The Impact of Artificial Intelligence Recommendation System on Consumers’ Impulse Purchase

DOI

10.2991/978-2-38476-509-6_41How to use a DOI?

Keywords

Artificial Intelligence Recommendation System; Impulsive Purchasing Behavior; User Decision-Making Path; Psychological Induction Mechanism for E-commerce

Abstract

Against the background of digital acceleration, the Artificial Intelligence (AI) recommendation system has evolved from an information tool to a decision-making influencer, reshaping consumer behavior. TikTok, Taobao and Amazon’s recommendation algorithms guide users with differentiated logic, which leads to different impulse buying modes. Based on the research of the three platforms, this paper finds that TikTok is based on users’ real-time interests, which realizes the real-time binding of content and goods and promotes rapid decision-making; Taobao combines search and browsing behaviors for personalized matching to guide users to make decisions in a medium period; Amazon, on the other hand, relies on long-term user data to build a robust recommendation model, and pays more attention to stimulating repeated purchases rather than instant conversion. There are significant differences among the three in behavior induction paths. The results show that although the recommendation system can improve shopping efficiency and tap potential demand, the negative effects such as over-pushing, content duplication and user decision-making pressure cannot be ignored. This paper not only fills a gap in the comparison of recommendation logics across platforms but also offers ideas for balancing behavioral guidance and ethical responsibility in algorithm design.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Zishuo Zhao
PY  - 2025
DA  - 2025/12/15
TI  - The Impact of Artificial Intelligence Recommendation System on Consumers’ Impulse Purchase
BT  - Proceedings of the 2025 International Conference on Mental Growth and Human Resilience (MGHR 2025)
PB  - Atlantis Press
SP  - 377
EP  - 384
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-509-6_41
DO  - 10.2991/978-2-38476-509-6_41
ID  - Zhao2025
ER  -