Chapter
Mar 18, 2024

An Accurate-Pricing Estimate Game-Theoretic Model for Determining Price Escalations in Construction Projects during Economic Uncertainties

Publication: Construction Research Congress 2024

ABSTRACT

Economic market uncertainties, such as those experienced during the COVID-19 pandemic, can make determining accurate prices estimate for construction materials a challenging task. While previous research focused on the contractual aspect of this issue by studying price escalation clauses, there is still a gap in the literature when it comes to proposing an accurate pricing model. Thus, this study develops an accurate pricing-estimate game-theoretical model that can efficiently and competitively account for escalations in construction materials prices during uncertain market conditions. First, data on past Producer Price Indexes (PPIs) of different construction materials were collected. Second, the percentage changes in the prices of four common construction materials, including asphalt, aggregates, non-reinforced concrete, and steel reinforcement, were calculated. Third, an algorithmic game theory model that leverages learning from historical bid data was proposed. The findings provided insights on how to account for construction materials price escalation under uncertain market conditions. Overall, this study contributes to the growing body of research related to construction materials price escalation under uncertain market conditions by proposing a practical approach that combines predictive modeling with game theory models.

Get full access to this article

View all available purchase options and get full access to this chapter.

REFERENCES

Aibinu, A. A., and Jagboro, G. O. (2002). The effects of construction delays on project delivery in Nigerian construction industry. International journal of project management, 20(8), 593–599.
Alsharef, A., Banerjee, S., Uddin, S. J., Albert, A., and Jaselskis, E. (2021). Early impacts of the COVID-19 pandemic on the United States construction industry. International journal of environmental research and public health, 18(4), 1559.
Al-Zarrad, M. A., Moynihan, G. P., and Vereen, S. C. (2015). Guideline to apply hedging to mitigate the risk of construction materials price escalation. 5th International/11th Construction Specialty Conference Vancouver British Columbia, 2015.
Assaad, R. H., and El-adaway, I. H. (2021b). Stock prices of architectural, engineering, and construction firms as leading economic indicator: A computational deep-learning econometrics model to complement the architecture billings index. Journal of Architectural Engineering, 27(4), 04021043.
Assaad, R., and El-Adaway, I. H. (2020). Enhancing the knowledge of construction business failure: A social network analysis approach. Journal of construction engineering and management, 146(6), 04020052.
Assaad, R., and El-adaway, I. H. (2021a). Impact of dynamic workforce and workplace variables on the productivity of the construction industry: New gross construction productivity indicator. Journal of Management in Engineering, 37(1), 04020092.
Assaad, R., Ahmed, M. O., El-adaway, I. H., Elsayegh, A., and Siddhardh Nadendla, V. S. (2021). Comparing the impact of learning in bidding decision-making processes using algorithmic game theory. Journal of management in engineering, 37(1), 04020099.
Chao, L. C., and Liaw, S. J. (2019). Fuzzy logic model for determining minimum overheads-cum-markup rate. Journal of Construction Engineering and Management, 145(4), 04019008.
Chen, Y., Chen, S., Hu, C., Jin, L., and Zheng, X. (2020). Novel probabilistic cost estimation model integrating risk allocation and claim in hydropower project. Journal of Construction Engineering and Management, 146(8), 04020092.
Choi, M. S., and Kim, M. H. (2006). A Delphi Study on the Price Escalation Clause in a Construction Contract. Architectural research, 8(1), 69–76.
Crump, D. (1985). Natural Gas Price Escalation Clauses: A Legal and Economic Analysis. Minn. L. Rev., 70, 61.
Dickey, D. A., and Fuller, W. A. (1979). “Distribution of the estimators for autoregressive time series with a unit root.” J. Am. Stat. Assoc. 74 (366): 427–431.
Erev, I., and Roth, A. E. (1998). “Predicting how people play games: Reinforcement learning in experimental games with unique, mixed strategy equilibria.” Am. Eco. Rev. 88(4):848–881.
Faghih, S. A. M., and Kashani, H. (2018). Forecasting construction material prices using vector error correction model. J. construction engineering and management, 144(8), 04018075.
Ghali, H. (2023). Price Prediction Models of Metals Considering International Crises.
Hamilton, E. (2023). The global supply chain consequences of the Russia-Ukraine war. <https://news.ufl.edu/2023/02/russia-ukraine-global-supply-chain/>(accessed April. 26,2023).
Haddad, B. (2022). Construction estimating challenges after COVID 19-the effect of price escalation and material shortages on construction cost and contract management. Industry, Engineering & Conference Management Systems Conference.
Ioannou, P. G. (2019). “Friedman’s bidding model: Errors and corrections.” Journal of Journal of Construction Engineering and Management, 147(4), 04021025.
Kalan, D., and Ozbek, M. E. (2020). Development of a construction project bidding decision-making tool. Practice Periodical on Structural Design and Construction, 25(1), 04019032.
Lau, A. Y. F., Srinivasan, D., and Reindl, T. (2013, April). A reinforcement learning algorithm developed to model GenCo strategic bidding behavior in multidimensional and continuous state and action spaces. In 2013 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL) (pp. 116–123). IEEE.
Li, G., Zhang, G., Chen, C., and Martek, I. (2020). Empirical bid or no bid decision process in international construction projects: Structural equation modeling framework. Journal of Construction Engineering and Management, 146(6), 04020050.
Liew, V. K. S., Chong, T. T. L., and Lim, K. P. (2003). The inadequacy of linear autoregressive model for real exchange rates: empirical evidence from Asian economies. Applied Economics, 35(12), 1387–1392.
Maran, R., Rajendran, S., and Kalidindi, S. (2011). Material cost and escalation clauses in Indian construction contracts. Proceedings of the Institution of Civil Engineers-Construction Materials, 164(2), 95–108.
Malkanthi, S. N., Dharmaratne, P. D., and Galabada, G. H. (2023). Impact of Using Price Fluctuation Related Conditions on Construction Projects. Engineer, 56(01), 43–49.
Naghadehi, M. Z., Benardos, A., Javdan, R., Tavakoli, H., and Rojhani, M. (2016). The probabilistic time and cost risk analysis of a challenging part of an urban tunneling project. Tunnelling and Underground Space Technology, 58, 11–29.
Navon, R. (2005). Automated project performance control of construction projects. Automation in construction, 14(4), 467–476.
Odeyinka, H. A., Lowe, J., and Kaka, A. (2008). An evaluation of risk factors impacting construction cash flow forecast. Journal of Financial Management of Property and Construction.
Oladimeji, O. (2022). Influence of COVID-19 pandemic on local construction firms’ viability. Journal of Engineering, Design and Technology, 20(1), 201–221.
Olaniran, O. J., Love, P. E., Edwards, D., Olatunji, O. A., and Matthews, J. (2015). Cost overruns in hydrocarbon megaprojects: A critical review and implications for research. Project Management Journal, 46(6), 126–138.
Omede, V., and Saidu, I. (2020). Factors Influencing Building Material Price Fluctuations in Abuja, Nigeria.
Puteri Fadzline, T., Juhary, A., and Nazaruddin, I. (2017). Entrepreneurial competencies and networks in the construction industry. International Journal of Applied Engineering Research, 12(23), 13374–13380.
Rastegar, H., Arbab Shirani, B., Mirmohammadi, S. H., and Akhondi Bajegani, E. (2021). Stochastic programming model for bidding price decision in construction projects. Journal of construction engineering and management, 147(4), 04021025.
Somboonpisan, J., and Limsawasd, C. (2021). Environmental weight for bid evaluation to promote sustainability in highway construction projects. Journal of Construction Engineering and Management, 147(4), 04021013.
Spillane, J. P., Oyedele, L. O., Von Meding, J., Konanahalli, A., Jaiyeoba, B. E., and Tijani, I. K. (2011). Challenges of UK/Irish contractors regarding material management and logistics in confined site construction. International Journal of Construction Supply Chain Management, 1(1), 25–42.
The New York Times. (2018). The Real Risks of Trump’s Steel and Aluminum Tariffs. <https://www.nytimes.com/2018/03/01/upshot/trump-tariff-steel-aluminum-explain.html>(accessed April. 26,2023).
Yule, G. U. (1926). Why do we sometimes get nonsense-correlations between Time-Series?--a study in sampling and the nature of time-series. Journal of the royal statistical.
Yan, S., Chen, W., Hu, G., Wu, K., Zhao, K., Fan, W., and Zhou, X. (2022, April). Agent-Based Modeling for generation bidding strategy Using Policy Gradient Algorithm. In 2022 7th Asia Conference on Power and Electrical Engineering (ACPEE) (pp. 398–403). IEEE.

Information & Authors

Information

Published In

Go to Construction Research Congress 2024
Construction Research Congress 2024
Pages: 1170 - 1180

History

Published online: Mar 18, 2024

Permissions

Request permissions for this article.

ASCE Technical Topics:

Authors

Affiliations

Yasser Jezzini [email protected]
1Ph.D. Student, John A. Reif, Jr. Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ. Email: [email protected]
Rayan H. Assaad, Ph.D. [email protected]
2Assistant Professor of Construction and Civil Infrastructure and Founding Director of the Smart Construction and Intelligent Infrastructure Systems (SCIIS) Lab, Dept. of Civil and Environmental Engineering, New Jersey Institute of Technology, Newark, NJ. Email: [email protected]
Islam H. El-adaway, Ph.D. [email protected]
3Hurst-McCarthy Professor of Construction Engineering and Management, Professor of Civil Engineering, and Founding Director of Missouri Consortium for Construction Innovation, Dept. of Civil, Architectural, and Environmental Engineering and Dept. of Engineering Management and Systems Engineering, Missouri Univ. of Science and Technology, Rolla, MO. Email: [email protected]
Mohamad Abdul Nabi [email protected]
4Ph.D. Candidate, Dept. of Civil, Architectural, and Environmental Engineering and Dept. of Engineering Management and Systems Engineering, Missouri Univ. of Science and Technology, Rolla, MO. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$276.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Paper
$35.00
Add to cart
Buy E-book
$276.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share