Residential location,vehicle ownership and travel in Asia: a comparative analysis of Kei-Han-Shin and Kuala Lumpur metropolitan areas

The study examines the relationships between residential location, vehicle ownership and mobility in two metropolitan areas of Asia, Kei-Han-Shin area of Japan and Kuala Lumpur area of Malaysia. It shows that, behind apparent similarities of household auto ownership and travel time expenditure per household member, there are many causal relationships that are distinct between the areas. The similarities and differences between the two areas point to the conjecture that the evolution of a metropolitan area may be unique and path dependent, being heavily influenced by the history and culture of the locale, spatial and geographical constraints, and historical progression in infrastructure development.

Financing public transport systems in Kuala Lumpur,Malaysia: challenges and prospects

Most major cities across the world today are facing an intractable challenge of financing public transport. In Kuala Lumpur for example, public transport services are somewhat poor in part because of the failure of major operators to secure ample funding. Previous funding programs implemented in the city have failed to produce a replicable model for financing public transport. Due to numerous financial problems and the dismal performance of privately owned transport firms, the State has in the recent past emerged as a key source of funding for the public transport sector in Kuala Lumpur. This article argues that, despite the insuperable challenges, prospects for the future funding of public transport in Kuala Lumpur appears to be good. The article also draws lessons from both Tokyo and Hong Kong. In order to address the funding deficit facing the public transport industry in the city it is crucial that more viable strategies and policies such as value capture and public–private sector partnerships are adopted by the urban authorities.

Singapore motorisation restraint and its implications on travel behaviour and urban sustainability

The example of Singapore shows that rapid urban and economic growth does not have to bring traffic congestion and pollution. Singapore has chosen to restrain car traffic demand due to its limited land supply. Transport policy based on balanced development of road and transit infrastructure and restraint of traffic has been consistently implemented for the past 30 years. Combined with land use planning, it resulted in a modern transport system, which is free from major congestion and provides users with different travel alternatives. As the economic growth caused a substantial increase in demand for cars, several pricing policies were introduced with the aim of restraining car ownership and usage. Growth of the vehicle population is now controlled and potentially congested roads are subject to road pricing. These measures help to keep the roads free from major congestion, maintain car share of work trips below 25% and keep the transport energy usage low. Although Singapore conditions are in many aspects unique, its travel demand experience can provide useful lessons for other rapidly growing cities in Asia.

A case for measuring individuals’ access to private-vehicle travel as a matter of degrees: lessons from focus groups with Mexican immigrants in California

In auto-oriented communities, access to an automobile is essential for good mobility, but not everyone owns a car or is able to drive. Little is known about how individuals in these circumstances might still use vehicles for transportation. To provide insight on the nature of vehicle use by those with potentially limited vehicle access, we present qualitative findings from focus groups with recent Mexican immigrants living in California, half of whom owned no cars. Our results demonstrate varying degrees of participants’ access to vehicle travel not always corresponding to auto ownership, with extensive sharing of cars, borrowing of cars, and getting rides. We describe the different dimensions of vehicle access that participants experienced and identify specific factors that seemed to influence their access levels. We discuss the implications of our findings for transportation policy and future research.

Variation of households<Emphasis Type="Bold">’</Emphasis> car ownership across time: application of a panel data model

For economic and environmental policy formulation and with the effort of creating less car dependent societies, it is important to study the changing characteristics of car ownership in a household through time as well as factors responsible of these variations. There is a vast body of literature on empirical studies of car ownership and use. These studies have investigated the socio-economic background of the decision maker, the built environment and the perception associated with owning a car as determinant factors of car ownership and use. In most cases, these analyses have been carried out using cross-sectional data sets. However, the analysis of factors determining changes in travel behavior of an individual or household requires information on their behavior over time (longitudinal data set). In this study, the German Mobility Panel (1996–2006) is used to examine variation of car ownership through time and across households. The panel data modeling results showed that there are variations of car ownership between households whereas changes in car ownership of a given household over time (within household variations) are insignificant. The influence of other factors such as the households’ socio-economic background, the availability of public transportation and shopping/leisure facilities, perception on parking difficulties and satisfaction with existing public transportation services on the car owning characteristics of households is also presented and discussed in this paper.

Utilization patterns of park and ride facilities among Kuala Lumpur commuters

A parking utilization survey was undertaken with the main objective of analyzing and comparing the daily workday utilization patterns of two main park and ride stations within the Kuala Lumpur conurbation. This study also aimed to gauge the level of usage of the park and ride facilities. The findings showed that the overall utilization pattern of the facilities was very high with a utilization rate of between 80 and 95%. The stations, however, recorded a contrasting accumulation pattern. The study further revealed that most of the rail-based suburban park and ride users were long term parkers. The results of this study are comparable to results of similar studies in Seoul, Calgary, Tyne and Wear and others. Since parking availability is an important factor that has influence on the behavior of a park and ride user, more accurate information relating to the supply and demand of the park and ride facility will assist in planning new transport infrastructure.

Evaluating the pedestrian realm: instrumental rationality,communicative rationality and phenomenology

Following the passage of ISTEA, increased attention to pedestrian planning has led to the development of pedestrian plans, particularly at the metropolitan and municipal levels. This has raised the issue of how cities and metropolitan areas evaluate the walkability of the pedestrian realm and identify improvement projects. Three approaches to evaluating the pedestrian realm are examined: instrumental rationality, communicative rationality, and phenomenology. Case studies demonstrating the application of these approaches to the development of pedestrian plans are examined in the Phoenix metropolitan area, Portland, Oregon, and Cambridge, Massachusetts.

Estimation of the determinants of bicycle mode share for the journey to work using census data

A model is presented that relates the proportion of bicycle journeys to work for English and Welsh electoral wards to relevant socio-economic, transport and physical variables. A number of previous studies have exploited existing disaggregate data sets. This study uses UK 2001 census data, is based on a logistic regression model and provides complementary evidence based on aggregate data for the determinants of cycle choice. It suggests a saturation level for bicycle use of 43%. Smaller proportions cycle in wards with more females and higher car ownership. The physical condition of the highway, rainfall and temperature each have an effect on the proportion that cycles to work, but the most significant physical variable is hilliness. The proportion of bicycle route that is off-road is shown to be significant, although it displays a low elasticity (+0.049) and this contrasts with more significant changes usually forecast by models constructed from stated preference based data. Forecasting shows the trend in car ownership has a significant effect on cycle use and offsets the positive effect of the provision of off-road routes for cycle traffic but only in districts that are moderately hilly or hilly. The provision of infrastructure alone appears insufficient to engender higher levels of cycling.

Using census aggregates to proxy for household characteristics: an application to vehicle ownership

Traditionally, researchers studying transportation choice have used data either acquired from household surveys or broad, region-wide aggregates. At the disaggregate level, researchers usually do not have access to important variables or observations. This study investigates the potential usefulness of a proxy approach to modeling discrete choice vehicle ownership: substituting narrow area-based aggregate proxies for missing micro-level explanatory variables by accessing large, publicly maintained datasets. We use data from the 2000 Bay Area Travel Survey (BATS) and the contemporaneous U.S. Census file to compare three models of vehicle ownership, drawing area-wide proxies from increasing levels of aggregation. The models with proxies are compared with a parallel model that uses only survey data. The results indicate that the proxy models are preferred in terms of model selection criteria, and predict vehicle ownership as well or better than the survey model. Parameter values produced by the proxy method effectively approximate those returned by household survey models in terms of coefficient sign and significance, particularly when the aggregate variables are representative of their household-level counterparts. The proxy model with the narrowest level of aggregation achieved the best fit, coefficient precision, and percentage of correct prediction.

Land use-transportation scenario planning: promise and reality

Land use-transportation scenario planning has become increasingly common in regional and sub-regional planning processes. The technique promises to provide citizens with opportunities to engage in constructive dialogue about the future of their communities, and to serve as a basis for assertive action to direct the course of that future. This study reviews 80 scenario planning projects from more than 50 U.S. metropolitan areas. The analysis reveals important gaps in the practice of scenario planning—particularly in the areas of public participation, methodology, and institutional structures—and recent efforts to address the shortcomings.

Separation of car-dependent commuters from normal-choice riders in mode-choice analysis

The ever-increasing use of cars is a big problem in metropolitan areas. To manage the traffic stream and alleviate air pollution, most metropolitan governments are attempting to discourage the use of cars. Nevertheless, the results have not been satisfactory. It is well known that normal-choice riders choose their travel mode based on utility, which is determined by mode-specific impedances and individual characteristics. On the other hand, this study focuses on identifying car-dependent commuters who tend to keep driving cars regardless of the circumstances they are confronted with. For this study, psychometric factors characterizing car-dependent commuters were investigated. However, the performance of the mode-choice model was not sufficiently enhanced despite incorporation of the psychometric factors. The performance improved considerably when the car-dependent commuters were excluded. Based on psychometric factors, the support vector machine successfully separated the car-dependent commuters from normal-choice riders.

What do people know about their public transport options?

This paper studies the memory representations of residents regarding the public transport system in their city. Telephone interviews were conducted with a representative sample of 204 inhabitants in a selected residential inner-city area in Stockholm. Route knowledge questions, recognition tasks, free-recall tasks and estimations of service frequency were used to explore memory representations. The results showed that, in general, residents in metropolitan areas have good knowledge of the public transport options along well-known transport corridors. The memory representation of lesser-known transport corridors tends to be of a poorer quality. In the results presented here, the variables gender, age, employment status, level of education and car availability had no correlation with the quality of the memory representation, but experience increased knowledge. Although frequent users of public transport had a more detailed representation of the system, the less frequent users also had a considerable- and good-memory representation. An explorative hierarchy for representation of public transport lines in the memory is proposed. It is hypothesised that memory representations of a transport line can be affected by the following three factors: the extent to which a line is visible in the urban area, the straightness of the routes and whether or not stops are labelled, for example, by destination area. Simply put, these factors determine how well a person knows a line. It was found that people first remember a commuter train and a trunk bus line, followed by metro lines and suburban buses and finally normal inner-city buses with the poorest anchorage in memory.

The ambivalence of ridesharing

Ridesharing is quite a popular topic of discussion among transport authority personnel. It is perceived to be a viable alternative to classical modes of transportation, and receives a great deal of political support from transport planners. However, not much objective information is available on ridesharing behaviors. We use travel survey data to study the evolution of the ridesharing market in an urban area. Our study is based on data from four large-scale OD surveys conducted in the Greater Montreal Area (1987, 1993, 1998 and 2003). In the latest survey conducted in Montreal, car passengers were asked to identify the driver who gave them the opportunity to travel in this way. Their answers were classified according to the type of driver; for instance, a member of their household, a neighbor or a co-worker. We use this information to calibrate a model matching car passengers and car drivers belonging to the same household. This will be referred to as IHHR (intra-household ridesharing). Preliminary results reveal that approximately 70% of all trips made by car passengers are the result of IHHR. Furthermore, around 15% of those trips are questionable, in that they were exclusively generated for another individual’s purposes, consequently generating an additional trip for the journey back home. Moreover, this percentage increased over time. Objective data regarding ridesharing and its evolution in an urban area will undoubtedly help decision makers gain a clearer profile of this means of travel and help to realign attitudes on the issue.

Curbing automobile use for sustainable transportation: analysis of mode choice on short home-based trips

This paper analyzes transportation mode choice for short home-based trips using a 1999 activity survey from the Puget Sound region of Washington State, U.S.A. Short trips are defined as those within the 95th percentile walking distance in the data, here 1.40 miles (2.25 km). The mean walking distance was 0.4 miles (0.6 km). The mode distribution was automobile (75%), walk (23%), bicycle (1%), and bus (1%). Walk and bicycle are found less likely as the individual’s age increases. People are more likely to drive if they can or are accustomed to. People in multi-person families are less likely to walk or use bus, especially families with children. An environment that attracts people’s interest and provides activity opportunities encourages people to walk on short trips. Influencing people’s choice of transport mode on short trips should be an important part of efforts encouraging the use of non-automobile alternatives.

Institutional constraints on transport policymaking: the case of company cars in Israel

Transportation analysis emphasizes the necessity to internalize the transport externalities of car usage through taxation. Yet taxation decisions are often made with non-transport goals in mind. In such cases, transport policies are made ‘by the way.’ This paper examines such a case: Israel’s taxation policy on company cars. It shows that current taxation policies result in increasing numbers of company cars and growing numbers of transport users who are not sensitive to the marginal cost of car use and make excessive use of the car. As a result, a significant portion of Travel Demand Management (TDM) measures cannot affect this group. The Israeli case of company car tax reform demonstrates the problematic effect of a policy that does not take its overall consequences on other policy fields into account and thereby impairs efforts to reduce the negative impacts of the transport system. Also, it demonstrates the importance of institutional aspects of transport policymaking.

Effect of attitudes, habit and affective appraisal on mode choice: an application to university workers

Traditionally, car use and modal choice, in general, have been studied under the random utility framework, assuming that individuals choose a particular mode based on their own socio-economic characteristics and the attributes describing the available options. This approach has originated useful models which have been able to explain modal split. However, at the same time, it has received critics because of its poor characterization of human behaviour and the weakness of its assumptions. Research has suggested that socio-psychological factors could help to understand better the choice process. In this paper, attitudinal theory and its link to human behaviour were used to select attitudes, habit and affective appraisals as explanatory variables. They were measured using ad-hoc instruments, which were combined with a revealed preference questionnaire, in order to obtain information about the traveller and the chosen mode. This instrument was applied to a sample extracted from staff members of the University of Concepcion, Chile. Analyses of attitudinal variables showed that car use habit was positively correlated to attitude and positive emotions towards car, implying that breaking the vicious circle of car use through persuasive techniques might be difficult. Estimation of discrete choice models showed that attitudinal variables presented a significant contribution to modal utility, and helped to improve both fitness and statistical significance. Results showed that choice can be influenced by factors related to attitudes and affective appraisal, and that their study is necessary in order to achieve an effective car use reduction.

The transition to electric bikes in China: history and key reasons for rapid growth

Annual electric bike (e-bike) sales in China grew from 40,000 in 1998 to 10 million in 2005. This rapid transition from human-powered bicycles, buses and gasoline-powered scooters to an all-electric vehicle/fuel technology system is special in the evolution of transportation technology and, thus far, unique to China. We examine how and why e-bikes developed so quickly in China with particular focus on the key technical, economic, and political factors involved. This case study provides important insights to policy makers in China and abroad on how timely regulatory policy can change the purchase choice of millions and create a new mode of transportation. These lessons are especially important to China as it embarks on a large-scale transition to personal vehicles, but also to other countries seeking more sustainable forms of transportation.

Immigration, residential location, car ownership, and commuting behavior: a multivariate latent class analysis from California

Using latent class cluster analysis, this paper investigates the spatial, social, demographic, and economic determinants of immigrants’ joint distribution among travel time, mode choice, and departure time for work using the 2000 Census long form data. Through a latent tree structure analysis, age, residential location, immigration stage, gender, personal income, and race are found to be the primary determinants in the workplace commute decision-making process. By defining several relatively homogeneous population segments, the likelihood of falling into each segment is found to differ across age groups and geography, with different indicators affecting each group differentially. This analysis complements past studies that used regression models to investigate socio-demographic indicators and their impact on travel behavior in two distinct ways: (a) analysis is done by considering travel time, mode choice, and departure time for work simultaneously, and (b) heterogeneity in behavior is accounted for using methods that identify different groups of behavior and then their determinants. Conclusively the method here is richer than many other methods used to study the ethnically diverse population of California and shows the addition of geographic location and latent segment identification to greatly improve our understanding of specific behaviors. It also provides evidence that immigrants are as diverse as the non-immigrant population and transportation policies need to be defined accordingly.

Uncertainty in traffic forecasts: literature review and new results for The Netherlands

This paper provides a review of transport model applications that not only provide a central traffic forecast (or forecasts for a few scenarios), but also quantify the uncertainty in the traffic forecasts in the form of a confidence interval or related measures. Both uncertainty that results from using uncertain inputs (e.g. on income) and uncertainty in the model itself are treated. The paper goes on to describe the methods used and the results obtained for a case study in quantifying uncertainty in traffic forecasts in The Netherlands.

A methodological approach for developing and assessing business models for flexible transport systems

Flexible transport services include a wide range of demand responsive transport systems that provide non-conventional passenger and freight transportation services. Several alternative business models varying according to the local market conditions, the socio-economic, legal, and institutional framework may be developed for the provision of Flexible Transport Systems (FTS). The objective of this paper is twofold: first to present an integrated methodological framework for developing and assessing alternative FTS business models and second to demonstrate its applicability to a case study regarding the prioritization of alternative FTS business models for the provision of flexible passenger transport services in Helsinki.