Purpose Drawing on the information system model and attachment theory, the purpose of the current research is to validate how standardization and personalization jointly affect users' continuous use intention of artificial intelligence (AI) chatbots through emotional attachment. Design/methodology/approach Empirical data were collected from 551 active users through the online survey platform Credamo. Partial least squares structural equation modeling was employed to assess both the measurement model and the structural model. Additionally, the PROCESS macro based on SPSS was used for the examination of the parallel–serial mediation model. Findings Standardization and personalization are positively correlated with information quality and system quality. Moreover, information quality and system quality exhibit positive correlations with emotional attachment. Furthermore, the parallel–serial mediation analysis affirms the significant indirect effect of standardization and personalization on continuous use intention. Research limitations/implications This study enhances societal comprehension of the nuanced interplay between information quality, system quality and emotional responses within the AI chatbot domain. It provides actionable insights for AI enterprises and developers seeking to improve interaction experiences and drive the evolution of AI chatbot systems. Originality/value In human–computer interaction, developers face a persistent challenge in balancing service standardization for reliability with personalization for relevance. While research has often advanced these in parallel, the joint influence of these two seemingly contradictory strategies on long-term user engagement remains theoretically underdeveloped. This study addresses this critical gap by proposing and testing a model that illuminates the psychological mechanisms linking this strategic balance to continuous use.
Pang et al. (Thu,) studied this question.