A Dual-Theory Perspective of BRT and IRT: Exploring ChatGPT Adoption for Learning and Knowledge Development in the Age of Generative AI

In the emerging knowledge economy, digital knowledge tools such as ChatGPT are transforming how knowledge is created, accessed, and shared in higher education. This study aims to investigate the reasons for (motivation) and the reasons against (resistance) factors influencing students’ attitudes and intentions toward adopting ChatGPT for academic learning and knowledge development by integrating Behavioral Reasoning Theory and Innovation Resistance Theory. The study adopted a quantitative approach, collecting data from Malaysian higher-education students and analyzing the results using structural equation modeling (SmartPLS 3). The study revealed that factors such as relative advantage and personal advantage were identified as “RF” factors, while image barrier and risk barrier were identified as “RA” factors that significantly affect attitudes and adoption intentions toward ChatGPT. The findings confirmed that values influence reasons for and against, but there is no significant effect on attitudes towards ChatGPT adoption intention. Lastly, attitudes significantly mediate the relationship between reasons and intention. These findings highlight how AI-based tools can facilitate access to and diffusion of knowledge in tourism and hospitality education. This study advances beyond the Technology Acceptance Model (TAM) by integrating Behavioral Reasoning Theory (BRT) and Innovation Resistance Theory (IRT) to develop a unified framework that simultaneously examines RF-enabling and RA-inhibiting factors shaping ChatGPT adoption among tourism and hospitality students.