Published In
IEEE Transactions on Engineering Management
Document Type
Post-Print
Publication Date
3-2024
Subjects
Blockchain Adoption, Blockchains (Databases) -- United States
Abstract
The increasing popularity of Blockchain technology has led to its adoption in various sectors, including higher education. However, the sustainability of Blockchain in higher education is yet to be fully understood. Therefore, this research examines the determinants affecting Blockchain sustainability by developing a theoretical model that integrates the protection motivation theory (PMT) and expectation confirmation model (ECM). Based on 374 valid responses collected from university students, the proposed model is evaluated through a deep learning-based hybrid structural equation modeling (SEM) and artificial neural network (ANN) approach. The PLS-SEM results confirmed most of the hypotheses in the proposed model. The sensitivity analysis outcomes discovered that users’ satisfaction is the most important factor affecting Blockchain sustainability, with 100% normalized importance, followed by perceived usefulness (58.8%), perceived severity (12.1%), and response costs (9.2%). The findings of
Rights
© Copyright the author(s) 2024
Locate the Document
DOI
10.1109/TEM.2024.3365041
Persistent Identifier
https://archives.pdx.edu/ds/psu/41447
Citation Details
AlShamsi, Mohammed; Al-Emran, Mostafa; Daim, Tugrul; Al-Sharafi, Mohammed A.; Bolatan, Gulin Idil Sonmezturk; and Shaalan, Khaled, "Uncovering the Critical Drivers of Blockchain sustainability in higher education using a deep learning-based hybrid SEM-ANN approach" (2024). Engineering and Technology Management Faculty Publications and Presentations. 342.
https://archives.pdx.edu/ds/psu/41447
Description
This article has been accepted for publication in IEEE Transactions on Engineering Management. This is the author's version which has not been fully edited and content may change prior to final publication. Citation information: DOI 10.1109/TEM.2024.3365041