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Evaluating the barriers affecting cybersecurity behavior in the Metaverse using PLS-SEM and fuzzy sets (fsQCA)

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dc.citedby4
dc.contributor.authorAl-Emran M.en_US
dc.contributor.authorAl-Sharafi M.A.en_US
dc.contributor.authorForoughi B.en_US
dc.contributor.authorIranmanesh M.en_US
dc.contributor.authorAlsharida R.A.en_US
dc.contributor.authorAl-Qaysi N.en_US
dc.contributor.authorAli N.en_US
dc.contributor.authorid56593108000en_US
dc.contributor.authorid57196477711en_US
dc.contributor.authorid56266779100en_US
dc.contributor.authorid55226710300en_US
dc.contributor.authorid57217735651en_US
dc.contributor.authorid57205206257en_US
dc.contributor.authorid54985243500en_US
dc.date.accessioned2025-03-03T07:41:58Z
dc.date.available2025-03-03T07:41:58Z
dc.date.issued2024
dc.description.abstractWhile offering novel user experiences, the Metaverse introduces complex cybersecurity challenges due to the sophisticated interaction of augmented reality (AR), virtual reality (VR), and web technologies. Addressing the barriers to cybersecurity behavior is essential to protect users against risks such as identity theft and loss of digital assets. Therefore, this research aims to investigate these barriers by developing a theoretical model that draws factors from the Technology Threat Avoidance Theory (TTAT) and considers variables such as privacy concerns, perceived risks, and response costs. The data were collected from 395 Metaverse users and were analyzed using the Partial Least Squares-Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM findings showed that perceived threats, privacy concerns, and response costs have a significant negative impact on cybersecurity behavior, while perceived risks have an insignificant negative influence. The fsQCA results revealed that there is not a single pathway leading to robust cybersecurity behavior. Instead, eight configurations that include the presence and absence of certain conditions can lead to this desirable outcome. The findings not only advance the academic conversation on Metaverse security but also offer actionable strategies for stakeholders to reinforce user protection in this dynamic virtual environment. ? 2024 Elsevier Ltden_US
dc.description.natureFinalen_US
dc.identifier.ArtNo108315
dc.identifier.doi10.1016/j.chb.2024.108315
dc.identifier.scopus2-s2.0-85195105429
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85195105429&doi=10.1016%2fj.chb.2024.108315&partnerID=40&md5=2fa2fabb148e290d314b101fa6660304
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36333
dc.identifier.volume159
dc.publisherElsevier Ltden_US
dc.sourceScopus
dc.sourcetitleComputers in Human Behavior
dc.subjectAugmented reality
dc.subjectCybersecurity
dc.subjectFuzzy sets
dc.subjectVirtual reality
dc.subjectBarrier
dc.subjectCyber security
dc.subjectCybersecurity behavior
dc.subjectFuzzy Set Qualitative Comparative Analysis
dc.subjectMetaverses
dc.subjectPartial least square-structural equation modeling
dc.subjectPartial least-squares
dc.subjectStructural equation models
dc.subjectTechnology threat avoidance theory
dc.subjectThreat-avoidance theory
dc.subjectarticle
dc.subjectaugmented reality
dc.subjectavoidance behavior
dc.subjectcomputer security
dc.subjectcontrolled study
dc.subjectconversation
dc.subjecthuman
dc.subjectidentity theft
dc.subjectpartial least squares regression
dc.subjectprivacy
dc.subjectsignal transduction
dc.subjectstructural equation modeling
dc.subjecttheoretical model
dc.subjectvirtual reality
dc.subjectLeast squares approximations
dc.titleEvaluating the barriers affecting cybersecurity behavior in the Metaverse using PLS-SEM and fuzzy sets (fsQCA)en_US
dc.typeArticleen_US
dspace.entity.typePublication
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