Citation

Ramakrishnan, Kannan and Kannan, Rathimala and Ersoy, Ayse Begum and Contu, Davide and Stachowicz-Stanusch, Aagata and Mataruna, Leonardo (2026) AI‑Based Algorithmic Predictions of Purchase Intention, and Loyalty: A Multi‑country Study. Expert Applications and Security, 1823. pp. 65-74. ISSN 2367-3370

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Abstract

This study investigates the impact of AI tools (chatbots, virtual assistants, augmented reality, visual search, and voice assistants) on online shopping behavior across Malaysia, UAE, Russia, and Brazil. Utilizing machine learning approaches including Random Forest, Gradient Boosting, and Decision Trees, we analyzed data from 2,613 respondents to predict purchase intention, customer satisfaction, and loyalty. Our findings reveal significant variation in AI tool awareness and effectiveness across countries, with Malaysia and UAE demonstrating higher adoption rates compared to Russia and Brazil. The predictive models achieved accuracies ranging from 67% to 99%, with particular strength in predicting purchase intention (79–84%) and customer loyalty (83–90%). Feature importance analysis identified ease of use, trust, and perception as primary drivers in Russia and Malaysia, while demographic factors like age and income were more influential in UAE and Brazil. This research provides valuable insights for businesses implementing AI strategies across different markets, highlighting the need for contextual adaptation to maximize consumer engagement and loyalty.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA150-272.5 Algebra
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	31 Jul 2026 06:38
Last Modified:	31 Jul 2026 06:38
URII:	http://shdl.mmu.edu.my/id/eprint/16418

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