Skip to main content

ORIGINAL RESEARCH article

Front. Psychol.
Sec. Addictive Behaviors
Volume 15 - 2024 | doi: 10.3389/fpsyg.2024.1462376
This article is part of the Research Topic An Integrative Proposal in Addiction and Health Behaviors Psychosocial Research: Overview of New Trends and Future Orientations View all 9 articles

Predicting Online Shopping Addiction: A Decision Tree Model Analysis

Provisionally accepted
Xueli Wan Xueli Wan 1Jie Zeng Jie Zeng 1*Ling Zhang Ling Zhang 2
  • 1 Chengdu Normal University, Chengdu, China
  • 2 Chongqing Three Gorges University, Wanzhou, Chongqing Municipality, China

The final, formatted version of the article will be published soon.

    Background: Internet shopping addictionOnline shopping addiction has been identified as a detrimental behavioral pattern, necessitating the development of effective mitigation strategies.Objective: This pioneering study in online shopping addictiononline shopping addiction prediction offers valuable tools and research support for identifying and understanding this behavioral addiction, potentially informing future intervention strategies and research directions. This study provides research support for improving people's understanding and management of behavioral addictions and promoting healthier online shopping habits.

    Keywords: internet shopping addictiononline shopping addiction, c5.0 decision tree model, predictive analysis, behavioral addiction, academic procrastination, social anxiety, self-efficacy, Psychological mechanisms

    Received: 10 Jul 2024; Accepted: 11 Dec 2024.

    Copyright: © 2024 Wan, Zeng and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jie Zeng, Chengdu Normal University, Chengdu, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.