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Barrier Verification and Leading-Indicator Governance for High-Risk Technical Operations in Oil & Gas and Construction Projects: An Integrative Review
Subject area: Science,Engineering and Technology · Area of research: Construction Projects
Abstract
High-risk technical operations in oil and gas facilities and construction projects remain difficult to control because work is temporary, interfaces are fragmented, hazardous energy is frequently introduced or released, and schedule pressure can weaken otherwise mature safety systems. This review examines how safety interventions can be configured so that engineered barriers, work-control verification, competence assurance, contractor governance and leading indicators operate as a connected assurance system rather than as isolated programs. A structured integrative review of peer-reviewed literature published from 2020 to 2025 was undertaken, with emphasis on construction safety, oil and gas safety climate, proactive indicators, digital work controls and sociotechnical risk management. The evidence shows that personal-safety programs are valuable for routine exposure reduction, but they do not by themselves provide credible assurance against low-frequency, high-consequence events. Stronger intervention logic emerges when the control selected is matched to the failure mode: physical barriers for hazardous energy, verified permits and isolations for temporary configuration change, competence controls for judgement-intensive tasks, disclosure mechanisms for weak signals, and governance controls for contractor and schedule interfaces. Leading indicators are most useful when they measure the condition of these controls rather than the volume of safety activity. The review develops an integrated assurance framework and proposes practical indicator families for project and operational settings. The central conclusion is that intervention quality depends less on the number of safety initiatives than on whether each critical control is owned, independently verifiable, time-sensitive and connected to decision authority before exposure escalates.
Keywords
barrier verification; leading indicators; process safety; construction safety; oil and gas; contractor governance; permit to work
References
[1] Umar T (2020). Safety climate factors in construction – a literature review. Policy and Practice in Health and Safety, 18(2), 80–99. https://doi.org/10.1080/14773996.2020.1777799
[2] Alkaissy M, Arashpour M, Ashuri B, Bai Y, Hosseini R (2020). Safety management in construction: 20 years of risk modeling. Safety Science, 129, 104805. https://doi.org/10.1016/j.ssci.2020.104805
[3] Sanni-Anibire MO, Mahmoud AS, Hassanain MA, Salami BA (2020). A risk assessment approach for enhancing construction safety performance. Safety Science, 121, 15–29. https://doi.org/10.1016/j.ssci.2019.08.044
[4] Mosly I, Makki AA (2020). Safety climate perceptions in the construction industry of Saudi Arabia: The current situation. International Journal of Environmental Research and Public Health, 17(18), 6717. https://doi.org/10.3390/ijerph17186717
[5] Esmaeili B, Hallowell MR, Rajagopalan B (2020). The association between subcontractor safety management programs and worker perceived safety climate in commercial construction projects. Journal of Safety Research, 74, 279–288. https://doi.org/10.1016/j.jsr.2020.06.010
[6] Guo BHW, Zou Y, Fang Y, Goh YM, Zou PXW (2021). Computer vision technologies for safety science and management in construction: A critical review and future research directions. Safety Science, 135, 105130. https://doi.org/10.1016/j.ssci.2020.105130
[7] Xia N, Xie Q, Hu X, Wang X, Meng H (2021). A review of construction safety climate: Definitions, factors, relationship with safety behavior and research agenda. Safety Science, 142, 105391. https://doi.org/10.1016/j.ssci.2021.105391
[8] Paneru S, Jeelani I (2021). Computer vision applications in construction: Current state, opportunities & challenges. Automation in Construction, 132, 103940. https://doi.org/10.1016/j.autcon.2021.103940
[9] Xu Z, Zheng N (2021). Incorporating virtual reality technology in safety training solution for construction site of urban cities. Sustainability, 13(1), 243. https://doi.org/10.3390/su13010243
[10] Ajmal M, Isha ASN, Nordin SM, Al-Mekhlafi ABA (2022). Safety-management practices and the occurrence of occupational accidents: Assessing the mediating role of safety compliance. Sustainability, 14(8), 4569. https://doi.org/10.3390/su14084569
[11] Alruqi WM, Hallowell MR (2022). Analysis of safety climate factors and safety compliance relationships in the oil and gas industry. Safety Science, 151, 105744. https://doi.org/10.1016/j.ssci.2022.105744
[12] Yadav N, Sadeghi N, Kang J (2022). On-body placement of wearable safety promotion devices based on wireless communication for construction workers-on-foot: State-of-the-art review. Sensors, 22(9), 3134. https://doi.org/10.3390/s22093134
[13] Gao R, Mu B, Lyu S, Wang H, Yi C (2022). Review of the application of wearable devices in construction safety: A bibliometric analysis from 2005 to 2021. Buildings, 12(3), 344. https://doi.org/10.3390/buildings12030344
[14] Xu J, Cheung C, Manu P, Ejohwomu O, Too J (2023). Implementing safety leading indicators in construction: Toward a proactive approach to safety management. Safety Science, 157, 105929. https://doi.org/10.1016/j.ssci.2022.105929
[15] Bayramova A, Edwards DJ, Roberts C, Rillie I (2023). Enhanced safety in complex socio-technical systems via safety-in-cohesion. Safety Science, 164, 106176. https://doi.org/10.1016/j.ssci.2023.106176
[16] Alkaissy M, Arashpour M, Golafshani EM, Hosseini MR, Khanmohammadi S, Bai Y, Feng H (2023). Enhancing construction safety: Machine learning-based classification of injury types. Safety Science, 162, 106102. https://doi.org/10.1016/j.ssci.2023.106102
[17] Cavalcanti M, Lessa L, Vasconcelos BM (2023). Construction accident prevention: A systematic review of machine learning approaches. Work, 76(2), 507–519. https://doi.org/10.3233/WOR-220533
[18] Dobrucali E, Demirkesen S, Sadikoglu E, Zhang C, Damci A (2024). Investigating the impact of emerging technologies on construction safety performance. Engineering, Construction and Architectural Management, 31(3), 1322–1347. https://doi.org/10.1108/ECAM-07-2022-0668
[19] Golabchi H, Abellanosa AD, Lefsrud L, Pereira E, Mohamed Y (2024). A comprehensive systematic review of safety leading indicators in construction. Safety Science, 172, 106433. https://doi.org/10.1016/j.ssci.2024.106433
[20] Sarvari H, Edwards D, Rillie I, Posillico JJ (2024). Building a safer future: Analysis of studies on Safety-I and Safety-II in the construction industry. Safety Science, 178, 106621. https://doi.org/10.1016/j.ssci.2024.106621
[21] Larbi JA, Tang LC, Larbi RA, Abankwa DA, Danquah RD (2024). Developing an integrated digital delivery framework and workflow guideline for construction safety management in a project delivery system. Safety Science, 175, 106486. https://doi.org/10.1016/j.ssci.2024.106486
[22] Zhang Y, et al. (2024). Causal inference of construction safety management measures towards workers’ safety behaviors: A multidimensional perspective. Safety Science, 172, 106432. https://doi.org/10.1016/j.ssci.2024.106432
[23] Li X, et al. (2024). Study on construction safety management in megaprojects from the perspective of resilient governance. Safety Science, 173, 106442. https://doi.org/10.1016/j.ssci.2024.106442
[24] Xia N, Ding S (2024). Safety climate in construction: A systematic literature review. Engineering, Construction and Architectural Management, 31(10), 3973–4000. https://doi.org/10.1108/ECAM-11-2022-1074
[25] Niu M, Leicht RM (2024). Evaluating the safety climate in construction projects: A longitudinal mixed-methods study. Buildings, 14(12), 4070. https://doi.org/10.3390/buildings14124070
[26] Maali O, Ko CH, Nguyen PHD (2024). Applications of existing and emerging construction safety technologies. Automation in Construction, 158, 105231. https://doi.org/10.1016/j.autcon.2023.105231
[27] Rabbi ABK, Jeelani I (2024). AI integration in construction safety: Current state, challenges, and future opportunities in text, vision, and audio based applications. Automation in Construction, 164, 105443. https://doi.org/10.1016/j.autcon.2024.105443
[28] Kim JM, Yum SG, Adhikari MD, Bae J (2024). A deep-learning approach to leveraging natural hazard indicators for improved safety on construction sites. Safety Science, 177, 106596. https://doi.org/10.1016/j.ssci.2024.106596
[29] Liu W, Meng Q, Li Z, Chong HY, Li K, Tang H (2025). Linking organizational safety support and construction workers’ safety behavior: the roles of safety motivation, emotional exhaustion and psychosocial safety climate. Engineering, Construction and Architectural Management, 32(10), 6536–6565. https://doi.org/10.1108/ECAM-02-2024-0182
[30] Shafei H, Rahman RA, Lee YS (2025). Evaluating Construction 4.0 technologies in enhancing safety and health: Case study of a national strategic plan. Journal of Engineering, Design and Technology, 23(4), 1211–1242. https://doi.org/10.1108/JEDT-08-2023-0330
How to cite this paper
@article{1724308,
author = {Rafiullah Khan},
title = {Barrier Verification and Leading-Indicator Governance for High-Risk Technical Operations in Oil & Gas and Construction Projects: An Integrative Review},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {4},
pages = {3545-3556},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1724308.pdf},
abstract = {High-risk technical operations in oil and gas facilities and construction projects remain difficult to control because work is temporary, interfaces are fragmented, hazardous energy is frequently introduced or released, and schedule pressure can weaken otherwise mature safety systems. This review examines how safety interventions can be configured so that engineered barriers, work-control verification, competence assurance, contractor governance and leading indicators operate as a connected assurance system rather than as isolated programs. A structured integrative review of peer-reviewed literature published from 2020 to 2025 was undertaken, with emphasis on construction safety, oil and gas safety climate, proactive indicators, digital work controls and sociotechnical risk management. The evidence shows that personal-safety programs are valuable for routine exposure reduction, but they do not by themselves provide credible assurance against low-frequency, high-consequence events. Stronger intervention logic emerges when the control selected is matched to the failure mode: physical barriers for hazardous energy, verified permits and isolations for temporary configuration change, competence controls for judgement-intensive tasks, disclosure mechanisms for weak signals, and governance controls for contractor and schedule interfaces. Leading indicators are most useful when they measure the condition of these controls rather than the volume of safety activity. The review develops an integrated assurance framework and proposes practical indicator families for project and operational settings. The central conclusion is that intervention quality depends less on the number of safety initiatives than on whether each critical control is owned, independently verifiable, time-sensitive and connected to decision authority before exposure escalates.},
keywords = {barrier verification; leading indicators; process safety; construction safety; oil and gas; contractor governance; permit to work},
month = {October},
}