Efficient design for willingness to pay in choice experiments: evidence from the field (original) (raw)
Related papers
2008
We apply a design efficiency criterion to construct conjoint choice experiments specifically focused on the accuracy of marginal W T P estimates. In a simulation study and a numerical example, the resulting W T P-optimal designs are compared to alternative designs suggested in the literature. It turns out that W T P-optimal designs not only improve the estimation accuracy of the marginal W T P , as expected on the basis of the nature of the efficiency criterion, but they also considerably reduce the occurrence of extreme estimates, which also exhibit smaller deviations from the real values. The proposed criterion is therefore valuable for non-market valuation studies as it reduces the sample size required for a given degree of accuracy and it produces estimates with fewer outliers.
Choice experiment adaptive design benefits: a case study*
Australian Journal of Agricultural and Resource Economics, 2010
Efficient experimental designs offer the potential to reduce required sample sizes, or to reduce confidence intervals for parameters of interest, in choice experiments. Choice experiment designs have typically addressed efficiency of utility function parameter estimates. The recently developed concept of C-efficiency recognises the salience of willingness to pay estimates rather than utility function parameters in studies that seek to put money values on attributes. C-efficiency design benefits have been illustrated in a theoretical context, but have not been tested in applied settings. This study reports a choice experiment field application that used initial responses to update statistical designs to maximise C-efficiency. Consistent with theoretical predictions, the revised design delivered significant reductions in the variance of willingness to pay estimates, illustrating that C-efficient designs can indeed decrease costs of choice experiments by reducing required sample sizes.
Bayesian conjoint choice designs for measuring willingness to pay
2011
In this paper, we propose a new criterion for selecting efficient conjoint choice designs when the interest is in quantifying willingness to pay (WTP).The new criterion, which we call the WTP-optimality criterion, is based on the c-optimality criterion which is often used in the optimal experimental design literature. We use a simulation study to evaluate the designs generated using the WTP-optimality criterion and discuss the design of a real-life conjoint experiment from the literature. The results show that the new criterion leads to designs that yield more precise estimates of the WTP than Bayesian D-optimal conjoint choice designs, which are increasingly being seen as the state-of-the-art designs for conjoint choice studies, and to a substantial reduction in the occurrence of unrealistically high WTP estimates.
Efficiency benefits of choice model experimental design updating: a case study
Efficient experimental designs offer the potential to reduce confidence intervals for parameters of interest in choice models, or to reduce required sample sizes. C-efficiency recognises the salience of willingness to pay estimates rather than utility function parameters. This study reports on a choice model application that incorporated updated statistical designs based on initial responses in order to maximise C-efficiency. The revised design delivered significant improvements.
A Comparison of Criteria to Design Efficient Choice Experiments
Journal of Marketing Research, 2006
To date, no attempt has been made to design efficient choice experiments by means of the G-and V-optimality criteria. These criteria are known to make precise response predictions, which is exactly what choice experiments aim to do. In this article, the authors elaborate on the G-and V-optimality criteria for the multinomial logit model and compare their prediction performances with those of the D-and A-optimality criteria. They make use of Bayesian design methods that integrate the optimality criteria over a prior distribution of likely parameter values. They employ a modified Fedorov algorithm to generate the optimal choice designs. They also discuss other aspects of the designs, such as level overlap, utility balance, estimation performance, and computational effectiveness.
Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price?
Journal of Consumer Research, 2008
The discrete choice experiment is a widely used methodology in consumer studies. However, applying this method to investigate the market of products sold in a wide price range could present issues as to the quality of the estimate of preferences. In fact, for this `type of product, frequently consumers may have different behaviours when faced with different price levels. For example, some market segments may refrain from purchasing products below certain price thresholds, considering them of an unacceptable quality, while others choose only below certain prices. To work around this problem area, we propose a methodology in which each respondent declares his own price interval of reference and consequently participates in a choice experiment with a price vector coherent with his habits. In this manner, we are able to grasp and include in the estimations the heterogeneity of consumers with respect to price and thus obtain more accurate willingness to pay estimates. The method describes a procedure to bypass issues related to identifying the price vector in discrete choice experiments that involve products sold in a wide price range.
Sequential choice designs to estimate the heterogeneity distribution of willingness-to-pay
Quantitative Marketing and Economics, 2011
Two prominent approaches exist nowadays for estimating the distribution of willingness-to-pay (WTP) based on choice experiments. One is to work in the usual preference space in which the random utility model is expressed in terms of partworths. These partworths or utility coefficients are estimated together with their distribution. The WTP and the corresponding heterogeneity distribution of WTP is derived from these results. The other approach reformulates the utility in terms of WTP (called WTP-space) and estimates the WTP and the heterogeneity distribution of WTP directly. Though often used, working in preference space has severe drawbacks as it often leads to WTP-distributions with long flat tails, infinite moments and therefore many extreme values. By moving to WTP-space, authors have tried to improve the estimation of WTP and its distribution from a modeling perspective. In this paper we will further improve the estimation of individual level WTP and corresponding heterogeneity distribution by designing the choice sets more efficiently. We will generate individual sequential choice designs in WTP space. The use of this sequential approach is motivated by findings of Yu et al. (2011) who show that this approach allows for superior estimation of the utility coefficients and their distribution. The key feature of this approach is
Environmental and Resource Economics, 2006
Stated choice (SC) methods are now a widely accepted data paradigm in the study of behavioural response of agents (be they individuals, households, or other organizations). Their popularity since the pioneering contributions of Louviere and Woodworth (1983) and Louviere and Hensher (1983) has spawned an industry of applications in fields as diverse as transportation, environmental science, health economics and policy, marketing, political science and econometrics. With rare exception, empirical studies have used a single SC design, in which the numbers of attributes, alternatives, choice sets, attribute levels and ranges have been fixed across the entire design. As a consequence the opportunity to investigate the influence of design dimensionality on behavioural response has been denied. Accumulated wisdom has promoted a large number of positions on what design features are specifically challenging for respondents (eg the number of choice sets to evaluate); and although a number of studies have assessed the influence of subsets of design dimensions (eg varying the range of attribute levels), there exists no single study (that we are aware of) that has systematically varied all of the main dimensions of SC experiments. This paper reports the findings of a study that uses a Design of Designs (DoD) SC experiment in which the 'attributes' of the design are the design dimensions themselves including the attributes of each alternative in a choice set. The design dimensions that are varied are the number of choice sets presented, the number of alternatives in each choice set, the number of attributes per alternative, the number of levels of each attribute and the range of attribute levels. This paper details the designs and how they are used in the search for design impacts on willingness to pay (ie attribute valuation), using a sample of respondents in Sydney choosing amongst trip attribute bundles for their commuting trip.
Design criteria to develop choice experiments to measure the WTP accurately
2008
To measure the willingness-to-pay (W T P) accurately, Vermeulen et al. [2008] apply the c-optimality criterion to generate designs for conjoint choice experiments. This criterion is based on minimizing the sum of the variances of the W T P estimators approximated by the delta method. Designs generated based on this criterion lead to more accurate W T P estimates than the ones obtained by standard designs and reduce considerably the occurence of extreme W T P estimates, although they do not exclude them. In this paper, other optimality criteria are considered to tackle this problem. We distinguish between criteria in preference space on the one hand and criteria in W T P-space on the other hand. In a simulation study and a numerical example, we compare the accuracy of the W T P and the utility coefficient estimates yielded by the designs based on these new criteria.
Testing for consistency in willingness to pay experiments
Journal of Economic Psychology, 2000
Given the increased use of willingness to pay (WTP) experiments to elicit the economic value of goods, it is becoming increasingly important to assess the validity of the instrument. Given the problems of testing for external validity in the absence of market, other methods must be developed to test the validity of WTP responses. This paper develops a simple test of consistency in WTP experiments which is based on the theoretical basis of the technique ± if commodity A is preferred to B, then individuals should be willing to pay more for A than B. The test is applied to elicit womenÕs preferences for two alternative treatments for menorrhagia: conservative treatment versus hysterectomy. Thirty percent of respondents failed the consistency test. Cost-based responses were found to partly explain inconsistent responses. This simple test highlights potential problems when using WTP experiments within a cost-bene®t analysis framework. Possible solutions to avoid Ôcost-basedÕ WTP responses are suggested.