An analytic network process based risk assessment model for PPP hydropower investments
Abstract
The number of public-private partnership (PPP) projects has gone up especially in developing countries. The risk assessment of PPP projects is essential in ensuring project success. The objective of this study is to develop an Analytic Network Process (ANP) based risk assessment model for hydropower investments, and a tool to facilitate quantification of risk ratings based on this model. The results show that the three most important risk factors that affect the overall risk rating of a PPP hydropower investment are legal risks, contractor/subcontractor risks, and operator risks. In addition, the three most important risk clusters were identified as stakeholders, government requirements, and resources, whereas market was the least important cluster. The tool that measures the risk rating of a PPP of hydropower project was tested on ten real cases, and satisfactory results were obtained in terms of its predictive capability. The contributions of this research include (1) identification of the risk factors and clusters of factors associated with PPP hydropower investments; (2) determination of the priority of each risk factor and cluster; (3) development a tool that guides the investors through the risk assessment of PPP hydropower investments.
Keyword : renewable energy, PPP, hydropower investment, ANP
How to Cite
Akcay, E. C. (2021). An analytic network process based risk assessment model for PPP hydropower investments. Journal of Civil Engineering and Management, 27(4), 268-277. https://doi.org/10.3846/jcem.2021.14650
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Choma, A. A. (2008). How to reduce risks in contractors’ management. In PMI® Global Congress 2008, North America, Denver, CO. Project Management Institute, Newtown Square, PA.
Chou, J., & Pramudawardhani, D. (2015). Cross-country comparisons of key drivers, critical success factors and risk allocation for public-private partnership projects. International Journal of Project Management, 33, 1136–1150. https://doi.org/10.1016/j.ijproman.2014.12.003
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El-Abbasy, M. S., Zayed, T., Ahmed, M., Alzraiee, H., & Abouhamad, M. (2013). Contractor selection model for highway projects using integrated simulation and analytic network process. Journal of Construction Engineering and Management, 139(7), 755–767. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000647
Erdem, D., & Ozorhon, B. (2015). Assessing real estate project success using an Analytic Network Process. Journal of Management in Engineering, 31(4), 04014065. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000281
Ghorbani, A., Ravanshadnia, M., & Nobakht, M. B. (2014). A survey of risks in public private partnership highway projects in Iran. In 2014 International Conference on Construction and Real Estate Management, Kunming, China. https://doi.org/10.1061/9780784413777.058
Hasnain, M., Thaheem, M. J., & Ullah, F. (2018). Best value contractor selection in road construction projects: ANP-based decision support system. International Journal of Civil Engineering, 16, 695–714. https://doi.org/10.1007/s40999-017-0199-2
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Ibrahim, A. D., Price, A. D. F., & Dainty, A. R. J. (2006). The analysis and allocation of risks in public private partnerships in infrastructure projects in Nigeria. Journal of Financial Management of Property and Construction, 11(3), 149–163. https://doi.org/10.1108/13664380680001086
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Keers, B. B. M., & Fenema, P. C. V. (2018). Managing risks in public-private partnership formation projects. International Journal of Project Management, 36, 861–875. https://doi.org/10.1016/j.ijproman.2018.05.001
Ke, Y., Wang, S., Chan, A. P. C., & Lam, P. T. I. (2010). Preferred risk allocation in China’s Public Private Partnership (PPP) projects. Journal of Project Management, 28, 482–492. https://doi.org/10.1016/j.ijproman.2009.08.007
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Kuru, K., & Artan, D. (2020). A canvas model for risk assessment and performance estimation in public-private partnerships. International Journal of Construction Management, 20(6), 704–719. https://doi.org/10.1080/15623599.2020.1763898
Li, H., Dong, K., Jiang, H., Sun, R., Guo, X., & Fan, Y. (2017). Risk assessment of China’s overseas oil refining investment using a fuzzy-grey comprehensive evaluation method. Sustainability, 9, 696. https://doi.org/10.3390/su9050696
Li, Y., & Wang, X. (2019). Using fuzzy analytic network process and ISM methods for risk assessment of public-private partnership: A China perspective. Journal of Civil Engineering and Management, 25(2), 168–183. https://doi.org/10.3846/jcem.2019.8655
Liu, J., Love, P. E. D., Smith, J., Regan, M., & Davis, P. R. (2015). Life cycle critical success factors for public-private partnership infrastructure projects. Journal of Management in Engineering, 31(5), 04014073. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000307
Mazher, K. M., Chan, A. P. C., Zahoor, H., Khan, M. I., & Ameyaw, E. E. (2018). Fuzzy integral-based risk-assessment approach for public-private partnership infrastructure projects. Journal of Construction Engineering and Management, 144(12), 04018111. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001573
Meade, L. M., & Presley, A. (2002). R&D project selection using the analytic network process. IEEE Transactions on Engineering Management, 49(1), 59–66. https://doi.org/10.1109/17.985748
Nguyen, A., Mollik, A., & Chih, Y. (2018). Managing critical risks affecting the financial viability of public-private partnership projects: Case study of toll road projects in Vietnam. Journal of Construction Engineering and Management, 144(12), 05018014. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001571
Niemira, M. P., & Saaty, T. L. (2004). An analytical network process model for financial-crisis forecasting. International Journal of Forecasting, 20(4), 573–587. https://doi.org/10.1016/j.ijforecast.2003.09.013
Osei-Kyei, R., & Chan, A. (2015). Review of studies on the critical success factors for public–private partnership (PPP) projects from 1990 to 2013. International Journal of Project Management, 33(6), 1335–1346. https://doi.org/10.1016/j.ijproman.2015.02.008
Ozcan-Deniz, G., & Zhu, Y. (2015). A multi-objective decisionsupport model for selecting environmentally conscious highway construction methods. Journal of Civil Engineering and Management, 21(6), 733–747. https://doi.org/10.3846/13923730.2014.893915
Ozorhon, B., Dikmen, I., & Birgonul, M. T. (2007). Using analytic network process to predict the performance of international construction joint ventures. Journal of Management in Engineering, 23(3), 156–163. https://doi.org/10.1061/(ASCE)0742-597X(2007)23:3(156)
Palaco, I., Park, M. J., Kim, S. K., & Rho, J. J. (2019). Public–private partnerships for e-government in developing countries: An early stage assessment framework. Evaluation and Program Planning, 72, 205–218. https://doi.org/10.1016/j.evalprogplan.2018.10.015
Saaty, T. L. (1994). How to make a decision: The analytic hierarchy process. Interfaces, 24(6), 19–43. https://doi.org/10.1287/inte.24.6.19
Saaty, T. L. (1996). Decision making with dependence and feedback: The analytic network process. Pittsburgh: RWS Publications.
Saaty, T. L. (2003). Decision-making with the AHP: Why is the principal eigenvector necessary? European Journal of Operational Research, 145(1), 86–91. https://doi.org/10.1016/S0377-2217(02)00227-8
Saaty, T. L. (2004). Fundamentals of the analytical network process-dependence and feedback in decision-making with a single network. Journal of Systems Science and Systems Engineering, 13(2), 129–157. https://doi.org/10.1007/s11518-006-0158-y
Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98. https://doi.org/10.1504/IJSSCI.2008.017590
Shang, J. S., Tjader, Y., & Ding, Y. (2004). A unified framework for multicriteria evaluation of transportation projects. IEEE Transactions on Engineering Management, 51(3), 300–313. https://doi.org/10.1109/TEM.2004.830848
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