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Factors driving cybersecurity behavior in virtual reality: Evidence from SEM-ANN approach

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  • Alsharida, Rawan A.
  • Al-Emran, Mostafa
  • Al-Sharafi, Mohammed A.

Abstract

Despite the growing adoption of virtual reality (VR) in education, health, and gaming, empirical research on users’ cybersecurity behaviors remains scarce, leaving a critical gap in understanding how threat perceptions and individual propensities shape protective actions in these immersive spaces. This study aims to address this void by extending the Technology Threat Avoidance Theory (TTAT) with privacy concerns and perceived awareness to examine the determinants of cybersecurity behavior among VR users. Data were collected from 297 VR users and analyzed using a hybrid partial least squares-structural equation modeling (PLS-SEM) and artificial neural network (ANN) approach. The PLS-SEM results confirmed the impact of perceived severity, perceived vulnerability, distrust propensity, and risk propensity on perceived threats. Privacy concerns, perceived awareness, and perceived threats were found to significantly affect cybersecurity behavior. The ANN analysis ranked perceived threats as the most influential factor affecting cybersecurity behavior, with a normalized importance of 100%. By refining TTAT for VR contexts, this research provides theoretical advancements and practical guidance for various stakeholders to enhance user trust, reduce vulnerabilities, and promote safer adoption of immersive technologies.

Suggested Citation

  • Alsharida, Rawan A. & Al-Emran, Mostafa & Al-Sharafi, Mohammed A., 2026. "Factors driving cybersecurity behavior in virtual reality: Evidence from SEM-ANN approach," Technology in Society, Elsevier, vol. 86(C).
    • Handle: RePEc:eee:teinso:v:86:y:2026:i:c:s0160791x26001065
    DOI: 10.1016/j.techsoc.2026.103317
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    References listed on IDEAS

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