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Exploring ChatGPT adoption among business and management students through the lens of diffusion of Innovation Theory

Authors :
Alaa Amin Abdalla
Mohd Abass Bhat
Chandan Kumar Tiwari
Shagufta Tariq Khan
Abel Dula Wedajo
Source :
Computers and Education: Artificial Intelligence, Vol 7, Iss , Pp 100257- (2024)
Publication Year :
2024
Publisher :
Elsevier, 2024.

Abstract

Purpose: this study aims to present an innovative approach (Diffusion of Innovation Theory) to investigate the adoption of ChatGPT by business and management students. The theory emphasizes integrating the variables Viz. relative advantage, compatibility, complexity, trialability, observability, attitude, and intention to adopt ChatGPT in the context of management education. Method: ology: a non-probability purposive sample of 383 students enrolled in management of Indian public and private institutions was taken to conduct survey to administer questionnaires. Partial Least Square-Structural Equation Modelling was employed to analyze the data using Smart PLS software. Findings: the findings suggest that students' attitude toward the integration of ChatGPT for educational purposes and knowledge acquisition are overwhelmingly positive. Moreover, relative benefit, compatibility, complexity, trialability, and observability indicate a favorable disposition toward the intention to use ChatGPT among business and management students’ community. Implications: the study asserts significant implications for multiple sectors, including global society, businesses, and academia. The application of the Diffusion of Innovation Theory to the examination of management students' attitude towards ChatGPT provides valuable practical and theoretical insights. Originality: the originality of the study lies in the innovative approach it takes in investigating the utilization of ChatGPT in management education. Hence, the application of the Diffusion of Innovation theory and the inclusion of context-specific characteristics contribute to the uniqueness of the study.

Details

Language :
English
ISSN :
2666920X
Volume :
7
Issue :
100257-
Database :
Directory of Open Access Journals
Journal :
Computers and Education: Artificial Intelligence
Publication Type :
Academic Journal
Accession number :
edsdoj.5d0c69632bc54b1b94a5ffe2b478c71d
Document Type :
article
Full Text :
https://doi.org/10.1016/j.caeai.2024.100257