 Obtaining more information from conjoint experiments by best-worst choicesBart Vermeulen, Peter Goos () and Martina Vandebroek Computational Statistics & Data Analysis, 2010, vol. 54, issue 6, 1426-1433 Abstract: Conjoint choice experiments elicit individuals' preferences for the attributes of a good by asking respondents to indicate repeatedly their most preferred alternative in a number of choice sets. However, conjoint choice experiments can be used to obtain more information than that revealed by the individuals' single best choices. A way to obtain extra information is by means of best-worst choice experiments in which respondents are asked to indicate not only their most preferred alternative but also their least preferred one in each choice set. To create D-optimal designs for these experiments, an expression for the Fisher information matrix for the maximum-difference model is developed. Semi-Bayesian D-optimal best-worst choice designs are derived and compared with commonly used design strategies in marketing in terms of the D-optimality criterion and prediction accuracy. Finally, it is shown that best-worst choice experiments yield considerably more information than choice experiments. Keywords: Bayesian; optimal; design; Best-worst; choices; Maximum-difference; model; Conjoint; analysis; D-optimality (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:54:y:2010:i:6:p:1426-1433 Access Statistics for this article Computational Statistics & Data Analysis is currently edited by S.P. Azen More articles in Computational Statistics & Data Analysis from Elsevier |
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