artificial intelligence (AI) tools, particularly the Chat Generative Pre-Trained Transformer (ChatGPT), in higher education settings, with a focus on financial management education in Iran. Given the analytical and decision-intensive nature of financial management, this domain provides a suitable context for investigating technology-enhanced learning behaviors.



The research population consisted of undergraduate and postgraduate students majoring in Financial Management across the Payame Noor University centers in Iran. A total of 260 valid questionnaires were collected and analyzed using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach.



The results revealed that Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Perceived Fear (PF), and Protective Motivation (PM) exerted significant positive effects on Actual Use (AU) of ChatGPT. Moreover, Peer Influence (PI) had both a direct effect on Continued Use (CU) and a moderating effect on the relationship between AU and CU. Model fit indices confirmed satisfactory predictive validity of the proposed framework.



The main contribution of this study lies in integrating the Technology Acceptance Model (TAM) and the Protection Motivation Theory (PMT) within the context of higher education in a developing country. By emphasizing actual user behavior rather than behavioral intention, the research fills a major gap in the literature on generative AI adoption in emerging educational environments and provides valuable insights for policy-making and strategic planning in digital learning.