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This study contributes to the understanding of the health effects of pesticides exposure and of how pesticides have been and should be regulated.

This study presents literature reviews for the period 2000–2013 on (i) the health effects of pesticides and on (ii) preference valuation of health risks related to pesticides, as well as a discussion of the role of benefit-cost analysis applied to pesticide regulatory measures.

This study indicates that the health literature has focused on individuals with direct exposure to pesticides, i.e. farmers, while the literature on preference valuation has focused on those with indirect exposure, i.e. consumers. The discussion highlights the need to clarify the rationale for regulating pesticides, the role of risk perceptions in benefit-cost analysis, and the importance of inter-disciplinary research in this area.

This study relates findings of different disciplines (health, economics, public policy) regarding pesticides, and identifies gaps for future research.

The purpose of this study is to implement an innovative approach to analyze children’s impact on family decisions. Furthermore, a new strategy to collect children’s preferences is shown to reduce the lack of children’s voices in the tourism literature.

A stated preference (SP) experiment with a two-step procedure is applied: in the first step, children’s preferences are collected through pictures and a rating scale based on emoticons; in the second step, the SP is submitted to their parents to understand how children influence decisions. Parents faced six choice tasks, each of them showing three different activities that they could evaluate on the basis of three attributes: the cost of the activity, the distance from the place of interview and children’s degree of satisfaction in participating in the activity.

The majority of children interviewed show a high preference for swimming pool/lido, and their preference is highly taken into account by parents. Parents prefer closer and cheaper activities, but children’s preferences play a fundamental role in the final choice. In addition, parents are willing to pay an extra 100 CHF, for the whole family, to choose an activity that fulfills children’s preferences, rather than an activity that children do not like.

The originality contribution of this paper consists of using an innovative procedure to collect children’s preferences and combine them in an SP experiment submitted to their parents. Children’s influence on decisions is also measured by parent’s willingness to pay to satisfy their preferences.

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.

Purpose — The main objective of this survey is to collect data for the development of six models in a freight modeling framework. The framework aims to simulate the interactions between shippers and carriers in a freight market.

Methodology/approach — A web-based survey was designed using stated preference methods and experimental auctions, to collect information about shipper and carrier behavior when facing hypothetical situations. Hypothetical situations were constructed using information collected during the survey.

Findings — The modeling results are available for one model, the carrier selection model. In this model, data were collected using stated preference (SP) methods. Nine SP designs were developed using D-designs and an approach to minimize the nonattendance problem. A multinomial probit model was used. No bias was found due to the position of alternatives on the screen, signs of the parameters are as expected, and level of service attributes are relevant in the carrier selection process.

Research limitations/implications — The final response rate was small (about 9%) which is not uncommon in surveys with freight managers. This response rate might result in nonresponse bias of the estimates, which is the subject of future research.

Practical implications — Since freight transport is the output of a freight market, the application of the freight modeling framework presented in this chapter has potential to improve forecasts of freight flows.

Originality/value of chapter — To the best of our knowledge, the survey presented in this chapter consists of an innovative data collection procedure for the development of an original freight modeling framework.

This study was performed to examine the relationship between dynamic traffic information and driver's route choice behavior when non-recurrent events cause traffic jams. To enhance the effectiveness and applicability of the information system as a traffic control measure, it is important to investigate the influence of the software aspects of a dynamic traffic information system; these software aspects include information content and the timing of information delivery. This study was undertaken to investigate whether providing drivers with dynamic traffic information might relieve traffic jams and improve travel time reliability. A questionnaire survey was conducted to obtain data regarding the respondents' attitudes to detours and their stated preference (SP) of route choice behavior. These data are used to analyze the characteristics of drivers who show negative and positive attitudes to detours, including driver information usage and knowledge about the alternative routes. Also, this study analyzes the relation between the way to provide drivers with information and driver's decision-making on route using the SP data. Especially, the analytical attentions are paid to the influences of both timing and contents of information provided upon the respondent' route choices.