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

Author

Listed:
  • SHWEDEH Fanar

    (City University Ajman, Ajman, UNITED ARAB EMIRATES)

  • DABASH Amro

    (The British University in Dubai, Dubai, UNITED ARAB EMIRATES)

  • DABBAGH Tamadher AL

    (City University Ajman, Ajman, UNITED ARAB EMIRATES)

  • ABURAYYA Ahmad

    (City University Ajman, Ajman, UNITED ARAB EMIRATES)

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.

Suggested Citation

  • SHWEDEH Fanar & DABASH Amro & DABBAGH Tamadher AL & ABURAYYA Ahmad, 2024. "Enhancing Marketing Personalized Shopping Recommendations in the UAE: Leveraging Logic Mining and Advanced Technologies," Foundations of Management, Sciendo, vol. 16(1), pages 345-358.
    • Handle: RePEc:vrs:founma:v:16:y:2024:i:1:p:345-358:n:1021
    DOI: 10.2478/fman-2024-0021
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    References listed on IDEAS

    as
    1. Onofrei, George & Filieri, Raffaele & Kennedy, Lorraine, 2022. "Social media interactions, purchase intention, and behavioural engagement: The mediating role of source and content factors," Journal of Business Research, Elsevier, vol. 142(C), pages 100-112.
    2. Xin Qi & Huaming Yu & Angelika Ploeger, 2020. "Exploring Influential Factors Including COVID-19 on Green Food Purchase Intentions and the Intention–Behaviour Gap: A Qualitative Study among Consumers in a Chinese Context," IJERPH, MDPI, vol. 17(19), pages 1-22, September.
    3. G. Onofrei & R. Filieri & L. Kennedy, 2022. "Social media interactions, purchase intention, and behavioural engagement on social networking platforms: The mediating role of source and content factors," Post-Print hal-04779119, HAL.
    4. Akram, Umair & Junaid, Muhammad & Zafar, Abaid Ullah & Li, Zhiwen & Fan, Mingyue, 2021. "Online purchase intention in Chinese social commerce platforms: Being emotional or rational?," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    5. Fanar Shwedeh & Ayotunde Adetola Adelaja & Gbemisola Ogbolu & Abdelkarim Kitana & Abdallah Taamneh & Ahmad Aburayya & Said A Salloum, 2023. "Entrepreneurial innovation among international students in the UAE: Differential role of entrepreneurial education using SEM analysis," International Journal of Innovative Research and Scientific Studies, Innovative Research Publishing, vol. 6(2), pages 266-280.
    6. Mahmud Akhter Shareef & Vinod Kumar & Uma Kumar & Subhas C. Misra, 2008. "The role of e-sellers' overall reputation on trust formation, purchase intention and purchase satisfaction: a developing country perspective," International Journal of Electronic Marketing and Retailing, Inderscience Enterprises Ltd, vol. 2(2), pages 105-134.
    7. George Stalidis & Iphigenia Karaveli & Konstantinos Diamantaras & Marina Delianidi & Konstantinos Christantonis & Dimitrios Tektonidis & Alkiviadis Katsalis & Michail Salampasis, 2023. "Recommendation Systems for e-Shopping: Review of Techniques for Retail and Sustainable Marketing," Sustainability, MDPI, vol. 15(23), pages 1-33, November.
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    More about this item

    Keywords

    Personalized Recommendation Systems; Consumer Challenges; Trust and Satisfaction; User Engagement; Digital Marketplace;
    All these keywords.

    JEL classification:

    • M30 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - General

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