Policy-Oriented Risk Assessment and Control Strategies for Engineering Costs: Insights from Gray System Modeling
DOI:
https://doi.org/10.52152/3048Keywords:
gray system; entropy weight method; gray correlation; engineering cost; risk assessmentAbstract
In order to ensure the economic benefits and quality standards of construction projects, engineering cost risk assessment and control is particularly important in engineering project management. This paper constructs the engineering cost risk assessment index system based on the identification process of engineering cost risk factors and the establishment process of assessment index system. Then use the entropy weight method to solve the risk assessment index weights, combined with the gray system theory to obtain the gray correlation degree of cost risk assessment, and modeling assessment of engineering cost risk index. Taking a construction project as an example, the cost risk assessment is used to propose the engineering cost risk control strategy. The impact of the design stage in the cost risk assessment is the largest (0.3273), the impact of the completion stage is the smallest (0.0581), and the gray correlation of the overall cost risk is between 0.223 and 0.236, which is at the level of low risk and general risk. After the implementation of cost risk assessment management, the return yield of the investor increased by 8.52 percentage points. By analyzing the importance of project cost risk assessment and discussing its theoretical basis and practical application, in order to provide theoretical support and practical guidance for improving the level of project cost risk control.
References
Jung, W., & Han, S. H. (2017). Which risk management is most crucial for controlling project cost?. Journal of Management in Engineering, 33(5), 04017029.
Ali, Z., Zhu, F., & Hussain, S. (2018). Risk assessment of ex-post transaction cost in construction projects using structural equation modeling. Sustainability, 10(11), 4017.
Portugal-Pereira, J., Ferreira, P., Cunha, J., Szklo, A., Schaeffer, R., & Araújo, M. (2018). Better late than never, but never late is better: Risk assessment of nuclear power construction projects. Energy Policy, 120, 158-166.
Yuan, T., Xiang, P., Li, H., & Zhang, L. (2020). Identification of the main risks for international rail construction projects based on the effects of cost-estimating risks. Journal of Cleaner Production, 274, 122904.
Gunduz, M., & Maki, O. L. (2018). Assessing the risk perception of cost overrun through importance rating. Technological and Economic Development of Economy, 24(5), 1829-1844.
Aljohani, A., Ahiaga-Dagbui, D., & Moore, D. (2017). Construction projects cost overrun: What does the literature tell us?. International Journal of Innovation, Management and Technology, 8(2), 137.
Islam, M. S., Nepal, M. P., Skitmore, M., & Attarzadeh, M. (2017). Current research trends and application areas of fuzzy and hybrid methods to the risk assessment of construction projects. Advanced Engineering Informatics, 33, 112-131.
Wibawa, I. G. S., Santiana, I. M. A., Suasira, I. W., Sudiasa, I. W., & Sumardika, A. R. (2023). Risk analysis of material management that causes cost and time deviations in high-story building projects. International Research Journal of Engineering, IT and Scientific Research, 9(6), 231-239.
Ghaffarianhoseini, A., Tookey, J., Ghaffarianhoseini, A., Naismith, N., Azhar, S., Efimova, O., & Raahemifar, K. (2017). Building Information Modelling (BIM) uptake: Clear benefits, understanding its implementation, risks and challenges. Renewable and sustainable energy reviews, 75, 1046-1053.
Silvius, A. G., Kampinga, M., Paniagua, S., & Mooi, H. (2017). Considering sustainability in project management decision making; An investigation using Q-methodology. International Journal of Project Management, 35(6), 1133-1150.
Marinina, O., & Nevskaya, M. (2017). Cost management of mining project life cicle. International Multidisciplinary Scientific GeoConference: SGEM, 17(1.3), 175-179.
Zou, Y., Kiviniemi, A., & Jones, S. W. (2017). A review of risk management through BIM and BIM-related technologies. Safety science, 97, 88-98.
Lo, H. W., & Liou, J. J. (2018). A novel multiple-criteria decision-making-based FMEA model for risk assessment. Applied soft computing, 73, 684-696.
Alves, A., Gersonius, B., Kapelan, Z., Vojinovic, Z., & Sanchez, A. (2019). Assessing the Co-Benefits of green-blue-grey infrastructure for sustainable urban flood risk management. Journal of environmental management, 239, 244-254.
Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: An approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289.
Liu, S., Yang, Y., & Forrest, J. (2017). Grey data analysis. Springer Singapore, Singapore, Doi, 10(1007), 978-981.
Ou-Yang, C., & Chen, W. L. (2017). Applying a risk assessment approach for cost analysis and decision-making: a case study for a basic design engineering project. Journal of the Chinese Institute of Engineers, 40(5), 378-390.
Afzal, F., Yunfei, S., Nazir, M., & Bhatti, S. M. (2021). A review of artificial intelligence based risk assessment methods for capturing complexity-risk interdependencies: Cost overrun in construction projects. International Journal of Managing Projects in Business, 14(2), 300-328.
Xia, N., Wang, X., Wang, Y., Yang, Q., & Liu, X. (2017). Lifecycle cost risk analysis for infrastructure projects with modified Bayesian networks. Journal of Engineering, Design and Technology, 15(1), 79-103.
Islam, M. S., Nepal, M. P., Skitmore, M., & Kabir, G. (2019). A knowledge-based expert system to assess power plant project cost overrun risks. Expert Systems with Applications, 136, 12-32.
Islam, M. S., Nepal, M. P., & Skitmore, M. (2019). Modified fuzzy group decision-making approach to cost overrun risk assessment of power plant projects. Journal of Construction Engineering and Management, 145(2), 04018126.
Shehadeh, A., Alshboul, O., & Hamedat, O. (2022). Risk assessment model for optimal gain–pain share ratio in target cost contract for construction projects. Journal of Construction Engineering and Management, 148(2), 04021197.
Afzal, F., Yunfei, S., Junaid, D., & Hanif, M. S. (2020). Cost-risk contingency framework for managing cost overrun in metropolitan projects: Using fuzzy-AHP and simulation. International Journal of Managing Projects in Business, 13(5), 1121-1139.
Bo Yu & Tao Yu. (2023). Risk assessment method of transmission and transformation project cost based on Monte Carlo simulation. International Journal of Sustainable Development(3-4),278-290.
Wang Jiao. (2020). Construction of Risk Evaluation Index System for Power Grid Engineering Cost by Applying WBS-RBS and Membership Degree Methods. Mathematical Problems in Engineering.
Yang Yuanyue & Li Huimin. (2018). Evaluation on Cost Overrun Risks of Long-distance Water Diversion Project Based on SPA-IAHP Method. IOP Conference Series: Earth and Environmental Science(1),012012-012012.
Longqing Shi,Yu Li,Jin Han & Xiao Yang. (2024). Water Richness Evaluation of Coal Roof Aquifers Based on the Game Theory Combination Weighting Method and the TOPSIS Model. Mine Water and the Environment(prepublish),1-16.
Zeng Qinglong,Dai Fengjuan & Zhang Ran. (2024). Prediction of concrete sulfuric acid corrosion evaluation index model based on grey system theory. Vibroengineering Procedia194-200.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Lex localis - Journal of Local Self-Government
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
