期刊名称：European Journal of Management and Business Economics
印刷版ISSN：2444-8451
出版年度：2016
卷号：25
期号：3
页码：142-149
DOI：10.1016/j.redee.2015.10.001
摘要：Conjoint analysis has become the most used technique for measuring preferences for new products to be launched in the market. Experimental design models are key elements for its use in market research. Such models involve a matrix in which attributes and levels are combined, making product concepts that respondents then evaluate. Experimental design has emerged as a key element in conjoint analysis’ success because its application generates statistical and reliability implications for part-worth factor estimations and for the type of heuristics followed by respondents. This paper proposes a conceptualization of both statistical and cognitive efficiency criteria for experimental designs. A review of the most used statistical optimization criteria is presented, as well as a methodology for optimizing cognitive efficiency. Finally, we suggest a dynamic algorithm for optimizing the objective function in a sequential manner.
