Browsing by Author "Ozbiltekin-Pala, Melisa"

Now showing 1 - 2 of 2

Evaluating Human-Centric Cybersecurity Risks in the Manufacturing Industry
(inderscience Enterprises Ltd, 2024) Ayrancı, Gönül; Ozbiltekin-Pala, Melisa; Ozkan-Ozen, Yesim Deniz
With rapidly developing technology and digitalisation, the importance of cybersecurity is increasing, underlining the importance of human-centric cybersecurity risks, especially in the manufacturing industry. This study aims to reveal the sector's human-centric cybersecurity risks due to the manufacturing industry's complex processes and continuity-based structure. In this study, eight risks were identified and evaluated using the fuzzy CRITIC method. This study identified the top three human-centric cybersecurity risks in the manufacturing industry as follows: 'employee resistance to cybersecurity practices and data privacy', 'lack of employee training and education on cybersecurity' and 'lack of human-machine integration'. This comprehensive analysis of human-centric cybersecurity risks in the manufacturing industry highlights the need for cybersecurity strategies to include human-centric measures. The results suggest that managers, security professionals, and practitioners develop an effective combat strategy against human-centric cybersecurity risks in the manufacturing industry.
Risks to Energy Efficiency in Supply Chain Resilience: From an Emerging Economy Context
(Taylor & Francis Ltd, 2025) Ayranci, Gonul; Ozbiltekin-Pala, Melisa; Mangla, Sachin Kumar; Kazancoglu, Yigit
Supply chains, involving multiple stakeholders and complex operations, are vulnerable to disruptions; therefore, ensuring their resilience is crucial. Recently, the concept of an energy-efficient supply chain has gained attention, because it reduces costs and supports social and environmental development. However, many risks arise while improving energy efficiency in supply chains, and it is important to identify these risks, particularly in emerging economies. This study identifies these risks and their interrelations through literature review and expert opinions. By integrating Bayesian Belief Network and Monte Carlo Simulation, scenario analyses are conducted to explore the possible consequences of these risks, and the study finds that natural events are the most critical risks to energy efficiency in supply chain resilience. It contributes to the small body of literature on risks to energy efficiency in supply chain resilience, and innovatively applies scenario analysis to these risks, providing managers and practitioners with valuable insights.