AN ENHANCED INNOVATION RESISTANCE THEORY TO MEASURE THE BARRIERS OF AI-BASED CHATBOTS USAGE AMONG TEACHER TRAINEES

In recent years, Information and Communication Technology (ICT) has experienced tremendous progress (especially the advancement of AI-based Chatbots), profoundly affecting the global economic structure, social transformation, business innovation, education models, soft skills acquisition, human lifestyles, and so on. The main objective of this study is to develop and validate an enhanced Innovation Resistance Theory (IRT) model to measure the barriers of AI-based Chatbots usage among teacher trainees. This study mainly uses the quantitative research method and PLS-SEM for data analysis. This study finds that Value Barrier (VB), Risk Barrier (RB), Image Barrier (IB), Information Quality Barrier (IQB), and Job Relevance Barrier (JRB) have a significant and direct influence on teacher trainees’ resistance to AI-based Chatbots (RTAC). However, the effects of Usage Barrier (UB) and Tradition Barrier (TB) on teacher trainees’ RTAC are less significant. VB plays a mediating role in the relationship between Technology Anxiety (TA) and RTAC. RB mediates the relationship between the Electronic Word-of-Mouth Barrier (E-WOMB) and RTAC. JRB can also play a mediating role. This study not only proposes a new theoretical model, which is based on the traditional IRT model and combines new constructs (e.g., IQB and E-WOMB) and new paths (e.g., the mediating role of JRB), but also contributes to the cultivation of future technological talents and the spread and development of AI-based Chatbots in the future.