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Risk causation model to capture and transfer knowledge in international construction projects

    Fengfeng Zhu   Affiliation
    ; Hao Hu Affiliation
    ; Feng Xu   Affiliation

Abstract

International construction projects are facing various severe risks from country, partner, company, and project. Global contractors have suffered heavy losses. Previous researches have proved that an available organizational risk repository is a reliable knowledge source that can be used to introduce experience-based solutions of how specific risks can be managed in international construction projects. The construction of the organizational risk repository calls for an effective feedback mechanism that dispels the organizational culture of unwillingness to disclose management failure and encourages proactive creation and retention of data and information on historical projects and risk-related knowledge. Hence, this paper proposes a risk causation model for international construction projects (RCM_ICP) to support such a mechanism. RCM_ICP links response measures to the chain of risks to identify management failures and conduct modifications, thereby promoting thinking on the part of the management and capturing key risk management experiences. It includes a category component for the efficient retrieval of relevant knowledge based on country-related factors. Besides, this paper proposes the risk review procedures as the instruction of RCM_ICP. Hence, this research breaks the barriers of sharing information between project and organization levels in a project-based industry.

Keyword : risk management, accident causation model, international construction projects, knowledge management, organizational learning

How to Cite
Zhu, F., Hu, H., & Xu, F. (2022). Risk causation model to capture and transfer knowledge in international construction projects. Journal of Civil Engineering and Management, 28(6), 457–468. https://doi.org/10.3846/jcem.2022.16925
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Jun 6, 2022
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Akgul, B. K., Ozorhon, B., Dikmen, I., & Birgonul, M. T. (2017). Social network analysis of construction companies operating in international markets: case of Turkish contractors. Journal of Civil Engineering and Management, 23(3), 327–337. https://doi.org/10.3846/13923730.2015.1073617

Bu-Qammaz, A. S., Dikmen, I., & Birgonul, M. T. (2009). Risk assessment of international construction projects using the analytic network process. Canadian Journal of Civil Engineering, 36(7), 1170–1181. https://doi.org/10.1139/l09-061

Chang, T., Deng, X., Hwang, B. G., & Zhao, X. (2018a). Political risk paths in international construction projects: case study from Chinese construction enterprises. Advances in Civil Engineering, Article ID 6939828. https://doi.org/10.1155/2018/6939828

Chang, T., Deng, X., Zuo, J., & Yuan, J. (2018b). Political risks in Central Asian countries: factors and strategies. Journal of Management in Engineering, 34(2), 10–19. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000588

Charkhakan, M. H., & Heravi, G. (2018). Risk manageability assessment to improve risk response plan: case study of construction projects in Iran. Journal of Construction Engineering and Management, 144(11), 05018012. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001562

Chen, Y., Hu, Z. G., & Liu, Q. (2019). Exploring the properties of cost overrun risk propagation network (CORPN) for promoting cost management. Journal of Civil Engineering and Management, 25(1), 1–18. https://doi.org/10.3846/jcem.2019.7462

Chen, Y. J., Feng, W., Jiang, Z. Q., Duan, L. L., & Cheng, S. Y. (2021). An accident causation model based on safety information cognition and its application. Reliability Engineering & System Safety, 207, 107363. https://doi.org/10.1016/j.ress.2020.107363

Chua, D. K. H., & Goh, Y. M. (2004). Incident causation model for improving feedback of safety knowledge. Journal of Construction Engineering and Management, 130(4), 542–551. https://doi.org/10.1061/(ASCE)0733-9364(2004)130:4(542)

Coners, A., & Matthies, B. (2018). Perspectives on reusing codified project knowledge: a structured literature review. International Journal of Information Systems and Project Management, 6(2), 25–43. https://doi.org/10.12821/ijispm060202

Dikmen, I., Birgonul, M. T., Anac, C., Tah, J. H. M., & Aouad, G. (2008). Learning from risks: a tool for post-project risk assessment. Automation in Construction, 18(1), 42–50. https://doi.org/10.1016/j.autcon.2008.04.008

Ding, L. Y., Zhong, B. T., Wu, S., & Luo, H. B. (2016). Construction risk knowledge management in bim using ontology and semantic web technology. Safety Science, 87, 202–213. https://doi.org/10.1016/j.ssci.2016.04.008

Eken, G., Bilgin, G., Dikmen, I., & Birgonul, M. T. (2020). A lessons-learned tool for organizational learning in construction. Automation in Construction, 110, 102977. https://doi.org/https://doi.org/10.1016/j.autcon.2019.102977

Eybpoosh, M., Dikmen, I., & Birgonul, M. T. (2011). Identification of risk paths in international construction projects using structural equation modeling. Journal of Construction Engineering and Management, 137(12), 1164–1175. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000382

Fidan, G., Dikmen, I., Tanyer, A. M., & Birgonul, M. T. (2011). Ontology for relating risk and vulnerability to cost overrun in international projects. Journal of Computing in Civil Engineering, 25(4), 302–315. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000090

Hastak, M., & Shaked, A. (2000). ICRAM-1: Model for international construction risk assessment. Journal of Management in Engineering, 16(1), 59–69. https://doi.org/10.1061/(ASCE)0742-597X(2000)16:1(59)

Heinrich, H. W. (1941). Industrial accident prevention: A scientific approach. McGraw-Hill.

Hulme, A., Stanton, N. A., Walker, G. H., Waterson, P., & Salmon, P. M. (2019). What do applications of systems thinking accident analysis methods tell us about accident causation? A systematic review of applications between 1990 and 2018. Safety Science, 117, 164–183. https://doi.org/10.1016/j.ssci.2019.04.016

International Organization for Standardization. (2018). Risk management – Guidelines (ISO Standard No. 31000:2018). https://www.iso.org/obp/ui/#iso:std:iso:31000:ed-2:v1:en

Isaka, T., Yoneda, W., & Koga, T. (2017). Proposal on hybrid risk evaluation method (HREM) for bidding decision in international infrastructure project. Journal of Advanced Mechanical Design, Systems and Manufacturing, 11(5), JAMDSM0063. https://doi.org/10.1299/jamdsm.2017jamdsm0063

Kivrak, S., Arslan, G., Dikmen, I., & Birgonul, M. T. (2008). Capturing knowledge in construction projects: knowledge platform for contractors. Journal of Management in Engineering, 24(2), 87–95. https://doi.org/10.1061/(ASCE)0742-597X(2008)24:2(87)

Lam, C. Y., & Tai, K. (2020). Network topological approach to modeling accident causations and characteristics: analysis of railway incidents in Japan. Reliability Engineering & System Safety, 193, 106626. https://doi.org/10.1016/j.ress.2019.106626

Lee, K.-W., & Han, S. H. (2017). Quantitative analysis for country classification in the construction industry. Journal of Management in Engineering, 33(4), 04017014. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000522

Lee, K. W., Han, S. H., Park, H., & Jeong, H. D. (2016). Empirical analysis of host-country effects in the international construction market: an industry-level approach. Journal of Construction Engineering and Management, 142(3), 04015092. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001083

Li, G. H., Chen, C., Zhang, G. M., & Martek, I. (2020). Bid/no-bid decision factors for Chinese international contractors in international construction projects. Engineering Construction and Architectural Management, 27(7), 1619–1643. https://doi.org/10.1108/ECAM-11-2018-0526

Liu, J. Y., Zhao, X. B., & Yan, P. (2016). Risk paths in international construction projects: Case study from Chinese contractors. Journal of Construction Engineering and Management, 142(6), 05016002. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001116

Niu, Y. L., Deng, X. P., Zhang, L. M., & Duan, X. C. (2019). Understanding critical variables contributing to competitive advantages of international high-speed railway contractors. Journal of Civil Engineering and Management, 25(2), 184–202. https://doi.org/10.3846/jcem.2019.8427

Okudan, O., Budayan, C., & Dikmen, I. (2021). A knowledge-based risk management tool for construction projects using case-based reasoning. Expert Systems with Applications, 173, 114776. https://doi.org/10.1016/j.eswa.2021.114776

Project Management Institute. (2017). A guide to the project management body of knowledge (6 ed.). Project Management Institute, Inc.

Tah, J. H. M., & Carr, V. (2001). Towards a framework for project risk knowledge management in the construction supply chain. Advances in Engineering Software, 32(10), 835–846. https://doi.org/10.1016/S0965-9978(01)00035-7

Tserng, H. P., Yin, S. Y. L., Dzeng, R. J., Wou, B., Tsai, M. D., & Chen, W. Y. (2009). A study of ontology-based risk management framework of construction projects through project life cycle. Automation in Construction, 18(7), 994–1008. https://doi.org/10.1016/j.autcon.2009.05.005

Viswanathan, S. K., Tripathi, K. K., & Jha, K. N. (2020). Influence of risk mitigation measures on international construction project success criteria – a survey of Indian experiences. Construction Management and Economics, 38(3), 207–222. https://doi.org/10.1080/01446193.2019.1577987

Woolley, M., Goode, N., Salmon, P., & Read, G. (2020). Who is responsible for construction safety in Australia? A STAMP analysis. Safety Science, 132, 104984. https://doi.org/10.1016/j.ssci.2020.104984

Yildiz, A. E., Dikmen, I., Birgonul, M. T., Ercoskun, K., & Alten, S. (2014). A knowledge-based risk mapping tool for cost estimation of international construction projects. Automation in Construction, 43, 144–155. https://doi.org/10.1016/j.autcon.2014.03.010

Zhu, F., Hu, H., Xu, F., & Tang, N. (2019). Predicting profit performance of international construction projects. In the IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Macao, China https://doi.org/10.1109/IEEM44572.2019.8978561

Zhu, F., Hu, H., Xu, F., & Tang, N. (2021). Predicting the impact of country-related risks on cost overrun for overseas infrastructure projects. Journal of Construction Engineering and Management, 147(2), 04020166. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001959