ABSTRACT

Cost management is key to real estate development. Previous studies have provided a conceptual scheme and quantity take-off tool improving the speed and accuracy of construction cost management (CMM) work. However, cost management requires cross-functional coordination and internal iterations—an efficient environment for data communication and computation. This study developed an ontology-based system to conceptualize CCM knowledge in terms of stages and disciplines. Multiple ontology models and their associated concepts, properties, and rules are extracted from extensive literature and expert interviews to describe CCM procedures for cost estimation and cost management. With the development of data infrastructure and operation platforms presented here, information necessary for and deriving from cost management work is simultaneously updated in the database and distributed following inference rules. Empowered by the model, organizations can save time for planning and decision-making through automatic data reuse and disposal. Construction cost has been well controlled in development, with an average deviation of 2% in our local application. Applications for the design and tender stages are implemented to demonstrate the effectiveness of the proposed model in the domain of cost management in real estate development.

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REFERENCES

Didkovskaya, O. V., Mamayeva, O. A., and Ilyina, M. V. (2016). “Development of cost engineering system in construction.” Procedia Engineering, 153, 131–135.
Ding, S. (2018). Cost management of construction projects, China Building Industry Press, Beijing. (in Chinese).
Donald, T. (2013). Cost management of construction projects, Cambridge University Press, Cambridge.
Dong, C., Wang, F., Li, H., Ding, L. Y., and Luo, H. B. (2018). “Knowledge dynamics-integrated map as a blueprint for system development: Applications to safety risk management in Wuhan metro project.” Automation in Construction, 93, 112–122.
Durdyev, S. (2021). “Review of construction journals on causes of project cost overruns.” Engineering, Construction and Architectural Management, 28(04), 1241–1260.
Fazeli, A., Dashti, M. S., Jalaei, F., and Khanzadi, M. (2020). “An integrated BIM-based approach for cost estimation in construction projects.” Engineering, Construction and Architectural Management, 28(04), 2828–2854.
Idowu, O. S., and Lam, K. C. (2019). “Web-based application for predesign cost planning of vertical building envelopes.” Automation in Construction, 106, 102909.
Lee, S. K., Kim, K. R., and Yu, J. H. (2014). “BIM and ontology-based approach for building cost estimation.” Automation in Construction, 41, 96–105.
Liu, H. X., Lu, M., and Al-Hussein, M. (2016). “Ontology-based semantic approach for construction-oriented quantity take-off from BIM models in the light-frame building industry.” Advanced Engineering Informatics, 30(02), 190–207.
Ma, Z. L., Wei, Z. H., and Zhang, X. D. (2013). “Semi-automatic and specification-compliant cost estimation for tendering of building projects based on IFC data of design model.” Automation in Construction, 30, 126–135.
Mao, S. Z., and Xiao, F. Y. (2019). “A novel method for forecasting construction cost index based on complex network.” Physica A: Statistical Mechanics and its Applications, 527.
MHURDPRC (Ministry of Housing and Urban-Rural Development of the People’s Republic of China). (2013). Unified standard for constructional quality acceptance of building engineering, GB 50300-2013, Beijing. (in Chinese).
Niknam, M., and Karshenas, S. (2015). “Integrating distributed sources of information for construction cost estimating using Semantic Web and Semantic Web Service technologies.” Automation in Construction, 57, 222–238.
Ren, G. Q., Li, H. J., Liu, S., Goonetillake, J., Khudhair, A., and Arthur, S. (2021). “Aligning BIM and ontology for information retrieve and reasoning in value for money assessment.” Automation in Construction, 124(1), 103565.
Wu, C. K., Wu, P., Wang, J., Jiang, R., Chen, M. C., and Wang, X. Y. (2021). “Ontological knowledge base for concrete bridge rehabilitation project management.” Automation in Construction, 121, 103428.
W3C (World Wide Web Consortium). (2015). “Good Relations.” <https://www.w3.org/wiki/GoodRelations>(Jun. 6, 2022).
Xiao, J., Li, X. D., Zhang, Z. H., and Zhang, J. H. (2018). “Ontology-based knowledge model to support construction noise control in China.” Journal of Construction Engineering and Management, 144(2), 04017103.
Yildiz, A. E., Dikmen, I., Birgonul, M. T., Eroskun, K., and Alten, S. (2014). “A knowledge-based risk mapping tool for cost estimation of international construction projects.” Automation in Construction, 43, 144–155.
Zhong, B. T., Ding, L. Y., Love, P. E. D., and Luo, H. B. (2015). “An ontological approach for technical plan definition and verification in construction.” Automation in Construction, 55, 47–57.

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ICCREM 2022
Pages: 838 - 854

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Published online: Dec 15, 2022

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Zhichao Zhang [email protected]
1Senior Engineer, China Overseas Land and Investment Limited, Shenzhen, China. Email: [email protected]
Huiming Liu [email protected]
2Senior Engineer, China Overseas Land and Investment Limited, Shenzhen, China. Email: [email protected]
3Senior Engineer, China Overseas Land and Investment Limited, Shenzhen, China. Email: [email protected]
4Senior Engineer, China Overseas Land and Investment Limited, Shenzhen, China. Email: [email protected]
Haibo Liu, Ph.D. [email protected]
5China Overseas Land and Investment Limited, Shenzhen, China. Email: [email protected]
Jun Xiao, Ph.D. [email protected]
6China Overseas Land and Investment Limited, Shenzhen, China. Email: [email protected]

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