Uncovering the Critical Drivers of Blockchain Sustainability in Higher Education Using a Deep Learning-Based Hybrid SEM-ANN Approach
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Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee-Inst Electrical Electronics Engineers Inc
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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 and expectation confirmation model. 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 approach. The partial least squares-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 this research provide valuable insights for higher education institutions and other stakeholders looking to sustain the use of blockchain technology.
Açıklama
Anahtar Kelimeler
Blockchains, Education, Sustainable development, Mathematical models, Informatics, Fraud, Supply chain management, Blockchain, deep learning, drivers, higher education, structural equation modeling and artificial neural network (SEM-ANN), sustainability
Kaynak
Ieee Transactions on Engineering Management
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
71
