Unlocking students' continuance intention to use generative AI for educational purposes: the dual role of habit

Purpose Generative artificial intelligence (GenAI) plays a crucial role in academic sustainability as it enables personalized learning experiences and fosters innovative problem-solving approaches. Based on the technology readiness index (TRI) and the expectancy–confirmation model (ECM), this study aims to propose and validate a research model that examines the nexus between individual technology-related traits, performance expectancy, confirmation of expectations, satisfaction and continuance intention to use GenAI for learning purposes. Furthermore, the mediating and moderating mechanisms of habit on the relationship between satisfaction and continuance intention are clarified. Design/methodology/approach Data were collected through paper-based questionnaires administered to 419 higher education students from universities in Hanoi, using a non-probability convenience sampling technique. Partial least squares structural equation modeling was used for empirical analysis. Findings Results show that optimism and innovativeness positively influence performance expectancy and confirmation of expectations. Insecurity negatively influences confirmation of expectations, while discomfort negatively affects performance expectancy. The study confirms the positive relationships between confirmation of expectations, performance expectancy, satisfaction and continuance intention, as proposed by the ECM. Interestingly, habit serves as both a positive mediator and a negative moderator in the relationship between satisfaction and continuance intention. Originality/value This research contributes to understanding higher education students' behavior toward GenAI usage for learning in the post-adoption stage. The findings confirm that individual characteristics predict ECM variables, advancing our understanding of ECM antecedents and TRI outcomes. Notably, this study reveals the dual role of habit in the satisfaction-continuance intention relationship: habit positively mediates the effect of satisfaction on continuance intention and negatively moderates the same relationship. These findings enrich the literature on the mechanisms and boundary conditions affecting the relationship between satisfaction and continuance intention.

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Publication Details

Journal
Journal of Trade Science
Published
2026-02-04
DOI
https://doi.org/10.1108/jts-08-2025-0038
Primary Topic
Technology Adoption and User Behaviour
Type
article
Field-Weighted Citation Impact
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article

Unlocking students' continuance intention to use generative AI for educational purposes: the dual role of habit

Alvedi Sabani, Mohamed Farah, Darren Le, Hoang Giang Nguyen
Journal of Trade Science
Technology Adoption and User Behaviour
article

Unlocking students' continuance intention to use generative AI for educational purposes: the dual role of habit

Alvedi Sabani, Mohamed Farah, Darren Le, Hoang Giang Nguyen
article en

Abstract

Purpose Generative artificial intelligence (GenAI) plays a crucial role in academic sustainability as it enables personalized learning experiences and fosters innovative problem-solving approaches. Based on the technology readiness index (TRI) and the expectancy–confirmation model (ECM), this study aims to propose and validate a research model that examines the nexus between individual technology-related traits, performance expectancy, confirmation of expectations, satisfaction and continuance intention to use GenAI for learning purposes. Furthermore, the mediating and moderating mechanisms of habit on the relationship between satisfaction and continuance intention are clarified. Design/methodology/approach Data were collected through paper-based questionnaires administered to 419 higher education students from universities in Hanoi, using a non-probability convenience sampling technique. Partial least squares structural equation modeling was used for empirical analysis. Findings Results show that optimism and innovativeness positively influence performance expectancy and confirmation of expectations. Insecurity negatively influences confirmation of expectations, while discomfort negatively affects performance expectancy. The study confirms the positive relationships between confirmation of expectations, performance expectancy, satisfaction and continuance intention, as proposed by the ECM. Interestingly, habit serves as both a positive mediator and a negative moderator in the relationship between satisfaction and continuance intention. Originality/value This research contributes to understanding higher education students' behavior toward GenAI usage for learning in the post-adoption stage. The findings confirm that individual characteristics predict ECM variables, advancing our understanding of ECM antecedents and TRI outcomes. Notably, this study reveals the dual role of habit in the satisfaction-continuance intention relationship: habit positively mediates the effect of satisfaction on continuance intention and negatively moderates the same relationship. These findings enrich the literature on the mechanisms and boundary conditions affecting the relationship between satisfaction and continuance intention.

Journal of Trade ScienceVol. 14(1)
PepsiCo (United Kingdom) (GB), MIT University (MK), Research Institute of Posts and Telecommunications (SK)
Openalex Percentile: Top 68%
Technology Adoption and User Behaviour
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