文章基本信息

标题：Dynamic Attribute-Level Best Worst Discrete Choice Experiments
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作者：Amanda Working ; Mohammed Alqawba ; Norou Diawara 等
期刊名称：International Journal of Marketing Studies
印刷版ISSN：1918-719X
电子版ISSN：1918-7203
出版年度：2019
卷号：11
期号：2
页码：1-14
DOI：10.5539/ijms.v11n2p1
出版社：Canadian Center of Science and Education
摘要：Dynamic modelling of decision maker choice behavior of best and worst in discrete choice experiments (DCEs) has numerous applications. Such models are proposed under utility function of decision maker and are used in many areas including social sciences, health economics, transportation research, and health systems research. After reviewing references on the study of such experiments, we present example in DCE with emphasis on time dependent best-worst choice and discrimination between choice attributes. Numerical examples of the dynamic DCEs are simulated, and the associated expected utilities over time of the choice models are derived using Markov decision processes. The estimates are computationally consistent with decision choices over time.
关键词：discrete choice models; best-worst scaling; Markov decision processes