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Throughout the past few years, the oil and gas industry in the United Arab Emirates has grown significantly, and is currently one of the top ten oil producers in the world. As a result, it is at risk of physical security threats, including theft, unauthorized access, vandalism, espionage, and other incidents which could disrupt its operation. Consequently, significant investments in the latest security technologies are necessary to protect this critical infrastructure and maintain its international standing. Therefore, the main objective of this study is to examine whether integrating facial recognition technology (FRT) with a physical security system in this sector would improve physical security performance and efficiently mitigate potential threats. A quantitative approach was applied to collect the essential information with a sample size of 371 selected through a simple random sampling method to ensure the validity and reliability of the research results. In addition, regression analysis was conducted using Smart-PLS version 3.3.9 based on (SEM) to define the significant relationships between the hypothesis applied in the conceptual model. Furthermore, the findings were significant as they provided the basis for future studies for the practical application of FRT to enhance the UAE oil and gas company’s resilience to physical security threats.
Zaabi et al. (Fri,) studied this question.