Utility in Willingness to Pay Space: A Tool to Address Confounding Random Scale Effects in Destination Choice to the Alps

We compare two approaches for estimating the distribution of consumers' willingness to pay (WTP) in discrete choice models. The usual procedure is to estimate the distribution of the utility coefficients and then derive the distribution of WTP, which is the ratio of coefficients. The alternative is to estimate the distribution of WTP directly. We apply both approaches to data on site choice in the Alps. We find that the alternative approach fits the data better, reduces the incidence of exceedingly large estimated WTP values, and provides the analyst with greater control in specifying and testing the distribution of WTP. © 2008 Agricultural and Applied Economics Association.

Preferences for a third-trimester ultrasound scan in a low-risk obstetric population: a discrete choice experiment

Objective: Establish maternal preferences for a third-trimester ultrasound scan in a healthy, low-risk pregnant population.

Design: Cross-sectional study incorporating a discrete choice experiment.

Setting: A large, urban maternity hospital in Northern Ireland.

Participants: One hundred and forty-six women in their second trimester of pregnancy.

Methods: A discrete choice experiment was designed to elicit preferences for four attributes of a third-trimester ultrasound scan: health-care professional conducting the scan, detection rate for abnormal foetal growth, provision of non-medical information, cost. Additional data collected included age, marital status, socio-economic status, obstetric history, pregnancy-specific stress levels, perceived health and whether pregnancy was planned. Analysis was undertaken using a mixed logit model with interaction effects.

Main outcome measures: Women's preferences for, and trade-offs between, the attributes of a hypothetical scan and indirect willingness-to-pay estimates.

Results: Women had significant positive preference for higher rate of detection, lower cost and provision of non-medical information, with no significant value placed on scan operator. Interaction effects revealed subgroups that valued the scan most: women experiencing their first pregnancy, women reporting higher levels of stress, an adverse obstetric history and older women.

Conclusions: Women were able to trade on aspects of care and place relative importance on clinical, non-clinical outcomes and processes of service delivery, thus highlighting the potential of using health utilities in the development of services from a clinical, economic and social perspective. Specifically, maternal preferences exhibited provide valuable information for designing a randomized trial of effectiveness and insight for clinical and policy decision makers to inform woman-centred care.

, Lexicographic Preferences in Discrete Choice Experiments: Consequences on Individual-Specific Willingness to Pay Estimates

In discrete choice experiments respondents are generally assumed to consider all of the attributes across each of the alternatives, and to choose their most preferred. However, results in this paper indicate that many respondents employ simplified lexicographic decision-making rules, whereby they have a ranking of the attributes, but their choice of an alternative is based solely on the level of their most important attribute(s). Not accounting for these simple decision-making heuristics introduces systemic errors and leads to biased point estimates, as they are a violation of the continuity axiom and a departure from the use of compensatory decision-making. In this paper the implications of lexicographic preferences are examined. In particular, using a mixed logit specification this paper investigates the sensitivity of individual-specific willingness to pay (WTP) estimates conditional on whether lexicographic decision-making rules are accounted for in the modelling of discrete choice responses. Empirical results are obtained from a discrete choice experiment that was carried out to address the value of a number of rural landscape attributes in Ireland

Using attribute importance rankings within discrete choice experiments: an application to valuing bread attributes

We present a new Bayesian econometric specification for a hypothetical Discrete Choice Experiment (DCE) incorporating respondent ranking information about attribute importance. Our results indicate that a DCE debriefing question that asks respondents to rank the importance of attributes helps to explain the resulting choices. We also examine how mode of survey delivery (online and mail) impacts model performance, finding that results are not substantively a§ected by the mode of survey delivery. We conclude that the ranking data is a complementary source of information about respondent utility functions within hypothetical DCEs

Practice location of physicians: a discrete choice model approach

Economists and policymakers have long been concerned with increasing the supply of health professionals in rural and remote areas. This work seeks to understand which factors influence physicians’ choice of practice location right after completing residency. Differently from previous papers, we analyse the Brazilian missalocation and assess the particularities of developing countries. We use a discrete choice model approach with a multinomial logit specification. Two rich databases are employed containing the location and wage of formally employed physicians as well as details from their post-graduation. Our main findings are that amenities matter, physicians have a strong tendency to remain in the region they completed residency and salaries are significant in the choice of urban, but not rural, communities. We conjecture this is due to attachments built during training and infrastructure concerns.

A practical guide for operational validation of discrete simulation models

As the number of simulation experiments increases, the necessity for validation and verification of these models demands special attention on the part of the simulation practitioners. By analyzing the current scientific literature, it is observed that the operational validation description presented in many papers does not agree on the importance designated to this process and about its applied techniques, subjective or objective. With the expectation of orienting professionals, researchers and students in simulation, this article aims to elaborate a practical guide through the compilation of statistical techniques in the operational validation of discrete simulation models. Finally, the guide's applicability was evaluated by using two study objects, which represent two manufacturing cells, one from the automobile industry and the other from a Brazilian tech company. For each application, the guide identified distinct steps, due to the different aspects that characterize the analyzed distributions. © 2011 Brazilian Operations Research Society.