The British colonial ‘divide and rule’ concept: its influence to transport access in inner city of George Town,Penang

George Town, Penang, is the oldest British colonial city in South East Asia. The colonial settlement layout in the inner city area is still intact today. The establishment of George Town as a trading centre had attracted immigrants from all over the world, especially from Asia (Chinese, Indians and Arabs). Recently, George Town has been enlisted under the UNESCO World Heritage Lists as an outstanding example of traditional multi-cultural settlement. The uniqueness of this inner city is that the formation of its urban pattern is the result of ‘divide and rule’ concept adopted by the British authority. Under the ‘divide and rule’ concept, these immigrants were located to settlement areas based on their ethnic background under one leader known as ‘kapitan’ (captain). The study finds that transport access in this inner city was influenced by the ‘divide and rule’ concept. Unlike formation of well-planned gridiron pattern in other British colonial cities such as in North America, Canada and Australia, the formation of the urban pattern in George Town has an irregular gridiron pattern. This type of urban pattern is typical under ‘divide and rule’ concept and this had indirectly influenced the setting and planning of the present street access and transport networks.

Transportation and land-use preferences and residents’ neighborhood choices: the sufficiency of compact development in the Atlanta region

This paper analyzes the transportation and land-use preference and actual neighborhood choices of a sample of 1,455 residents of metro Atlanta. We develop a stated-preference scale on which desires for neighborhood type are gauged, from preferences for low-density, auto-oriented environments to desires for compact, walkable, and transit-oriented neighborhoods. This scale is then related to desires for change in one’s own neighborhood characteristics after a hypothetical move. If all neighborhood preferences were equally likely to be satisfied, then neighborhood preferences would not be correlated with a desire for change. By contrast, in the current study, stronger preferences for a more walkable environment are associated with greater desire for change in one’s neighborhood characteristics. This suggests an undersupply of compact, walkable, and transit-friendly neighborhood types relative to current demand.

Nature or nurture: why do railroads carry greater freight share in the United States than in Europe?

During the 1950s, the share of freight carried by railroads was similar and declining in both the United States and Europe. By 2000, the railroads’ share of freight (measured in ton–kilometers) had reached 38% in the United States while falling to 8% in Europe. This paper examines the reasons for the difference in rail’s share of freight in Europe and the United States. We find that almost 83% of the gap in 2000 is probably due to natural or inherent differences, principally geography, shipment distance, and commodity mix. However, 17% of the gap cannot be explained by these inherent differences and is presumably due to public policies including priority of passenger service, lack of interoperability at borders, service quality and rates, and incentives of the rail operators. We estimate that if that policy gap were closed, railroads’ share of freight in Europe would increase from 8% to 13%.

A hybrid model of fuzzy and AHP for handling public assessments on transportation projects

Having an effective public participation in transportation planning and project development processes has been a major concern for developed countries. In the United States, for instance, all state Departments of Transportation are subject to the Transportation Equity Act (TEA-21) that formally requires public involvement in transportation planning. Since transportation planning involves public resources and values, judgments by the public should play a key role in determining final decisions. Therefore, all these agencies are required not only to disseminate information to the public, but also to solicit and consider public opinion in forming transportation policy. This work presents a decision support model, with public involvement and public oversight, to help policy makers select appropriate transportation projects for implementation. Since focus groups will face multiple objectives and inexact information in the process, a hybrid model of fuzzy logic and analytical hierarchy process (AHP) is proposed. A set of ‘if–then’ rules based on Weber’s psycho-physical law of 1834 is presented to reason from fuzzy numbers to capture essential subjective preferences, pairwise, among the alternatives. The AHP is then incorporated to estimate preference allotments among alternatives. An example application of the suggested method is provided seeking public approval of an appropriate public bus transportation system choosing between one run by municipal authorities and one run by private agencies to show how this procedure works.

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.

Disentangling the influence of neighborhood type and self-selection on driving behavior: an application of sample selection model

The causality issue has become one of the key questions in the debate over the relationships between the built environment and travel behavior. Although previous studies have tested statistical and/or practical significance of the built environment on travel behavior, few have quantified the relative roles of the built environment and residential self-selection in influencing travel behavior. Using 1,479 residents living in four traditional and four suburban neighborhoods in Northern California, this study explores the causal effect of neighborhood type on driving behavior and its relative contribution to the total influence of neighborhood type. Specifically, this study applied Heckman’s sample selection model to separate the effect of the built environment itself and the effect of self-selection. The results showed that, on average, the effect of neighborhood type itself on driving distance was 25.8 miles per week, which accounted for more than three quarters of the total influence of neighborhood type and 16% of individuals’ overall vehicle miles driven. These results suggest that the effect of the built environment on driving behavior outweighs that of self-selection. This paper also discussed the advantages and weaknesses of applying the Heckman’s model to address the self-selection issue.

Assessing asymmetric response effect of behavioral intention to service quality in an integrated psychological decision-making process model of intercity bus passengers: a case of Taiwan

This study introduces the concept of loss aversion to consumer behavioral intention at the personal psychological level to develop an integrative structural equation model for analyzing traveler psychological decision making. In this model, the relationship between behavioral intention and service quality is a non-smooth function based on the theory of loss aversion. The expectation service quality in the SERVQUAL model proposed by Parasuraman, Zeithaml, and Berry (PZB) serves as a reference point. This model can be applied to analyze the effect of non-smooth response of behavioral intention to service quality in a traveler psychological decision-making process model. Intercity travel among cities in Taiwan is used as an empirical example. Data were gathered in cities in Taiwan via a questionnaire survey, and the model was tested using path analysis performed by LISREL. The empirical result shows that all causal relationships are statistically significant. Service quality loss influences repurchase intention more than does Service quality gain. Finally, this study concludes by discussing managerial implications and suggesting directions for future research.

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.

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.

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.

Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ² increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries.

Extending stated choice analysis to recognise agent-specific attribute endogeneity in bilateral group negotiation and choice: a think piece

This paper is a think piece on variations in the structure of stated preference studies when modelling the joint preferences of interacting agents who have the power to influence the attribute levels on offer. The approach proposed is an extension of standard stated choice methods, known as ‘stated endogenous attribute level’ (SEAL) analysis. It allows for interactive agents to adjust attribute levels off a base stated choice specification that are within their control, in an effort to reach agreement in an experimental setting. This accomplishes three goals: (1) the ability to place respondents in an environment that more closely matches interactive settings in which some attribute levels are endogenous to a specific agent, should the modeller wish to capture such behaviour; (2) the improved ability of the modeller to capture the behaviour in such settings, including a greater wealth of information on the related interaction processes, rather than simply outcomes; and (3) the expansion of the set of situations that the modeller can investigate using experimental data.

Children’s mode choice for the school trip: the role of distance and school location in walking to school

Rising levels of childhood obesity in the United States and a 75% decline in the proportion of children walking to school in the past 30 years have focused attention on school travel. This paper uses data from the US Department of Transportation’s 2001 National Household Travel Survey to analyze the factors affecting mode choice for elementary and middle school children. The analysis shows that walk travel time is the most policy-relevant factor affecting the decision to walk to school with an estimated direct elasticity of −0.75. If policymakers want to increase walking rates, these findings suggest that current policies, such as Safe Routes to School, which do not affect the spatial distribution of schools and residences will not be enough to change travel behavior. The final part of the paper uses the mode choice model to test how a land use strategy—community schools—might affect walking to school. The results show that community schools have the potential to increase walking rates but would require large changes from current land use, school, and transportation planning practices.

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.

An exploratory analysis of joint-activity participation characteristics using the American time use survey

This paper presents a detailed exploratory analysis of joint activity participation characteristics using the American Time Use Survey (ATUS). As a very large nationwide survey that explicitly elicited information on both household and non-household companions for each activity episode, the ATUS is ideally suited for this analysis. Several intuitive and interesting results are obtained. Joint episodes are found to be of longer durations, significantly likely to take place at the residence of other people, and often confined to certain time periods of the weekday. In addition, important differences in these characteristics are also observed based on activity purpose, companion type, and the day of the week. These findings are intended to provide the basis for the justification of detailed collection of joint activity–travel participation information in household activity–travel surveys, and also as a stimulant for further empirical analysis and modeling of joint activity participation behavior.

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.

The effect of financial constraints on the optimal design of public transport services

Recent experience with the design of bus services in Santiago, Chile, seems to confirm Jansson's (1980) assertion regarding observed planned bus frequency and size being too low and too large, respectively. We offer an explanation based upon the relation between cost coverage, pricing and optimal design variables. We recall that average social cost decreases with patronage, which generates an optimal monetary fare below the average operators' cost, inducing an optimal subsidy. Then we compare optimal frequency and bus size—those that minimize total social costs—with those that minimize operators' costs only. We show that an active constraint on operators' expenses is equivalent to diminish the value of users' time in the optimal design problem. Inserting this property back in the optimal pricing scheme, we conclude that a self-financial constraint, if active, always provokes an inferior solution, a smaller frequency and, under some circumstances, larger than optimal buses.

Model,process, technique,and the good thing

The paper unpacks the planning process into its component parts: model, process, technique, and goals—the “good thing”. The paper advances the concept that planning, policy-making, and organizational restructuring can be analyzed under the same framework. Each of the four components is described and reductionist examples are presented to clarify the intention and to illustrate the technique that the transport analyst teams employ in their work. The examples cover both successes and failures. They point toward the enormous scientific task ahead for planning to become meaningful and relevant to the problems of today. Finally, in the frame of the willingness to pay, the paper puts forward a case for an institutional framework for a financially autonomous road administration. Similarly organized, administered, and managed entities are relevant also for other transport modes.

Grouping travelers on the basis of their different car and transit levels of use

Market segmentation studies in travel behavior research are ordinarily based on socioeconomic characteristics and personality traits. This study explores the usefulness of a different approach, where the actual overall mobility levels across different ground transportation modes, along with desired changes in the use of cars and transit, are used as clustering variables. Using a given mode can in fact influence the personal representation of that mode, which in turn has been proven to be a key element in transport behaviours. We form such multimodality-based clusters from two field studies, one involving employees of the French transportation research institute INRETS and the other a representative sample of residents of the US San Francisco Bay Area. We find that strong users of a given mode would like to bring more balance to their “modal consumptions” by decreasing the use of this mode more than the average, and increasing the use of the alternative mode. However, concerning ground transport travel budgets, the desire to travel more (or less) overall seems less strongly related to the composition of the modal balance. The US dataset shows also a greater latent demand for travel than the French one. Socioeconomic characteristics of the clusters could not explain the patterns that were found, confirming the importance of taking into account multimodality issues in travel behavior research. Some policy implications from these findings are finally reported.

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.