Towards the Investigation of Online Shopping Behaviours Using a Fuzzy Inference System

Anett Forgács; Judit Lukács; Ágnes Csiszárik-Kocsir; Richárd Horváth

doi:10.31181/dmame7220241059

Authors

Anett Forgács Doctoral School on Safety and Security Sciences, Óbuda University, Hungary https://orcid.org/0009-0008-4341-7400
Judit Lukács Bánki Donát Faculty of Mechanical and Safety Engineering, Óbuda University, Hungary https://orcid.org/0000-0001-9011-8368
Ágnes Csiszárik-Kocsir Keleti Károly Faculty of Business and Management, Óbuda University, Hungary https://orcid.org/0000-0001-5454-7843
Richárd Horváth Bánki Donát Faculty of Mechanical and Safety Engineering, Óbuda University, Hungary https://orcid.org/0000-0002-4924-3244

DOI:

https://doi.org/10.31181/dmame7220241059

Keywords:

Online Shopping, EuroStat, Fuzzy Inference System, Marketing, Target Group Selection

Abstract

Online shopping has experienced substantial growth over the past decade, and this trend is expected to persist. The convenience it offers consumers serves as a driving force behind this expansion. Online retailers stand to benefit from a comprehensive understanding of consumer behavior and online shopping habits, as it enables them to formulate more effective marketing strategies and tailor their communications to the preferences of online shoppers. This paper aimed to develop a bespoke questionnaire leveraging data from a EuroStat report in 2021. As novel methodology a Sugeno- type predictive fuzzy model was constructed using these data, empowering businesses to make more precise predictions regarding the requirements and behaviors of distinct consumer groups. The study examined the following areas of consumers: online shoppers belonging to the X, Y, and Z generations; living in small towns, towns, or in the capital; and studying, working, or both. In addition, the likelihood of spending money online was determined regarding the following product categories: Bills, utilities; (2) Food, shopping; (3) Entertainment; (4) Wellness, beauty; (5) Electronic items; (6) Fashion; (7) Home, decoration and (8) Other goods. The results of this survey, combined with the fuzzy model developed, serve as valuable resources for online retailers seeking to enhance their marketing strategies and gain a deeper understanding of customer preferences. The conclusions highlight patterns and preferences among different age groups and locations, providing valuable insights for online retailers to enhance their marketing strategies when identifying main target groups for specific products. Additionally, the research offers a more comprehensive understanding of demographic attributes associated with these age cohorts than EuroStat data.

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