Information Quality, Source Trustworthiness, and the UTAUT Model: Understanding ChatGPT Usage Intentions Among Manila-Based University Student

Abstract

By adding the concepts of Information Quality (IQ) and Source Trustworthiness (ST) to the Unified Theory of Acceptance and Use of Technology (UTAUT), this study examines the acceptance of ChatGPT among undergraduate students in Manila. An online survey was used to gather 249 valid responses from various universities between January and April of 2025. Smart PLS 4.0 was used to analyze the dataset in order to assess the measurement and structural models. The findings showed that IQ ($\boldsymbol{\beta}=0.313, \mathrm{p}=0.001$) and ST ($\boldsymbol{\beta}= 0.302, \mathrm{p}\lt 0.001)$ had a significant impact on Performance Expectancy (PE), which in turn predicted students’ Intention to Use (IT) along with Effort Expectancy (EE), Social Influence (SI), and Facilitating Conditions (FC). Of these, EE showed the weakest but significant effect, while PE was the strongest predictor $(\beta=0.402, \mathrm{p}\lt 0.001)$, followed by FC and SI. With Q2 values verifying predictive relevance, the model accounted for $48 \%$ of the variance in IT and 32.5% of the variance in PE. The results highlight how crucial perceived utility, institutional support, and trust are in determining ChatGPT adoption in higher education.

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