A multi-product approach for detecting subjects’ and objects’ covariates in consumer preferences

Abstract

Purpose

A different framework based on a parametric version of the process generating the hedonic scores is adopted. More precisely, a probability distribution for ordinal responses is proposed as a mixture of two components, denoted as feeling (as expressed preference) and uncertainty component (as inherent indecision). The purpose of this paper is to analyse the effect of covariates on the consumers’ behaviour pattern according to a statistical model.

Design/methodology/approach

Sample data come from a multidisciplinary research aimed to improve the quality and marketability of soft fruits. Then, a stochastic model with subjects’ and objects’ covariates is built and the interpretation of significant results is discussed.

Findings

The joint effects of personal characteristics and chemical contents of juice on the hedonic scores given by consumers are examined and graphically depicted by means of a significant model.

Originality/value

The paper suggests a multi-product approach to expressed hedonic scores by means of a generalization of CUB models.

Citation

Capecchi, S., Endrizzi, I., Gasperi, F. and Piccolo, D. (2016), "A multi-product approach for detecting subjects’ and objects’ covariates in consumer preferences", British Food Journal, Vol. 118 No. 3, pp. 515-526. https://doi.org/10.1108/BFJ-10-2015-0343