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Understanding Consumer Behavior Through AI-Powered Recommender Systems : A Systematic Review and Bibliometric Perspective (Record no. 132790)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02013nam a2200145 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250912b |||||||| |||| 00| 0 eng d |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Aparna Kumari |
| 245 ## - TITLE STATEMENT | |
| Title | Understanding Consumer Behavior Through AI-Powered Recommender Systems : A Systematic Review and Bibliometric Perspective |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | pp9-32 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. biblio.abstract | Purpose : This study examined the evolving landscape of recommender systems (RSs) and their impact on consumer purchasing behavior by identifying key research themes, trends, and gaps in the current literature.<br/><br/>Methodology : A bibliometric analysis and systematic literature review (SLR) of 312 articles was conducted using the R package to perform performance analysis and scientific mapping, aiming to investigate the intellectual framework of the field, emerging issues, and research trends.<br/><br/>Findings : The study identified four prominent themes: the role of RSs and AI in consumer decision support, trust, and adoption; the consumer privacy paradox in personalized commerce; and communication strategies in web personalization. The research indicated a shift toward adaptive, emotionally intelligent, and privacy-conscious RSs.<br/><br/>Practical Implications : The results provided crucial insights for platform practitioners and developers to create RSs that enhanced personalization while addressing key issues related to trust, privacy, and user engagement, thereby improving the consumer experience and retention.<br/><br/>Originality : This paper offered a comprehensive and organized summary of the fragmented literature on RSs and consumer behavior. By integrating bibliometric analysis with an SLR presented a unique, data-driven framework for future academic exploration and responsible innovation in digital commerce. |
| 654 ## - SUBJECT ADDED ENTRY--FACETED TOPICAL TERMS | |
| Subject | <a href=" recommender system"> recommender system</a> |
| -- | <a href="science mapping">science mapping</a> |
| -- | <a href="consumer behavior">consumer behavior</a> |
| -- | <a href="R-package">R-package</a> |
| -- | <a href="bibliometrics">bibliometrics</a> |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Vishal Kumar Laheri |
| 773 0# - HOST ITEM ENTRY | |
| Host Biblionumber | 80314 |
| Host Itemnumber | 113840 |
| Place, publisher, and date of publication | India Associated Management Consultants |
| Title | Indian Journal of Marketing |
| International Standard Serial Number | 0973 8703 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Journal Article |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Location (home branch) | Sublocation or collection (holding branch) | Date acquired | Koha issues (times borrowed) | Piece designation (barcode) | Koha date last seen | Price effective from | Koha item type |
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| Dewey Decimal Classification | SNDT Juhu | SNDT Juhu | 12/09/2025 | jp926.1 | 12/09/2025 | 12/09/2025 | Journal Article |