Enhancing Marketing Personalized Shopping Recommendations in the UAE: Leveraging Logic Mining and Advanced Technologies

Fanar Shwedeh (), Amro Dabash (), DABBAGH Tamadher Al () and Ahmad Aburayya ()
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Fanar Shwedeh: City University Ajman, Ajman, UNITED ARAB EMIRATES
Amro Dabash: The British University in Dubai, Dubai, UNITED ARAB EMIRATES
DABBAGH Tamadher Al: City University Ajman, Ajman, UNITED ARAB EMIRATES
Ahmad Aburayya: City University Ajman, Ajman, UNITED ARAB EMIRATES

Foundations of Management, 2024, vol. 16, issue 1, 345-358

Abstract: This study investigates how personalized recommendation systems in e-commerce operate, using Social Exchange Theory as its theoretical basis. Through empirical research, we analyze the effects of improving consumer experiences, enhancing product suggestions, and building trust and satisfaction on the effectiveness of personalized recommendation systems. Our study combines practical techniques with theoretical knowledge to improve user engagement and build long-lasting brand loyalty. This research provides valuable insights for e-commerce stakeholders, suggesting that individualized recommendations might enhance consumer satisfaction in the digital marketplace.

Keywords: Personalized Recommendation Systems; Consumer Challenges; Trust and Satisfaction; User Engagement; Digital Marketplace (search for similar items in EconPapers)
JEL-codes: M30 (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:founma:v:16:y:2024:i:1:p:345-358:n:1021

DOI: 10.2478/fman-2024-0021

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