IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v17y2025i2p94-d1593705.html
   My bibliography  Save this article

CORES: Context-Aware Emotion-Driven Recommendation System-Based LLM to Improve Virtual Shopping Experiences

Author

Listed:
  • Abderrahim Lakehal

    (LRSD Laboratory, Faculty of Sciences, Computer Science Department, University Ferhat Abbas Sétif-1, Sétif P.O. Box 19000, Algeria)

  • Adel Alti

    (LRSD Laboratory, Faculty of Sciences, Computer Science Department, University Ferhat Abbas Sétif-1, Sétif P.O. Box 19000, Algeria
    Department of Management Information Systems & Production Management College of Business & Economics, Qassim University, P.O. Box 6633, Buraidah 51452, Saudi Arabia)

  • Boubakeur Annane

    (LRSD Laboratory, Faculty of Sciences, Computer Science Department, University Ferhat Abbas Sétif-1, Sétif P.O. Box 19000, Algeria)

Abstract

In today’s business landscape, artificial intelligence (AI) plays a pivotal role in shopping processes and customization. As the demand for customization grows, virtual reality (VR) emerges as an innovative solution to improve users’ perception and decision making in virtual shopping experiences (VSEs). Despite its potential, limited research has explored the integration of contextual information and emotions in VR to deliver effective product recommendations. This paper presents CORES (context-aware emotion-driven recommendation system), a novel approach designed to enrich users’ experiences and to support decision making in VR. CORES combines advanced large language models (LLMs) and embedding-based context-aware recommendation strategies to provide customized products. Therefore, emotions are collected from social platforms, and relevant contextual information is matched to enable effective recommendation. Additionally, CORES leverages transformers and retrieval-augmented generation (RAG) capabilities to explain recommended items, facilitate VR visualization, and generate insights using various prompt templates. CORES is applied to a VR shop of different items. An empirical study validates the efficiency and accuracy of this approach, achieving a significant average accuracy of 97% and an acceptable response time of 0.3267s in dynamic shopping scenarios.

Suggested Citation

  • Abderrahim Lakehal & Adel Alti & Boubakeur Annane, 2025. "CORES: Context-Aware Emotion-Driven Recommendation System-Based LLM to Improve Virtual Shopping Experiences," Future Internet, MDPI, vol. 17(2), pages 1-31, February.
    • Handle: RePEc:gam:jftint:v:17:y:2025:i:2:p:94-:d:1593705
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/17/2/94/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/17/2/94/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bin Kim, Woo & Jung Choo, Ho, 2023. "How virtual reality shopping experience enhances consumer creativity: The mediating role of perceptual curiosity," Journal of Business Research, Elsevier, vol. 154(C).
    2. Han, Sang-Lin & An, Myounga & Han, Jerry J. & Lee, Jiyoung, 2020. "Telepresence, time distortion, and consumer traits of virtual reality shopping," Journal of Business Research, Elsevier, vol. 118(C), pages 311-320.
    3. Gousia Habib & Sparsh Sharma & Sara Ibrahim & Imtiaz Ahmad & Shaima Qureshi & Malik Ishfaq, 2022. "Blockchain Technology: Benefits, Challenges, Applications, and Integration of Blockchain Technology with Cloud Computing," Future Internet, MDPI, vol. 14(11), pages 1-22, November.
    4. Meißner, Martin & Pfeiffer, Jella & Peukert, Christian & Dietrich, Holger & Pfeiffer, Thies, 2020. "How virtual reality affects consumer choice," Journal of Business Research, Elsevier, vol. 117(C), pages 219-231.
    5. Kowalczuk, Pascal & Siepmann (née Scheiben), Carolin & Adler, Jost, 2021. "Cognitive, affective, and behavioral consumer responses to augmented reality in e-commerce: A comparative study," Journal of Business Research, Elsevier, vol. 124(C), pages 357-373.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Yunen & Shao, Wei & Quach, Sara & Thaichon, Park & Li, Qianmin, 2024. "Examining the moderating effects of shopping orientation, product knowledge and involvement on the effectiveness of Virtual Reality (VR) retail environment," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    2. Mkedder, Nadjim & Jain, Varsha & Salunke, Parth, 2024. "Determinants of virtual reality stores influencing purchase intention: An interpretive structural modeling approach," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    3. Shulin Wang & Shanhua Wu, 2023. "Optimizing the Location of Virtual-Shopping-Experience Stores Based on the Minimum Impact on Urban Traffic," Sustainability, MDPI, vol. 15(13), pages 1-25, June.
    4. Xi, Nannan & Hamari, Juho, 2021. "Shopping in virtual reality: A literature review and future agenda," Journal of Business Research, Elsevier, vol. 134(C), pages 37-58.
    5. Kostyk, Alena & Sheng, Jie, 2023. "VR in customer-centered marketing: Purpose-driven design," Business Horizons, Elsevier, vol. 66(2), pages 225-236.
    6. Gong, Taeshik & Park, JungKun, 2023. "Effects of augmented reality technology characteristics on customer citizenship behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    7. Rana Muhammad Sohail Jafar & Wasim Ahmad & Yi Chen, 2024. "Metaverse in Human Behavior: The Role of Telepresence and Flow Experience on Consumers’ Shopping Behavior in the Metaverse," SAGE Open, , vol. 14(2), pages 21582440241, June.
    8. Bin Kim, Woo & Jung Choo, Ho, 2023. "How virtual reality shopping experience enhances consumer creativity: The mediating role of perceptual curiosity," Journal of Business Research, Elsevier, vol. 154(C).
    9. Xiaowei Fan & Jiyao Xun & Les Dolega & Lin Xiong, 2025. "The Role of Augmented and Virtual Reality in Shaping Retail Marketing: A Meta-Analysis," Sustainability, MDPI, vol. 17(2), pages 1-37, January.
    10. Eggenschwiler, Matthias & Linzmajer, Marc & Roggeveen, Anne L. & Rudolph, Thomas, 2024. "Retailing in the metaverse: A framework of managerial considerations for success," Journal of Retailing and Consumer Services, Elsevier, vol. 79(C).
    11. Jafar, Rana Muhammad Sohail & Ahmad, Wasim & Sun, Yanming, 2023. "Unfolding the impacts of metaverse aspects on telepresence, product knowledge, and purchase intentions in the metaverse stores," Technology in Society, Elsevier, vol. 74(C).
    12. Anderson, Kelley Cours & Laverie, Debra A., 2022. "In the consumers’ eye: A mixed-method approach to understanding how VR-Content influences unbranded product quality perceptions," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    13. Caboni, Federica & Basile, Vincenzo & Kumar, Harish & Agarwal, Diksha, 2024. "A holistic framework for consumer usage modes of augmented reality marketing in retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    14. Xu, Xiao-Yu & Jia, Qing-Dan & Tayyab, Syed Muhammad Usman, 2024. "Exploring the stimulating role of augmented reality features in E-commerce: A three-staged hybrid approach," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    15. Han-Jen Niu & Fei-Hsu Sun Hung & Po-Ching Lee & Yensen Ni & Yuhsin Chen, 2023. "Eco-Friendly Transactions: Exploring Mobile Payment Adoption as a Sustainable Consumer Choice in Taiwan and the Philippines," Sustainability, MDPI, vol. 15(24), pages 1-18, December.
    16. Andry Alamsyah & Gede Natha Wijaya Kusuma & Dian Puteri Ramadhani, 2024. "A Review on Decentralized Finance Ecosystems," Future Internet, MDPI, vol. 16(3), pages 1-29, February.
    17. Sun, Chunhua & Fang, Yuan & Kong, Meng & Chen, Xiayu & Liu, Yezheng, 2022. "Influence of augmented reality product display on consumers’ product attitudes: A product uncertainty reduction perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    18. Aslam, Usman, 2023. "Understanding the usability of retail fashion brand chatbots: Evidence from customer expectations and experiences," Journal of Retailing and Consumer Services, Elsevier, vol. 74(C).
    19. Lambillotte, Laetitia & Magrofuoco, Nathan & Poncin, Ingrid & Vanderdonckt, Jean, 2022. "Enhancing playful customer experience with personalization," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    20. M. L. Sworna Kokila & E. Fenil & N. P. Ponnuviji & G. Nirmala, 2024. "Securing cloud-based medical data: an optimal dual kernal support vector approach for enhanced EHR management," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(7), pages 3495-3507, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jftint:v:17:y:2025:i:2:p:94-:d:1593705. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.