Share:


Exploring the properties of cost overrun risk propagation network (CORPN) for promoting cost management

    Yun Chen   Affiliation
    ; Zhigen Hu   Affiliation
    ; Quan Liu   Affiliation

Abstract

Construction cost overrun chronically plagues contractors. To address the issue, numerous studies have explored cost overrun risks (CORs). Nevertheless, their methods of identifying risk relationship are susceptible to experts’ experience. In addition, they fail to unearth the relationship structure information and analyze the risk propagation effect. To fill these gaps, this paper intends to propose a methodology that integrates the engineering case analysis and complex network theory, so as to obtain a stable relationship structure and reveal its inherent property. First, 52 CORs and 158 risk paths are extracted from 156 engineering cases, followed by the establishment of a cost overrun risk propagation network (CORPN). Finally, the statistical properties of CORPN are explored. The results indicate that CORPN presents the topological property of heterogeneity. A large number of risk paths can be blocked through preventing the CORs with large total degree, like delay in construction period and engineering quantity increase. Meanwhile, CORPN shows the small-world property. The efficiency of risk propagation can be reduced through preventing the CORs with high betweenness centrality, such as lack of technical skill and experience. These findings contribute to the formulation of beforehand strategies that promote the cost management.

Keyword : cost management, construction cost overrun, cost overrun risks, cost overrun risk propagation network, complex network theory, case analysis

How to Cite
Chen, Y., Hu, Z., & 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
Published in Issue
Jan 21, 2019
Abstract Views
1500
PDF Downloads
940
SM Downloads
248
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Akinci, B., & Fischer, M. (1998). Factors affecting contractors’ risk of cost overburden. Journal of Management in Engineering, 14(1), 67-76. https://doi.org/10.1061/(asce)0742-597x(1998)14:1(67)

Akintoye, A. S., & MacLeod, M. J. (1997). Risk analysis and management in construction. International Journal of Project Management, 15(1), 31-38. https://doi.org/10.1016/S0263-7863(96)00035-X

Albert, R., & Barabasi, A. L. (2002). Statistical mechanics of complex networks. Reviews of Modern Physics, 74(1), 47-97. https://doi.org/10.1103/RevModPhys.74.47

Bai, J. S. (2006). Analysis of engineering claims and contract management in hydropower project construction. Beijing: China Water & Power Press (in Chinese).

Barabasi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509-512. https://doi.org/10.1126/science.286.5439.509

Boateng, P., Chen, Z., Ogunlana, S., & Ikediashi, D. (2012). A system dynamics approach to risks description in megaprojects development. Organization, Technology and Management in Construction, 4(3), 593-603. https://doi.org/10.5592/otmcj.2012.3.3

Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., & Hwang, D. U. (2006). Complex networks: Structure and dynamics. Physics Reports – Review Section of Physics Letters, 424(4-5), 175-308. https://doi.org/10.1016/j.physrep.2005.10.009

Chen, G., Yang, X. H., & Xu, X. L. (2012). Weighted scaling in non-growth random networks. Communications in Theoretical Physics, 58(3), 456-462. https://doi.org/10.1088/0253-6102/58/3/24

Chen, Y., Hu, Z. G., Liu, Q., & Zhao, M. Y. (2018). Risk propagation of delayed payment in stakeholder network of large hydropower project construction considering risk resistance and mitigation. Mathematical Problems in Engineering, 8013207. https://doi.org/10.1155/2018/8013207

Cheng, Y. M. (2014). An exploration into cost-influencing factors on construction projects. International Journal of Project Management, 32(5), 850-860. https://doi.org/10.1016/j.ijproman.2013.10.003

Choudhry, R. M., Aslam, M. A., Hinze, J. W., & Arain, F. M. (2014). Cost and schedule risk analysis of bridge construction in Pakistan: Establishing risk guidelines. Journal of Construction Engineering and Management, 140(7), 04014020. https://doi.org/10.1061/(asce)co.1943-7862.0000857

Creedy, G. D., Skitmore, M., & Wong, J. K. W. (2010). Evaluation of risk factors leading to cost overrun in delivery of highway construction projects. Journal of Construction Engineering and Management, 136(5), 528-537. https://doi.org/10.1061/(asce)co.1943-7862.0000160

Crucitti, P., Latora, V., Marchiori, M., & Rapisarda, A. (2003). Efficiency of scale-free networks: Error and attack tolerance. Physica A: Statistical Mechanics and Its Applications, 320, 622-642. https://doi.org/10.1016/s0378-4371(02)01545-5

Deng, Y., Song, L., Zhou, Z., & Liu, P. (2017). An approach for understanding and promoting coal mine safety by exploring coal mine risk network. Complexity, 7628569. https://doi.org/10.1155/2017/7628569

Derakhshanalavijeh, R., & Teixeira, J. M. C. (2017). Cost overrun in construction projects in developing countries, gas-oil industry of Iran as a case study. Journal of Civil Engineering and Management, 23(1), 125-136. https://doi.org/10.3846/13923730.2014.992467

Dikmen, I., Birgonul, M. T., & Han, S. (2007). Using fuzzy risk assessment to rate cost overrun risk in international construction projects. International Journal of Project Management, 25(5), 494-505. https://doi.org/10.1016/j.ijproman.2006.12.002

Doloi, H. (2013). Cost overruns and failure in project management: Understanding the roles of key stakeholders in construction projects. Journal of Construction Engineering and Management, 139(3), 267-279. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000621

Duenas-Osorio, L., & Vemuru, S. M. (2009). Cascading failures in complex infrastructure systems. Structural Safety, 31(2), 157-167. https://doi.org/10.1016/j.strusafe.2008.06.007

Eteifa, S. O., & El-adaway, I. H. (2018). Using social network analysis to model the interaction between root causes of fatalities in the construction industry. Journal of Management in Engineering, 34(1), 04017045. https://doi.org/10.1061/(asce)me.1943-5479.0000567

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

Flyvbjerg, B., Bruzelius, N., & Rothengatter, W. (2003a). Megaprojects and risk: An anatomy of ambition. Cambridge: Cambridge University Press. https://doi.org/10.1017/CBO9781107050891

Flyvbjerg, B., Holm, M. K. S., & Buhl, S. L. (2003b). How common and how large are cost overruns in transport infrastructure projects?. Transport Reviews, 23(1), 71-88. https://doi.org/10.1080/01441640309904

Forcada, N., Rusinol, G., Macarulla, M., & Love, P. E. D. (2014). Rework in highway projects. Journal of Civil Engineering and Management, 20(4), 455-465. https://doi.org/10.3846/13923730.2014.893917

Gharaibeh, H. M. (2014). Cost control in mega projects using the Delphi method. Journal of Management in Engineering, 30(5), 04014024. https://doi.org/10.1061/(asce)me.1943-5479.0000218

Gonzalez, A. M. M., Dalsgaard, B., & Olesen, J. M. (2010). Centrality measures and the importance of generalist species in pollination networks. Ecological Complexity, 7(1), 36-43. https://doi.org/10.1016/j.ecocom.2009.03.008

Hu, X. B., Gheorghe, A. V., Leeson, M. S., Leng, S. P., Bourgeois, J., & Qu, X. B. (2016). Risk and safety of complex network systems. Mathematical Problems in Engineering, 8983915. https://doi.org/10.1155/2016/8983915

Huang, W. Q., Zhuang, X. T., Yao, S., & Uryasev, S. (2016). A financial network perspective of financial institutions’ systemic risk contributions. Physica A: Statistical Mechanics and Its Applications, 456, 183-196. https://doi.org/10.1016/j.physa.2016.03.034

Huang, Y. C., Cheng, W. Y., Luo, S. D., Luo, Y., Ma, C. C., & He, T. L. (2016). Features of the asynchronous correlation between the China coal price index and coal mining accidental deaths. Plos One, 11(11), 0167198. https://doi.org/10.1371/journal.pone.0167198

Iyer, K. C., & Sagheer, M. (2010). Hierarchical structuring of PPP risks using interpretative structural modeling. Journal of Construction Engineering and Management, 136(2), 151-159. https://doi.org/10.1061/(asce)co.1943-7862.0000127

Jin, Y., Zhang, Q., & Li, S. P. (2016). Topological properties and community detection of venture capital network: Evidence from China. Physica A: Statistical Mechanics and Its Applications, 442, 300-311. https://doi.org/10.1016/j.physa.2015.09.029

Kartam, N. A. (1996). Making effective use of construction lessons learned in project life cycle. Journal of Construction Engineering and Management, 122(1), 14-21. https://doi.org/10.1061/(asce)0733-9364(1996)122:1(14)

Khanzadi, M., Eshtehardian, E., & Esfahani, M. M. (2017). Cash flow forecasting with risk consideration using Bayesian belief networks (BBNS). Journal of Civil Engineering and Management, 23(8), 1045-1059. https://doi.org/10.3846/13923730.2017.1374303

Larsen, J. K., Shen, G. Q., Lindhard, S. M., & Brunoe, T. D. (2016). Factors affecting schedule delay, cost overrun, and quality level in public construction projects. Journal of Management in Engineering, 32(1), 04015032. https://doi.org/10.1061/(asce)me.1943-5479.0000391

Latora, V., & Marchiori, M. (2001). Efficient behavior of small-world networks. Physical Review Letters, 87(19), 198701. https://doi.org/10.1103/PhysRevLett.87.198701

Li, Q. M., Song, L. L., List, G. F., Deng, Y. L., Zhou, Z. P., & Liu, P. (2017). A new approach to understand metro operation safety by exploring metro operation hazard network (MOHN). Safety Science, 93, 50-61. https://doi.org/10.1016/j.ssci.2016.10.010

Li, X., & Chen, G. R. (2003). A local-world evolving network model. Physica A: Statistical Mechanics and Its Applications, 328(1-2), 274-286. https://doi.org/10.1016/s0378-4371(03)00604-6

Liu, J. Z., & Tang, Y. F. (2005). An exponential distribution network. Chinese Physics, 14(4), 643-645. https://doi.org/10.1088/1009-1963/14/4/001

Nasir, D., McCabe, B., & Hartono, L. (2003). Evaluating risk in construction-schedule model (ERIC-S): Construction schedule risk model. Journal of Construction Engineering and Management, 129(5), 518-527. https://doi.org/10.1061/(asce)0733-9364(2003)129:5(518)

Newman, M. E. J. (2003). The structure and function of complex networks. SIAM Review, 45(2), 167-256. https://doi.org/10.1137/s003614450342480

Shane, J. S., Molenaar, K. R., Anderson, S., & Schexnayder, C. (2009). Construction project cost escalation factors. Journal of Management in Engineering, 25(4), 221-229. https://doi.org/10.1061/(asce)0742-597x(2009)25:4(221)

Simonsen, I. (2005). Diffusion and networks: A powerful combination!. Physica A: Statistical Mechanics and Its Applications, 357(2), 317-330. https://doi.org/10.1016/j.physa.2005.06.032

Simonsen, I., Buzna, L., Peters, K., Bornholdt, S., & Helbing, D. (2008). Transient dynamics increasing network vulnerability to cascading failures. Physical Review Letters, 100(21), 218701. https://doi.org/10.1103/PhysRevLett.100.218701

Small, M., & Tse, C. K. (2005). Clustering model for transmission of the SARS virus: Application to epidemic control and risk assessment. Physica A: Statistical Mechanics and Its Applications, 351(2-4), 499-511. https://doi.org/10.1016/j.physa.2005.01.009

Sovacool, B. K., Gilbert, A., & Nugent, D. (2014). Risk, innovation, electricity infrastructure and construction cost overruns: Testing six hypotheses. Energy, 74, 906-917. https://doi.org/10.1016/j.energy.2014.07.070

Tabak, B. M., Takami, M., Rocha, J. M. C., Cajueiro, D. O., & Souza, S. R. S. (2014). Directed clustering coefficient as a measure of systemic risk in complex banking networks. Physica A: Statistical Mechanics and Its Applications, 394, 211-216. https://doi.org/10.1016/j.physa.2013.09.010

Tavakolan, M., & Etemadinia, H. (2017). Fuzzy weighted interpretive structural modeling: Improved method for identification of risk interactions in construction projects. Journal of Construction Engineering and Management, 143(11), 04017084. https://doi.org/10.1061/(asce)co.1943-7862.0001395

Touran, A., & Suphot, L. (1997). Rank correlations in simulating construction costs. Journal of Construction Engineering and Management, 123(3), 297-301. https://doi.org/10.1061/(asce)0733-9364(1997)123:3(297)

Wambeke, B. W., Liu, M., & Hsiang, S. M. (2012). Using Pajek and centrality analysis to identify a social network of construction trades. Journal of Construction Engineering and Management, 138(10), 1192-1201. https://doi.org/10.1061/(asce)co.1943-7862.0000524

Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics ‘small-world’ networks. Nature, 393, 440-442. https://doi.org/10.1038/30918

Wright, E. R., Cho, K., & Hastak, M. (2014). Assessment of critical construction engineering and management aspects of nuclear power projects. Journal of Management in Engineering, 30(4), 04014016. https://doi.org/10.1061/(asce)me.1943-5479.0000286

Zhang, Y. L., & Yang, N. D. (2013). Research on robustness of R&D network under cascading propagation of risk with gray attack information. Reliability Engineering & System Safety, 117, 1-8. https://doi.org/10.1016/j.ress.2013.03.009

Zhou, Z. P., Irizarry, J., & Li, Q. M. (2014). Using network theory to explore the complexity of subway construction accident network (SCAN) for promoting safety management. Safety Science, 64, 127-136. https://doi.org/10.1016/j.ssci.2013.11.029

Zhou, J., Xu, W. X., Guo, X., & Ding, J. (2015). A method for modeling and analysis of directed weighted accident causation network (DWACN). Physica A: Statistical Mechanics and Its Applications, 437, 263-277. https://doi.org/10.1016/j.physa.2015.05.112