of commitment in mode use: a comparison of Switzerland, Germany and Great Britain

Travellers commit themselves to particular behaviours through the ownership of cars and season tickets. They trade a large one-off payment for low or zero marginal cost at the point of use. It can be assumed that these commitments influence travel behaviour. To the knowledge of the authors there is no literature which addresses the choice between the commitment to the one or the other mode and its impacts on travel behaviour.The paper presents models using structural equation modelling to test a-priori hypotheses on the paths linking car-availability, season-ticket-ownership and modal usage. Modal usage is operationalised as the number of trips by car, public transport, or as the distances travelled by car or public transport. The models are based on three different surveys: Switzerland, Germany and Great Britain. The results confirm the dominance of car-availability, which drives the other variables, but the relationships are more complicated than generally assumed.     

School travel mode choice in Beijing,China

This study explores school travel mode choice behavior of 7–18 year-old students in Beijing, China, based on the data collected in Fifth Travel Survey of Beijing Inhabitants. The integration of tree-based and logit-based models is employed to examine the influence of key variables on school travel mode choice. In particular, the tree-based model is used to preliminarily select the traits which have a statistical effect on mode choice, and the logit-based model is used to provide deeper understanding of the underlying decision processes and the correlation effects of the variables. Results show that car ownership, poor walking/cycling environment, and adults' convenience for escorting students significantly stimulate the use of cars in school commuting. Students are more inclined to choose cars when their departure time is at rush hour compared to the other time. Moreover, the longer distance encourages the use of motorized transport, where the households with local hukou (usually related to the car ownership and other welfares) are more willing to drive their children to school. A number of recommendations on car restraint, sustainable travel environment improvement, different working hour implementing, and educational resources layout for the encouragement and promotion of sustainable travel practices are lastly proposed.     

The multiplicity of self-selection: What do travel attitudes influence first,residential location or work place?

Residential self-selection has been widely considered as an important issue in quantifying the impacts of the residential built environment on travel behavior and much empirical evidence regarding the nature and magnitude of the self-selection effect has been reported. Nevertheless, people may be based on travel attitudes/needs to self-select not only residential location, but also work place, car ownership, etc. In other words, the impacts of long-term decisions other than residential location choices (e.g., decisions on work place, car ownership, etc.) on travel behavior may also be biased by the self-selection effect. However, self-selection concerning these long-term decisions has not been explored much in the travel behavior literature. The role of residential self-selection would not be properly evaluated if self-selections concerning other long-term decisions were not considered because they are often related. This paper addresses this research gap in the travel behavior literature by exploring the multiplicity of travel-based self-selection. We jointly examine the possible self-selections concerning residential location, workplace, commuting distance and car ownership in an integrated framework, taking into consideration the interrelationships among these decisions. Data are derived from an activity-travel diary survey conducted in 2016 in Beijing, China. We classify the respondents into two groups based on the choice order of their current residential and work locations and conduct a comparative analysis using structural equation models. It is found that self-selection exists in all long-term choices examined in the study. The choices of residential location and work place are found to be mutually dependent. Consequently, both choices have indirect impacts on travel behavior through the other choice.     

Mobility design as a means of promoting non-motorised travel behaviour? A literature review of concepts and findings on design functions

To promote non-motorised travel, many travel behaviour studies acknowledge the importance of the built environment to modal choice, for example with its density or mix of uses. From a mobility design theory perspective, however, objects and environments affect human perceptions, assessments and behaviour in at least three different ways: by their practical, aesthetic and emblematic functions. This review of existing evidence will argue that travel behaviour research has so far mainly focused on the practical function of the built environment. For that purpose, we systematically identified 56 relevant studies on the impacts of the built environment on non-motorised travel behaviour in the Web of Science database. The focus of research on the practical design function primary involves land use distribution, street network connectivity and the presence of walking and cycling facilities. Only a small number of papers address the aesthetic and emblematic functions. These show that the perceived attractiveness of an environment and evoked feelings of traffic safety increase the likelihood of walking and cycling. However, from a mobility design perspective, the results of the review indicate a gap regarding comprehensive research on the effects of the aesthetic and emblematic functions of the built environment. Further research involving these functions might contribute to a better understanding of how to promote non-motorised travel more effectively. Moreover, limitations related to survey techniques, regional distribution and the comparability of results were identified.     

Indicators of transport and accessibility problems in rural Australia

Australia belongs to a small group of countries that are low density but affluent, and characterised by very high vehicle ownership levels but very little public transport in rural areas. It is widely believed that there are few problems of mobility and accessibility, apart from long distances, because everyone has a car. A literature review generally confirms this perception, although there are hardly any suitable local case studies. An analysis of the rural areas of New South Wales, Victoria and South Australia sought indicators of transport-related problems, using mainly census data. While the basic urban/rural distinction is clearly defined, within the rural areas patterns of vehicle ownership are unusual, and in the remotest areas are not as high as would be expected. Relationships with socio-economic variables are not consistent. Accessibility measures are incorporated in the analysis, and a travel needs index suggested. Appropriate case studies are required to establish travel behaviour patterns and the responses of disadvantaged groups.     

Investigating household vehicle ownership,mode choice and trip sharing decisions using a combined revealed preference/stated preference Nested Logit model: case study in Bangkok Metropolitan Region

This study proposes a Nested Logit model to investigate household travel behaviour in respect to vehicle ownership, mode choice and trip sharing decisions. The model is analysed using revealed preference (RP) and stated preference (SP) data since a combined estimation of RP/SP data is an effective method of expressing complex travel behaviour and forecasting travel demand for new transport services. In the proposed model, the nesting structure has two levels. The upper level shows car ownership, motorcycle ownership, and no vehicle-ownership choices, and the lower level shows the mode choice combinations for two-traveller households. Trip sharing is considered as one of the mode-choice options in the model. The proposed model is analysed using data from the Bangkok Metropolitan Region. The analysis conducted informs that Central Business District (CBD) travel, long distance travel, household income, job status, age of travellers and presence of school children in households are key aspects in household travel decisions. Based on these aspects, households make important decisions on vehicle ownership, mode choice and trip sharing. In addition, this study reveals commuters’ hidden preferences for modes that are not in existence, in particular the Mass Rapid Transit System in the Bangkok Metropolitan Region due to be fully implemented in 2010.     

Exploring transport to arts and cultural activities as a facilitator of social inclusion

This paper explores the relationship between travel and social inclusion in relation to a relatively rarely examined group of travel destinations—arts and cultural activities. This paper examines travel behaviour to arts and cultural activities and how this relates to social inclusion. Research literature associated with these issues is examined and then an analysis of a household travel survey in Melbourne, Australia, is undertaken to explore how travel to arts and cultural activities varies by income, car ownership and location. The paper outlines a range of evidence linking participation in arts and cultural activities and positive outcomes for social inclusion. Arts and cultural activities do not fit well into traditional household travel survey definitions of trip purposes. There is also no definitional difference between travel to activities and ‘participation’ or ‘attendance’ in arts and cultural activities. This is unfortunate since social outcomes may vary by participation or attendance. Travel survey analysis shows that like other activities trip rates to arts and cultural activities increase with income. However higher participation is demonstrated for zero- and one-car households, which contrasts with previous research of work, education and social travel. Higher participation is also demonstrated for those living in inner parts of the city. The paper suggests that most travel to arts and cultural activity is quite localised and hence much travel may be led by the diversity and range of local opportunities provided. These are particularly high in inner parts of the city. A high share of travel is also demonstrated for older people, who are thought to have the time and desire for greater participation in arts and cultural activities.     

Residential self-selection and travel behaviour: What are the effects of attitudes,reasons for location choice and the built environment?

In studies of the effect of built environment on travel behaviour, residential self-selection is an increasingly important issue. Self-selection implies that households locate in places that provide them with conducive conditions for their preferred way of travelling. In these studies, it is assumed that attitudes toward different travel modes are an important factor in location choice, and that households are unconstrained in choosing their preferred residential location. This paper challenges these assumptions, by distinguishing between the more passive travel attitude and travel considerations as a deliberate reason to locate in a certain place. Based on a survey among 355 recently relocated households in Dutch TOD locations, we find that the association between travel attitude and residential environment is weak, and that the association between travel attitude and travel as a factor in location choice is moderate at best. Multivariate models show that both travel attitude and travel being a reason for location choice influence travel mode use, suggesting that travel attitude is insufficient to fully reflect self-selection processes. In comparison to other travel modes, train travel is most influenced by the fact whether residents deliberately chose to live in an environment conducive to using this mode.     

Interrelations between travel mode choice and trip distance: trends in Germany 1976–2002

In recent decades, trends in travel behaviour have been characterised by increasing trip distances and a modal shift towards the private car. This paper reports findings from longitudinal analyses of the German nation-wide travel survey KONTIV for the period 1976–2002. It focuses on travel mode choice, subdivided by distance categories, and also takes car availability and city size into account. In addition, trends in car availability itself are examined by city size categories. The results indicate that even within the same distance categories car use has considerably increased. In some cases bicycle use has increased as well. Gains in the use of the private car are mainly at the expense of trips on foot and by public transport. Accordingly, the shift in modal split towards the car is not (only) caused by increasing trip distances but took place even within distance classes. Once car availability is taken into account, the modal shifts appear to be considerably weaker. This suggests that once car availability is held constant the decision rationales of mode choice for a certain trip distance have remained relatively stable. The increase in motorisation over the study period was considerably weaker in large cities than in small towns, although the cities started from a lower level in the 1970s. Thus, the motorisation divide between cities on the one hand, and suburban and rural areas on the other hand has become ever wider. For travel mode choice, the picture is similar. What is more, the results suggest that even car owners are more inclined to walk a given distance in the cities than in small towns, even more so if they live in a central urban area. The built environment, thus, appears to have a strong impact on whether an available car is used or not.     

Understanding the process that gives rise to household car ownership level changes

Quantitative studies have revealed that changes to the number of cars owned by households are more likely to occur at the time of life events. However, causal explanations of such relationships are either absent or lacking evidence. To address this knowledge gap, this paper presents a qualitative study which enabled the development of a new conceptual framework to explain the process through which the number of cars owned by households changes over time. The framework emerged through an inductive analysis of 15 in-depth biographical interviews and was validated through a mixed methods survey of 184 households located in Bristol (UK). The following mechanisms of the process are identified: Life events alter roles, relationships, spatial contexts and lifestyle preferences. This can lead to a condition of stress which relates to a discrepancy between satisfaction with the current car ownership level and a more desirable alternative. Attempts to adjust to the new situation are made through processes of travel behaviour adaptation and consideration of whether the car ownership level ought to be altered. A propensity to change car ownership level can emerge from this. However, given the effort involved in taking action, households tend to resist making changes to their car ownership level in the short term. Action to change car ownership level is found to often be prompted by another external stimulus such as the receipt of a maintenance bill. A key message from the analysis is that changes in household car ownership level should be considered as the outcome of a continuous process of development over the life course, rather than as discrete decisions.     

Influences of rural built environment on travel mode choice of rural residents: The case of rural Sichuan

China has entered a stage in which new rural construction and urbanization are rapidly developing. Considerable changes are occurring in rural China, and the built environment is different from that in the past; such difference directly influences the travel mode choice of rural residents. However, our knowledge on how the rural built environment influences the travel mode choice of rural residents in China remains limited. To fill this gap, this study combines on-site measurement methods, geographic information system (GIS) technology, and activity diary survey to obtain basic data regarding the built environment and the daily activities of rural residents. The multinomial logit (MNL) model is used to explore the relationship between the rural built environment and the travel mode choice of rural residents. Results show that building density significantly positively affects private car trips. This finding challenges earlier urban built environment research due to the considerable gap between rural and urban areas. An increase in road density increases the travel frequency of electric bicycles and motorcycles. Accessibility perception and preferences positively affect the probability of choosing to walk. Safety and neighborhood harmony perception positively affect the travel frequency of motorcycles and private cars. Rural residents who prefer a safe living environment are likely to choose walking for their daily travel. Despite the considerable achievements in the construction of rural roads, the frequency of public transportation remains low for rural residents. Therefore, additional attention should be given to the investment and construction of public transport facilities during rural urbanization.