Stated Preference Survey Design Research Articles

Stated-Preference Survey Design and Testing in Health Applications.

Following the conceptualization of a well-formulated and relevant research question, selection of an appropriate stated-preference method, and related methodological issues, researchers are tasked with developing a survey instrument. A major goal of designing a stated-preference survey for health applications is to elicit high-quality data that reflect thoughtful responses from well-informed respondents. Achieving this goal requires researchers to design engaging surveys that maximize response rates, minimize hypothetical bias, and collect all the necessary information needed to answer the research question. Designing such a survey requires researchers to make numerous interrelated decisions that build upon the decision context, selection of attributes, and experimental design. Such decisions include considering the setting(s) and study population in which the survey will be administered, the format and mode of administration, and types of contextual information to collect. Development of a survey is an interactive process in which feedback from respondents should be collected and documented through qualitative pre-test interviews and pilot testing. This paper describes important issues to consider across all major steps required to design and test a stated-choice survey to elicit patient preferences for health preference research.

Analysis of the Impact of Sample Size, Attribute Variance and Within-Sample Choice Distribution on the Estimation Accuracy of Multinomial Logit Models Using Simulated Data

Literature review indicates that sample size, attribute variance and within-sample choice distribution of alternatives are important considerations in the estimation of multinomial logit (MNL) models, but their impacts on the estimation accuracy have not been systematically studied. Therefore, the objective of this paper is to provide an empirical examination to the above issues through a set of simulated discrete choice preference and rank ordered preference datasets. In this paper, the utility coefficients, alternative specific constants (ASCs), and the mean and standard deviation of the four attributes for a set of seven hypothetical alternatives are specified as a priori. Then, synthetic datasets, with varying sample size, attribute variance and within-sample choice distribution are simulated. Based on these datasets, the utility coefficients and ASCs of the specified MNLs are re-estimated and compared with the original values specified as the priori. It is found that (1) the estimation accuracy of utility parameters increases as the sample size increases; (2) the utility coefficients can be re-estimated with reasonable accuracy, but the estimates of the ASCs are confronted with much larger errors; (3) as the variances of the alternative attributes increase, the estimation accuracy improves significantly; and (4) as the distribution of chosen choices becomes more balanced across alternatives within sample datasets, the hit-ratio decreases. The results indicate that (a) under a similar setting presented in this paper, a large sample consisting of a few thousand observations (3000–4000) may be needed in order to provide reasonable estimates for utility coefficients, particularly for ASCs; (b) a larger, but realistic attribute space is preferred in the stated preference survey design; and (c) choice datasets with unbalanced “chosen” choice frequency distribution is preferred, in order to better capture the elasticity between the “perceived utility” associated with alternative’s attributes.

What to Value and How? Ecological Indicator Choices in Stated Preference Valuation

The ecological literature accepts that many policy outcomes cannot be observed directly and must be characterized using indicators. Multiple indicators can often be used to communicate similar ecological outcomes. Previous studies using alternative indicators in stated preference surveys suggest that welfare estimates may be indicator-dependent, casting doubt on whether welfare estimates are sufficiently reliable for cost benefit analysis. We suggest that the reason for such indicator dependence may be that indicators used in these prior studies represented different outcomes valued by respondents. This possibility underscores the need for greater attention to selection of indicators and their properties within stated preference survey design. This paper develops a model introducing the concept of outcome equivalent indicators, defined as indicators that provide alternative representations of identical underlying outcomes. To assess empirically whether welfare estimates are indeed robust to indicator choice when alternative indicators are expected to be outcome equivalent, we analyze data from a choice experiment estimating willingness to pay for migratory fish restoration in Rhode Island, USA. Results demonstrate that welfare estimates are robust to the use of alternative ecological indicators within stated preference scenarios.

Evaluating the demand for new cycle facilities

There are many studies which report attitudes to cycling and factors affecting the propensity to cycle but very few which evaluate the detailed costs and benefits of new cycle facilities. As part of a review of cycle facility provision in Bradford, West Yorkshire, a large scale survey of current and potential cyclists was conducted in 1994. A stated preference survey design was used to estimate the value placed on the different attributes of four alternative cycle routes under consideration. The results found that safety is more highly valued than time and that some new cycle schemes can be economically justified on the basis of benefits to current cyclists, even in circumstances of relatively low cycle use. The findings are important in the context of the current promotion of cycle facilities and highlights the need for further research and monitoring.