Uncovering the Critical Drivers of Blockchain Sustainability in Higher Education Using a Deep Learning-Based Hybrid SEM-ANN Approach

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dc.authorid0000-0003-0726-6031
dc.authorid0000-0003-0823-8390
dc.authorid0000-0003-1432-8958
dc.authorid0000-0001-6505-4331
dc.authorid0000-0002-9668-3584
dc.contributor.authorAlShamsi, Mohammed
dc.contributor.authorAl-Emran, Mostafa
dc.contributor.authorDaim, Tugrul
dc.contributor.authorAl-Sharafi, Mohammed A.
dc.contributor.authorBolatan, Gulin Idil S.
dc.contributor.authorShaalan, Khaled
dc.date.accessioned2026-01-24T12:29:01Z
dc.date.available2026-01-24T12:29:01Z
dc.date.issued2024
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractThe 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.
dc.identifier.doi10.1109/TEM.2024.3365041
dc.identifier.endpage8208
dc.identifier.issn0018-9391
dc.identifier.issn1558-0040
dc.identifier.scopus2-s2.0-85185370780
dc.identifier.scopusqualityQ1
dc.identifier.startpage8192
dc.identifier.urihttps://doi.org/10.1109/TEM.2024.3365041
dc.identifier.urihttps://hdl.handle.net/20.500.12868/5073
dc.identifier.volume71
dc.identifier.wosWOS:001216284400002
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIeee-Inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Transactions on Engineering Management
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20260121
dc.subjectBlockchains
dc.subjectEducation
dc.subjectSustainable development
dc.subjectMathematical models
dc.subjectInformatics
dc.subjectFraud
dc.subjectSupply chain management
dc.subjectBlockchain
dc.subjectdeep learning
dc.subjectdrivers
dc.subjecthigher education
dc.subjectstructural equation modeling and artificial neural network (SEM-ANN)
dc.subjectsustainability
dc.titleUncovering the Critical Drivers of Blockchain Sustainability in Higher Education Using a Deep Learning-Based Hybrid SEM-ANN Approach
dc.typeArticle

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