Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

中文翻译：

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自动售货机上的食品购买行为：货架图和购物时间的作用

目的

本文的目的是通过分析货架图的影响来研究食品和饮料的自动零售环境，货架图是一种可视化的商品销售实践，而购物时间（花费的购买时间）是食品消费者购买行为的一部分，以进一步丰富食品的零售行为关于公司吸收客户知识的能力的辩论。

设计/方法/方法

使用在自动售货机（AVM）上对消费者购买决策过程的27,230个有效观察的样本进行了真实世界的实验。数据由购物者行为分析系统收集，可以更好地了解AVM用户的行为。进行了两组回归以检验这两个假设。

发现

实验结果表明，货架图-AVM中产品的计划化，系统化组织-对食品购买产生积极影响。货架图可充当购物时间与购买之间关系的中介者，从而缩短购物时间并增加购买量。

创意/价值

这项工作着重于食品和饮料自动购物环境中的客户行为，从而增加了客户知识文献。用来收集实时数据的购物者分析技术可以更好地了解AVM用户的购买行为，并提供有关AVM性能的新营销和零售见解，零售商可以使用这些见解来改进其营销策略。