Empirical Study for Capturing and Allocating Significant Risk Factors in School Construction Projects in Iraq
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Abstract
In Iraq, more than 1031 school projects have been halted due to disputes and claims resulting from financial, contractual, or other issues. This research aims to identify, prioritize, and allocate the most critical risk factors that threaten these projects’ success for the duration (2017-2022). Based on a multi-step methodology developed through systematic literature reviews, realistic case studies, and semi-structured interviews, 47 risk factors were identified. Based on 153 verified responses, the survey reveals that the top-ranked risk factors are corruption and bribery, delaying the payments of the financial dues to the contractors or sub-contractors, absence of risk management strategy, multiple change orders due to changing designs and specifications during construction; inaccuracy in time and budget estimation; construction material price; financial and economic crisis/financial instability; selecting the contractor only based on the lowest bid, regardless of technical competence; instability within the political system of the government/instability of the government as a client; foreign exchange rates fluctuate against the Iraqi dinar. The study also showed that the respondents recommended allocating four risks to the owner, eight risk factors to the contractor, one risk to the consultant, and 32 factors allocated as shared. The study concluded that the results could help identify the most critical risks facing this type of project and the contracting party that can bear the risks and manage them efficiently.
Article received: 06/02/2023
Article accepted: 01/11/2023
Article published: 01/12/2023
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Abbas, N.N., and Burhan, A.M. 2023. Evaluation of the current status of the cost control processes in Iraqi construction projects. Journal of Engineering, 29(1), pp. 128-144. Doi:10.31026/j.eng.2023.01.08.
Al-Mhdawi, M.K.S., Brito, M.P., Abdul Nabi, M., El-Adaway, I.H., and Onggo, B.S., 2021. Capturing the impact of COVID-19 on construction projects in developing countries: A case study of Iraq. Journal of management in engineering, 38(1), P. 05021015. Doi:10.1061/(ASCE)ME.1943-5479.0000991.
Al-Mhdawi, M.K.S., O’Connor, A., Brito, M., Qazi, A. and Rashid, H.A., 2022. Modeling the effects of construction risks on the performance of oil and gas projects in developing countries: Project managers “perspective”. In Proc., Civil Engineering Research in Ireland Conf.(CERI 2022), Dublin, Ireland, 25-26 August 2022, Niall Holmes, Caitriona De Paor & Roger P. West (pp. 486-491).
Alvand, A., Mirhosseini, S. M., Ehsanifar, M., Zeighami, E., and Mohammadi, A., 2021. Identification and assessment of risk in construction projects using the integrated FMEA-SWARA-WASPAS model under fuzzy environment: a case study of a construction project in Iran. International journal of construction management, pp. 1-23. Doi:10.1080/15623599.2021.1877875.
Annamalaisami, C.D., and Kuppuswamy, A., 2019. Reckoning construction cost overruns in building projects through methodological consequences. International Journal of Construction Management, 22(6), pp. 1079-1089. Doi:10.1080/15623599.2019.1683689.
Bajjou, M.S., and Chafi, A., 2018. Empirical study of schedule delay in Moroccan construction projects. International Journal of Construction Management, 20(7), pp. 783-800. Doi:10.1080/15623599.2018.1484859
Chatterjee, K., Zavadskas, E.K., Tamošaitienė, J., Adhikary, K., and Kar, S., 2018. A hybrid MCDM technique for risk management in construction projects. Symmetry, 10(46), pp. 1-28. Doi:10.3390/sym10020046.
Chen, G.X., Shan, M., Chan, A.P., Liu, X., and Zhao, Y.Q., 2017. Investigating the causes of delay in grain bin construction projects: the case of China. International Journal of Construction Management, 19(1), pp. 1-14. Doi: 10.1080/15623599.2017.1354514.
Cronbach, L.J., and Shavelson, R.J., 2004. My current thoughts on coefficient alpha and successor procedures. Educational and psychological measurement, 64(3), pp. 391-418. Doi:10.1177/0013164404266386.
CSO, 2021. (Central Statistics Organization/Iraq) https://cosit.gov.iq/ar/national-accounts/income.
Dang, C.N., Le-Hoai, L., Kim, S.Y., Nguyen, C.V., Lee, Y.D., and Lee, S.H., 2017. Identification of risk patterns in Vietnamese road and bridge construction: Contractor’s perspective. Built Environment Project and Asset Management, 7(1), pp. 59-72. Doi:10.1108/BEPAM-11-2015-0065
Durdyev, S., Omarov, M., and Ismail, S., 2017. Causes of delay in residential construction projects in Cambodia. Cogent Engineering, 4(1), pp. 1-12. Doi:10.1080/23311916.2017.1291117.
Egwim, C.N., Alaka, H., Toriola-Coker, L.O., Balogun, H., and Sunmola, F., 2021. Applied artificial intelligence for predicting construction projects delay. Machine Learning with Applications, 6, pp. 1-15. Doi:10.1016/j.mlwa.2021.100166.
El-Sayegh, S.M., Manjikian, S., Ibrahim, A., Abouelyousr, A., and Jabbour, R., 2018. Risk identification and assessment in sustainable construction projects in the UAE. International Journal of Construction Management, 21(4), pp. 327-336. Doi:10.1080/15623599.2018.1536963.
Gondia, A., Siam, A., El-Dakhakhni, W., and Nassar, A. H., 2020. Machine learning algorithms for construction projects delay risk prediction. Journal of Construction Engineering and Management, 146(1), pp. 1-16. Doi:10.1061/(ASCE)CO.1943-7862.0001736.
Grubbs, F.E., 1969. Procedures for detecting outlying observations in samples. Technometrics, 11(1), pp. 1-21. Doi:10.1080/00401706.1969.10490657.
Gunduz, M., and Elsherbeny, H.A., 2021. Critical assessment of contract administration using multidimensional fuzzy logic approach. Journal of Construction Engineering and Management, 147(2), pp. 1-12. Doi:10.1061/(ASCE)CO.1943-7862.0001975.
Gillham, B., 2000. Developing a questionnaire Continuum. London: Bloomsbury Academic.
Hadi, M., and Abd, A.M., 2021. Using of an artificial neural networks with particle swarm optimization (ANN-PSO) model in prediction of cost and delay in construction projects. Diyala Journal of Engineering Sciences, 14(3), pp. 78-93. Doi:10.24237/djes.2021.14307.
Hair Jr, J.F., Black, W.C., Babin, B.J., and Anderson, R.E., 2014. Multivariate data analysis. (7th edition), London: Pearson Education.
Hiyassat, M.A., Alkasagi, F., El-Mashaleh, M., and Sweis, G.J., 2020. Risk allocation in public construction projects: the case of Jordan. International journal of construction management, 22(8), pp. 1478-1488. Doi:10.1080/15623599.2020.1728605.
Hung, L., 2018. A risk assessment framework for construction project using artificial neural network. Journal of Science and Technology in Civil Engineering (STCE)-HUCE, 12(5), pp. 51-62. Doi:10.31814/stce.nuce2018-12(5)-06.
Jaber, A.Z., 2019. Assessment risk in construction projects in Iraq using COPRAS-SWARA combined method. Journal of Southwest Jiaotong University, 54(4), pp. 1-13. Doi:10.35741/issn.0258-2724.54.4.28.
Jahan, S., Khan, K.I.A., Thaheem, M.J., Ullah, F., Alqurashi, M., and Alsulami, B.T., 2022. Modeling profitability-influencing risk factors for construction projects: A System Dynamics Approach. Buildings, 12(6), pp. 1-22. Doi:10.3390/buildings12060701.
Kassem, M., Khoiry, M.A., and Hamzah, N., 2020. Theoretical review on critical risk factors in oil and gas construction projects in Yemen. Engineering, Construction and Architectural Management, 28(4), pp. 934-968. Doi:10.1108/ECAM-03-2019-0123.
Khanh, H.D., and Kim, S.Y., 2014. Evaluating impact of waste factors on project performance cost in Vietnam. KSCE Journal of Civil Engineering, 18, pp. 1923-1933. Doi:10.1007/s12205-014-1219-2.
Khlaifat, D.M., Alyagoub, R.E., Sweis, R.J., and Sweis, G.J., 2017. Factors leading to construction projects' failure in Jordon. International Journal of Construction Management, 19(1), pp. 65-78. Doi:10.1080/15623599.2017.1382092.
Lam, K.C., Wang, D., Lee, P.T., and Tsang, Y.T., 2007. Modelling risk allocation decision in construction contracts. International journal of project management, 25(5), pp. 485-493.
Doi:10.1016/j.ijproman.2006.11.005
Majewska, J., 2015. Identification of multivariate outliers–problems and challenges of visualization methods. Studia Ekonomiczne, (247), pp. 69-83.
Marwa, M., and Altaie, M. R. 2022. Use risk score method to identify the qualitative risk analysis criteria in tendering phase in construction projects. Journal of Engineering, 28(7), pp. 31-42. Doi:10.31026/j.eng.2022.07.03.
MOP (Ministry of Planning), 2022. https://mop.gov.iq/archives/8272.
Patel, T. D., Haupt, T. C., and Bhatt, T., 2019. Fuzzy probabilistic approach for risk assessment of BOT toll roads in Indian context. Journal of Engineering, Design and Technology, 18(1), pp. 251-269. Doi:10.1108/JEDT-05-2019-0138.
Peckiene, A., Komarovska, A., and Ustinovicius, L., 2013. Overview of risk allocation between construction parties. Procedia Engineering, 57, pp. 889-894. Doi:10.1016/j.proeng.2013.04.113.
Rachid, Z., Toufik, B., and Mohammed, B., 2018. Causes of schedule delays in construction projects in Algeria. International Journal of Construction Management, 19(5), pp. 371-381.
Rasheed, N., Shahzad, W., Khalfan, M., and Rotimi, J.O.B., 2022. Risk identification, assessment, and allocation in PPP projects: A systematic review. Buildings, 12(8), pp. 1-19. Doi:10.3390/buildings12081109.
Rasul, N., Malik, M.S.A., Bakhtawar, B., and Thaheem, M.J., 2019. Risk assessment of fast-track projects: a systems-based approach. International Journal of Construction Management, 21(11), pp. 1099-1114. Doi:10.1080/15623599.2019.1602587.
Renault, B.Y., and Agumba, J.N., 2016. Critical risk factors in construction projects: perspective of contractors in South Africa. In Transforming the Future of Infrastructure through Smarter Information: Proceedings of the International Conference on Smart Infrastructure and Construction, ICE Publishing, pp. 707-714.
Saleem, R., Khaleel, T.A., and Salam, H., 2016. Risk management which affects school building construction. Engineering and Technology Journal, 34(1 Part (A) Engineering), pp. 1-12. Doi:10.30684/etj.34.1A.17.
Sami Ur Rehman, M., Thaheem, M.J., Nasir, A.R., and Khan, K.I.A., 2020. Project schedule risk management through building information modelling. International Journal of Construction Management, 22(8), pp. 1489-1499. Doi: 10.1080/15623599.2020.1728606.
Sanni-Anibire, M.O., Zin, R.M., and Olatunji, S.O., 2020. Machine learning model for delay risk assessment in tall building projects. International Journal of Construction Management, 22(11), pp. 2134-2143. Doi:10.1080/15623599.2020.1768326.
Santoso, D.S., and Gallage, P.G.M.P., 2019. Critical factors affecting the performance of large construction projects in developing countries: A case study of Sri Lanka. Journal of Engineering, Design and Technology, 18(3), pp. 531-556. Doi:10.1108/JEDT-05-2019-0130.
Shang, G., and Sui Pheng, L., 2014. Barriers to lean implementation in the construction industry in China. Journal of Technology Management in China, 9(2), pp. 155-173. Doi:10.1108/JTMC-12-2013-0043.
Siraj, N.B., and Fayek, A.R., 2019. Risk identification and common risks in construction: Literature review and content analysis. Journal of Construction Engineering and Management, 145(9), pp. 1-13. Doi:10.1061/(ASCE)CO.1943-7862.0001685.
Tembo-Silungwe, C.K., and Khatleli, N., 2017. A Conceptual Model for Risk Allocation in the Construction Industry. American Journal of Applied Sciences, 14(7), pp. 690–700. Doi:10.3844/ajassp.2017.690.700.
Tepeli, E., Taillandier, F., and Breysse, D., 2019. Multidimensional modelling of complex and strategic construction projects for a more effective risk management. International Journal of Construction Management, 21(12), pp. 1218-1239. Doi:10.1080/15623599.2019.1606493.
Wuni, I.Y., and Shen, G.Q., 2020. Fuzzy modelling of the critical failure factors for modular integrated construction projects. Journal of Cleaner Production, 264, pp. 1-32. Doi:10.1016/j.jclepro.2020.121595.
Xu, X., Wang, J., Li, C.Z., Huang, W., and Xia, N., 2018. Schedule risk analysis of infrastructure projects: A hybrid dynamic approach. Automation in Construction, 95, pp. 20-34. Doi:10.1016/j.autcon.2018.07.026.
Yaseen, Z.M., Ali, Z.H., Salih, S.Q., and Al-Ansari, N., 2020. Prediction of risk delay in construction projects using a hybrid artificial intelligence model. Sustainability, 12(4), pp. 1-14. Doi:10.3390/su12041514.
Yeganeh, A., Younesi Heravi, M., Razavian, S.B., Behzadian, K., and Shariatmadar, H., 2021. Applying a new systematic fuzzy FMEA technique for risk management in light steel frame systems. Journal of Asian Architecture and Building Engineering, 21(6), pp. 2481-2502. Doi:10.1080/13467581.2021.1971994.