The Metaverse, an expansive online 3D virtual realm, has transformed how people work, socialize, and engage, but its growth brings critical cybersecurity challenges, particularly in data security and privacy. Since many cybersecurity incidents stem from human behavior, understanding factors influencing users’ cybersecurity practices in the Metaverse is vital. This study addresses the gap by proposing an integrated model based on Protection Motivation Theory (PMT), Health Belief Model (HBM), and Theory of Interpersonal Behavior (TIB), with trust as an additional construct. Using a hybrid structural equation modeling-artificial neural network (SEM-ANN) approach, data from 531 Metaverse users were analyzed. The results indicated that perceived vulnerability, self-efficacy, cues to action, habit, and trust significantly affect cybersecurity behavior, with “cues to action” identified as the most critical factor (97.8% normalized importance). Conversely, perceived severity, response efficacy, response costs, and facilitating conditions showed no significant impact. The findings offer theoretical insights and practical implications for Metaverse stakeholders and cybersecurity strategies.
Read full abstract