Frontiers in psychology · 2026
Determinants of information security policy compliance: integrating task-technology fit and threat avoidance appraisals in the digital workplace.
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Alassaf Mada, Alkhalifah Ali
Аннотация
INTRODUCTION: The integrity of organizational information systems fundamentally relies on the psychological commitment of users to adhere to security protocols. Informational security policy (ISP) depends on users' compliance to protect their organization's information and technology assets against security threats.
METHODS: Drawing on the intersection of cognitive and behavioral psychology, this study examines information security policy compliance (ISPC) behavior by integrating the Task-Technology Fit (TTF) model, technology threat avoidance theory (TTAT), and the Theory of Planned Behavior (TPB). This study proposes a comprehensive research model to elucidate the cognitive factors and motivational drivers that shape an employee's behavioral intention to comply. Utilizing a partial least squares structural equation modeling (PLS-SEM) approach, we empirically tested the model with data from 288 employees across public and private sectors in Saudi Arabia.
RESULTS: The results show that Task and technology characteristics significantly drive task-technology fit, which, along with self-efficacy, social influence, and policy effectiveness, positively predicts security compliance intentions and subsequent behavior. Conversely, compliance intention is hindered by perceived costs, while the influence of perceived security threats remains statistically insignificant. The study discusses key theoretical and applied insights, providing a roadmap for future research in the field.
METHODS: Drawing on the intersection of cognitive and behavioral psychology, this study examines information security policy compliance (ISPC) behavior by integrating the Task-Technology Fit (TTF) model, technology threat avoidance theory (TTAT), and the Theory of Planned Behavior (TPB). This study proposes a comprehensive research model to elucidate the cognitive factors and motivational drivers that shape an employee's behavioral intention to comply. Utilizing a partial least squares structural equation modeling (PLS-SEM) approach, we empirically tested the model with data from 288 employees across public and private sectors in Saudi Arabia.
RESULTS: The results show that Task and technology characteristics significantly drive task-technology fit, which, along with self-efficacy, social influence, and policy effectiveness, positively predicts security compliance intentions and subsequent behavior. Conversely, compliance intention is hindered by perceived costs, while the influence of perceived security threats remains statistically insignificant. The study discusses key theoretical and applied insights, providing a roadmap for future research in the field.