An Empirical Analysis of Risk Similarity among Major Transportation Projects Using Natural Language Processing
Publication: Journal of Construction Engineering and Management
Volume 147, Issue 12
Abstract
Risk management is widely recognized as a best practice for public agencies to ensure the successful implementation of major transportation projects. The conventional approach to identify and evaluate project risks is dominated by getting input from subject matter experts at risk workshops. However, the uniqueness of such a risk assessment approach remains unexamined. How different are the risks among various projects? Does the risk register reflect the unique feature of a project? The goal of this study is to measure the similarity of project risks across various groups by evaluating 70 major transportation projects delivered under various methods. The similarity index is calculated at three levels, that is, the entire document of the risk register, individual risk item, and the probability and consequence of each risk using a systematic comparative analysis based on natural language processing (NLP) and a state-of-the-art deep learning algorithm named Word2vec. Our study reports a high similarity of risk registers among different projects at all three levels. The analysis does show a lower similarity of risk registers for public–private partnerships (P3) projects. The primary contributions of this study are (1) develop a new approach to analyze the risk registers at the project level as the main output of risk management practice, and (2) establish the relation of risk uniqueness and project delivery method in transportation projects. Results suggest that a data-driven approach may be possible to help project teams develop a common risk register while allowing the teams to focus on each project’s unique risks.
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, code, and models that supports findings of this study will be available from the corresponding author by reasonable request.
Acknowledgments
This research was partially supported by the Federal Highway Administration (FHWA) and Volpe Center. Opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the view of the FHWA, Volpe Center, or the US government.
References
Abdelgawad, M., and A. R. Fayek. 2010. “Risk management in the construction industry using combined fuzzy FMEA and fuzzy AHP.” J. Constr. Eng. Manage. 136 (9): 1028–1036. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000210.
Antons, D., E. Grünwald, P. Cichy, and T. O. Salge. 2020. “The application of text mining methods in innovation research: Current state, evolution patterns, and development priorities.” R&D Manage. 50 (3): 329–351. https://doi.org/10.1111/radm.12408.
Baker, H., M. R. Hallowell, and A. J. P. Tixier. 2020. “Automatically learning construction injury precursors from text.” Autom. Constr. 118 (Oct): 103145. https://doi.org/10.1016/j.autcon.2020.103145.
Bilal, M., L. O. Oyedele, J. Qadir, K. Munir, S. O. Ajayi, O. O. Akinade, H. A. Owolabi, H. A. Alaka, and M. Pasha. 2016. “Big Data in the construction industry: A review of present status, opportunities, and future trends.” Adv. Eng. Inf. 30 (3): 500–521. https://doi.org/10.1016/j.aei.2016.07.001.
Bypaneni, S. P., and D. Q. Tran. 2018. “Empirical identification and evaluation of risk in highway project delivery methods.” J. Manage. Eng. 34 (3): 04018007. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000602.
Creedy, G. D., M. Skitmore, and J. K. 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.
Demetracopoulou, V., W. J. O’Brien, and N. Khwaja. 2020. “Lessons learned from selection of project delivery methods in highway projects: The Texas experience.” J. Leg. Aff. Dispute Resolut. Eng. Constr. 12 (1): 04519040. https://doi.org/10.1061/(ASCE)LA.1943-4170.0000340.
De Winter, J. C. 2013. “Using the student’s t-test with extremely small sample sizes.” Pract. Assess. Res. Eval. 18 (1): 10. https://doi.org/10.7275/e4r6-dj05.
Diao, C., R. Liang, D. Sharma, and Q. Cui. 2020. “Litigation risk detection using Twitter data.” J. Leg. Aff. Dispute Resolut. Eng. Constr. 12 (1): 04519047. https://doi.org/10.1061/(ASCE)LA.1943-4170.0000356.
Di Giuda, G. M., M. Locatelli, M. Schievano, L. Pellegrini, G. Pattini, P. E. Giana, and E. Seghezzi. 2020. “Natural language processing for information and project management.” In Digital transformation of the design, construction and management processes of the built environment, 95–102. Cham, Switzerland: Springer.
El-Sayegh, S. M., and M. H. Mansour. 2015. “Risk assessment and allocation in highway construction projects in the UAE.” J. Manage. Eng. 31 (6): 04015004. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000365.
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. https://doi.org/10.1177/0976747920963222.
Fan, H., and H. Li. 2013. “Retrieving similar cases for alternative dispute resolution in construction accidents using text mining techniques.” Autom. Constr. 34 (Sep): 85–91. https://doi.org/10.1016/j.autcon.2012.10.014.
Fang, W., H. Luo, S. Xu, P. E. Love, Z. Lu, and C. Ye. 2020. “Automated text classification of near-misses from safety reports: An improved deep learning approach.” Adv. Eng. Inf. 44 (Apr): 101060. https://doi.org/10.1016/j.aei.2020.101060.
Flyvbjerg, B., N. Bruzelius, and W. Rothengatter. 2003. Megaprojects and risk: An anatomy of ambition. Cambridge, UK: Cambridge University Press.
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.
Hassan, F. U., and T. Le. 2020. “Automated requirements identification from construction contract documents using natural language processing.” J. Leg. Aff. Dispute Resolut. Eng. Constr. 12 (2): 04520009. https://doi.org/10.1061/(ASCE)LA.1943-4170.0000379.
Islam, M. S., M. P. Nepal, and M. Skitmore. 2019. “Modified fuzzy group decision-making approach to cost overrun risk assessment of power plant projects.” J. Constr. Eng. Manage. 145 (2): 04018126. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001593.
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.
Jallan, Y., E. Brogan, B. Ashuri, and C. M. Clevenger. 2019. “Application of natural language processing and text mining to identify patterns in construction-defect litigation cases.” J. Leg. Aff. Dispute Resolut. Eng. Constr. 11 (4): 04519024. https://doi.org/10.1061/(ASCE)LA.1943-4170.0000308.
Jung, W., and S. H. Han. 2017. “Which risk management is most crucial for controlling project cost?” J. Manage. Eng. 33 (5): 04017029. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000547.
Kim, T., and S. Chi. 2019. “Accident case retrieval and analyses: Using natural language processing in the construction industry.” J. Constr. Eng. Manage. 145 (3): 04019004. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001625.
Le, T., and H. David Jeong. 2017. “NLP-based approach to semantic classification of heterogeneous transportation asset data terminology.” J. Comput. Civ. Eng. 31 (6): 04017057. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000701.
Lee, J., Y. Ham, J. S. Yi, and J. Son. 2020. “Effective risk positioning through automated identification of missing contract conditions from the contractor’s perspective based on FIDIC contract cases.” J. Manage. Eng. 36 (3): 05020003. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000757.
Leva, M. C., N. Balfe, B. McAleer, and M. Rocke. 2017. “Risk registers: Structuring data collection to develop risk intelligence.” Saf. Sci. 100 (Dec): 143–156. https://doi.org/10.1016/j.ssci.2017.05.009.
Linton, J. 2018. “High-speed rail cost overrun reporting raises questions of media bias.” Accessed October 09, 2020. https://cal.streetsblog.org/2018/01/24/high-speed-rail-cost-overrun-reporting-raises-questions-of-media-bias/.
Mahfouz, T., A. Kandil, and S. Davlyatov. 2018. “Identification of latent legal knowledge in differing site condition (DSC) litigations.” Autom. Constr. 94 (Oct): 104–111. https://doi.org/10.1016/j.autcon.2018.06.011.
Mikolov, T., I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. 2013. “Distributed representations of words and phrases and their compositionality.” In Advances in neural information processing systems, 3111–3119. Stroudsburg, PA: Association for Computational Linguistics.
Molenaar, K. R. 2006. Guide to risk assessment and allocation for highway construction management. Washington, DC: Federal Highway Administration.
Molenaar, K. R. 2010. Vol. 658 of Guidebook on risk analysis tools and management practices to control transportation project costs. Washington, DC: Transportation Research Board.
Mousavi, S. M., R. Tavakkoli-Moghaddam, A. Azaron, S. M. H. Mojtahedi, and H. Hashemi. 2011. “Risk assessment for highway projects using jackknife technique.” Expert Syst. Appl. 38 (5): 5514–5524. https://doi.org/10.1016/j.eswa.2010.10.085.
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’Har, J. P., C. W. Senesi, and K. R. Molenaar. 2017. “Development of a risk register spreadsheet tool for enterprise- and program-level risk management.” Transp. Res. Rec. 2604 (1): 19–27. https://doi.org/10.3141/2604-03.
Papajohn, D., Q. Cui, and M. E. Bayraktar. 2011. “Public-private partnerships in US transportation: Research overview and a path forward.” J. Manage. Eng. 27 (3): 126–135. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000050.
Partnerships, V. P. P. 2015. “P3 risk management guidelines.” In The commonwealth. Washington, DC: Aspen Institute.
Patterson, F. D., and K. Neailey. 2002. “A risk register database system to aid the management of project risk.” Int. J. Project Manage. 20 (5): 365–374. https://doi.org/10.1016/S0263-7863(01)00040-0.
Pennington, J., R. Socher, and C. D. Manning. 2014. Glove: Global vectors for word representation. In Proc., 2014 Conf. on Empirical Methods in Natural Language Processing (EMNLP), 1532–1543. Stroudsburg, PA: Association for Computational Linguistics.
PMI (Project Management Institute). 2013. The project management body of knowledge (PMBOK guide). 5th ed. Newtown Square, PA: PMI.
Roberds, W., T. McGrath, K. Molenaar, M. Loulakis, and T. Ferragut. 2015. Developing the ‘Guide for the process of managing risk on rapid renewal projects’. Washington, DC: National Academies of Sciences, Engineering, and Medicine.
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.
Shahmirzadi, O., A. Lugowski, and K. Younge. 2019. “Text similarity in vector space models: A comparative study.” In Proc., 2019 18th IEEE Int. Conf. on Machine Learning and Applications (ICMLA), 659–666. New York: IEEE.
Sidorov, G. 2019. “Vector space model for texts and the tf-idf measure.” In Syntactic n-grams in computational linguistics, 11–15. Cham, Switzerland: Springer.
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.
Slowey, K. 2019. “Delays bring Maryland Purple Line costs to $6 B.” Accessed October 09, 2020. https://www.constructiondive.com/news/delays-bring-maryland-purple-line-costs-close-to-6b/551301/.
Snyder, P., G. Ullrich, and Z. Waller. 2020. Airport risk identification and prioritization practices. Washington, DC: National Academies of Sciences, Engineering, and Medicine.
Soman, R. K., and J. K. Whyte. 2020. “Codification challenges for data science in construction.” J. Constr. Eng. Manage. 146 (7): 04020072. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001846.
Tang, L., Y. Zhang, F. Dai, Y. Yoon, Y. Song, and R. S. Sharma. 2017. “Social media data analytics for the US Construction industry: Preliminary study on Twitter.” J. Manage. Eng. 33 (6): 04017038. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000554.
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.
Tran, D. Q., and K. R. Molenaar. 2015. “Risk-based project delivery selection model for highway design and construction.” J. Constr. Eng. Manage. 141 (12): 04015041. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001024.
Wang, M. T., and H. Y. Chou. 2003. “Risk allocation and risk handling of highway projects in Taiwan.” J. Manage. Eng. 19 (2): 60–68. https://doi.org/10.1061/(ASCE)0742-597X(2003)19:2(60).
Xue, J., G. Q. Shen, Y. Li, J. Wang, and I. Zafar. 2020. “Dynamic stakeholder-associated topic modeling on public concerns in megainfrastructure projects: Case of Hong Kong–Zhuhai–Macao bridge.” J. Manage. Eng. 36 (6): 04020078. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000845.
Yan, H., N. Yang, Y. Peng, and Y. Ren. 2020. “Data mining in the construction industry: Present status, opportunities, and future trends.” Autom. Constr. 119 (Nov): 103331. https://doi.org/10.1016/j.autcon.2020.103331.
Zayed, T., M. Amer, and J. Pan. 2008. “Assessing risk and uncertainty inherent in Chinese highway projects using AHP.” Int. J. Project Manage. 26 (4): 408–419. https://doi.org/10.1016/j.ijproman.2007.05.012.
Zhang, F. 2019. “A hybrid structured deep neural network with Word2Vec for construction accident causes classification.” Int. J. Construct. Manage. 1–21. https://doi.org/10.1080/15623599.2019.1683692.
Zhang, J., and N. M. El-Gohary. 2016. “Semantic NLP-based information extraction from construction regulatory documents for automated compliance checking.” J. Comput. Civ. Eng. 30 (2): 04015014. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000346.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 147 • Issue 12 • December 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Nov 5, 2020
Accepted: Sep 8, 2021
Published online: Oct 12, 2021
Published in print: Dec 1, 2021
Discussion open until: Mar 12, 2022
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
- Xu Ren, Chenmeng Jia, Mengying Wang, Policy Effect on Technology Innovation in Prefabricated Buildings: An Empirical Study Using the Difference-in-Differences Approach, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-14524, 150, 10, (2024).
- Liping Fu, Huajun Sun, Ya’nan Fang, Kaibo Xu, A SYSTEMATIC REVIEW OF THE PUBLIC–PRIVATE PARTNERSHIP LITERATURE PUBLISHED BETWEEN 2012 AND 2021, JOURNAL OF CIVIL ENGINEERING AND MANAGEMENT, 10.3846/jcem.2023.17926, 29, 3, (238-252), (2023).
- Abdolmajid Erfani, Paul J. Hickey, Qingbin Cui, Likeability versus Competence Dilemma: Text Mining Approach Using LinkedIn Data, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5213, 39, 3, (2023).
- Mengjue Xing, Jiming Cao, Dongping Cao, Impacts of Policy Mix Comprehensiveness on BIM Implementation: Moderating Effects of Environmental State and Response Uncertainty, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-12716, 149, 2, (2023).
- Abdolmajid Erfani, Zihui Ma, Qingbin Cui, Gregory B. Baecher, Ex Post Project Risk Assessment: Method and Empirical Study, Journal of Construction Engineering and Management, 10.1061/JCEMD4.COENG-12588, 149, 2, (2023).
- Rouzbeh Shabani, Olav Torp, Ole Jonny Klakegg, Agnar Johansen, Knowledge about the Origins of Uncertainties from the Pre-Project Phase of Road Projects, Infrastructures, 10.3390/infrastructures8010001, 8, 1, (1), (2022).
- Abdolmajid Erfani, Qingbin Cui, Predictive risk modeling for major transportation projects using historical data, Automation in Construction, 10.1016/j.autcon.2022.104301, 139, (104301), (2022).