[go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v296y2022i2p679-695.html
   My bibliography  Save this article

Multi-factor dependence modelling with specified marginals and structured association in large-scale project risk assessment

Author

Listed:
  • Kim, Byung-Cheol
Abstract
This paper examines the high-dimensional dependence modelling problem in the context of project risk assessment. As the dimension of uncertain performance units (i.e., itemized costs and activity times) in a project increases, specifying a feasible correlation matrix and eliciting relevant pair-wise information, either from historical data or with expert judgement, becomes practically unattainable or simply not economical. This paper presents a factor-driven dependence elicitation and modelling framework with scalability to large-scale project risks. The multi-factor association model (MFAM) accounts for hierarchical relationships of multiple association factors and provides a closed-form solution to a complete and mathematically consistent correlation matrix. Augmented with the structured association (SA) technique for systematic identification of hierarchical association factors, the MFAM offers additional flexibility of utilizing the minimum information available in standardized, ubiquitous project plans (e.g., work breakdown structure, resource allocation, or risk register), while preserving the computational efficiency and the scalability to high dimensional project risks. Numerical applications and simulation experiments show that the MFAM, further combined with extended analytics (i.e., parameter calibration and optimization), provides credible risk assessments (with accuracy comparable to full-scale simulation) and further enhances the realism of dealing with high-dimensional project risks utilizing all relevant information.

Suggested Citation

  • Kim, Byung-Cheol, 2022. "Multi-factor dependence modelling with specified marginals and structured association in large-scale project risk assessment," European Journal of Operational Research, Elsevier, vol. 296(2), pages 679-695.
  • Handle: RePEc:eee:ejores:v:296:y:2022:i:2:p:679-695
    DOI: 10.1016/j.ejor.2021.04.043
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221721003787
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ejor.2021.04.043?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. Werner, Christoph & Bedford, Tim & Cooke, Roger M. & Hanea, Anca M. & Morales-Nápoles, Oswaldo, 2017. "Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions," European Journal of Operational Research, Elsevier, vol. 258(3), pages 801-819.
    2. Philip M. Lurie & Matthew S. Goldberg, 1998. "An Approximate Method for Sampling Correlated Random Variables from Partially-Specified Distributions," Management Science, INFORMS, vol. 44(2), pages 203-218, February.
    3. Trietsch, Dan & Mazmanyan, Lilit & Gevorgyan, Lilit & Baker, Kenneth R., 2012. "Modeling activity times by the Parkinson distribution with a lognormal core: Theory and validation," European Journal of Operational Research, Elsevier, vol. 216(2), pages 386-396.
    4. Richard M. Van Slyke, 1963. "Letter to the Editor---Monte Carlo Methods and the PERT Problem," Operations Research, INFORMS, vol. 11(5), pages 839-860, October.
    5. Robert T. Clemen & Gregory W. Fischer & Robert L. Winkler, 2000. "Assessing Dependence: Some Experimental Results," Management Science, INFORMS, vol. 46(8), pages 1100-1115, August.
    6. van Dorp, Johan René, 2020. "A dependent project evaluation and review technique: A Bayesian network approach," European Journal of Operational Research, Elsevier, vol. 280(2), pages 689-706.
    7. Richard J. Schonberger, 1981. "Why Projects Are “Always” Late: A Rationale Based on Manual Simulation of a PERT/CPM Network," Interfaces, INFORMS, vol. 11(5), pages 66-70, October.
    8. Claire Palmer & Esmond N. Urwin & Ali Niknejad & Dobrila Petrovic & Keith Popplewell & Robert I. M. Young, 2018. "An ontology supported risk assessment approach for the intelligent configuration of supply networks," Journal of Intelligent Manufacturing, Springer, vol. 29(5), pages 1005-1030, June.
    9. Asadabadi, Mehdi Rajabi & Zwikael, Ofer, 2021. "Integrating risk into estimations of project activities' time and cost: A stratified approach," European Journal of Operational Research, Elsevier, vol. 291(2), pages 482-490.
    10. Malik Ranasinghe, 2000. "Impact of correlation and induced correlation on the estimation of project cost of buildings," Construction Management and Economics, Taylor & Francis Journals, vol. 18(4), pages 395-406.
    11. D. G. Malcolm & J. H. Roseboom & C. E. Clark & W. Fazar, 1959. "Application of a Technique for Research and Development Program Evaluation," Operations Research, INFORMS, vol. 7(5), pages 646-669, October.
    12. Demirtas, Hakan & Hedeker, Donald, 2011. "A Practical Way for Computing Approximate Lower and Upper Correlation Bounds," The American Statistician, American Statistical Association, vol. 65(2), pages 104-109.
    13. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2021. "Using Schedule Risk Analysis with resource constraints for project control," European Journal of Operational Research, Elsevier, vol. 288(3), pages 736-752.
    14. Cho, Sungbin, 2009. "A linear Bayesian stochastic approximation to update project duration estimates," European Journal of Operational Research, Elsevier, vol. 196(2), pages 585-593, July.
    15. Joel Goh & Melvyn Sim, 2011. "Robust Optimization Made Easy with ROME," Operations Research, INFORMS, vol. 59(4), pages 973-985, August.
    16. van Dorp, J. Rene, 2005. "Statistical dependence through common risk factors: With applications in uncertainty analysis," European Journal of Operational Research, Elsevier, vol. 161(1), pages 240-255, February.
    17. P E D Love & C-P Sing & X Wang & D J Edwards & H Odeyinka, 2013. "Probability distribution fitting of schedule overruns in construction projects," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(8), pages 1231-1247, August.
    Full references (including those not matched with items on IDEAS)

    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. Werner, Christoph & Bedford, Tim & Cooke, Roger M. & Hanea, Anca M. & Morales-Nápoles, Oswaldo, 2017. "Expert judgement for dependence in probabilistic modelling: A systematic literature review and future research directions," European Journal of Operational Research, Elsevier, vol. 258(3), pages 801-819.
    2. Hajdu M. & Isaac S., 2016. "Sixty years of project planning: history and future," Organization, Technology and Management in Construction, Sciendo, vol. 8(1), pages 1499-1510, December.
    3. Tianyang Wang & James S. Dyer & Warren J. Hahn, 2017. "Sensitivity analysis of decision making under dependent uncertainties using copulas," EURO Journal on Decision Processes, Springer;EURO - The Association of European Operational Research Societies, vol. 5(1), pages 117-139, November.
    4. Elise D. Miller-Hooks & Hani S. Mahmassani, 2000. "Least Expected Time Paths in Stochastic, Time-Varying Transportation Networks," Transportation Science, INFORMS, vol. 34(2), pages 198-215, May.
    5. Vaseghi, Forough & Martens, Annelies & Vanhoucke, Mario, 2024. "Analysis of the impact of corrective actions for stochastic project networks," European Journal of Operational Research, Elsevier, vol. 316(2), pages 503-518.
    6. Serpell Alfredo Federico & Ferrada Ximena & Rubio Larissa, 2019. "Measuring the performance of project risk management: a preliminary model," Organization, Technology and Management in Construction, Sciendo, vol. 11(1), pages 1984-1991, January.
    7. I-Tung Yang, 2006. "Using Gaussian copula to simulate repetitive projects," Construction Management and Economics, Taylor & Francis Journals, vol. 24(9), pages 901-909.
    8. M Revie & T Bedford & L Walls, 2010. "Evaluation of elicitation methods to quantify Bayes linear models," Journal of Risk and Reliability, , vol. 224(4), pages 322-332, December.
    9. Colin, Jeroen & Vanhoucke, Mario, 2014. "Setting tolerance limits for statistical project control using earned value management," Omega, Elsevier, vol. 49(C), pages 107-122.
    10. Creemers, Stefan, 2018. "Moments and distribution of the net present value of a serial project," European Journal of Operational Research, Elsevier, vol. 267(3), pages 835-848.
    11. Ahti Salo & Edoardo Tosoni & Juho Roponen & Derek W. Bunn, 2022. "Using cross‐impact analysis for probabilistic risk assessment," Futures & Foresight Science, John Wiley & Sons, vol. 4(2), June.
    12. R A Bowman, 2007. "Efficient sensitivity analysis of PERT network performance measures to significant changes in activity time parameters," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(10), pages 1354-1360, October.
    13. Wang, Fan & Li, Heng & Dong, Chao & Ding, Lieyun, 2019. "Knowledge representation using non-parametric Bayesian networks for tunneling risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    14. Martens, Annelies & Vanhoucke, Mario, 2019. "The impact of applying effort to reduce activity variability on the project time and cost performance," European Journal of Operational Research, Elsevier, vol. 277(2), pages 442-453.
    15. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2022. "Using Earned Value Management and Schedule Risk Analysis with resource constraints for project control," European Journal of Operational Research, Elsevier, vol. 297(2), pages 451-466.
    16. R L Bregman, 2009. "Preemptive expediting to improve project due date performance," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 120-129, January.
    17. Fernando Acebes & David Poza & Jose M Gonzalez-Varona & Javier Pajares & Adolfo Lopez-Paredes, 2024. "On the project risk baseline: integrating aleatory uncertainty into project scheduling," Papers 2406.00077, arXiv.org.
    18. Joel Goh & Nicholas G. Hall, 2013. "Total Cost Control in Project Management via Satisficing," Management Science, INFORMS, vol. 59(6), pages 1354-1372, June.
    19. Huifen Chen, 2001. "Initialization for NORTA: Generation of Random Vectors with Specified Marginals and Correlations," INFORMS Journal on Computing, INFORMS, vol. 13(4), pages 312-331, November.
    20. David Hudak & Mark Maxwell, 2007. "A macro approach to estimating correlated random variables in engineering production projects," Construction Management and Economics, Taylor & Francis Journals, vol. 25(8), pages 883-892.

    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:ejores:v:296:y:2022:i:2:p:679-695. 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: http://www.elsevier.com/locate/eor .

    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.