IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i20p11277-d654968.html
   My bibliography  Save this article

A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

Author

Listed:
  • Georgios K. Koulinas

    (Department of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias St., 67100 Xanthi, Greece)

  • Olympia E. Demesouka

    (Department of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias St., 67100 Xanthi, Greece)

  • Konstantinos A. Sidas

    (Department of Engineering Project Management, Faculty of Science & Technology, Hellenic Open University, Parodos Aristotelous 18 St., 26335 Patra, Greece)

  • Dimitrios E. Koulouriotis

    (Department of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias St., 67100 Xanthi, Greece)

Abstract

In this paper, we propose a process that combines the Risk Matrix approach with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Monte Carlo Simulation for assessing risk factors that have an impact on the duration of a construction project’s activities and predict if it is feasible to terminate the project within the prescribed deadlines. Initially, we identified the risks affecting each task of the specific project, and then, we applied the risk matrix approach for determining the probability and impact of every risk to each activity. The resulting ranking is used to assign uncertainty to activities’ durations and estimate the probability of on-time project completion, employing the Monte Carlo Simulation approach. The main contribution of this paper is the development of an innovative framework that coordinates an established qualitative and quantitative risk classification approach, with a popular multicriteria method and a powerful simulation approach, to effectively predict time deviations while executing complex construction projects under uncertainty. The proposed framework was applied to estimate the possibility of a timely execution of an artificial lake real project on the island of Alonissos, Greece. The analysis results illustrate that this approach clearly could help the project risk manager proactively perform risk mitigation measures while allocating budget and programming a project with a significant impact on the quality of life of residents and tourists of a small island.

Suggested Citation

  • Georgios K. Koulinas & Olympia E. Demesouka & Konstantinos A. Sidas & Dimitrios E. Koulouriotis, 2021. "A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11277-:d:654968
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/20/11277/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/20/11277/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Chengshan & Jiao, Bingqi & Guo, Li & Tian, Zhe & Niu, Jide & Li, Siwei, 2016. "Robust scheduling of building energy system under uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 366-376.
    2. Jae Yeol Song & Eun-Sung Chung, 2016. "Robustness, Uncertainty and Sensitivity Analyses of the TOPSIS Method for Quantitative Climate Change Vulnerability: a Case Study of Flood Damage," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(13), pages 4751-4771, October.
    3. Kaur, Harpreet & Prakash Singh, Surya, 2021. "Multi-stage hybrid model for supplier selection and order allocation considering disruption risks and disruptive technologies," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. M. Islam & Rehan Sadiq & Manuel Rodriguez & Homayoun Najjaran & Alex Francisque & Mina Hoorfar, 2013. "Evaluating Water Quality Failure Potential in Water Distribution Systems: A Fuzzy-TOPSIS-OWA-based Methodology," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(7), pages 2195-2216, May.
    5. Faghih-Roohi, Shahrzad & Akcay, Alp & Zhang, Yingqian & Shekarian, Ehsan & de Jong, Eelco, 2020. "A group risk assessment approach for the selection of pharmaceutical product shipping lanes," International Journal of Production Economics, Elsevier, vol. 229(C).
    6. Oluwatomi Adetunji & John Bischoff & Christopher J. Willy, 2018. "Managing system obsolescence via multicriteria decision making," Systems Engineering, John Wiley & Sons, vol. 21(4), pages 307-321, July.
    7. Zida Song & Quan Liu & Zhigen Hu, 2020. "Decision-Making Framework, Enhanced by Mutual Inspection for First-Stage Dam Construction Diversion Scheme Selection," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(2), pages 563-577, January.
    8. Vanhoucke, Mario, 2011. "On the dynamic use of project performance and schedule risk information during projecttracking," Omega, Elsevier, vol. 39(4), pages 416-426, August.
    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. Frantisek Kuda & Petr Dlask & Marek Teichmann & Vaclav Beran, 2022. "Time–Cost Schedules and Project–Threats Indication," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    2. F. Acebes & J. M. González-Varona & A. López-Paredes & J. Pajares, 2024. "Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    3. Andrea Senova & Alica Tobisova & Robert Rozenberg, 2023. "New Approaches to Project Risk Assessment Utilizing the Monte Carlo Method," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    4. Jianwang Wang & Lan Luo & Rina Sa & Wei Zhou & Zihan Yu, 2023. "A Quantitative Analysis of Decision-Making Risk Factors for Mega Infrastructure Projects in China," Sustainability, MDPI, vol. 15(21), pages 1-25, October.

    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. Georgios K. Koulinas & Alexandros S. Xanthopoulos & Konstantinos A. Sidas & Dimitrios E. Koulouriotis, 2021. "Risks Ranking in a Desalination Plant Construction Project with a Hybrid AHP, Risk Matrix, and Simulation-Based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(10), pages 3221-3233, August.
    2. Kaur, Harpreet & Gupta, Mahima & Singh, Surya Prakash, 2024. "Integrated model to optimize supplier selection and investments for cyber resilience in digital supply chains," International Journal of Production Economics, Elsevier, vol. 275(C).
    3. Richard E. Wendell & Timothy J. Lowe & Mike M. Gordon, 2023. "Dangers in using earned duration and other earned value metrics to measure a project’s schedule performance," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 31(2), pages 665-680, June.
    4. Zhang, Jiyuan & Tang, Hailong & Chen, Min, 2019. "Linear substitute model-based uncertainty analysis of complicated non-linear energy system performance (case study of an adaptive cycle engine)," Applied Energy, Elsevier, vol. 249(C), pages 87-108.
    5. Dilupa Nakandala & Yung Po Tsang & Henry Lau & Carman Ka Man Lee, 2022. "An Industrial Blockchain-Based Multi-Criteria Decision Framework for Global Freight Management in Agricultural Supply Chains," Mathematics, MDPI, vol. 10(19), pages 1-23, September.
    6. Tang, Kayu & Parsons, David J. & Jude, Simon, 2019. "Comparison of automatic and guided learning for Bayesian networks to analyse pipe failures in the water distribution system," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 24-36.
    7. Roger Silva Wegner & Deoclécio Junior Cardoso Silva & Claudimar Pereira Veiga & Vania Fátima Barros Estivalete & Vanessa Piovesan Rossato & Michel Barboza Malheiros, 2024. "Performance analysis of social media platforms: evidence of digital marketing," Journal of Marketing Analytics, Palgrave Macmillan, vol. 12(3), pages 599-610, September.
    8. Zhou, Jing & Liu, Yu & Liang, Decui & Tang, Maochun, 2023. "A new risk analysis approach to seek best production action during new product introduction," International Journal of Production Economics, Elsevier, vol. 262(C).
    9. Maciej Urbaniak & Piotr Rogala & Piotr Kafel, 2023. "Expectations of manufacturing companies regarding future priorities of improvement actions taken by their suppliers," Operations Management Research, Springer, vol. 16(1), pages 296-310, March.
    10. Ahamd Radmehr & Shahab Araghinejad, 2015. "Flood Vulnerability Analysis by Fuzzy Spatial Multi Criteria Decision Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(12), pages 4427-4445, September.
    11. Daeryong Park & Huan-Jung Fan & Jun-Jie Zhu & Taesoon Kim & Myoung-Jin Um & Siyeon Kim & Seol Jeon & Kichul Jung, 2021. "Prioritization in Strategic Environmental Assessment Using Fuzzy TOPSIS Method with Random Generation for Absent Information in South Korea," Sustainability, MDPI, vol. 13(3), pages 1-16, January.
    12. Katerina Fotova Čiković & Ivana Martinčević & Joško Lozić, 2022. "Application of Data Envelopment Analysis (DEA) in the Selection of Sustainable Suppliers: A Review and Bibliometric Analysis," Sustainability, MDPI, vol. 14(11), pages 1-30, May.
    13. Amin Mahmoudi & Saad Ahmed Javed, 2022. "Probabilistic Approach to Multi-Stage Supplier Evaluation: Confidence Level Measurement in Ordinal Priority Approach," Group Decision and Negotiation, Springer, vol. 31(5), pages 1051-1096, October.
    14. Urbaniak Maciej, 2021. "Role of supplier evaluation criteria in risk mitigation related to purchasing process," Engineering Management in Production and Services, Sciendo, vol. 13(2), pages 96-106, June.
    15. M. Shafiqul Islam & Rehan Sadiq & Manuel J. Rodriguez & Homayoun Najjaran & Alex Francisque & Mina Hoorfar, 2014. "Water distribution system failure: a framework for forensic analysis," Environment Systems and Decisions, Springer, vol. 34(1), pages 168-179, March.
    16. Madjid Tavana & Shahryar Sorooshian & Hassan Mina, 2024. "An integrated group fuzzy inference and best–worst method for supplier selection in intelligent circular supply chains," Annals of Operations Research, Springer, vol. 342(1), pages 803-844, November.
    17. Vanhoucke, Mario & Colin, Jeroen, 2016. "On the use of multivariate regression methods for longest path calculations from earned value management observations," Omega, Elsevier, vol. 61(C), pages 127-140.
    18. Afaf Haial & Loubna Benabbou & Abdelaziz Berrado, 2021. "Designing a Transportation-Strategy Decision-Making Process for a Supply Chain: Case of a Pharmaceutical Supply Chain," IJERPH, MDPI, vol. 18(4), pages 1-29, February.
    19. Hu, Shaolong & Dong, Zhijie Sasha & Dai, Rui, 2024. "A machine learning based sample average approximation for supplier selection with option contract in humanitarian relief," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    20. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "GHG-mitigation oriented and coal-consumption constrained inexact robust model for regional energy structure adjustment – A case study for Jiangsu Province, China," Renewable Energy, Elsevier, vol. 123(C), pages 549-562.

    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:gam:jsusta:v:13:y:2021:i:20:p:11277-:d:654968. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.