ChatGPT: Advocacy or Opposition Through Mixed Methods

Abstract

Since its inception, ChatGPT has sparked debates regarding its benefits and drawbacks, which ultimately influence users’ decision-making about its usage. This study aims to investigate the effects of ChatGPT’s system reliability and utilitarian value on users’ behavioral responses. It employs a mixed-method technique comprising topic modeling analysis of 211,301 tweets and structural equation modeling using data collected from 210 full-time working professionals. The results demonstrate the significant influence of users’ perceptions of ChatGPT system reliability, which are shaped by perceived intelligence, system availability, immaturity, and privacy concerns. Additionally, the study reveals that ease of use and information quality have substantial effects on users’ perception of its utilitarian value, which, in conjunction with system reliability, contribute positively to users’ satisfaction. Furthermore, the findings affirm the positive effects of users’ satisfaction on their continuous use and recommendation intentions of ChatGPT to others. The findings provide theoretical and practical implications.

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