Designing Discrete Choice Experiments: Do Optimal Designs Come at a Price?

By Jordan J. Louviere, Towhidul Islam, Nada Wasi, Deborah J. Street, Leonie Burgess. 2008

279 citations recorded by the source corpus.

Subfields: Economics and Econometrics, General Decision Sciences, Marketing

View Paper: https://www.semanticscholar.org/paper/7a19a5e1de177b3050d0ae7dbfe68d651fad3215

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Citations in the corpus

Complexity in Choice Experiments: Choice of the Status Quo Alternative and Implications for Welfare Measurement (2009, background): “…and Resource Economics Society Inc. and Blackwell Publishing Asia Pty Ltd Other literature on complexity in choice has indicated that increasing complexity can affect the variance of choices or the stochastic component of the random utility (Swait and Adamowicz 2001a; Louviere et al. 2008).”
Discrete Choice Experiments in Health Economics: Past, Present and Future (2018, unknown): “These reviews, as well as published checklists [12] and best-practice guidelines [13–17], have been developed to provide specific guidance and potentially improve quality [12, 18].”
Discrete Choice Experiments Are Not Conjoint Analysis (2010, methodology): “There is much overlap in the traditional CA analysis and DCE literatures, with most of the work done in DCE applications (e.g., Carson et al. 1994; Louviere et al. 2008).”
Contemporary Guidance for Stated Preference Studies (2017, background): “Louviere et al. (2008) andDeShazo and Fermo (2002) find that as statistical efficiency and choice complexity increase, the consistency of respondent choices declines.”
The Generalized Multinomial Logit Model: Accounting for Scale and Coefficient Heterogeneity (2010, methodology): “However, as shown by Louviere et al. (2008b), it is possible to estimate individuallevel models from stated preference data obtained using efficient experimental designs.”
The Strength of Strong Ties in an Emerging Industry: Experimental Evidence of the Effects of Status Hierarchies and Personal Ties in Venture Capitalist Decision Making: The Strength of Strong Ties (2015, unknown): “expressed by its rating or ranking is broken down into the preferences of the particular attributes and attribute levels (e.g., Green and Rao, 1971; Green and Srinivasan, 1990; Louviere et al., 2003; Louviere et al., 2008; McFadden, 1986).”
Whatever the customer wants, the customer gets? Exploring the gap between consumer preferences and default electricity products in Germany (2013, background): “Comparisons across attributes are facilitated by converting part-worth utilities to willingness to pay (see section below), which implies the advantage of canceling out the scale effect (e.g. Louviere et al., 2008).”
Experimental design influences on stated choice outputs: An empirical study in air travel choice (2009, background): “Overall, we were unable to substantiate the findings of Louviere et al. (2008) in terms of efficient designs tend to induce greater error variance, although we have also conjectured here that that might indeed be the case.”
Conducting Discrete Choice Experiments to Inform Healthcare Decision Making (2012, background): “[98] Thus which eliminates the need to make distributional far, two types of BWS have been used in health assumptions about preference heterogeneity.[67] economics: (i) asking respondents to choose the best”
Can scale and coefficient heterogeneity be separated in random coefficients models? (2012, background): “…is being captured in random parameter models is actually not heterogeneity in individual sensitivities1, but at least in part differences in scale across choice tasks or respondents (see e.g. Louviere et al., 1999, 2002; Louviere and Eagle, 2006; Louviere and Meyer, 2008; Louviere et al., 2008).”