Exploring the Acceptance of ChatGPT for Translation: An Extended TAM Model Approach

The increasing reliance on ChatGPT for instant translation among researchers, professors, and students worldwide underscores its growing significance. Despite its widespread use, academic literature has not thoroughly examined the factors influencing the intention to use ChatGPT, particularly in the context of its impact. This study aims to bridge this gap by investigating the acceptance of ChatGPT in the United Arab Emirates (UAE), focusing on how users’ attitudes may differ based on the language pairs involved in translation, namely from source language (SL) to target language (TL) and vice versa. Employing an extended Technology Acceptance Model (TAM), this research adopts a quantitative methodology. The proposed model was empirically tested through a survey of 257 respondents, analyzed using Structural Equation Modeling (SEM-PLS). The findings reveal that Perceived Ease of Use, Perceived Usefulness, and Motivation significantly influence Behavioral Intentions to use ChatGPT for translation. Additionally, Perceived Usefulness and Motivation were found to notably affect Perceived Ease of Use, with Perceived Usefulness being further influenced by users’ prior experience. These results offer valuable insights for translation researchers, educators, and machine translation (MT) system developers, contributing both theoretical and practical perspectives on the factors driving the adoption and use of ChatGPT in translation contexts.