A tri-theory examination of GenAI adoption in academic research using BRT, UTAUT3, and IRT

Abstract

Purpose This study aims to explore the reasons for and against factors that could substantially impact researchers' attitudes towards adopting ChatGPT for academic research, using BRT, UTAUT3, and IRT. Design/methodology/approach This study employed a quantitative research design; data were collected from higher education researchers and analyzed using Structural Equation Modeling (SEM) via SmartPLS 4. Findings The study identified performance expectancy, effort expectancy, and social influence as “RF” factors; in contrast, image barrier and risk barrier were identified as “RA” factors that significantly influence the higher education researchers attitudes and adoption intentions of ChatGPT. The findings confirmed that values affect (RF) and (RA) towards ChatGPT adoption intentions, while values has an insignificant effect on attitude. Finally, attitudes significantly mediate the relationship between reasons and intentions. Practical implications The findings suggest that research policymakers and tourism and hospitality universities should strengthen the reasons for ChatGPT adoption, while immediately addressing the reasons against it that may hinder adoption. Originality/value This research makes a significant advance in examining the attitudes and intentions of tourism and hospitality higher education researchers towards ChatGPT adoption for academic research, utilising BRT, UTAUT3, and IRT, and combining the “reasons for” and “reasons against” adoption into a single framework.

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