  Since the public release of Chat Generative Pre-Trained Transformer
(ChatGPT), extensive discourse has emerged concerning the potential advantages
and challenges of integrating Generative Artificial Intelligence (GenAI) into
education. In the realm of information systems, research on technology adoption
is crucial for understanding the diverse factors influencing the uptake of
specific technologies. Theoretical frameworks, refined and validated over
decades, serve as guiding tools to elucidate the individual and organizational
dynamics, obstacles, and perceptions surrounding technology adoption. However,
while several models have been proposed, they often prioritize elucidating the
factors that facilitate acceptance over those that impede it, typically
focusing on the student perspective and leaving a gap in empirical evidence
regarding educators viewpoints. Given the pivotal role educators play in higher
education, this study aims to develop a theoretical model to empirically
predict the barriers preventing educators from adopting GenAI in their
classrooms. Acknowledging the lack of theoretical models tailored to
identifying such barriers, our approach is grounded in the Innovation
Resistance Theory (IRT) framework and augmented with constructs from the
Technology-Organization-Environment (TOE) framework. This model is transformed
into a measurement instrument employing a quantitative approach, complemented
by a qualitative approach to enrich the analysis and uncover concerns related
to GenAI adoption in the higher education domain.
