تعداد نشریات | 161 |
تعداد شمارهها | 6,532 |
تعداد مقالات | 70,502 |
تعداد مشاهده مقاله | 124,116,775 |
تعداد دریافت فایل اصل مقاله | 97,221,576 |
توسعه و ارزیابی چارچوب حاکمیت ریسک در صنعت نفتوگاز | ||
مدیریت صنعتی | ||
دوره 15، شماره 1، 1402، صفحه 3-29 اصل مقاله (767.95 K) | ||
نوع مقاله: مقاله علمی پژوهشی | ||
شناسه دیجیتال (DOI): 10.22059/imj.2023.350212.1007999 | ||
نویسندگان | ||
محسن آقابگلو1؛ کامران رضایی* 2؛ سید علی ترابی3 | ||
1دانشجوی دکتری، دانشکده مهندسی صنایع، دانشکدگان فنی، دانشگاه تهران، تهران، ایران. | ||
2دانشیار، دانشکده مهندسی صنایع، دانشکدگان فنی دانشگاه تهران، تهران، ایران. | ||
3استاد، دانشکده مهندسی صنایع، دانشکدگان فنی دانشگاه تهران، تهران، ایران. | ||
چکیده | ||
هدف: چارچوب حاکمیت ریسک شورای بینالمللی حاکمیت ریسک، بهطور گسترده در زمینههای مختلف پیادهسازی شده است؛ اما بهدلیل نگرانیهای فرهنگی و ژئوپلیتیکی، باید برای اهداف مختلف سفارشیسازی شود. در این مقاله، چارچوب شورای بینالمللی حاکمیت ریسک با توجه به ماهیت و نیازهای صنعت نفتوگاز ایران سفارشی شده است؛ سپس مجموعهای از معیارها برای اندازهگیری عملکرد این چارچوب تعریف میشود. روش: ابتدا با استفاده از یک روش تصمیمگیری چندمعیاره ترکیبی فازی، مؤلفههای مختلف مدل حاکمیت ریسک اولویتبندی میشوند؛ سپس شاخص عملکرد حاکمیت ریسک برای محاسبه عملکرد چنین چارچوبی، بر اساس اولویتبندی مؤلفهها پیشنهاد میشود. جمعآوری اطلاعات برای تعیین مؤلفههای چارچوب پیشنهادی و محاسبه اهمیت نسبی آنها و همچنین انتخاب شاخصهای ارزیابی از طریق انجام مصاحبه بوده و صحهگذاری مدل با استفاده از روش روایی صوری انجام شده است. بهمنظور بررسی کاربردپذیری، این رویکرد در سه سایت صنعتی در حوزه نفتوگاز ارزیابی شده است. یافتهها: چنین رویکردی به سازمانهای صنایع نفتوگاز کمک میکند تا با توجه به وضعیت مدیریت ریسک در سازمان خود و بر اساس اهمیت هر یک از مؤلفههای حاکمیت ریسک، برنامههای بهبود مدیریت ریسک را بهصورت کارا و اثربخش تعریف کنند. نتیجهگیری: بر اساس مطالعه موردی، شناسایی گزینهها و راهکارها و پیادهسازی آنها بهعنوان مؤلفههای مهم در موفقیت چارچوب حاکمیت ریسک صنعت نفتوگاز شناسایی شدند. | ||
کلیدواژهها | ||
ارزیابی ریسک؛ تصمیمگیری فازی؛ حاکمیت ریسک؛ صنعت نفتوگاز؛ مدیریت ریسک | ||
عنوان مقاله [English] | ||
Developing and Evaluating Risk Governance Framework in the Oil and Gas Industry | ||
نویسندگان [English] | ||
Mohsen Aghabegloo1؛ Kamran Rezaie2؛ Seyed Ali Torabi3 | ||
1Ph.D. Candidate, School of Industrial Engineering, College of Engineering, University of Tehran, Iran. | ||
2Associate Prof., School of Industrial Engineering, College of Engineering, University of Tehran, Iran. | ||
3Prof., School of Industrial Engineering, College of Engineering, University of Tehran, Iran. | ||
چکیده [English] | ||
Objective: Numerous stakeholders with divergent perspectives have complicated the risk management process in the oil and gas sector. Additionally, systemic risks such as population growth in industrial areas or the severe decline in oil and gas prices have cast doubt on the effectiveness of organizational risk management strategies. As a result, an appropriate framework should be used that incorporates the expertise, values, and interests of many stakeholders into the risk management decision-making process. Although the International Risk Governance Committee (IRGC) framework has been widely implemented in different contexts, it should be customized for different purposes due to cultural and geopolitical concerns. This paper customizes the IRGC framework to propose a modified framework for the oil and gas industry in Iran. Then, it defines a set of criteria to measure the risk governance framework's performance. Methods: To carry out this research, a fuzzy hybrid multi-attribute decision-making method was applied to prioritize the elements of distinct phases to offer valuable information for resource allocation in different aspects. A risk-governance performance index was then proposed to calculate the performance of such a framework based on the prioritization of the elements. Different interviews were also conducted to collect the required information for the determination of the framework’s elements and calculate their relative importance as well as the selection of evaluation. The model was validated through the face validity method. A case study at three oil and gas industrial sites was conducted to test the applicability of the proposed framework. Results: To determine the relative importance of each element and optimize resource allocation for the success of the IRGC framework, it is necessary to assess the impact of each element. This article used the DEMATEL-Fuzzy ANP method for this purpose. Two important parts of the risk governance framework include the "realization of selected options" and "identification of options". The oil and gas industry should communicate with all stakeholders regarding the various risk mitigation options, as the options presented usually impact the operation of industrial sites. Implementing the selected options will ensure the framework's survival and contribute to the continuity of operations at industrial sites, while minimizing strategic, operational, safety, and environmental concerns. Additionally, according to the results of this article, "interaction with evaluators and consulting companies" significantly affects the success of the risk governance framework. Therefore, companies in the oil and gas industry should specify the areas of communication and how to communicate with evaluators and consulting companies in writing and evaluate the effectiveness of these communications. Conclusion: To support all stakeholders, the organization should conduct a thorough exploration of the drivers and advantages of a risk governance framework. Integrating managerial decision-making and risk management, allocating shareholder capital, maintaining production continuity, minimizing safety and environmental risks, and managing emerging risks are all critical in this context. Our proposed framework considers all these drivers to determine the importance of risk governance elements for oil and gas companies. Moreover, this study proposes a set of criteria to measure the risk governance framework's performance. | ||
کلیدواژهها [English] | ||
Risk management, Risk Governance, Risk assessment, Oil & Gas industry, Fuzzy decision making | ||
مراجع | ||
امیری، مقصود (1392). ارائه روشی برای رتبهبندی ریسک فعالیتهای پروژه با استفاده از شبکه CPM و روش TOPSIS در حالت فازی. چشمانداز مدیریت صنعتی، 3(2)، 169- 183.
بهادران، مریم؛ فدایی اشکیکی، مهدی؛ طالقانی، محمد و همایون فر، مهدی (1401). طراحی شبکه زنجیرۀ تأمین حلقه بسته تابآور تحت شرایط ریسکهای عملیاتی و اختلال با رویکرد مالوی. مدیریت صنعتی، 14(4)، 595- 617.
جعفری نژاد، نوید؛ مقبل باعرض، عباس و آذر، عادل (1393). شناسایی و استخراج مؤلفههای اصلی مدیریت ریسک سازمان با استفاده از روش فراترکیب. چشمانداز مدیریت صنعتی، 4(3)، 85- 107.
جولای، فریبرز و زمانی، فاطمه (1401). بهینهسازی و تحلیل حساسیت قراردادهای IPC با در نظرگرفتن مدل پویای مخزن و مدل تصادفی قیمت نفت. مدیریت صنعتی، 14(1)، 143–167.
دوستمحمدی، ایمان؛ عالم تبریز، اکبر؛ راد، عباس و زندیه، مصطفی (1399). طراحی و تبیین مدل تخصیص منبع افزونه و بافر برای بهبود پایایی پروژهها در شرایط عدم قطعیت زمان و هزینه (مورد مطالعه: صنعت نفتوگاز). مدیریت صنعتی، 12(4)، 521–544.
محقر، علی، صفری، حسین و معین نجفآبادی، فقیهه (1400). طراحی متدولوژی تعالی سازمانی صنعت نفت ایران. مدیریت صنعتی، 13(3)، 370–390.
منیری، محمدرضا؛ عالم تبریز، اکبر و عیوق، اشکان (1401). ارزیابی ریسک پروژههای تعمیرات اساسی در صنایع فرایندی بالادستی نفت با استفاده از یک روش تصمیمگیری چندشاخصه فازی ترکیبی. چشمانداز مدیریت صنعتی، 12(2)، 135- 173.
References Amiri, M. (2013). Presentation of a Model for Ranking a Project Activities Risk using CPM Network and TOPSIS Method in Fuzzy Environment. Industrial Management Perspective, 10, 169–183. (in Persian) Aven, T. (2015). Risk analysis (2nd ed.). Wiley. Aven, T. & Renn, O. (2012). On the risk management and risk governance of petroleum operations in the Barents Sea area. Risk Analysis: An International Journal, 32(9), 1561–1575. Aven, T., Vinnem, J. E. & Wiencke, H. S. (2007). A decision framework for risk management, with application to the offshore oil and gas industry. Reliability Engineering & System Safety, 92(4), 433–448. Bahadoran, M., Fadaei Ashkiki, M., Taleghani, M. & Homayounfar, M. (2022). Designing a Resilient Closed-Loop Supply Chain Network under Operational Risk and Disruption Conditions by the Mulvey Approach. Industrial Management Journal, 14(4), 595-617. doi: 10.22059/imj.2022.336976.1007909 (in Persian) Bank, I.A. D. (2011). Indicators for Disaster Risk and Risk Management. Bromiley, P., McShane, M., Nair, A. & Rustambekov, E. (2015). Enterprise risk management: Review, critique, and research directions. Long Range Planning, 48(4), 265–276. Bucelli, M., Paltrinieri, N. & Landucci, G. (2018). Integrated risk assessment for oil and gas installations in sensitive areas. Ocean Engineering, 150, 377–390. Carreño, M.L., Cardona, O.D. & Barbat, A.H. (2007). A disaster risk management performance index. Natural Hazards, 41(1), 1–20. Casal, A. & Olsen, H. (2016). Operational Risks in QRA. Chemical Engineering Transactions, 48, 589–94. Choua, Y. C., Sun, C.-C. & Yen, H.-Y. (2012). Evaluating the criteria for human resource for science and technology (HRST) based on an integrated fuzzy AHP and fuzzy DEMATEL approach. Applied Soft Computing, 12(1), 64–71. Darbra, R.M., Palacios, A. & Casal, J. (2010). Domino effect in chemical accidents: Main features and accident sequences. 183, 565–573. https://doi.org/10.1016/j.jhazmat.2010.07.061 Doost Mohamadi, I., Alem Tabriz, A., Raad, A. & Zandieh, M. (2020). Designing and Explaining a Redundancy Resource and Buffer allocation Model for Project Reliability Improvement with Time and Cost Uncertainty (The Case of Oil and Gas Industry Projects). Industrial Management Journal, 12(4), 521-544. doi: 10.22059/imj.2021.303889.1007745 (in Persian) Florin, M.-V. & Bürkler, M. T. (2017). Introduction to the IRGC risk governance framework. EPFL. Fraser, J. R., Schoening-Thiessen, K. & Simkins, B. J. (2008). Who reads what most often? A survey of enterprise risk management literature read by risk executives. Journal of Applied Finance, 18(1), 73. Goerlandt, F. & Ronald, P. (2020). An Exploratory Application of the International Risk Governance Council’s Risk Governance Framework to Shipping Risks in the Canadian Arctic. In Governance of Arctic Shipping (pp. 15–41). Springer, Cham. Guo, X., Jie, J., Khan, F. & Ding, L. (2020). Fuzzy bayesian network based on an improved similarity aggregation method for risk assessment of storage tank accident. Process Safety and Environmental Protection, 144, 242–252. https://doi.org/10.1016/j.psep.2020.07.030 Haapasaari, P., Helle, I., Lehikoinen, A., Lappalainen, J. & Kuikka, S. (2015). A proactive approach for maritime safety policy making for the Gulf of Finland: Seeking best practices. Marine Policy, 60, 107–118. IAM. (2015). Asset Management- an Anatomy. IRGC. (2017). Risk governance: Towards an integrative approach. ISO. (2018). ISO 31000:2018 Risk management — Guidelines. Jafarinejad, N., Baarz, A. M. & Azar, A. (2014). Identify and Extract the Main Dimensions of Enterprise Risk Management Based on Meta-Synthesis. Industrial Management Perspective, 4(3), 85–107. (in Persian) Jolai, F. & Zamani, F. (2022). Dynamic Reservoir and Stochastic Oil Pricing Model of IPC Contracts: Optimizing and Sensitivity Analyzing. Industrial Management Journal, 14(1), 143-167. doi: 10.22059/imj.2022.328510.1007857 (in Persian) Khameneh, A.H., Taheri, A. & Ershadi, M. (2016). Offering a framework for evaluating the performance of project risk management system. Procedia-Social and Behavioral Sciences, 226, 82–90. Klinke, A. & Renn, O. (2012). Adaptive and integrative governance on risk and uncertainty. Journal of Risk Research, 15(3), 273–292. Lechner, P. & Gatzert, N. (2018). Determinants and value of enterprise risk management: empirical evidence from Germany. The European Journal of Finance, 24(10), 867–887. Li, C.-W. & Tzeng, G.-H. (2009). Identification of a threshold value for the DEMATEL method using the maximum mean de-entropy algorithm to find critical services provided by a semiconductor intellectual property mall. Expert Systems with Applications, 36(6), 9891–9898. Liaropoulos, A., Sapountzaki, K. & Nivolianitou, Z. (2019). Adopting risk governance in the offshore oil industry and in diverse cultural and geopolitical context: North Sea vs Eastern Mediterranean countries. Safety Science, 120, 471–483. Liou, J. J. H. (2012). Developing an integrated model for the selection of strategic alliance partners in the airline industry. Knowledge-Based Systems, 28, 59–67. https://doi.org/10.1016/j.knosys.2011.11.019 Mahmoudi, A., Honari, H., Habibi Rad, A. & Rasouli, S. M. (2017). Assessing the validity and reliability of the Persian version of the questionnaire of endorsement of famous athletes on sports products from the customers’ point of view. Journal of Research in Sports Management and Movement Behavior, 15, 65–79. Marsh. (2020). 100 Largest Losses in the Hydrocarbon Industry 1974-2019. Mitchell, J. S. (2012). Physical Asset Management Handbook (4th ed.). Reliabilityweb.com. Moniri, M., Alem Tabriz, A. & Ayough, A. (2022). Upstream Oil Process Plants Turnaround Projects Risk Evaluation Using a Hybrid Fuzzy MADM Method. Journal of Industrial Management Perspective, 12(2), 135-173. (in Persian) Mohaghar, A., Safari, H. & Moein Najaf Abadi, F. (2022). Designing Organizational Excellence Methodology for Iran’s Oil Industry. Industrial Management Journal, 13(3), 370-390. doi: 10.22059/imj.2021.334178.1007889 (in Persian) Muralidhar, K. (2010). Enterprise risk management in the Middle East oil industry: an empirical investigation across GCC countries. International Journal of Energy Sector Management. Neves, A. A. S., Pinardi, N., Martins, F., Janeiro, J., Samaras, A., Zodiatis, G. & De Dominicis, M. (2015). Towards a common oil spill risk assessment framework–adapting ISO 31000 and addressing uncertainties. Journal of Environmental Management, 159, 158–168. Pitchforth, J. & Mengersen, K. (2013). A proposed validation framework for expert elicited Bayesian Networks. Expert Systems With Applications, 40(1), 162–167. Rasid, S. Z. A., Golshan, N., Mokhber, M., Tan, G.-G. & Mohd-Zamil, N. A. (2017). Enterprise risk management, performance measurement systems and organizational performance in Malaysian Public Listed Firms. International Journal of Business and Society, 18(2). Renn, O. (2015). Stakeholder and public involvement in risk governance. International Journal of Disaster Risk Science, 6(1), 8–20. Renn, O., Klinke, A. & Van Asselt, M. (2011). Coping with complexity, uncertainty and ambiguity in risk governance: a synthesis. Ambio, 40(2), 231–246. Saaty, T. L. (1980). The Analytic Hierarchy Process. McGraw-Hill. Shad, M. K., Fong-Woon, L., Fatt, C. L., Klemeš, J. J. & Bokhari, A. (2019). Integrating sustainability reporting into enterprise risk management and its relationship with business performance: A conceptual framework. Journal of Cleaner Production, 208, 415–425. Skogdalen, J. E. & Vinnem, J. E. (2011). Quantitative risk analysis offshore—human and organizational factors. Reliability Engineering & System Safety, 96(4), 468–479. Sparrevik, M. & Breedveld, G. D. (2010). From ecological risk assessments to risk governance: evaluation of the Norwegian management system for contaminated sediments. Integrated Environmental Assessment and Management: An International Journal, 6(2), 240–248. Van der Vegt, R. G. (2018). Risk assessment and risk governance of liquefied natural gas development in Gladstone, Australia. Risk Analysis: An International Journal, 38(0), 1830–1846. Walker, P. L., Shenkir, W. G. & Barton, T. L. (2002). ERM: Pulling It all Together." The IIA Research Foundation. Altamonte Springs, FL. Yang, X., Stein, H. & Paltrinieri, N. (2018). Clarifying the concept of operational risk assessment in the oil and gas industry. Safety Science, 108, 259–268. | ||
آمار تعداد مشاهده مقاله: 492 تعداد دریافت فایل اصل مقاله: 394 |