Exploring the Effect of Attachment on Technology Addiction to Generative AI Chatbots: A Structural Equation Modeling Analysis

结构方程建模 生成语法 心理学 上瘾 认知科学 计算机科学 人工智能 神经科学 机器学习
作者
Yiting Huang,Hanyun Huang
出处
期刊:International Journal of Human-computer Interaction [Taylor & Francis]
卷期号:: 1-10 被引量:3
标识
DOI:10.1080/10447318.2024.2426029
摘要

With the advancement of artificial intelligence technology, generative AI chatbots (GAIC) such as ChatGPT, are integrating into various aspects of society and quietly changing people's lives. However, although there is a plethora of research concerning social media usage and addiction, discussions about chatbots remain far from adequate. Investigating the use and potential technology addiction to generative AI chatbots (TAGAIC) holds both theoretical and practical significance. Drawing on attachment theory, this study aims to investigate the formative factors in TAGAIC. A structural equation model was used to analyze the data collected from a questionnaire survey of 364 GAIC users. Results reveal that technology addiction is positively influenced by emotional attachment but not by functional attachment. Besides, perceived anthropomorphism and perceived empathy have a positive effect on emotional attachment, while system quality and information quality have a positive effect on functional attachment. Limitations of the study were discussed.
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