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2016-11

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cc-by-nc-nd (c) Academia Europea de Dirección y Economía de la Empresa, 2016
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/120688

Statistical and cognitive optimization of experimental designs in conjoint analysis

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https://doi.org/10.1016/j.redee.2015.10.001

Abstract

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.

Subject

Estadística, Optimització combinatòria, Anàlisi multivariable

Subject (English)

Statistics, Combinatorial optimization, Multivariate analysis

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Articles publicats en revistes (Empresa)

Citation

HUERTAS GARCÍA, Rubén, NÚÑEZ CARBALLOSA, Ana and MIRAVITLLES MATAMOROS, Paloma. Statistical and cognitive optimization of experimental designs in conjoint analysis. European Journal of Management and Business Economics. 2016. Vol. 25, num. 3, pags. 142-149. ISSN 2444-8451. [consulted: 9 of August of 2026]. Available at: https://hdl.handle.net/2445/120688

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