Abstract

Purpose: The main aim of this paper is to explore consumer decisions and emotions during shopping at the self-service store with fast-moving consumer goods (FMCG). Design/methodology/approach: The subject of the study is to assess the impact of emotions during the choice-making process on consumers' buying decisions. The respondents are citizens of the West Pomeranian region, Poland. The survey was conducted using state-of-the-art data acquisition technologies, i.e., Virtual Reality and EEG. An interview was also used as a complementary form. The research was both qualitative and quantitative, with a research sample of 34 respondents and took place in the virtual world. The researchers used primary data. The results presented here are part of a broader research project that used a triangulation of research methods to allow a deeper analysis of the conscious and unconscious aspects of the subjects. Findings: The research provided independent data on consumer emotions. The authors identified 4 groups of emotions that appeared during the selection of a product and were highly differentiated and strongly dependent on such characteristics as consumer type and gender. It has also been noticed that the longer a product is held, the lower emotional “sleepiness’. Research limitations/implications: One of the main limitations is the data collection process, which is relatively expensive, so the sample size is limited. The results obtained can be a signpost for a researcher who would like to use this new technology for further research. Practical implications: The results obtained can be used by shop managers in planning the sales activities or shop space to help the customer decide. Originality/value: In the research was used an innovative combination of virtual reality (VR) equipment and an electroencephalogram (EEG). To the best of the authors' knowledge, the results of a study from the FMCG industry using both devices simultaneously have never been published. Keywords: consumer behaviour, virtual reality, new technology, EEG. Category of the paper: Research paper.

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