Technical Papers
Jul 6, 2022

Simulating Competitive Bidding in Construction Collusive Bidding Cases

Publication: Journal of Management in Engineering
Volume 38, Issue 5

Abstract

Collusive bidding is regarded as one of the most socially harmful, anticompetitive, and illegal practices in the construction sector. Bid-rigging, which is a form of collusion, refers to the process in which several bidders illegally form a consortium to fix the winner of the bid. Bid-rigging, also referred to as collusive tendering, occurs when two or more competitors agree they will not compete genuinely with each other for tenders, allowing one of the cartel members to win the tender. Bid-rigging results in economic harm to the owner that is seeking the bids, and to the public. An analysis of economic harm due to bid-rigging is intended to demonstrate that the realized price in bid-rigging is an overestimate of the price that bids would have fetched in the absence of collusion. However, in civil antitrust litigation concerning bid-rigging, proof of injury-in-fact and damages have often been the most troublesome elements. Thus, simulating competitive bidding is essential in bid-rigging damages estimation, because the amount of overcharge suffered requires an estimate of what the winning bids would have been if true competitive bidding had occurred. However, simulation models for forecasting the damages due to bid-rigging, especially in design–bid–build (DBB) contracts in the construction management literature, are very scarce. In this paper, a statistical simulation model is proposed for predicting the damage due to bid-rigging in DBB contracts, based on decision-making theory. This empirical study suggests that, for projects with rigged bids, the model simulates competitive bids that are close to the actual competitive bidding environment. The model is validated with an actual bid-rigging case collected from the Korean construction industry. The empirical evidence collected in this study on the possible damages due to bid-rigging provides valuable insight into the challenges faced by the construction industry. The study’s result expands upon competitive bidding theory by developing a process to simulate what the optimal bidding strategy would be in the absence of collusion, to predict the damage due to bid-rigging in DBB construction contracts.

Get full access to this article

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

Data Availability Statement

Some or all data, models, or code generated or used in this study (such as cost data from the sample project) are proprietary or confidential in nature, and may only be provided with restrictions (only total cost can be provided).

References

Albright, S. C., and W. L. Winston. 2005. Spreadsheet modeling and applications. Belmont, CA: Thomson.
Ameyaw, E. E., E. Pärn, A. P. C. Chan, D.-G. Owuse-Manu, and A. Darko. 2017. “Corrupt practices in the construction industry: Survey of Ghanaian experience.” J. Manage. Eng. 33 (6): 05017006. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000555.
An, X., H. Li, J. Zuo, O. Ojuri, Z. Wang, and J. Ding. 2018. “Identification and prevention of unbalanced bids using the unascertained model.” J. Constr. Eng. Manage. 144 (11): 05018013. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001563.
Arai, K., I. Ishibashi, and R. Ishii-Ishibashi. 2011. “Research and analysis on bid-rigging mechanisms.” Jpn. World Econ. 23 (1): 1–5. https://doi.org/10.1016/j.japwor.2010.07.001.
Bagies, A., and C. Fortune. 2006. “Bid/ no-bid decision modelling for construction projects.” In Proc., 22nd Annual ARCOM Conf., edited by D. Boyd, 511–521. Birmingham, UK: Association of Researchers in Construction Management.
Bajari, P., and L. Ye. 2003. “Deciding between competition and collusion.” Rev. Econ. Stat. 85 (4): 971–989. https://doi.org/10.1162/003465303772815871.
Ballesteros-Pérez, P., M. C. González-Cruz, A. Cañavate-Grimal, and E. Pellicer. 2013. “Detecting abnormal and collusive bids in capped tendering.” Autom. Constr. 31 (May): 215–229. https://doi.org/10.1016/j.autcon.2012.11.036.
Ballesteros-Pérez, P., M. Skitmore, R. Das, and M. L. del Campo-Hitschfeld. 2015. “Quick abnormal-bid-detection method for construction contract auctions.” J. Constr. Eng. Manage. 141 (7): 04015010. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000978.
Ballesteros-Pérez, P., M. Skitmore, E. Sanz-Ablanedo, and P. Verhoeven. 2019. “Forecasting the number and distribution of new bidders for an upcoming construction auction.” J. Constr. Eng. Manage. 145 (10): 04019056. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001694.
Bartholomew, S. H. 2002. Construction contracting: Business and legal principles. Upper Saddle River, NJ: Pearson Education.
Brinker, L. 2014. “Introducing new weapons in the fight against bid rigging to achieve a more competitive US procurement market.” Public Contract Law J. 43 (3): 547–565.
Carr, P. G. 2005. “Investigation of bid price competition measured through Prebid project estimates, actual bid prices, and number of bidders.” J. Constr. Eng. Manage. 131 (11): 1165–1172. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:11(1165).
Cheng, M. Y., C. C. Hsaiang, H. C. Tsai, and H. L. Do. 2011. “Bidding decision making for construction company using a multi-criteria prospect model.” J. Civ. Eng. Manage. 17 (3): 424–436. https://doi.org/10.3846/13923730.2011.598337.
Chotibhongs, R., and D. Arditi. 2012. “Detection of collusive behavior.” J. Constr. Eng. Manage. 138 (11): 1251–1258. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000542.
Collier, K. 2001. Construction contracts. 3rd ed. Englewood Cliff, NJ: Prentice-Hall.
Deltas, G. 2002. “Determining damages from the operation of bidding rings: An analysis of the post-letting ‘knockout’ sale.” Econ. Theory 19 (2): 243–269. https://doi.org/10.1007/PL00004213.
Erfani, A., K. Zhang, and Q. Cui. 2021. “TAB bid irregularity: Data-driven model and its application.” J. Manage. Eng. 37 (5): 04021055. https://doi.org/10.1061/(ASCE)ME.1943-5479.0000958.
Fayek, A. 1998. “Competitive bidding strategy model and software system for bid preparation.” J. Constr. Eng. Manage. 124 (1): 1–10. https://doi.org/10.1061/(ASCE)0733-9364(1998)124:1(1).
Giosa, P. A. 2018. “Division of public contracts into lots and bid rigging: Can economic theory provide an answer?” Eur. Procure. Public Private Partnership Law Rev. 13 (1): 30–38. https://doi.org/10.21552/epppl/2018/1/6.
Halpin, D. W. 2006. Construction management. 3rd ed. New York: Wiley.
Howard, J. H., and D. Kaserman. 1989. “Proof of damages in construction industry bid-rigging cases.” Antitrust Bull. 34: 359.
Hyari, K. H. 2016. “Handling unbalanced bidding in construction projects: Prevention rather than detection.” J. Constr. Eng. Manage. 142 (2): 04015060. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001045.
Imhof, D. 2018. “Empirical methods for detecting bid-rigging cartels.” Ph.D. dissertation, Dept. of Economics and Finance, Université Bourgogne Franche-Comté.
Ioannou, P. G. 2019. “Friedman’s bidding model: Errors and corrections.” J. Constr. Eng. Manage. 145 (10): 04019058. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001695.
Ioannou, P. G., and S.-S. Leu. 1993. “Average-bid method—Competitive bidding strategy.” J. Constr. Eng. Manage. 119 (1): 131–147. https://doi.org/10.1061/(ASCE)0733-9364(1993)119:1(131).
Jaśkowski, P., and A. Czarnigowska. 2019. “Contractor’s bid pricing strategy: A model with correlation among competitors’ prices.” Open Eng. 9 (1): 159–166. https://doi.org/10.1515/eng-2019-0021.
Jones, R. M. 2003. “Update on proving and pricing inefficiency claims.” Constr. Lawyer 23: 3–11.
Lee, J.-S., W.-R. Kim, and K. Jeong. 2021. “Estimating damages from bid-rigging in the construction industry.” J. Leg. Aff. Dispute Resolut. Eng. Constr. 13 (3): 05021003. https://doi.org/10.1061/(ASCE)LA.1943-4170.0000476.
Maci, M. 2012. “Private enforcement in bid-rigging cases in the European Union.” Eur. Competition J. 8 (1): 211–227. https://doi.org/10.5235/174410512800369973.
Nassar, K. 2007. “Application of data-mining to state transportation agencies’ projects databases.” J. Inf. Technol. Construct. 12 (8): 139–149.
OECD (Organisation for Economic Co-Operation and Development). 2009. Guidelines for fighting bid rigging in public procurement. Paris: OECD.
Park, W. R., and W. B. Chapin. 1992. Construction bidding: Strategic pricing for profit. New York: Wiley.
Ryu, K., and S. Oh. 2010. “Antitrust damage estimation in multiple bid-rigging cases.” J. Appl. Econ. 12 (2): 87–112.
Signor, R., P. E. D. Love, A. T. N. Belarmino, and O. Alfred Olatunji. 2020. “Detection of collusive tenders in infrastructure projects: Learning from Operation Car Wash.” J. Constr. Eng. Manage. 146 (1): 05019015. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001737.
Skitmore, R. M., A. N. Pettitt, and R. McVinish. 2007. “Gates’ bidding model.” J. Constr. Eng. Manage. 133 (11): 855–863. https://doi.org/10.1061/(ASCE)0733-9364(2007)133:11(855).
Sweet, J., and M. M. Schneier. 2004. Legal aspect of architecture, engineering and the construction process. Toronto: Thomson.
Takano, Y., N. Ishii, and M. Muraki. 2014. “A sequential competitive bidding strategy considering inaccurate cost estimates.” Omega 42 (1): 132–140. https://doi.org/10.1016/j.omega.2013.04.004.
Tan, Y., L. Shen, and C. Langston. 2010. “Contractors’ competition strategies in bidding: Hong Kong study.” J. Constr. Eng. Manage. 136 (10): 1069–1077. https://doi.org/10.1061/(ASCE)CO.1943-7862.0000219.
Wang, X., K. Ye, and D. Arditi. 2021a. “Embodied cost of collusive bidding: Evidence from China’s construction industry.” J. Constr. Eng. Manage. 147 (6): 04021037. https://doi.org/10.1061/(ASCE)CO.1943-7862.0002044.
Wang, X., K. Ye, M. Chen, and Z. Yao. 2021b. A conceptual framework for the inclusion of exogenous factors into collusive bidding price decisions.” J. Manage. Eng. 37 (6): 04021071 https://doi.org/10.1061/(ASCE)ME.1943-5479.0000981.
Wu, M.-L., and H.-P. Lo. 2009. “Optimal strategy modeling for price-time biparameter construction bidding.” J. Constr. Eng. Manage. 135 (4): 298–306. https://doi.org/10.1061/(ASCE)0733-9364(2009)135:4(298).
Xinglin, Y., and X. Hefeng. 2013. “Research on bidding methods of national grid construction projects based on Friedman model.” Int. Bus. Manage. 6 (2): 98–104. https://doi.org/10.3968/j.ibm.1923842820130602.1095.
Yuliana, C., R. H. Kartadipura, and S. Taufik. 2016. “Bidding strategy using Friedman model for building construction project in Banjarbaru Indonesia.” J. Civ. Constr. Environ. Eng. 1 (1): 12–17. https://doi.org/10.11648/j.jccee.20160101.12.

Information & Authors

Information

Published In

Go to Journal of Management in Engineering
Journal of Management in Engineering
Volume 38Issue 5September 2022

History

Received: Dec 27, 2021
Accepted: May 9, 2022
Published online: Jul 6, 2022
Published in print: Sep 1, 2022
Discussion open until: Dec 6, 2022

Permissions

Request permissions for this article.

Authors

Affiliations

Jae-Seob Lee [email protected]
Professor, Division Architectural Engineering, Dongguk Univ., 30 Pildong-ro 1 gil, Jung-gu, Seoul 04620, Korea. 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.

Cited by

  • Modeling the Impact of Low-Carbon Procurement on Bidding Dynamics, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5997, 40, 4, (2024).
  • Exploring Corruption Factors Inhibiting Team Decision-Making on Construction Projects, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5873, 40, 5, (2024).
  • Detecting Red-Flag Bidding Patterns in Low-Bid Procurement for Highway Projects with Pattern Mining, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5514, 40, 1, (2024).
  • Impacts of External Environmental Factors on the Collusive Team Scale in Bidding: The Case of China, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5270, 39, 4, (2023).
  • Impact of Altering the Bid Selection Method to Below-Average Method: An Agent-Based Modeling Approach, Journal of Management in Engineering, 10.1061/JMENEA.MEENG-5084, 39, 3, (2023).

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 Article
$35.00
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 Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share