Analyzing behavioral intentions toward Generative Artificial Intelligence: the case of ChatGPT

Generative artificial intelligence (AI) is an innovative AI technology that has garnered considerable attention worldwide. This study aimed to facilitate the development of such technologies by examining the factors affecting individuals’ intentions toward generative AI (e.g., ChatGPT). Concretely, we developed a causal model by extending the expectation confirmation model with information system success theory, privacy concerns, and perceived innovativeness. Then, we tested the model by analyzing survey-based data from 252 Korean ChatGPT users. As a result, we found that antecedent variables -information quality, system quality, privacy concerns, and perceived innovativeness- play notable roles in affecting users’ intentions to continually use and recommend generative AI ChatGPT. Overall, the current research is one of the first attempts to track the variables influencing individuals’ intentions to continually use and recommend in the context of generative AI ChatGPT.