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.

What drives the gap? Applying the Blinder–Oaxaca decomposition method to examine generational differences in transportation-related attitudes

Transportation - Considerable recent work suggests that Millennials’ behaviors may be converging with those of Generation X as they enter later life stages, but few have investigated whether...     

Who doesn’t mind waiting? Examining the relationships between waiting attitudes and person- and travel-related attributes

Transportation - Waiting, whether for services, for someone, or for something, is an inescapable part of life. This paper addresses a gap in the waiting time literature by examining previously...     

Addressing the joint occurrence of self-selection and simultaneity biases in the estimation of program effects based on cross-sectional observational surveys: case study of travel behavior effects in carsharing

Transportation - We estimate the effect of carsharing on travel behavior (specifically, household vehicle holdings, frequency of transit usage, and frequency of biking and walking) using data from...     

Representing heterogeneity in structural relationships among multiple choice variables using a latent segmentation approach

Transportation - Travel model systems often adopt a single decision structure that links several activity-travel choices together. The single decision structure is then used to predict...     

Contents Volume 32 2005

Contents Volume

Contents Volume 32 2005     

Forecasting telecommuting

Transportation planners increasingly recognize telecommuting as an important trend. But while they often advocate telecommuting as a transportation demand management strategy, transportation planners have made little progress toward incorporating telecommuting into transportation forecasts, at least partly because of the limited data available. In this paper we explore four alternative methodologies for forecasting telecommuting and discuss the kinds of data that must be collected before these methodologies can be applied. The first approach is trend extrapolation, using curves of technological substitution. Sufficient data are currently available to produce forecasts, albeit highly uncertain forecasts, using this approach. However, even with better data this approach does not address underlying factors and trends that will affect the future of telecommuting. As a result, we explore three additional approaches that should produce more reliable forecasts but which require new data and knowledge about telecommuting: analyzing the characteristics of telecommuters in contrast to nontelecommuters, analyzing factors affecting the individual choice to telecommute, and incorporating telecommuting into traditional transportation forecasting models.     

A conceptual analysis of the transportation impacts of B2C e-commerce

This paper discusses, at a conceptual level, a number of issues related to the evaluation of the transportation and spatial impacts of e-shopping. We review the comparative advantages of store shopping and e-shopping, and conclude that neither type uniformly dominates the other. We identify the building blocks of the shopping process, and note that information and communications technologies are making possible the spatial and temporal fragmentation and recombination of those elements. We analyze future shopping-related changes in transportation as the net outcome of four different fundamental causes, that can be viewed hierarchically: (1) changes in shopping mode share (i.e. shifts in the proportion of shopping activities conducted through store shopping, e-shopping and other modes), keeping the volume of goods purchased and per capita consumption spending constant; (2) changes in the volume of goods purchased, keeping per capita consumption spending constant; (3) changes in per capita consumption spending, independent of demographic changes; and (4) demographic changes. Some factors result in reduced travel while others lead to increased travel. The combined outcome of all factors does not appear to support any hope that e-shopping will reduce travel on net; to the contrary there may be negative impacts due to increased travel, even if those impacts are likely to be localized and/or small in magnitude for the most part. Thus, on the whole, we are likely (with some exceptions) to see continued adoption of both store shopping and e-shopping. Consumers will blend both forms as they conduct a sequence of shopping activities, and retailers will blend both in marketing to and serving customers. Assessing the transportation impacts of e-shopping – even in the short term, let alone the long term – presents some formidable measurement challenges. Nevertheless, those challenges are worthy of our most creative efforts at solution.     

How do passengers use travel time? A case study of Shanghai–Nanjing high speed rail

Traditional travel behavior theory regards travel time as a waste. Recent studies suggest that it carries a positive utility, among other reasons for the benefit of the activities conducted while traveling. However, most studies of travel time use have focused on conventional trains in developed countries. Few have systematically examined the permeation of information and communication technology (ICT) into travel time use and the correlates of activity participation in developing countries, particularly on high speed rail (HSR). Using a survey conducted on the Shanghai–Nanjing corridor (N = 901), this study examines how HSR passengers use their travel time and explores the correlates of the different types of activities of business and non-business travelers, respectively, through multivariate probit models. We found that 96% of the respondents use ICT during their HSR journey and that most passengers spend some of their travel time on work-related activities. Moreover, items carried and advance planning as well as work-related travel attributes contribute significantly to activity participation. However, the factors affecting time use of business and non-business travelers differ. HSR service design should facilitate passenger engagement in various activities and improvement of their travel experience. A stable internet connection, adequate power sockets, and a noise-free environment will promote both work and leisure activities on the HSR.     

Does the political and economic context influence the success of a transport project? An analysis of transport public-private partnerships

The construction and provision of infrastructure services such as transport nowadays is often based on a partnership between three main actors: public sector, private sector and multilateral lenders, under a framework of Public-Private Partnerships (PPPs). This type of partnership has been employed in a wide range of projects in the transport sector and in various contexts in developing and developed countries. Given this observation, the objective of this paper is to examine how countries’ economic and political characteristics contribute to the success of PPPs in transport investments. Special focus in the analysis is given to how the perception of corruption and democratic accountability may influence the success of a PPP project in different transport sectors. We examine a database with 856 transport PPP projects using a generalized linear model in the form of a logit model in order to evaluate the transport database covering data from 72 countries, classified in six regions. The study highlights the importance of national experience. Not only does national macroeconomic experience appear to have a relevant role, but so also does its past experience (either positive or negative) of transport PPP projects. An interesting finding from the analysis is the importance of the rest of the world’s perception of a country’s level of corruption and democratic accountability for the final outcome of a PPP project.