Abstract

This study assesses the declared preferences of a sample of Italian consumers (n=657) towards chocolate, considering their sociodemographic variables, lifestyle and food habits. Firstly, the Best-Worst scaling (BWS) methodology was employed to define the relative importance assigned by consumers to 12 chocolate attributes. Additionally, the Latent Class analysis was used to identify different preference-based chocolate consumers segments. The Multinomial Logistic Regression was applied to explore the possible relationships between individuals’ socio-demographic, lifestyle and food habit variables and the cluster membership. The main findings showed that “typology”, “brand” and “label information” were the most important attributes for chocolate choices, while “quality certifications”, “ethical attributes” and “packaging” resulted as not important for product selection. Five different consumer clusters were defined: the MRL highlighted how certain socio-demographic variables, such as age or level of education, influence the orientation of consumer choices. Also, sports activity, food habits and choices explain group membership very well.

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