Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model

Khritish Swargiary

doi:10.20944/preprints202405.0210.v1

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preprints.org > arts and humanities > humanities > doi: 10.20944/preprints202405.0210.v1

Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model

Khritish Swargiary

Version 1 : Received: 3 May 2024 / Approved: 6 May 2024 / Online: 6 May 2024 (08:23:41 CEST)
Version 2 : Received: 14 May 2024 / Approved: 14 May 2024 / Online: 14 May 2024 (09:53:42 CEST)

How to cite: Swargiary, K. Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model. Preprints 2024, 2024050210. https://doi.org/10.20944/preprints202405.0210.v1 Swargiary, K. Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model. Preprints 2024, 2024050210. https://doi.org/10.20944/preprints202405.0210.v1

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MDPI and ACS Style

Swargiary, K. Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model. Preprints 2024, 2024050210. https://doi.org/10.20944/preprints202405.0210.v1

APA Style

Swargiary, K. (2024). Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model. Preprints. https://doi.org/10.20944/preprints202405.0210.v1

Chicago/Turabian Style

Swargiary, K. 2024 "Predicting Blockchain Technology Adoption in Education: An Application of the UTAUT2 Model" Preprints. https://doi.org/10.20944/preprints202405.0210.v1

Abstract

This quantitative, predictive correlation study examined the factors influencing behavioral intentions to adopt blockchain technology in educational settings across the United States. Grounded in the unified theory of acceptance and use of technology (UTAUT2) model, the research investigated the impact of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit on intentions to use blockchain in education among IT officers. Data was collected from 160 participants through an online survey and analyzed using partial least squares structural equation modeling (PLS-SEM). The findings revealed that performance expectancy and social influence significantly predicted behavioral intentions towards blockchain adoption, while effort expectancy, facilitating conditions, hedonic motivation, price value, and habit did not exhibit significant relationships. Furthermore, behavioral intention emerged as a strong predictor of actual blockchain technology utilization in educational institutions. The study contributes to the burgeoning field by validating UTAUT2's applicability to blockchain acceptance in education and providing insights to drive strategic implementation approaches. However, limitations related to causality, measurement, generalizability, and sample size are acknowledged, paving the way for future research endeavors across diverse stakeholder groups, contextual factors, and longitudinal perspectives.

Keywords

blockchain technology; education technology adoption; UTAUT2 model; user acceptance; predictive analytics

Subject

Arts and Humanities, Humanities

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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