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I Am ChatGPT, the ultimate AI Chatbot! Investigating the determinants of users' loyalty and ethical usage concerns of ChatGPT

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  • Niu, Ben
  • Mvondo, Gustave Florentin Nkoulou

Abstract

This research aims to explore the determinants of users' satisfaction and loyalty towards ChatGPT while also investigating ethical concerns related to the usage of the artificial intelligence (AI) chatbot. For this purpose, the study develops a framework based on five models and theories (information system success, technology acceptance model, affinity theory, coolness theory, and posthumanism) as well as other important constructs (user ethical perceptions and user ethical beliefs). Analysis of data collected from 456 actual ChatGPT users in the US reveals several key findings. First, information quality significantly and positively affects users' satisfaction, perceived usefulness, and coolness. Second, perceived usefulness, coolness, technology affinity, and posthuman ability also have a positive impact on users' satisfaction, which subsequently influences their loyalty to the AI chatbot. Furthermore, the findings demonstrate that user ethical perceptions and beliefs negatively moderate the relationship between satisfaction and loyalty. The main implication of this research is that brand managers and programmers should regularly assess the chatbot's performance to ensure that the information provided is relevant, reliable, concise, and delivered promptly. This is because users highly value the quality of information delivered by the AI chatbot. Additionally, they should prioritize the ethical aspect, as it directly influences users' satisfaction and loyalty towards the chatbot services.

Suggested Citation

  • Niu, Ben & Mvondo, Gustave Florentin Nkoulou, 2024. "I Am ChatGPT, the ultimate AI Chatbot! Investigating the determinants of users' loyalty and ethical usage concerns of ChatGPT," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
  • Handle: RePEc:eee:joreco:v:76:y:2024:i:c:s0969698923003132
    DOI: 10.1016/j.jretconser.2023.103562
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