Effects of increased awareness on choice of travel mode

This paper reports a field experiment with the purpose of studying the effects of increased awareness on travel mode choice. One hundred fifteen subjects were randomly assigned to an experimental and a control group. In the experimental group, a more deliberate choice of travel mode was induced and expected to result in a stronger relationship between attitude and behavior, a weaker relationship between habit and behavior, and a behavioral change among individuals with a strong habit. Attitude, habit, and behavior were measured in travel diaries and questionnaires. The results indicated no significant change in the relationship between attitude and behavior and no significant change in the relationship between habit and behavior. However, a temporally extended decrease in car use was observed in the experimental group. The effect was noted for individuals with a strong habit who reduced their car use but not for subjects with a weak habit.     

Travel mode choice and travel satisfaction: bridging the gap between decision utility and experienced utility

Over the past decades research on travel mode choice has evolved from work that is informed by utility theory, examining the effects of objective determinants, to studies incorporating more subjective variables such as habits and attitudes. Recently, the way people perceive their travel has been analyzed with transportation-oriented scales of subjective well-being, and particularly the satisfaction with travel scale. However, studies analyzing the link between travel mode choice (i.e., decision utility) and travel satisfaction (i.e., experienced utility) are limited. In this paper we will focus on the relation between mode choice and travel satisfaction for leisure trips (with travel-related attitudes and the built environment as explanatory variables) of study participants in urban and suburban neighborhoods in the city of Ghent, Belgium. It is shown that the built environment and travel-related attitudes—both important explanatory variables of travel mode choice—and mode choice itself affect travel satisfaction. Public transit users perceive their travel most negatively, while active travel results in the highest levels of travel satisfaction. Surprisingly, suburban dwellers perceive their travel more positively than urban dwellers, for all travel modes.     

Experiments with an activity-based travel model

Transportation - Experiments are described with an activity-based travel model, estimated on a 7-day activity-diary survey. The first part of the paper describes the model system in its final form,...     

Ride-hailing,travel behaviour and sustainable mobility: an international review

Transportation - A discussion of the sustainability and travel behaviour impacts of ride-hailing is provided, based on an extensive literature review of studies from both developed and developing...     

The interactions between online shopping and personal activity travel behavior: an analysis with a GPS-based activity travel diary

Accompanying the widespread use of the Internet, the popularity of e-commerce is growing in developing countries such as China. Online shopping has significant effects on in-store shopping and on other personal activity travel behavior such as leisure activities and trip chaining behavior. Using data collected from a GPS-based activity travel diary in the Shangdi area of Beijing, this paper investigates the relationships between online shopping, in-store shopping and other dimensions of activity travel behavior using a structural equation modelling framework. Our results show that online buying frequency has positive effects on the frequencies of both in-store shopping and online searching, and in-store shopping frequency positively affects the frequency of online searching. Frequent online purchasers tend to shop in stores on weekends rather than weekdays. We also found a negative effect of online buying on the frequency of leisure activities, indicating that online shopping may reduce out-of-home leisure trips.     

Habitual travel behaviour: Evidence from a six-week travel diary

This paper introduces different methods to measure similarity of travel behaviour addressing the question of how repetitious travel behaviour actually is. It compares empirical results of the different methods based on the data from a six-week travel diary. In general, the results show that the day-to-day behaviour is more variable if measured with trip-based methods instead of methods based on time budgets. Furthermore, it is confirmed that the similarity declines if the method captures more of the complexity of the travel pattern. It is also shown that travel behaviour is neither totally repetitious nor totally variable. Even for the whole observation period, it is demonstrated that two days always have some common elements. Additionally, it is found that the different methods yield the same pattern of variability for different types of day. Travel behaviour is clearly more stable on work days. Similar results for all methods are also obtained concerning the question of how long the minimum period of observation should be. All measures show that the period should not be less than two weeks if one aims at measuring variability.     

Teleworking in the Netherlands: an evaluation of changes in travel behaviour

This article describes the first experiment on teleworking in the Netherlands, and presents the results of an analysis of the impact of teleworking on the travel behaviour of the participants in the experiment and their household members. It was concluded that teleworking has resulted in a significant decrease in the total number of trips by teleworkers (–17%). Peak-hour traffic by car has been reduced even more (–26%). An unexpected result was that the household members of the teleworkers also appeared to travel less than before the experiment.     

Introduction: Habitual travel choice

In this introduction to the special issue on habitual travel choice, we provide a brief account of the role of habit in travel behaviour, discuss more generally what habitual choice is, and briefly review the issues addressed in the solicited papers. These issues include how habitual travel behaviour should be measured, how to model the learning process that makes travel choice habitual, and how to break and replace car-use habits.     

Apps,activities and travel: an conceptual exploration based on activity theory

With the continuous advancement of (mobile) ICT devices and applications, their impact on travel, activities and time use becomes more diverse. This holds in particular for apps developed for mobile devices (smartphones). In this paper, we argue that the effect of ICT on travel and activities should be analysed at the level of a single specific device or application, rather than for broad classes of ICT devices. We propose activity theory as a framework to analyse the impact of smartphone apps on travel and activities. Activity theory describes how subjects apply tools (such as apps) to work on an object and achieve an outcome that is in line with the subject’s motive. The application of the tool is embedded in an activity system which includes a community, formal and informal rules and in which a division of labour exists. We apply activity theory to analyse the effects of Whatsapp and travel feedback apps, based on existing literature about these apps. The analyses suggest that the activity systems of each app differ greatly in terms of object, motive, outcomes, community and rules, with implications for their use and impact. Both apps have an impact on travel, but differ with respect to whether this effect is intentional. For both apps contradictions in the activity system can be identified, which may give rise to further development of the activity system. These seem, however, to be largest for travel feedback apps. Based on our exploration, we argue that quantitative research on the impact of apps should be complemented by qualitative research based on activity theory. In particular, activity theory may help to gain a better understanding of underlying mechanism by which apps influence travel, to strengthen the theoretical underpinning and interpretation of the results of quantitative research and to explore changes in the development and use of apps and their impact on travel behaviour.     

Envisioning an emission diet: application of travel demand mechanisms to facilitate policy decision making

Emission reduction strategies are gaining attention as planning agencies work towards adherence to air quality conformity standards. Policymakers struggling to reduce greenhouse gases (GHG) must grapple with a growing number of travel demand policies. To consider any of these emerging demand mechanisms as a viable option to meet emission targets, planners and policymakers need tools to better understand the implications of such policies on travel behavior. In this paper we present an integrated multimodal travel demand and emission model of four policy strategies; presenting GHG and air pollutant reduction results at a very detailed level. Multiple policy outcomes are compared within a single modeling framework and study area. The results reveal that while no one demand mechanism is likely to reduce emissions to a level that meets policy-maker’s goals; a first-best pricing strategy that incorporates marginal social costs is the most effective emission reduction mechanism. Implementing such a mechanism may offer total emission reductions of up to 24 %. However, the efficacy of this strategy must be weighed against difficulties of establishing efficient pricing, a costly implementation, and substantial negative impacts to non-highway facilities. Decision makers must select a mixture of pricing and land use strategies to achieve emission goals on all road facilities.     

Congestion and variable user charging as an effective travel demand management instrument

Interest at the political level in congestion charging is gaining pace as cities struggle with ways to reduce the effects of growing traffic congestion on the liveability of cities. Despite a long history of promotion of a wide array of travel demand management (TDM) initiatives, very few have had a noticeable impact on the levels of traffic on the road networks of metropolitan areas. TDM success in this context has almost become ‘band-aid’ in the absence of a pricing strategy that not only promotes efficient use of the system but also hypothecates revenues to support essential complementary infrastructure and services such as public transport. This paper takes a look at the stream of pricing consciousness that is surfacing around the world. Although very few jurisdictions have implemented congestion charging, or any form of efficient variable car and truck user charging, the winds of change are well in place. The adage “it is not a matter of if but of when” seems to be the prevailing view. Our overview of global trends in positioning the debate and hopefully follow-through commitment to implementation provides a backdrop to papers submitted for this special issue on travel demand management. The predominance of papers on pricing is indicative of the priority that must be given to efficient charging and revenue disbursement.     

Subjective well-being and travel: retrospect and prospect

Although the improvement of well-being is often an implicitly-assumed goal of many, if not most, public policies, the study of subjective well-being (SWB) and travel has so far been confined to a relatively small segment of the travel behavior community. Accordingly, one main purpose of this paper is to introduce a larger share of the community to some fundamental SWB-related concepts and their application in transportation research, with the goal of attracting others to this rewarding area of study. At the same time, however, I also hope to offer some useful reflections to those already working in this field. After discussing some basic issues of terminology and measurement of SWB, I present from the literature four conceptual models relating travel and subjective well-being. Following one of those models, I review five ways in which travel can influence well-being. I conclude by examining some challenges associated with assessing the impacts of travel on well-being, as well as challenges associated with applying what we learn to policy.

     

Camionetas: Informal travel among immigrants

Camionetas are mini-vans privately operated as jitney services, run by immigrants for immigrants throughout cities in the US, Mexico, and Central America. Media accounts have portrayed camionetas as part of an unscrupulous industry that endangers and exploits riders, primarily farm workers and other undocumented laborers. Using interviews and ethnography, we analyze who patronizes camionetas in Southern California, and why. Patrons discussed why they use this service, their attitudes about it, other transportation options, and access to employment. Finally, we conducted empirical tests to determine whether these services are as exploitative of their riders as portrayed. This research suggests that camionetas are primarily used by Mexican immigrants with varied socio-economic characteristics who want to travel inter-regionally and transnationally. Patrons praised camioneta service for timesaving, Spanish-speaking drivers, more flexible and “out-of-the-way” stops, the inclusion of Spanish music and television in the vehicle, and door-to-door service. Our ethnographic evidence suggested that the camionetas operating in Southern California were comfortable and safe. But statistical tests suggest that undocumented patrons in our sample may face price discrimination due to the paucity of travel opportunities that do not require US identification. This research informs policy debates about transnational vehicle travel, safety, privatized transit, and access among marginalized groups.     

Understanding Travel Time Expenditures Around the World: Exploring the Notion of a Travel Time Frontier

Travel behavior researchers have been intrigued by the amount of time that people allocate to travel in a day, i.e., the daily travel time expenditure, commonly referred to as a “travel time budget”. Explorations into the notion of a travel time budget have once again resurfaced in the context of activity-based and time use research in travel behavior modeling. This paper revisits the issue by developing the notion of a travel time frontier (TTF) that is distinct from the actual travel time expenditure or budget of an individual. The TTF is defined in this paper as an intrinsic maximum amount of time that people are willing to allocate for travel. It is treated as an unobserved frontier that influences the actual travel time expenditure measured in travel surveys. Using travel survey datasets from around the world (i.e., US, Switzerland and India), this paper sheds new light on daily travel time expenditures by modeling the unobserved TTF and comparing these frontiers across international contexts. The stochastic frontier modeling methodology is employed to model the unobserved TTF as a production frontier. Separate models are estimated for commuter and non-commuter samples to recognize the differing constraints between these market segments. Comparisons across the international contexts show considerable differences in average unobserved TTF values.     

Values,attitudes and travel behavior: a hierarchical latent variable mixed logit model of travel mode choice

Values lie at the heart of an individual’s belief system, serving as prototypes from which attitudes and behaviors are subsequently manufactured. Attitudes and behaviors may evolve over time, but values represent a set of more enduring beliefs. This study examines the influence of values on travel mode choice behavior. It is argued that personal values influence individual attitudes towards different alternative attributes, which in turn impact modal choices. Using data from a sample of 519 German commuters drawn from a consumer panel, the study estimates an integrated choice and latent variable model of travel mode choice that allows for hierarchical relationships between the latent variables and flexible substitution patterns across the modal alternatives. Results from the empirical application support the value-attitude-behavior hierarchical model of cognition, and provide insights to planners and policy-makers on how better to sell public transit as a means of travel.     

Parking subsidies and travel choices: Assessing the evidence

This article reviews empirical studies of how employer-paid parking affects employees' travel choices. A strong effect is found: parking subsidies greatly increase solo driving. When employers reduce or remove parking subsidies, a significant number of solo drivers shift to carpools and/or transit. This conclusion is based on studies of parking subsidies in a variety of circumstances, including central city and suburban areas, private and public employers, and clerical and professional employees. Three measures are developed to compare changes in commute patterns: changes in the share of solo drivers. changes in the number of autos driven to work per 100 employees, and the parking price elasticity of demand for solo driving. The studies reviewed here show that 19 to 81 percent fewer employees drive to work alone when they pay for their own parking. Because 90 percent of American commuters who drive to work receive employer-paid parking, these findings are significant for designing transportation policies to reduce air pollution, traffic congestion, and energy consumption.     

Short-Term Prediction of Travel Time using Neural Networks on an Interurban Highway

The main purpose of this study was to investigate the predictability of travel time with a model based on travel time data measured in the field on an interurban highway. Another purpose was to determine whether the forecasts would be accurate enough to implement the model in an actual online travel time information service. The study was carried out on a 28-kilometre-long rural two-lane road section where traffic congestion was a problem during weekend peak hours. The section was equipped with an automatic travel time monitoring and information system. The prediction models were made as feedforward multilayer perceptron neural networks. The main results showed that the majority of the forecasts were close to the actual measured values. Consequently, use of the prediction model would improve the quality of travel time information based directly on the sum of the latest measured travel times.     

Wanting to travel,more or less: Exploring the determinants of the deficit and surfeit of personal travel

This study investigates the determinants of peoples desire to increase or decrease the amount of travel they do. We use data from 1,357 working commuters, residents of three different neighborhoods in the San Francisco Bay Area, California. The dependent variables are indicators of Relative Desired Mobility for ten categories of travel (short- and long-distance overall and by several mode- and purpose-specific categories). These variables are measured on a five-point ordinal scale ranging from much less to much more, through which the respondents indicated the amount of travel they want to do (in the category in question) compared to what they are doing now. Censored ordered probit models were developed for these variables, with explanatory variables including general travel attitudes, specific liking for travel in each of the same separate categories, objective and subjective measures of the amount currently traveled in each category, and personality, lifestyle, and socio-demographic characteristics. The results support the hypotheses that the liking for travel has a strong positive impact, and subjective qualitative assessments of mobility have a strong negative impact, on the desire to increase ones travel. Finally, a number of general types of effects on Relative Desired Mobility were identified, among them complementarity and substitution effects. The results of this study can provide policy makers and researchers with new and valuable insight into key principles that affect individual travel demand.     

Household travel surveys: Where are we going?

In this paper, we commence by reviewing the recent history of household travel surveys. We note some of the problems that contemporary surveys are encountering throughout the world. We also review the data demands of current and emerging travel demand models, concluding that there are many new demands being placed on data, both in terms of the extent of the data required and the accuracy and completeness of the data. Noting that the standard method for conducting most household travel surveys is, and has been for some years, a diary, we briefly explore the evolution of the diary survey from the late 1970s to the present. In the next section of the paper, we explore a number of facets of potential future data collection. We include in this the use of GPS devices to measure travel, the potential of panel designs and some of the alternatives within panel designs, the development of continuous household travel surveys, especially in Australia, and the emerging capabilities in data fusion. Using some of these emerging methods for data collection and data simulation, we then propose a new paradigm for data collection that places the emphasis on a paid, national panel that is designed as a rotating, split panel, with the cross-sectional component conducted as a continuing survey. The basis of the panel data collection is proposed as GPS with demographic data, and the continuing national sample would also use GPS at its core. The potential to add in such specialised surveys as stated choice and process surveys is also noted as an advantage of the panel approach. We also explore briefly the notion that a special access panel or panels could be included as part of the design.