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An Integrated SEM-ANN Approach to Evaluating Cybersecurity Behaviors in the Metaverse.

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Title: An Integrated SEM-ANN Approach to Evaluating Cybersecurity Behaviors in the Metaverse.
Authors: Alsharida, Rawan A. (AUTHOR), Al-rimy, Bander Ali Saleh (AUTHOR), Al-Emran, Mostafa (AUTHOR), Al-Sharafi, Mohammed A. (AUTHOR), Zainal, Anazida (AUTHOR)
Source: International Journal of Human-Computer Interaction. Nov2025, Vol. 41 Issue 22, p14622-14641. 20p.
Subjects: Planned behavior theory, Protection motivation theory, Artificial neural networks, Habit, Internet security, Structural equation modeling, Shared virtual environments
Abstract: The Metaverse is rapidly transforming virtual interactions, especially in education, but its growth also attracts cyber threats. Without understanding and addressing users' cybersecurity behaviors, the Metaverse's full potential is at risk, making investigating these behaviors a pressing necessity. Grounded on the theory of planned behavior (TPB), technology threat avoidance theory (TTAT), and protection motivation theory (PMT), this research develops an integrated theoretical model to evaluate users' cybersecurity behaviors in the Metaverse. Data were gathered from 701 Metaverse users and were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) approach. Of the 11 proposed hypotheses, the Partial Least Squares-Structural Equation Modeling results showed that nine were supported, explaining 63.1% of the variance in cybersecurity behavior. The ANN analysis revealed that avoidance motivation and attitude are the most significant factors influencing cybersecurity behavior. In addition to its theoretical contributions, the findings offer actionable insights for various stakeholders. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: An Integrated SEM-ANN Approach to Evaluating Cybersecurity Behaviors in the Metaverse.
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Human-Computer+Interaction%22">International Journal of Human-Computer Interaction</searchLink>. Nov2025, Vol. 41 Issue 22, p14622-14641. 20p.
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  Data: <searchLink fieldCode="DE" term="%22Planned+behavior+theory%22">Planned behavior theory</searchLink><br /><searchLink fieldCode="DE" term="%22Protection+motivation+theory%22">Protection motivation theory</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Habit%22">Habit</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br /><searchLink fieldCode="DE" term="%22Structural+equation+modeling%22">Structural equation modeling</searchLink><br /><searchLink fieldCode="DE" term="%22Shared+virtual+environments%22">Shared virtual environments</searchLink>
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  Data: The Metaverse is rapidly transforming virtual interactions, especially in education, but its growth also attracts cyber threats. Without understanding and addressing users' cybersecurity behaviors, the Metaverse's full potential is at risk, making investigating these behaviors a pressing necessity. Grounded on the theory of planned behavior (TPB), technology threat avoidance theory (TTAT), and protection motivation theory (PMT), this research develops an integrated theoretical model to evaluate users' cybersecurity behaviors in the Metaverse. Data were gathered from 701 Metaverse users and were analyzed using a hybrid structural equation modeling-artificial neural network (SEM-ANN) approach. Of the 11 proposed hypotheses, the Partial Least Squares-Structural Equation Modeling results showed that nine were supported, explaining 63.1% of the variance in cybersecurity behavior. The ANN analysis revealed that avoidance motivation and attitude are the most significant factors influencing cybersecurity behavior. In addition to its theoretical contributions, the findings offer actionable insights for various stakeholders. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Human-Computer Interaction is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1080/10447318.2025.2484650
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        Text: English
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              Text: Nov2025
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