Navigating the path to ChatGPT adoption among Indian students: unveiling the integration of UTAUT3 and TTF model

Purpose This study aims to determine the factors influencing adoption of ChatGPT among management students in India. Specifically, the study aims to generalise the unified theory of acceptance and use of technology 3 and task-technology-fit (TTF) model to make them usable in the new educational setting. Design/methodology/approach This study used non-probability convenience sampling to collect data from 780 management students from Delhi NCR region of India. Confirmatory factor analysis and structural equation modelling techniques were used to assess the validity of scale and test the hypotheses. Findings The findings reveal that the UTUAT3 model have strong prediction power to understand the adoption intention of ChatGPT among management students. The variables, performance expectancy, effort expectancy, social influence, facilitating conditions, habit, price value and personal innovativeness significantly and positively impacted the intention to use ChatGPT. In addition, the new predictors, learning value (LV) and TTF significantly and positively impacted the intention to use ChatGPT. Originality/value This study focuses on management students in India by introducing a novel model for ChatGPT adoption grounded in the UTAUT3 model. The study incorporated two additional constructs, LV and TTF to make the existing model more comprehensive and robust to understand the ChatGPT adoption intention.

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Publication Details

Journal
VINE Journal of Information and Knowledge Management Systems
Published
2025-04-09
DOI
https://doi.org/10.1108/vjikms-02-2024-0052
Citations
2
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
1.31
Controls
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article

Navigating the path to ChatGPT adoption among Indian students: unveiling the integration of UTAUT3 and TTF model

Saurabh Gupta, Priyanka Priyanka
2 citations
VINE Journal of Information and Knowledge Management Systems
Artificial Intelligence in Healthcare and Education
1.31
article

Navigating the path to ChatGPT adoption among Indian students: unveiling the integration of UTAUT3 and TTF model

Saurabh Gupta, Priyanka Priyanka
article en
2 citations

Abstract

Purpose This study aims to determine the factors influencing adoption of ChatGPT among management students in India. Specifically, the study aims to generalise the unified theory of acceptance and use of technology 3 and task-technology-fit (TTF) model to make them usable in the new educational setting. Design/methodology/approach This study used non-probability convenience sampling to collect data from 780 management students from Delhi NCR region of India. Confirmatory factor analysis and structural equation modelling techniques were used to assess the validity of scale and test the hypotheses. Findings The findings reveal that the UTUAT3 model have strong prediction power to understand the adoption intention of ChatGPT among management students. The variables, performance expectancy, effort expectancy, social influence, facilitating conditions, habit, price value and personal innovativeness significantly and positively impacted the intention to use ChatGPT. In addition, the new predictors, learning value (LV) and TTF significantly and positively impacted the intention to use ChatGPT. Originality/value This study focuses on management students in India by introducing a novel model for ChatGPT adoption grounded in the UTAUT3 model. The study incorporated two additional constructs, LV and TTF to make the existing model more comprehensive and robust to understand the ChatGPT adoption intention.

VINE Journal of Information and Knowledge Management SystemsVol. 56(1)
Alliance University (IN), Global University (LB)
Openalex Percentile: Top 17%
Artificial Intelligence in Healthcare and Education
1.31
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Navigating the path to ChatGPT adoption among Indian students: unveiling the integration of UTAUT3 and TTF model — Saurabh Gupta, Priyanka Priyanka · VINE Journal of Information and Knowledge Management Systems (2025) | TGRS Research Map | TGRS