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Purpose – Departure time choice not only depends on the desire to carry out activities at certain times and places; it is a complex decision making process influenced by travel conditions, congestion levels, activity schedules, and external trip factors. To estimate departure time choice models capturing the factors influencing it in appropriate form, a complex data collection procedure allowing to obtain detailed input data from different sources and at different time periods is required.

The main aim of this chapter is to describe and discuss the survey methodology we used in a time-of-day choice project, involving the collection of revealed preference (RP) and stated preference (SP) data to estimate hybrid discrete departure time choice models incorporating latent variables. Preliminary model results are also presented as an example.

Methodology/approach – Data was obtained from 405 workers at different private and public institutions located in the centre of Santiago, Chile. The survey process had three different stages and used various collection methods (e-mail, web-page, and personal interviews at the workplace) in order to satisfy efficiency, reliability and cost criteria.

The RP component survey design was based on the last origin-destination survey implemented in Santiago (i.e. a travel diary filled under an activity recall framework). Relevant level-of-service measures at different time periods were obtained from GPS data measured from instrumented vehicles in the public and private transport networks. A SP-off-RP optimal design considering dependence among attribute levels was also developed. Finally, several 1–7 Likert scale questions were included to incorporate the latent variables.

Findings – The survey methodology described in this chapter represents a successful experience in terms of collecting high quality data, from different sources, with the aim of estimating appropriate time-of-day choice models. The data collection process was carried out in different stages, by means of web pages, email, and personal interviews. The data was further enriched with level-of-service attributes measured at different times of the day with unusual precision. Preliminary results reported in this chapter show that data obtained through this methodology are appropriate to model time-of-day choices.

Originality/value of chapter – The novelty of the survey methodology described in this chapter is the collection of data of a different nature for time-of-day choice modelling through the integration of different collection techniques.

Acquisition of very precise information about preferred departure/arrival times, level of service at different times of the day, detailed information about flexibility in schedules, employment information and attitudes towards departure times, should allow practitioners to estimate hybrid time-of-day choice models incorporating latent variables.

Discrete choice models based on cross-sectional data have the important limitation of not considering habit and inertia effects and this may be especially significant in changing environments; notwithstanding, most demand models to date have been based on this type of data. To avoid this limitation, we started by building a mode choice panel around a drastically changing environment, the introduction of a radically new public transport system for the conurbation of Santiago de Chile. This paper presents the formulation and estimation of a family of discrete choice models that enables to treat two main elements: (i) the relative values of the modal attributes, as usual, and (ii) the shock resulting from the introduction of this radical new policy. We also analyse the influence of socioeconomic variables in these two forces.

We found that introducing this drastic new policy may even modify the perception of attribute values; in fact, the changes can be different among individuals, as socioeconomic characteristics act as either enhancers or softeners of the shock effects generated by the new policy.

Large-scale continuous mobility surveys have some advantages over less frequent (usually every 10 years), even larger-scale cross-sectional surveys; these advantages have been well documented in previous papers (Ampt & Ortúzar, 2004).

In this paper we first define what we mean by ‘ongoing mobility surveys’. We then describe the state of practice in this context, briefly reviewing the state of affairs in all the cases that we are aware of. We then discuss some problems encountered in practice and offer ideas for improvement. In particular, we discuss a wide range of issues that are likely to act as barriers to a high quality and sustainable implementation and suggest approaches for improvement. Issues covered include sampling frames and sampling methods, survey methods, respondent burden, weighting processes and expansion, and the increased importance of developing and maintaining field staff motivation. We also touch briefly on the practical/political issue of securing ongoing funding. Throughout, we advance some thoughts to try and explain why this method has not gained wider acceptance, particularly in the Northern Hemisphere where there are more examples of travel surveys in general.

The paper also raises some ideas and issues about the way in which ongoing mobility surveys can best collect data for the environmental accounting of travel. Finally, we raise questions about the environmental impact of the survey methods themselves as a stimulus for further consideration.

This paper investigates how respondents to conjoint experiments process information and choose among product profiles, and how this varies with their knowledge about the product. Models for estimating conjoint attribute weights are almost exclusively based on principles of compensatory decision making. The paper aims to explore to what extent and in what way these basic principles of conjoint modelling are violated.

Data were obtained from a verbal protocol study where 18 undergraduate students each performed a total of 28 stated choice tasks while “thinking aloud”.

Results show that cognitive operations consistent with compensatory decision rules constitute a majority of the total number of operations performed across tasks and respondents. However, few respondents exhibited a consistent use of compensatory‐type processes throughout their choice sets. Results suggest that individual preferences interact with characteristics of the choice sets to instigate changes in information processing. It also appears that complete strategies are seldom used. Finally, respondents' knowledge about the product influences the cognitive operations that respondents use in solving conjoint tasks.

Results are based on responses from 18 undergraduate students, which makes generalizations hard.

One implication of this work is that one should apply a more flexible model framework to allow detecting the existence of non‐compensatory strategies.

This paper is one of few which aim to implement findings in behavvioral decision research within the context of conjoint analysis.

This book provides an international perspective on improving information to support transportation decision making. It comprises a selection of papers plus workshop syntheses from the 9th International Conference on Transport Survey Methods in Chile in November 2011. The conference was organized into 14 workshops with both paper presentations and discussions in the workshops forming the majority of the conference activity. The papers reported primarily on research pertaining to continuous improvement in transport survey methods — the backbone of the transportation data pipeline in most countries. But some papers also addressed the new ways in which innovation — notably technological innovation — is being applied to the capture and analysis of data to produce necessary information faster, better, and less expensively. The conference program built on a rich legacy of intellectual pursuits spanning the past two decades, and it is anticipated that the conference will continue into the future. Thus, the contents of this book represent a 5–10 year view through a moving window on the international state of the practice and concerns in transport survey methods.