The relationship between instrumental, symbolic and affective factors as predictors of car use: A structural equation modeling approach

Traditionally, urban mobility has been studied from the utilitarian or practical viewpoint, focusing on instrumental motivations and ignoring symbolic and affective aspects that may play a relevant role. The purpose of this work is to analyze from a psychosocial perspective the influence of symbolic, affective, and instrumental motivations on the frequency of car use, taking into account diverse reasons for traveling. From a sample of the Spanish population, participants were 284 people (50.3% female), with a driver’s license, car owners and residents in cities of various sizes, who completed an anonymous questionnaire. The effect of each type of variable was estimated by a structural equation model. Results indicate that people’s affective link with their private vehicle explains 12% of frequency of car use, as a latent variable of different kinds of trips: visiting friends or relatives, going to work or to a study center, going shopping, or to leisure areas. The instrumental advantages associated with cars and thinking that it expresses one’s status predict the affective link with the car. These findings corroborate the relevance of the non-instrumental aspects involved in the selection of the means of transportation.     

Modeling time-of-day car use behavior: A Bayesian network approach

In this research, a Bayesian network (BN) approach is proposed to model the car use behavior of drivers by time of day and to analyze its relationship with driver and car characteristics. The proposed BN model can be categorized as a tree-augmented naive (TAN) Bayesian network. A latent class variable is included in this model to describe the unobserved heterogeneity of drivers. Both the structure and the parameters are learned from the dataset, which is extracted from GPS data collected in Toyota City, Japan. Based on inferences and evidence sensitivity analysis using the estimated TAN model, the effects of each single observed characteristic on car use measures are tested and found to be significant. The features of each category of the latent class are also analyzed. By testing the effect of each car use measure on every other measure, it is found that the correlations between car use measures are significant and should be considered in modeling car use behavior.     

A choice experiment on alternative fuel vehicle preferences of private car owners in the Netherlands

This paper presents results of an online stated choice experiment on preferences of Dutch private car owners for alternative fuel vehicles (AFVs) and their characteristics. Results show that negative preferences for alternative fuel vehicles are large, especially for the electric and fuel cell car, mostly as a result of their limited driving range and considerable refueling times. Preference for AFVs increases considerably with improvements on driving range, refueling time and fuel availability. Negative AFV preferences remain, however, also with substantial improvements in AFV characteristics; the remaining willingness to accept is on average € 10,000–€ 20,000 per AFV. Results from a mixed logit model show that consumer preferences for AFVs and AFV characteristics are heterogeneous to a large extent, in particular for the electric car, additional detour time and fuel time for the electric and fuel cell car. An interaction model reveals that annual mileage is by far the most important factor that determines heterogeneity in preferences for the electric and fuel cell car. When annual mileage increases, the preference for electric and fuel cell cars decreases substantially, whilst the willingness to pay for driving range increases substantially. Other variables such as using the car for holidays abroad and the daily commute also appear to be relevant for car choice.     

The effect of prices and income on car travel in the UK

The objective of this paper is to analyse the factors determining household car travel, and specifically the effects of household income and the prices of cars and motor fuels, and to explore the intertemporal pattern of adjustment. The question of asymmetry in the response to rising and falling income is also addressed. Such asymmetry may be caused by habit or resistance to change or the tendency to acquire habits to consume more easily than to abandon them. The impact of prices, the speed of adjustment and the resistance to change will be important in determining the possibility of influencing travel behaviour and specifically car use. The study utilises repeated cross-section data from the annual UK Family Expenditure Surveys and employs a pseudo-panel methodology. The results are compared with those for car ownership estimated on the basis of similar models.     

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.     

An empirical investigation of the impact of behavioural and psychographic consumer characteristics on car preferences: An integrated model of car type choice

Based on the data collected from a large-scale survey research of 1622 consumers, the present paper develops a disaggregate, compensatory choice model to collectively examine the impact of under-examined factors on consumer car type choice behaviour. All existing econometric forecasting models of vehicle type choice in the literature have so far considered objective measures as determinants of vehicle type choice. The proposed choice model considers 12 car-type alternatives and is successively extended to allow for choice probability distortions resulting from individual heterogeneity across a set of 30 variables, related to objective, behavioural and psychographic consumer characteristics. The results provide clear evidence that variables such as purpose of car use, prepurchase information source used, consumer’s proneness towards buying an ecological car, consumer’s involvement with cars, and consumer’s attachment to cars, significantly affect car type choice. The results yield important implications for manufacturers, transportation planners and researchers.     

Understanding engagement and disengagement from pro-environmental behaviour: The role of neutralization and affirmation techniques in maintaining persistence in and desistance from car use

Despite mounting evidence that car use is a prime culprit of global warming, our love affair with the car persists. General awareness of the environmental consequences of car usage is high but fails to correspond to moderated car use. This paper contributes to an understanding of how university students’ environmental beliefs affect decisions to engage in continued car use (persistence) and/or to discontinue or reduce car use (desistance). The aim of the research presented here was to explore the range of neutralizations and counter-neutralizations (affirmations) employed by students and to examine the ways in which they are used to justify and maintain either persistence or desistance in car use. The research consisted of six focus group sessions with thirty-four UK-based Higher Education students. Analysis of the study’s data highlights the range of neutralizations and counter-neutralizations employed by students in social settings. The article discusses the usefulness of neutralization theory in accounting for actual and/or intended non-environmentally friendly behaviour such as car use. In addition, the study’s findings are discussed in relation to prior research and to potential implications for public policy interventions which favour moderating car usage.     

A study on the determinants of private car ownership in China: Findings from the panel data

This study examines the determinants of private car ownership in China. The target cities are 32 provincial capital cities and the target period is from 2001 to 2011. In order to capture the individual effects (heterogeneity), the fixed and random effect models are adopted and compared, in which 8 explanatory variables are selected to include economic characteristics, urban characteristics, and transportation characteristics. Moreover, double natural logarithm model is employed to measure the elastic relationship between the private car ownership and regressors. The estimated results show that the fixed effect model performs better than pooled regression model and the random effect model. In addition, there are variations of private car ownership among cities and regions. Finally, the influence of factors responsible for these variations is also presented and discussed in this paper.     

Reducing car dependence in the heart of Europe: lessons from Germany,Austria, and Switzerland

Munich, Berlin, Hamburg, Vienna, and Zurich – the largest cities in Germany, Austria, and Switzerland – have significantly reduced the car share of trips over the past 25 years in spite of high motorisation rates. The key to their success has been a coordinated package of mutually reinforcing transport and land-use policies that have made car use slower, less convenient, and more costly, while increasing the safety, convenience, and feasibility of walking, cycling, and public transport. The mix of policies implemented in each city has been somewhat different. The German cities have done far more to promote cycling, while Zurich and Vienna offer more public transport service per capita at lower fares. All five of the cities have implemented roughly the same policies to promote walking, foster compact mixed-use development, and discourage car use. Of the car-restrictive policies, parking management has been by far the most important. The five case study cities demonstrate that it is possible to reduce car dependence even in affluent societies with high levels of car ownership and high expectations for quality of travel.     

A multinomial logit car use model for a megacity of the developing world: Istanbul

The increase in motor vehicle use is one of the important factors that cause traffic congestion, especially in megacities. Thus, the reasons behind this increase require serious attention. This paper offers an analysis of this kind, for a megacity from the developing world, Istanbul. A stratified multinomial logit model accounting for the availability of a second vehicle in the household is estimated for a sample drawn from a questionnaire to gather information of actual car use in Istanbul. This estimation is only possible through a unique data generation process that converts actual preferences into a choice study setting. In addition, a simulation study, generally utilized in the analyses of discrimination between certain layers of society, and a scenario analysis related to changes in income are also included in the paper for a better understanding of the nature of the topic. The results show that the behavior of households with a second vehicle available and not available varies significantly due to household, individual and professional-related characteristics.     

Car sharing in Norwegian urban areas: Examining interest,intention and the decision to enrol

This article’s objective is to investigate the effects of sociodemographic and residential built environments, directly and indirectly through personality traits, attitudes and car ownership, on willingness to use car sharing in the case of Norway. This is done by examining multiple dimensions of the adoption process: the stated general interest and intention to participate in car sharing among non-members, as well as the decision to enrol as a car sharing user by comparing members to non-members. In this study, we analyse web survey data from 2414 residents from urban areas in Norway, using three structural equation models. Our findings indicate that the adoption of car sharing is complexly related to car ownership, with a noteworthy discrepancy indicating greater car sharing interest, but lower car sharing membership rates among car owners. We also find that environmental concerns exert a clear positive effect on all three dimensions of the adoption process. Being careful with money is linked negatively to interest and intention to participate, while being sociable and agreeable exerts no effect. Car sharers’ sociodemographic profiles are typically that of early adopters, but many of the effects, especially on interest, are mediated by car ownership, environmental consciousness and/or being careful with money, rather than directly on the sociodemographic profiles. Finally, we find car sharing to be more prominent in denser areas, but we did not discover a clear connection with access to public transport.     

The relationship between land use and automobile travel utility: A Multiple Indicators Multiple Causes approach

The relationship between land use and the utility of automobile travel is examined by refining the utility concept, particularly by combining the microeconomic utility theory, which is concerned with the disutility of travel, and the perspective on the positive utility. A conceptual model is accordingly developed and then adjusted considering different purposes of travel. The purpose-specific models are tested through a Multiple Indicators Multiple Causes approach in Seoul, Korea, using datasets from a sample survey and geographic information systems. The major finding is that land use affects the utility mainly by changing synergy and affective utility rather than instrumental utility, which encompasses disutility variables. Among land use variables, the utility is found to be the most sensitive to the number of transit facilities for commuting and shopping travel and land use balance for leisure travel.     

Walking,cycling and the urban form: A Heckman selection model of active travel mode and distance by young adolescents

Physical inactivity of children and adolescents is a major public health challenge of the modern era but, when adequately promoted and nurtured, active travel offers immediate health benefits and forms future sustainable and healthy travel habits. This study explores jointly the choice and the extent of active travel of young adolescents while considering walking and cycling as distinct travel forms, controlling for objective urban form measures, and taking both a “street-buffer” looking at the immediate home surroundings and a “transport-zone” looking at wider neighborhoods. A Heckman selection model represents the distance covered while cycling (walking) given the mode choice being bicycle (walk) for a representative sample of 10–15 year-olds from the Capital Region of Denmark extracted from the Danish national travel survey. Results illustrate the necessity of different urban environments for walking and cycling, as the former relates to “street-buffer” urban form measures and the latter also to “transport-zone ” ones. Results also show that lessening the amount and the density of car traffic, diminishing the movement of heavy vehicles in local streets, reducing the conflict points with the density of intersections, and intervening on crash frequency and severity, would increase the probability and the amount of active travel by young adolescents. Last, results indicate that zones in rural areas and at a higher percentage of immigrants are likely to have lower probability and amount of active travel by young adolescents.     

Integrating parking behaviour in activity-based travel demand modelling: Investigation of the relationship between parking type choice and activity scheduling process

Traditionally, the parking choice/option is considered to be an important factor in only in the mode choice component of a four-stage travel demand modelling system. However, travel demand modelling has been undergoing a paradigm shift from the traditional trip-based approach to an activity-based approach. The activity-based approach is intended to capture the influences of different policy variables at various stages of activity-travel decision making processes. Parking is a key policy variable that captures land use and transportation interactions in urban areas. It is important that the influences of parking choice on activity scheduling behaviour be identified fully. This paper investigates this issue using a sample data set collected in Montreal, Canada. Parking type choice and activity scheduling decision (start time choice) are modelled jointly in order to identify the effects of parking type choice on activity scheduling behaviour. Empirical investigation gives strong evidence that parking type choice influences activity scheduling process. The empirical findings of this investigation challenge the validity of the traditional conception which considers parking choice as exogenous variable only in the mode choice component of travel demand models.     

A comparison of the sustainability of public and private transportation systems: Study of the Greater Toronto Area

A macroscopic assessment of the impacts of private and public transportation systems on the sustainability of the Greater Toronto Area (GTA) is undertaken from economic, environmental and social perspectives. The methodology draws upon the urban metabolism and sustainability indicators approaches to assessing urban sustainability, but compares modes in terms of passenger-kms. In assessing the economic sustainability of a city, transportation should be recognized as a product, a driver and a cost. In 1993, the traded costs of automobile use in the GTA were approximately balanced by the value of the automobile parts and assembly industry. But local transit costs 1/3 to 1/6 of the auto costs per person-km, in traded dollars, mainly because local labour is the primary cost.Public transportation is more sustainable from an environmental perspective. Automobile emissions are a major contributor to air pollution, which is a serious contemporary environmental health problem in Toronto. Public transportation modes are less energy intensive (including indirect energy consumption) and produce CO₂ at an order of magnitude lower, although these benefits are partially undermined by under-utilization of transit capacity and the source of electricity generation.The social benefits of automobile use are likely more significant than costs in determining GTA residents' preferential mode choice. The speed and access of auto use provide important economic benefits, e.g. relating to employment and product choice. Nevertheless, offsetting the service attributes of private transportation are large social costs in terms of accidents. The costs of automobile insurance provide one tangible measure of such negative impacts.In order to improve the sustainability of the GTA, innovative approaches are required for improving the performance level of public transportation or substantially reducing the need for the service level provided by automobiles. Efforts such as greater integration of bicycles with public transit, or construction of light-rail systems in wide roadways, might be considered. But to be sustainable overall, a transportation system has to be flexible and adaptable and so must combine a mixture of modes.     

Spatio-temporal analysis of car distance,greenhouse gases and the effect of built environment: A latent class regression analysis

This work examines the temporal–spatial variations of daily automobile distance traveled and greenhouse gas emissions (GHGs) and their association with built environment attributes and household socio-demographics. A GHGs household inventory is determined using link-level average speeds for a large and representative sample of households in three origin–destination surveys (1998, 2003 and 2008) in Montreal, Canada. For the emission inventories, different sources of data are combined including link-level average speeds in the network, vehicle occupancy levels and fuel consumption characteristics of the vehicle fleet. Urban form indicators over time such as population density, land use mix and transit accessibility are generated for each household in each of the three waves. A latent class (LC) regression modeling framework is then implemented to investigate the association of built environment and socio-demographics with GHGs and automobile distance traveled. Among other results, it is found that population density, transit accessibility and land-use mix have small but statistically significant negative impact on GHGs and car usage. Despite that this is in accordance with past studies, the estimated elasticities are greater than those reported in the literature for North American cities. Moreover, different household subpopulations are identified in which the effect of built environment varies significantly. Also, a reduction of the average GHGs at the household level is observed over time. According to our estimates, households produced 15% and 10% more GHGs in 1998 and 2003 respectively, compared to 2008. This reduction can be associated to the improvement of the fuel economy of vehicle fleet and the decrease of motor-vehicle usage – e.g., a decrease of 4% is observed for fuel efficiency rates and 12% for distance according to the raw average estimates from 1998 with respect to 2008. A strong link is also observed between socio-demographics and the two travel outcomes. While number of workers is positively associated with car distance and GHGs, low and medium income households pollute less than high-income households.     

Does Bus Rapid Transit Influence Urban Land Development and Property Values: A Review of the Literature

Abstract

Despite the proliferation of bus rapid transit (BRT) systems over the past few decades across developed and developing world cities, the impacts across these systems on the urban spatial development and property markets have not been comprehensively studied. The current paper attempts to fill this gap in the literature by reviewing the methodologies, underlying theories, and findings presented in the individual academic studies on BRT land-use and price impacts, mostly drawing on those that have focused on Latin American and Asian systems. The review shows that the land-use and value impacts have been less uniform across systems compared to such operational performance metrics as speed and travel time improvements. While predominantly relying on cross-sectional modeling techniques, the approaches used to evaluate land-use changes induced by the transit systems are not uniform either, with only some studies explicitly measuring changes in types of land use as opposed to simply land or rental price. The study also concludes that more rigorous evaluation is needed as to whether the BRT systems have improved accessibility for the populations that inhabited the corridors previously or whether, instead, the desired land value increases have in fact resulted in significant population displacement.     

Public financing of private freight rail infrastructure to reduce highway congestion: A case study of public policy and decision making in the United States

As goods movement continues to increase it is expected to outpace infrastructure capacity in the United States. Moving a larger share of goods by rail rather than truck is a potentially cost effective part of a solution. Freight rail not only offers a substitute for truck trips but is a cleaner, more energy efficient, and safer alternative. Recently a number of private freight rail projects have received public funding. The public funds are aimed at increasing freight rail capacity with the goal of diverting some goods currently moved by truck to rail. While the benefits of moving goods by rail are relatively clear, it is unclear if public decision makers can effectively identify strategic rail investments that will achieve their policy goals. This study critically examines the analytical methods, models, and data that are commonly used to support decisions to provide public funds for private freight rail projects. This is accomplished through a case study of California’s Trade Corridors Improvement Fund program which provided $680 million for 11 freight rail projects. The study’s contributions include identifying critical analytical flaws and challenges affecting the benefit estimates that public funding decisions rely on. Improvements to current evaluation methods are also identified as are regulatory reforms and policy interventions that may offer more effective and reliable outcomes.