A Study on Association between Users' Relatedness toward Generative AI and Continuous Use Intention

Purpose This study attempts to analyze association between users’ relatedness toward generative AI and continuous use intention.Methods The input variables include relatedness dimension, innovativeness dimension, social impact dimension, and resistance dimension, whereas the response is continuous use intention dimension. Significant if-then rules are produced by applying association rule method.Results For each item of continuous use intention dimension, major antecedents are identified. For item ‘use intention in the future’, social impact dimension is most influential, for items ‘product/service needs’ and ‘value judgement’, relatedness dimension is influential, for item ‘more frequency’, social impact dimension is influential, and for item ‘paid version’, innovativeness dimension is influential.Conclusion The empirical analysis results indicate that relatedness dimension, innovativeness dimension, social impact dimension, and resistance dimension are crucial for users’ continuous use intention for generative AI. Detailed findings might reveal managerial implication for corporate managers and policy directions for government officers.