Author Index Volume 30 2003

Authors Index

Author Index Volume 30 2003     

BOOK REVIEW

Abstract

Nationwide Transport Surveys and Time‐Use Surveys both reflect the daily agendas and schedules of the reporting individuals and should therefore yield comparable indicators of travel behaviour; for instance: immobility rate (share of persons not leaving the home on any one day), daily travel time, and number of trips per day. These two surveys exist in three countries from the same time period: Belgium, France, Great Britain. The comparisons demonstrate that they tell parallel stories, but that the levels of the variables are significantly different with lower immobility rates and longer travel times reported in the Time‐Use Surveys. These surveys should therefore be integrated in the analysis of travel behaviour analysis as a crucial yardstick. In Europe, where Nationwide Travel Surveys are intermittent and not harmonized, the harmonised Time‐Use Surveys allow for crucial European‐wide comparisions across time and space.     

Induced travel demand: Evidence from a pseudo panel data based structural equations model

Induced traffic, defined as additional demand generated by improvements in travel conditions, has been a topic of research for many years. While previous studies have focused on specific and localised changes, the research described in this paper deals with the aggregate effects of changed generalised costs of travel on traffic generation: the propensity of participating in out-of-home activities on a given day, the number of trips and journeys conducted, and the resulting total times out-of-home and distances travelled. The generalised cost and accessibility elasticities estimated with a structural equations model for a pseudo panel constructed with the Swiss National Travel surveys since 1974 are surprisingly substantial even after correcting for age, cohort and other socio-demographic effects.     

Activity‐based approaches to travel analysis: conceptual frameworks,models, and research problems

Recent policy discussions about information technology in transport and traffic demand management have increased interest in activity‐based approaches to the analysis of travel behaviour, in particular in the modelling of household activity scheduling which is at the core of many of the required changes in travel behaviour. This paper is a state‐of‐the‐art review of conceptualizations and models of activity scheduling with special regard to issues raised by the new policy instruments. In the course of the review, the validity of behavioural assumptions is examined critically and several needs for future research identified.     

The design of environmentally aware travel diaries

Any policy addressing the concerns and trends associated with the impact of travel on the environment should be based on a solid understanding of the activities giving rise to them. While the measurement of the total environment loads by air or noise measurement stations is essential, it needs to be matched by the observation of the human behaviours creating them. This is especially true in the transport sector, which has been rightly or wrongly identified as having the potential to make a substantial contribution to the reduction of air and noise pollution. While the contribution of freight transport is of growing concern and importance, this paper focuses on the measurement of passenger transport throughout.

In the past transport planners have largely relied on the travel diary as their prime instrument to measure traveller behaviour. The travel diary is a survey instrument designed to record all movements during the course of one or more days including their relevant details. It is complemented by spearate household and personal forms for recording general information. In the following paper the term travel diary implies all three elements (the diary, the person form and the household form).

The remainder of the paper discusses to what extent and how the travel diary can be used to capture data for the assessment of policies directed at reducing the impact of transport on the social and natural environment. The requirements of a travel diary and the potential uses of new technologies in realising such a travel diary are then presented. A brief outlook on the possibilities of reasling such a diary concludes the paper.     

Immobility in travel diary surveys

The share of immobile persons, i.e. persons not leaving their homes on a given reporting day, is both a central result and a prime quality indicator of a travel diary survey. The wide range of values for the share of immobiles reported in travel diary and time budget survey literature has motivated this in-depth analysis of the reasons for these disparities. This paper collates available evidence on the share of immobiles in travel diary surveys. The share of these non-travellers (UK), or no-trippers (US), varies greatly between otherwise similar surveys. After analysing both disaggregate and aggregate information, this paper concludes that the share of immobiles should be in the range of 8%–12% for the standard one-day, weekday-only travel diary. The analysis suggests that a substantial share of respondents refuse to participate in a soft way, i.e. by claiming not to have left the house. In its conclusions, the paper sketches new ways to reduce the share of such soft refusers during the interview and to identify them during the analysis.      

A joint time-assignment and expenditure-allocation model: value of leisure and value of time assigned to travel for specific population segments

Transportation - Based on a time-use model with a sound theoretical basis and carefully collected data for Austria, the value of leisure (VoL) for different population segments has been estimated....     

Dynamic model of activity-type choice and scheduling

This paper presents a model for the choice of activity-type and timing, incorporating the dynamics of scheduling, estimated on a six-week travel diary. The main focus of the study is the inclusion of past history of activity involvement and its influence on current activity choice. The econometric formulation adopted, explicitly accounts both for correlation across alternatives and for state dependency. The results indicate that behavioral variables are superior to socio-economic variables and that consideration of the correlation pattern over alternatives clearly improves the fit of the model. This is a first but significant contribution to changing the current static demand models into dynamic activity based ones. The availability of other multi-week travel surveys and the progress made recently on advanced econometric techniques should encourage the transferability of this study to different regions or model scale.     

An analysis of weekly out-of-home discretionary activity participation and time-use behavior

Activity-travel behavior research has hitherto focused on the modeling and understanding of daily time use and activity patterns and resulting travel demand. In this particular paper, an analysis and modeling of weekly activity-travel behavior is presented using a unique multi-week activity-travel behavior data set collected in and around Zurich, Switzerland. The paper focuses on six categories of discretionary activity participation to understand the determinants of, and the inter-personal and intra-personal variability in, weekly activity engagement at a detailed level. A panel version of the Mixed Multiple Discrete Continuous Extreme Value model (MMDCEV) that explicitly accounts for the panel (or repeated-observations) nature of the multi-week activity-travel behavior data set is developed and estimated on the data set. The model also controls for individual-level unobserved factors that lead to correlations in activity engagement preferences across different activity types. To our knowledge, this is the first formulation and application of a panel MMDCEV structure in the econometric literature. The analysis suggests the high prevalence of intra-personal variability in discretionary activity engagement over a multi-week period along with inter-personal variability that is typically considered in activity-travel modeling. In addition, the panel MMDCEV model helped identify the observed socio-economic factors and unobserved individual specific factors that contribute to variability in multi-week discretionary activity participation.