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Adoption of Artificial Intelligence: Influence of User Experience, Perceived Versatility and Educational Impact on Overall Satisfaction and Future Intentions

N. Meena Rani & Mary J. Metilda

Management and Labour Studies2026https://doi.org/10.1177/0258042x261432794article
AJG 1ABDC C
Weight
0.50

What the paper says

Artificial intelligence (AI) is rapidly developing as a game changer in higher education across geographies, and India is no exception. The main objective of this research is to investigate the adoption of generative AI tools such as ChatGPT in higher education and how management students perceive and adopt the same in order to meet their education needs. Primary data were gathered from 313 students from India pursuing management education. A structured questionnaire with previously validated and contextually adapted scale encompassing five elements, including user experience (UE), perceived versatility (VER), educational impact (EI), overall satisfaction (OAS) and intentions for future usage (FI), was used. The confirmatory factor analysis shows a strong association among UE, VER and EI as explanatory variables, and OAS and FI as outcome variables. This research is novel as it presents and confirms the VER construct as a strong and independent predictor. The research highlights the importance of AI tools that can support the varied learning styles and changing learning needs of management students. The results support the mediating nature of OAS between the perception linked to the user and future behavioural intentions. The study further confirms its centrality in technology adoption models in higher education settings. The results of the study provide valuable insights to educators, institutional leaders and developers of AI tools who endeavour to integrate generative AI tools in management education.

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https://doi.org/https://doi.org/10.1177/0258042x261432794

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@article{n.2026,
  title        = {{Adoption of Artificial Intelligence: Influence of User Experience, Perceived Versatility and Educational Impact on Overall Satisfaction and Future Intentions}},
  author       = {N. Meena Rani & Mary J. Metilda},
  journal      = {Management and Labour Studies},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1177/0258042x261432794},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.