IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v142y2015icp515-524.html
   My bibliography  Save this article

Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project

Author

Listed:
  • Wu, Wei-Shing
  • Yang, Chen-Feng
  • Chang, Jung-Chuan
  • Château, Pierre-Alexandre
  • Chang, Yang-Chi

Abstract

The sound development of marine resource usage relies on a strong maritime engineering industry. The perilous marine environment poses the highest risk to all maritime work. It is therefore imperative to reduce the risk associated with maritime work by using some analytical methods other than engineering techniques. This study addresses this issue by using an integrated interpretive structure modeling (ISM) and Bayesian network (BN) approach in a risk assessment context. Mitigating or managing maritime risk relies primarily on domain expert experience and knowledge. ISM can be used to incorporate expert knowledge in a systematic manner and helps to impose order and direction on complex relationships that exist among system elements. Working with experts, this research used ISM to clearly specify an engineering risk factor relationship represented by a cause–effect diagram, which forms the structure of the BN. The expert subjective judgments were further transformed into a prior and conditional probability set to be embedded in the BN. We used the BN to evaluate the risks of two offshore pipeline projects in Taiwan. The results indicated that the BN can provide explicit risk information to support better project management.

Suggested Citation

  • Wu, Wei-Shing & Yang, Chen-Feng & Chang, Jung-Chuan & Château, Pierre-Alexandre & Chang, Yang-Chi, 2015. "Risk assessment by integrating interpretive structural modeling and Bayesian network, case of offshore pipeline project," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 515-524.
    • Handle: RePEc:eee:reensy:v:142:y:2015:i:c:p:515-524
    DOI: 10.1016/j.ress.2015.06.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S095183201500188X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2015.06.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jitesh Thakkar & S.G. Deshmukh & A.D. Gupta & Ravi Shankar, 2007. "Development of a balanced scorecard," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 56(1), pages 25-59, January.
    2. Barton, D.N. & Saloranta, T. & Moe, S.J. & Eggestad, H.O. & Kuikka, S., 2008. "Bayesian belief networks as a meta-modelling tool in integrated river basin management -- Pros and cons in evaluating nutrient abatement decisions under uncertainty in a Norwegian river basin," Ecological Economics, Elsevier, vol. 66(1), pages 91-104, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Crispim, José & Fernandes, Jorge & Rego, Nazaré, 2020. "Customized risk assessment in military shipbuilding," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    2. Chen, Yinuo & Xie, Shuyi & Tian, Zhigang, 2022. "Risk assessment of buried gas pipelines based on improved cloud-variable weight theory," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    3. Qing Deng & Kuo Wang & Jiahao Wu & Feng Yu & Huiling Jiang & Lida Huang, 2023. "An integrated model for evaluating the leakage risk of urban gas pipe: a case study based on Chinese real accident data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 116(1), pages 319-340, March.
    4. Mohammad Yazdi, 2019. "A review paper to examine the validity of Bayesian network to build rational consensus in subjective probabilistic failure analysis," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 10(1), pages 1-18, February.
    5. Chunchang Zhang & Hu Sun & Yuanyuan Zhang & Gen Li & Shibo Li & Junyu Chang & Gongqian Shi, 2023. "Fire Accident Risk Analysis of Lithium Battery Energy Storage Systems during Maritime Transportation," Sustainability, MDPI, vol. 15(19), pages 1-12, September.
    6. Qazi, Abroon & Dickson, Alex & Quigley, John & Gaudenzi, Barbara, 2018. "Supply chain risk network management: A Bayesian belief network and expected utility based approach for managing supply chain risks," International Journal of Production Economics, Elsevier, vol. 196(C), pages 24-42.
    7. Kraidi, Layth & Shah, Raj & Matipa, Wilfred & Borthwick, Fiona, 2019. "Analyzing the critical risk factors associated with oil and gas pipeline projects in Iraq," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 14-22.
    8. Kraidi, Layth & Shah, Raj & Matipa, Wilfred & Borthwick, Fiona, 2020. "Using stakeholders’ judgement and fuzzy logic theory to analyze the risk influencing factors in oil and gas pipeline projects: Case study in Iraq, Stage II," International Journal of Critical Infrastructure Protection, Elsevier, vol. 28(C).
    9. Nina Shin & Sangwook Park, 2019. "Evidence-Based Resilience Management for Supply Chain Sustainability: An Interpretive Structural Modelling Approach," Sustainability, MDPI, vol. 11(2), pages 1-23, January.
    10. Dosung Kim & Yonghee Kim & Namyong Lee, 2018. "A Study on the Interrelations of Decision-Making Factors of Information System (IS) Upgrades for Sustainable Business Using Interpretive Structural Modeling and MICMAC Analysis," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
    11. Yongbo Li & Bathrinath Sankaranarayanan & D. Thresh Kumar & Ali Diabat, 2019. "Risks assessment in thermal power plants using ISM methodology," Annals of Operations Research, Springer, vol. 279(1), pages 89-113, August.
    12. Yin, Yuanbo & Yang, Hao & Duan, Pengfei & Li, Luling & Zio, Enrico & Liu, Cuiwei & Li, Yuxing, 2022. "Improved quantitative risk assessment of a natural gas pipeline considering high-consequence areas," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    13. Yang, Yang & Li, Suzhen & Zhang, Pengcheng, 2022. "Data-driven accident consequence assessment on urban gas pipeline network based on machine learning," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    14. Shengyu Guo & Jiali He & Jichao Li & Bing Tang, 2019. "Exploring the Impact of Unsafe Behaviors on Building Construction Accidents Using a Bayesian Network," IJERPH, MDPI, vol. 17(1), pages 1-15, December.
    15. Huang, Wencheng & Zhang, Yue & Kou, Xingyi & Yin, Dezhi & Mi, Rongwei & Li, Linqing, 2020. "Railway dangerous goods transportation system risk analysis: An Interpretive Structural Modeling and Bayesian Network combining approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    16. Alisha Lakra & Shubhkirti Gupta & Ravi Ranjan & Sushanta Tripathy & Deepak Singhal, 2022. "The Significance of Machine Learning in the Manufacturing Sector: An ISM Approach," Logistics, MDPI, vol. 6(4), pages 1-15, October.
    17. Gaurav Kumar Badhotiya & Gunjan Soni & Vipul Jain & Rohit Joshi & Sameer Mittal, 2022. "Assessing supply chain resilience to the outbreak of COVID-19 in Indian manufacturing firms," Operations Management Research, Springer, vol. 15(3), pages 1161-1180, December.
    18. Hong, Bingyuan & Shao, Bowen & Guo, Jian & Fu, Jianzhong & Li, Cuicui & Zhu, Baikang, 2023. "Dynamic Bayesian network risk probability evolution for third-party damage of natural gas pipelines," Applied Energy, Elsevier, vol. 333(C).
    19. Hosseini, Seyedmohsen & Barker, Kash, 2016. "A Bayesian network model for resilience-based supplier selection," International Journal of Production Economics, Elsevier, vol. 180(C), pages 68-87.
    20. Gaogeng Zhu & Guoming Chen & Jingyu Zhu & Xiangkun Meng & Xinhong Li, 2022. "Modeling the Evolution of Major Storm-Disaster-Induced Accidents in the Offshore Oil and Gas Industry," IJERPH, MDPI, vol. 19(12), pages 1-27, June.
    21. Chen, Qian & Zuo, Lili & Wu, Changchun & Cao, Yankai & Bu, Yaran & Chen, Feng & Sadiq, Rehan, 2021. "Supply reliability assessment of a gas pipeline network under stochastic demands," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    22. Jayaraman, Deepan & Ramu, Palaniappan, 2023. "L-moments and Bayesian inference for probabilistic risk assessment with scarce samples that include extremes," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    23. Qazi, Abroon & Quigley, John & Dickson, Alex & Ekici, Şule Önsel, 2017. "Exploring dependency based probabilistic supply chain risk measures for prioritising interdependent risks and strategies," European Journal of Operational Research, Elsevier, vol. 259(1), pages 189-204.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Moe, S. Jannicke & Haande, Sigrid & Couture, Raoul-Marie, 2016. "Climate change, cyanobacteria blooms and ecological status of lakes: A Bayesian network approach," Ecological Modelling, Elsevier, vol. 337(C), pages 330-347.
    2. Michail Tsagris, 2021. "A New Scalable Bayesian Network Learning Algorithm with Applications to Economics," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 341-367, January.
    3. McVittie, Alistair & Norton, Lisa & Martin-Ortega, Julia & Siameti, Ioanna & Glenk, Klaus & Aalders, Inge, 2015. "Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: An application to riparian buffer strips," Ecological Economics, Elsevier, vol. 110(C), pages 15-27.
    4. Ilkka Sillanpää, 2012. "Empirical Study of Measuring Supply Chain Performance," MIC 2012: Managing Transformation with Creativity; Proceedings of the 13th International Conference, Budapest, 22–24 November 2012 [Selected Papers],, University of Primorska, Faculty of Management Koper.
    5. Benjamin-Fink, Nicole & Reilly, Brian K., 2017. "A road map for developing and applying object-oriented bayesian networks to “WICKED” problems," Ecological Modelling, Elsevier, vol. 360(C), pages 27-44.
    6. Wang, Shunke & Chang, Jingjing & Xue, Jie & Sun, Huaiwei & Zeng, Fanjiang & Liu, Lei & Liu, Xin & Li, Xinxin, 2024. "Coupling behavioral economics and water management policies for agricultural land-use planning in basin irrigation districts: Agent-based socio-hydrological modeling and application," Agricultural Water Management, Elsevier, vol. 298(C).
    7. Dellink, Rob & Brouwer, Roy & Linderhof, Vincent & Stone, Karin, 2011. "Bio-economic modeling of water quality improvements using a dynamic applied general equilibrium approach," Ecological Economics, Elsevier, vol. 71(C), pages 63-79.
    8. Moglia, Magnus & Alexander, Kim S. & Thephavanh, Manithaythip & Thammavong, Phomma & Sodahak, Viengkham & Khounsy, Bountom & Vorlasan, Sysavanh & Larson, Silva & Connell, John & Case, Peter, 2018. "A Bayesian network model to explore practice change by smallholder rice farmers in Lao PDR," Agricultural Systems, Elsevier, vol. 164(C), pages 84-94.
    9. Hsu, David W.L. & Shen, Yung-Chi & Yuan, Benjamin J.C. & Chou, Chiyan James, 2015. "Toward successful commercialization of university technology: Performance drivers of university technology transfer in Taiwan," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 25-39.
    10. Xiaohong Jiang & Huiying Wang & Xiucheng Guo & Xiaolin Gong, 2019. "Using the FAHP, ISM, and MICMAC Approaches to Study the Sustainability Influencing Factors of the Last Mile Delivery of Rural E-Commerce Logistics," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    11. Barton, D.N. & Rusch, G. & May, P. & Ring, I. & Unnerstall, H. & Santos, R. & Antunes, P. & Brouwer, R. & Grieg-Gran, M. & Similä, J. & Primmer, E. & Romeiro, A. & DeClerck, F. & Ibrahim, M., 2009. "Assessing the role of economic instruments in a policy mix for biodiversity conservation and ecosystem services provision: a review of some methodological challenges," MPRA Paper 15554, University Library of Munich, Germany.
    12. V. R. Pramod & D. K. Banwet & P. R. S. Sarma, 2016. "Understanding the barriers of service supply chain management: an exploratory case study from Indian telecom industry," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 358-374, June.
    13. He-Yau Kang & Meng-Chan Hung & W. L. Pearn & Amy H. I. Lee & Mei-Sung Kang, 2011. "An Integrated Multi-Criteria Decision Making Model for Evaluating Wind Farm Performance," Energies, MDPI, vol. 4(11), pages 1-25, November.
    14. Balana, Bedru Babulo & Vinten, Andy & Slee, Bill, 2011. "A review on cost-effectiveness analysis of agri-environmental measures related to the EU WFD: Key issues, methods, and applications," Ecological Economics, Elsevier, vol. 70(6), pages 1021-1031, April.
    15. Carlo Fezzi & Michael Hutchins & Dan Rigby & Ian J. Bateman & Paulette Posen & David Hadley, 2010. "Integrated assessment of water framework directive nitrate reduction measures," Agricultural Economics, International Association of Agricultural Economists, vol. 41(2), pages 123-134, March.
    16. Kragt, Marit Ellen, 2013. "Integrating biophysical and economic systems in a Bayesian Network Hydro-economic framework," Working Papers 153334, University of Western Australia, School of Agricultural and Resource Economics.
    17. Barton, David N. & Benjamin, Tamara & Cerdán, Carlos R. & DeClerck, Fabrice & Madsen, Anders L. & Rusch, Graciela M. & Salazar, Álvaro G. & Sanchez, Dalia & Villanueva, Cristóbal, 2016. "Assessing ecosystem services from multifunctional trees in pastures using Bayesian belief networks," Ecosystem Services, Elsevier, vol. 18(C), pages 165-174.
    18. Kragt, Marit Ellen & Bennett, Jeffrey W., 2009. "Integrating economic values and catchment modelling," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47956, Australian Agricultural and Resource Economics Society.
    19. George HALKOS & Georgia GALANI, 2014. "Cost Effectiveness Analysis in Reducing Nutrient Loading in Baltic and Black Seas A Review," Journal of Advanced Research in Management, ASERS Publishing, vol. 5(1), pages 28-51.
    20. Cyril Bourgeois & Pierre-Alain Jayet & Florence Habets & Pascal Viennot, 2018. "Estimating the Marginal Social Value of Agriculturally Driven Nitrate Concentrations in an Aquifer: A Combined Theoretical-Applied Approach," Water Economics and Policy (WEP), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-30, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:142:y:2015:i:c:p:515-524. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.