Ex Post Project Risk Assessment: Method and Empirical Study
Publication: Journal of Construction Engineering and Management
Volume 149, Issue 2
Abstract
Project risk is an important part of managing large projects of any sort. This study contributes to the state of knowledge in project risk management by introducing a data-driven approach to measure risk identification performance using historical data. In the early phases of a project, the identification and assessment of risk is based largely on experience and expert judgment. As a project moves through its life cycle, these identified risks and the assessment of them evolve. Some risks become issues, some are mitigated, and some are retired as no longer important. This study investigated the quality of early risk registers and risk assessments on large transportation projects and compared them to how the identified risks evolved on historical projects. The investigation involved the use of textual analysis of archival risk register documents. Finite-state automation methods akin to Markov chain models were used to track the changes in risk attributes on large infrastructure projects as the projects matured. The objective was to be better able to anticipate how project risks will change as projects move forward and to be better able to forecast changes to the risk register from ex ante to ex post conditions. Results from 11 major US transportation projects suggested that, on average, fewer than 65% of ex ante identified risks ultimately occurred in projects and were mitigated, while more than 35% did not occur and were retired. In addition, more than half of the risks emerged during project execution when new information became available. Based on the categorization of risk management styles, we find that identifying risks early in the project life cycle is necessary, but not sufficient to ensure successful project delivery. A project team with positive doer behavior (i.e., actively monitoring and identifying risks during project execution) performed better in delivering projects on time and within budget.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Small or all data and models that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This study was initiated based on an early discussion with the Federal Highway Administration (FHWA) and the Build America Bureau. The opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the FHWA, the Build America Bureau, or the US government. Mr. Kunqi Zhang from the University of Maryland helped with data collection significantly. His efforts provided valuable inputs to the construction of this paper.
References
Al-Bahar, J. F., and K. C. Crandall. 1990. “Systematic risk management approach for construction projects.” J. Constr. Eng. Manage. 116 (3): 533–546. https://doi.org/10.1061/(ASCE)0733-9364(1990)116:3(533).
Baiardi, F., F. Martinelli, L. Ricci, C. Telmon, and L. B. Pontecorvo. 2008. “Constrained automata: A formal tool for risk assessment and mitigation.” J. Inf. Assur. Secur. 3 (4): 304–312.
Bhattacharya, C., and A. Ray. 2022. “Thresholdless classification of chaotic dynamics and combustion instability via probabilistic finite state automata.” Mech. Syst. Sig. Process. 164 (Feb): 108213. https://doi.org/10.1016/j.ymssp.2021.108213.
Charkhakan, M. H., and G. Heravi. 2018. “Risk manageability assessment to improve risk response plan: Case study of construction projects in Iran.” J. Constr. Eng. Manage. 144 (11): 05018012. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001562.
Chen, Q., and A. E. Mynett. 2003. “Effects of cell size and configuration in cellular automata based prey–predator modelling.” Simul. Modell. Pract. Theory 11 (7): 609–625. https://doi.org/10.1016/j.simpat.2003.08.006.
Creedy, G. D., M. Skitmore, and J. K. W. Wong. 2010. “Evaluation of risk factors leading to cost overrun in delivery of highway construction projects.” J. Constr. Eng. Manage. 136 (5): 528–537. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000160.
Curtis, J. A., and F. I. T. S. Program. 2012. Transportation risk management: International practices for program development and project delivery. Washington, DC: USDOT, Federal Highway Administration.
de Caso, G., V. Braberman, D. Garbervetsky, and S. Uchitel. 2009. “Validation of contracts using enabledness preserving finite state abstractions.” In Proc., 2009 IEEE 31st Int. Conf. on Software Engineering, 452–462. New York: IEEE.
de Caso, G., V. Braberman, D. Garbervetsky, and S. Uchitel. 2012. “Automated abstractions for contract validation.” IEEE Trans. Software Eng. 38 (1): 141–162. https://doi.org/10.1109/TSE.2010.98.
El-Sayegh, S. M., and M. H. Mansour. 2015. “Risk assessment and allocation in highway construction projects in the UAE.” J. Manag. Eng. 31 (6): 04015004. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000365.
Erfani, A., Q. Cui, and I. Cavanaugh. 2021. “An empirical analysis of risk similarity among major transportation projects using natural language processing.” J. Constr. Eng. Manage. 147 (12): 04021175. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002206.
Erfani, A., and M. Tavakolan. 2020. “Risk evaluation model of wind energy investment projects using modified fuzzy group decision-making and Monte Carlo simulation.” Arthaniti J. Econ. Theory Pract. 0976747920963222. https://doi.org/10.1177/0976747920963222.
Ermentrout, G. B., and L. Edelstein-Keshet. 1993. “Cellular automata approaches to biological modeling.” J. Theor. Biol. 160 (1): 97–133. https://doi.org/10.1006/jtbi.1993.1007.
Erol, H., I. Dikmen, G. Atasoy, and M. T. Birgonul. 2020. “Exploring the relationship between complexity and risk in megaconstruction projects.” J. Constr. Eng. Manage. 146 (12): 04020138. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001946.
Flood, M. D., and O. R. Goodenough. 2022. “Contract as automaton: Representing a simple financial agreement in computational form.” Artif. Intell. Law 30 (3): 391–416. https://doi.org/10.1007/s10506-021-09300-9.
Freire, J. G., and C. C. DaCamara. 2019. “Using cellular automata to simulate wildfire propagation and to assist in fire management.” Nat. Hazards Earth Syst. Sci. 19 (1): 169–179. https://doi.org/10.5194/nhess-19-169-2019.
Gao, N., and A. Touran. 2020. “Cost overruns and formal risk assessment program in US rail transit projects.” J. Constr. Eng. Manage. 146 (5): 05020004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001827.
Ghobaei-Arani, M., B. Anari, M. Ahmadi, and Z. Anari. 2013. “Optimizing risk management using learning automata.” Int. J. Comput. Sci. Issues 10 (3): 313–320.
Gondia, A., A. Siam, W. El-Dakhakhni, and A. H. Nassar. 2020. “Machine learning algorithms for construction projects delay risk prediction.” J. Constr. Eng. Manage. 146 (1): 04019085. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001736.
Gupta, V. K., and J. J. Thakkar. 2018. “A quantitative risk assessment methodology for construction project.” Sādhanā 43 (7): 116. https://doi.org/10.1007/s12046-018-0846-6.
Hartmanis, J. 1970. “A note on one-way and two-way automata.” Math. Syst. Theory 4 (1): 24–28. https://doi.org/10.1007/BF01705881.
Hastak, M., and A. Shaked. 2000. “ICRAM-1: Model for international construction risk assessment.” J. Manage. Eng. 16 (1): 59–69. https://doi.org/10.1061/(ASCE)0742-597X(2000)16:1(59).
Heravi, G., A. H. Taherkhani, S. Sobhkhiz, A. H. Mashhadi, and R. Zahiri-Hashemi. 2022. “Integrating risk management’s best practices to estimate deep excavation projects’ time and cost.” Built Environ. Project Asset Manage. 12 (2): 180–204. https://doi.org/10.1108/BEPAM-11-2020-0180.
Iqbal, S., R. M. Choudhry, K. Holschemacher, A. Ali, and J. Tamošaitienė. 2015. “Risk management in construction projects.” Technol. Econ. Dev. Econ. 21 (1): 65–78. https://doi.org/10.3846/20294913.2014.994582.
Jallan, Y., and B. Ashuri. 2020. “Text mining of the securities and exchange commission financial filings of publicly traded construction firms using deep learning to identify and assess risk.” J. Constr. Eng. Manage. 146 (12): 04020137. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001932.
James, F. 2019. “A risk management framework and a generalized attack automata for IoT based smart home environment.” In Proc., 2019 3rd Cyber Security in Networking Conf. (CSNet), 86–90. New York: IEEE.
Jung, W., and S. H. Han. 2017. “Which risk management is most crucial for controlling project cost?” J. Manag. Eng. 33 (5): 04017029. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000547.
Kaliprasad, M. 2006. “Proactive risk management.” Cost Eng. 48 (12): 26–35. https://doi.org/10.1016/j.ijproman.2013.06.006.
Mackenzie, D. 1995. “The automation of proof: A historical and sociological exploration.” IEEE Ann. Hist. Comput. 17 (3): 7–29. https://doi.org/10.1109/85.397057.
McNaughton, R. 1961. “The theory of automata, a survey.” Adv. Comput. 2 (Jan): 379–421. https://doi.org/10.1016/S0065-2458(08)60144-8.
Molenaar, K. R. 2006. Guide to risk assessment and allocation for highway construction management. Washington, DC: Federal Highway Administration.
Molenaar, K. R. 2010. Guidebook on risk analysis tools and management practices to control transportation project costs. Washington, DC: Transportation Research Board.
Monzer, N., A. R. Fayek, R. Lourenzutti, and N. B. Siraj. 2019. “Aggregation-based framework for construction risk assessment with heterogeneous groups of experts.” J. Constr. Eng. Manage. 145 (3): 04019003. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001614.
Nguyen, D. A., M. J. Garvin, and E. E. Gonzalez. 2018. “Risk allocation in US public-private partnership highway project contracts.” J. Constr. Eng. Manage. 144 (5): 04018017. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001465.
O’Regan, G. 2021. “Automata theory.” In Guide to discrete mathematics, 121–131. New York: Springer.
Pavlak, A. 2004. “Project troubleshooting: Tiger teams for reactive risk management.” Project Manage. J. 35 (4): 5–14. https://doi.org/10.1177/875697280403500403.
Pinto, A., I. L. Nunes, and R. A. Ribeiro. 2010. “Qualitative model for risk assessment in construction industry: A fuzzy logic approach.” In Proc., Emerging Trends in Technological Innovation, IFIP Advances in Information and Communication Technology, edited by L. M. Camarinha-Matos, P. Pereira, and L. Ribeiro, 105–111. Berlin: Springer.
PMI (Project Management Institute). 2017. A guide to the project management body of knowledge (PMBOK guide). Newtown Square, PA: PMI.
Rencher, A. C. 2002. “Methods of multivariate analysis. Wiley series in probability and mathematical statistics. New York: Wiley.
Richter, C. W., G. B. Sheble, and D. Ashlock. 1999. “Comprehensive bidding strategies with genetic programming/finite state automata.” IEEE Trans. Power Syst. 14 (4): 1207–1212. https://doi.org/10.1109/59.801874.
Sanchez-Cazorla, A., R. Alfalla-Luque, and A. I. Irimia-Dieguez. 2016. “Risk identification in megaprojects as a crucial phase of risk management: A literature review.” Project Manage. J. 47 (6): 75–93. https://doi.org/10.1177/875697281604700606.
Shannon, C. 1953. “Computers and automata.” Proc. IRE 41 (10): 1234–1241. https://doi.org/10.1109/JRPROC.1953.274273.
Shimura, K., and K. Nishinari. 2014. “Project management and critical path analysis: A cellular automaton model.” J. Cell. Autom. 9 (2/3): 257–270.
Siraj, N. B., and A. R. Fayek. 2019. “Risk identification and common risks in construction: Literature review and content analysis.” J. Constr. Eng. Manage. 145 (9): 03119004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001685.
Song, Z., F. Sun, R. Zhang, Y. Du, and G. Zhou. 2021. “An improved cellular automaton traffic model based on STCA model considering variable direction lanes in I-VICS.” Sustainability 13 (24): 13626. https://doi.org/10.3390/su132413626.
Szymański, P. 2017. “Risk management in construction projects.” Procedia Eng. 208 (Jan): 174–182. https://doi.org/10.1016/j.proeng.2017.11.036.
Taroun, A. 2014. “Towards a better modelling and assessment of construction risk: Insights from a literature review.” Int. J. Project Manage. 32 (1): 101–115. https://doi.org/10.1016/j.ijproman.2013.03.004.
Tavakolan, M., and H. Etemadinia. 2017. “Fuzzy weighted interpretive structural modeling: Improved method for identification of risk interactions in construction projects.” J. Constr. Eng. Manage. 143 (11): 04017084. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001395.
Wang, S. Q., M. F. Dulaimi, and M. Y. Aguria. 2004. “Risk management framework for construction projects in developing countries.” Construct. Manage. Econ. 22 (3): 237–252. https://doi.org/10.1080/0144619032000124689.
Wen, Y., and A. Ray. 2012. “Vector space formulation of probabilistic finite state automata.” J. Comput. Syst. Sci. 78 (4): 1127–1141. https://doi.org/10.1016/j.jcss.2012.02.001.
Xiong, W., X. Zhao, J.-F. Yuan, and S. Luo. 2017. “Ex post risk management in public-private partnership infrastructure projects.” Project Manage. J. 48 (3): 76–89. https://doi.org/10.1177/875697281704800305.
Zhang, Y., and Z.-P. Fan. 2014. “An optimization method for selecting project risk response strategies.” Int. J. Project Manage. 32 (3): 412–422. https://doi.org/10.1016/j.ijproman.2013.06.006.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 149 • Issue 2 • February 2023
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 18, 2022
Accepted: Oct 11, 2022
Published online: Dec 9, 2022
Published in print: Feb 1, 2023
Discussion open until: May 9, 2023
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Abdolmajid Erfani, Ali Mansoori, Shoib Khan, Unconscious Bias in Self-Presentation: Exploring Gender Disparities in Leadership within the Transportation Industry, International Conference on Transportation and Development 2024, 10.1061/9780784485521.040, (441-452), (2024).
- Evan P. Dicks, Keith R. Molenaar, Identification of Critical Transportation Risk Factors Using DEMATEL, Construction Research Congress 2024, 10.1061/9780784485286.008, (71-80), (2024).