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Abstract The physical security of critical facilities in the oil and gas industry has become a pressing concern due to scientific and technological progress and new mechanisms to bypass the physical security controls. The current study is dedicated to a critical examination of the performance of the physical security system in the Oil and Gas Industries and the potential of integrating facial recognition technology to improve its resilience towards physical security threats. The research was conducted within the integrative conceptual framework of the physical security culture that distinguishes between the technological, human, and organizational physical security domains. The author surveyed 186 employees working in an oil and gas company in the UAE. The organization has an effective physical security system that does not display critical vulnerabilities. Based on the study’s findings, the performance of this organization's physical security system is high across all three domains of physical security culture. Furthermore, most employees believe that the organization could benefit from integrating facial recognition technology as an additional defense layer against physical security threats to alleviate the negative impact of external factors on the company's physical security performance. Therefore, the study results could be valuable from the theoretical and practical perspectives by providing valuable insights into the projected performance of facial recognition technology. Downloads PDF Published 2023-01-25 How to Cite S. Al Zaabi, & R. Zamri. (2023). ENHANCING PHYSICAL SECURITY PERFORMANCE IN THE OIL AND GAS INDUSTRIES THROUGH THE INTEGRATION OF FACIAL RECOGNITION TECHNOLOGY. Journal of Engineering and Technology (JET), 13(1), 45–72. Retrieved from https://jet.utem.edu.my/jet/article/view/6126 More Citation Formats ACM ACS APA ABNT Chicago Harvard IEEE MLA Turabian Vancouver Download Citation Endnote/Zotero/Mendeley (RIS) BibTeX Issue Vol. 13 No. 1 (2022): JOURNAL OF ENGINEERING AND TECHNOLOGY Section Articles License Copyright (c) 2022 Journal of Engineering and Technology (JET)

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