Browsing by Author "Yasar, Okan"

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Digital Detox: Exploring the Impact of Cybersecurity Fatigue on Employee Productivity and Mental Health
(Springer Nature, 2025) Mizrak, Filiz; Demirel, Hatice Gokce; Yasar, Okan; Karakaya, Turhan
This study investigates the growing phenomenon of cybersecurity fatigue and its implications for employee productivity and mental health in the high-demand sectors of information technology (IT), finance, healthcare and education. Utilizing a quantitative research methodology, the study surveyed 351 employees from these industries to analyze the relationships between cybersecurity fatigue, work efficiency, and mental health indicators, including stress and anxiety. The findings highlight cybersecurity fatigue as a significant factor contributing to burnout, reduced productivity, and increased psychological strain. Structural Equation Modeling (SEM) demonstrates the moderating effects of digital detox initiatives and mental health support strategies in mitigating fatigue and improving employee well-being and organizational performance. This research addresses a critical gap by focusing on the human dimensions of cybersecurity management and offers practical recommendations for simplifying protocols and fostering resilience. The study provides actionable insights for organizations operating under stringent cybersecurity requirements, enabling them to enhance employee satisfaction and performance.
Strategic Deployment of Piezoelectric Energy Harvesting in Smart Urban Infrastructure: A Hybrid Qpfrs, M-SWARA, K-Means Clustering, and Promethee Evaluation for Sustainable Advantage
(Elsevier, 2025) Mizrak, Filiz; Yasar, Okan
This study develops a hybrid multi-criteria decision-making (MCDM) model to evaluate and prioritize kinetic energy harvesting materials for urban infrastructure, a critical area as cities increasingly adopt sustainable technologies to meet energy demands. The integration of Quadripartitioned Fuzzy Rough Sets (QPFRS), MSWARA, K-Means clustering, and PROMETHEE offers a novel approach for addressing the complexities of material selection by balancing factors such as energy efficiency, durability, cost, scalability, and environmental impact. The strategic importance of this research lies in its potential to guide urban planners and policymakers toward making informed decisions that align with long-term sustainability goals and competitive advantages in smart city development. The findings identify BaTiO3 and ZnO as the most suitable materials for large-scale urban projects, offering superior performance in scalability and environmental sustainability, while materials like PZT exhibit strong energy efficiency but pose environmental concerns. By offering a comprehensive, adaptable evaluation framework, this study contributes both methodologically and practically to the growing field of sustainable urban infrastructure, ensuring that material selection not only meets immediate energy needs but also supports long-term urban development strategies.