Factors affecting the purchase of private label food products. Issue 3 (16th November 2020)

• Record Type: Journal Article
• Authors: Sansone, Marcello; Musso, Fabio; Colamatteo, Annarita; Pagnanelli, Maria Anna
• Is Part Of: British food journal. Volume 123:Issue 3(2021)
• Page Start: 1207
• Page End: 1222
• Publication Date: 2020-11-16
• Subjects: Private label -- Purchase frequency -- Food products -- Consumer behaviour; Food industry and trade -- Periodicals; Food -- Marketing -- Periodicals; Food adulteration and inspection -- Periodicals; Food -- Periodicals; 381.456413
• DOI: 10.1108/BFJ-01-2020-0048
• Languages: English
• ISSNs: 0007-070X

Abstract

Abstract : Purpose: This research paper aims to understand which factors influence the purchase of private label food products, by measuring the importance of 14 variables for purchasing frequency. Design/methodology/approach: Data were collected through questionnaires to a sample of consumers. They have been analysed according to the extra tree classifier methodology, which allows providing a more reliable classification – compared to previous studies – of factors affecting consumers' choices of private label products. Findings: Results show that consumers' choices related to private label food products are influenced by groups of heterogeneous variables related to their perception on products, satisfaction of post-consumption, store's role and trust built over time by retailers. Research limitations/implications: Data have been collected through an online survey, which could generate the bias of self-selection; the sampling method is non-probabilistic. Practical implications: The study provides useful indications on the role of private labels in retailer management policies and on marketing competences and skills that are necessary for managing retailers' assortments. Originality/value: The existing literature lacks clarity on the factors that influence the frequency of purchasing private label food products. By considering a higher number of variables than previous studies, it has been possible to classify and measure the importance of each variable included in the analysis framework adopted, also in case of correlation between variables.