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.
Keywords
Acknowledgements
This work has been supported by FIRB2012 project at University of Perugia (code RBFR12SHVV) and the frame of Programme STAR (CUP E68C13000020003) at University of Naples Federico II, financially supported by UniNA and Compagnia di San Paolo.
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
Publisher
:Emerald Group Publishing Limited
Copyright © 2016, Emerald Group Publishing Limited