Understanding ChatGPT Adoption in Manila Universities: A UTAUT2 Approach on Hedonic Motivation and Habitual Use

Abstract

The paper investigates how behavioural intention and UATAUT2 constructions shape real use behaviour among Manila university students. After 256 legitimate replies were gathered via an online survey, the data was examined. Using Partial Least Squares Structural Equation Modelling (PLS-SEM), the current work tested numerous hypotheses about the interactions among these constructives. While social impact obviously matters, the results show that students' behavioural intention to use ChatGPT is much influenced by performance expectation, habit, and facilitating settings. But intention to use ChatGPT was found to be not much influenced by effort expectation or hedonic motivation. Strong predictors of use behaviour were shown to be behavioural intention, thereby validating that students who plan to use ChatGPT are quite likely to do so. These findings imply that stressing on improving habitual use and guaranteeing access to resources will be more effective than stressing effort expectation if ChatGPT is adopted in more general educational environments. Theoretically, this study refines UTAUT2 by validating its constructs in the context of generative AI, where constructs such as hedonic motivation behave differently. It also addresses a geographic gap in AI adoption research by focusing on the Philippines, a rapidly digitizing developing economy.

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