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Probabilistic Preferences Composition in the Classification of Apparel Retail Stores

Author

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  • Rodrigo Otávio de Araújo Ribeiro

    (IBOPE-DTM, Rio de Janeiro, Brazil)

  • Lidia Angulo Meza

    (Universidade Federal Fluminense, Niteroi, Brazil)

  • Annibal Parracho Sant'Anna

    (Universidade Federal Fluminense, Niteroi, Brazil)

Abstract

This paper employs the probabilistic composition of preferences to classify stores by their operational efficiency. Probabilistic composition of preferences is a multicriteria analysis methodology based on the transformation of assessments by multiple attributes into probabilities of choice. The numerical initial measurements provide estimates for location parameters of probability distributions that are compared to measure the preferences. The probabilities of choice according to each attribute separately are aggregated according to probabilistic composition rules. A classification of two sets of stores into five classes is performed.

Suggested Citation

  • Rodrigo Otávio de Araújo Ribeiro & Lidia Angulo Meza & Annibal Parracho Sant'Anna, 2015. "Probabilistic Preferences Composition in the Classification of Apparel Retail Stores," International Journal of Business Analytics (IJBAN), IGI Global, vol. 2(4), pages 64-78, October.
    • Handle: RePEc:igg:jban00:v:2:y:2015:i:4:p:64-78
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