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All Journal Priviet Social Sciences Journal
Masarroh, Itaul
Unknown Affiliation
Economics, Econometrics & Finance Education Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Effectiveness of recommendation algorithms on impulsive buying in e-commerce platforms: A systematic literature review Fadilah, Nuriya; Masarroh, Itaul; Wildan, Muhammad Alkirom
Priviet Social Sciences Journal Vol. 5 No. 8 (2025): August 2025
Publisher : Privietlab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55942/pssj.v5i8.485

Abstract

This study analyzes the effectiveness of recommendation algorithms in influencing impulsive buying behavior on e-commerce platforms. Through a comprehensive review of the existing research literature, it was revealed that personalization strategies such as collaborative filtering, content-based filtering, and artificial intelligence (AI) boost impulsive buying tendencies by alleviating cognitive burdens and enhancing elements such as limited-time offers, social proof, and emotional connection. Factors such as flow experience, positive feelings, and moderating elements such as age, social media influence, and economic circumstances also play a crucial role in determining the effectiveness of these algorithms. This study provides beneficial knowledge for algorithm developers and digital marketers to refine personalization efforts and to consider psychological and contextual influences when crafting more impactful marketing strategies.
Co-Authors Fadilah, Nuriya Wildan, Muhammad Alkirom