• Medientyp: E-Artikel
  • Titel: Food purchasing behaviour at automatic vending machines: the role of planograms and shopping time
  • Beteiligte: Marinelli, Luca; Fiano, Fabio; Gregori, Gian Luca; Daniele, Lucia Michela
  • Erschienen: Emerald, 2021
  • Erschienen in: British Food Journal
  • Sprache: Englisch
  • DOI: 10.1108/bfj-02-2020-0107
  • ISSN: 0007-070X
  • Schlagwörter: Food Science ; Business, Management and Accounting (miscellaneous)
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  • Beschreibung: <jats:sec><jats:title content-type="abstract-subheading">Purpose</jats:title><jats:p>The purpose of this paper is to investigate the food and beverage automatic retail environment by analysing the impact of planograms, conceived as a visual merchandising practice and shopping time – the time spent making a purchase – as part of food consumer purchasing behaviour to further enrich the debate on the ability of companies to absorb customer knowledge.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title><jats:p>A real-world experiment was conducted using a sample of 27,230 valid observations of consumer purchasing decision-making processes at automatic vending machines (AVMs). Data were collected by a shopper behaviour analytics system that allows for a better understanding of the AVM users' behaviour. Two sets of regressions were run to test the two hypotheses.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Findings</jats:title><jats:p>The experimental results demonstrated that planograms – the planned, systematic organisation of products in an AVM – positively impact food purchases. A planogram acts as a mediator in the relationship between shopping time and purchase, resulting in shorter shopping times and more purchases.</jats:p></jats:sec><jats:sec><jats:title content-type="abstract-subheading">Originality/value</jats:title><jats:p>This work adds to the customer knowledge literature by focussing on customer behaviour in the food and beverage automated shopping environment. The shopper analytics technology adopted to collect real-time data leads to a better understanding of the purchasing behaviour of AVMs' users and provides new marketing and retail insights into AVMs' performance that retailers can use to improve their marketing strategies.</jats:p></jats:sec>