Dyah Erny Herwindiati
Doctor of Management Science Department, Universitas Tarumanagara, Jakarta, Indonesia

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COGNITIVE FACTORS OF RECOMMENDATION SYSTEMS AND THEIR INFLUENCE IN BUILDING TRUST TO DRIVE CONSUMER PURCHASE INTENTION: A SYSTEMATIC LITERATURE REVIEW Desi Arisandi; Dyah Erny Herwindiati; Cokki Cokki
International Journal of Application on Economics and Business Vol. 4 No. 2 (2026): May 2026
Publisher : Graduate Program of Universitas Tarumanagara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24912/ijaeb.v4i2.545-555

Abstract

The development of technology has created recommendation systems as a tool for increasing user experience and marketing effectiveness in e-commerce platforms. Recommendation systems play a crucial role in helping consumers find relevant products. However, cognitive factors associated with the effectiveness of recommendation systems that, in turn, affect consumer trust and purchase intention require investigation. This study aims to systematically examine the cognitive factors that influence the effectiveness of recommendation systems and their influence on customer trust, which mediates the influence of recommendation systems on consumer purchase intention. This research utilized a Systematic Literature Review using the PRISMA protocol. 664 articles from the Scopus and Dimensions databases were gathered, and 13 articles qualified for the criteria of eligibility for further research. The analysis of these 13 studies reveals that cognitive properties like recommendation accuracy, novelty, precision, and explainability are the primary factors determining consumer trust in recommender systems. Although trust is often recognized as a construct in conceptual discussions, many empirical studies have not explicitly modeled trust as a variable that mediates the cognitive factors in recommendation systems with purchase intention. The lack of explicit mediation analysis in previous research highlights the theoretical gap between cognitive factors and behavioral outcomes, opening opportunities for future research to examine more rigorous causal pathways. Theoretically, this study advances our understanding of cognitive and affective interactions in recommendation systems, while also providing practical implications for e-commerce platform developers in balancing technical and behavioral aspects of users to enhance loyalty and purchase intention.