Detection of Collusive Tenders in Infrastructure Projects: Learning from Operation Car Wash
Article
Article Title | Detection of Collusive Tenders in Infrastructure Projects: Learning from Operation Car Wash |
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ERA Journal ID | 40479 |
Article Category | Article |
Authors | Signor, Regis (Author), Love, Peter E. D. (Author), Belarmino, Alexanders T. N. (Author) and Olatunji, Oluwole Alfred (Author) |
Journal Title | Journal of Construction Engineering and Management |
Journal Citation | 146 (1), pp. 1-10 |
Article Number | 05019015 |
Number of Pages | 10 |
Year | 2020 |
Publisher | American Society of Civil Engineers |
Place of Publication | United States |
ISSN | 0733-9364 |
1943-7862 | |
Digital Object Identifier (DOI) | https://doi.org/10.1061/(ASCE)CO.1943-7862.0001737 |
Web Address (URL) | https://ascelibrary.org/doi/10.1061/%28ASCE%29CO.1943-7862.0001737 |
Abstract | Procurement practices are often characterized by competitive tendering. The overarching purpose of this is to ingrain transparency, probity, and value for money into the processes of acquiring goods and services. When tenderers collude and clients are unable to detect them, bids will become uncompetitive. Yet, there have been a limited number of effective practical tools and methods developed that can be used by procurement authorities, controllers, and public officials to detect collusive tendering. Using data obtained from the Brazilian Federal Police and their ongoing criminal investigation titled Operation Car Wash, a robust and practical probabilistic method is developed. The main findings were that the method was able to accurately identify (81%–96%) the occurrence of collusion during a sealed tendering process. Conclusions are drawn from the lessons learned from the forensic investigations, indicating that the approach presented for detecting collusive behavior during tendering is grounded in reality. This paper presents a new way to utilize statistics and probability to identify the presence of and control collusion in public- and private-sector tendering. |
Keywords | Brazil; Corruption; Collusion; Public procurement; Sealed tender |
ANZSRC Field of Research 2020 | 330299. Building not elsewhere classified |
330207. Quantity surveying | |
330203. Building industry studies | |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Federal Police of Brazil |
Curtin University | |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q73yz/detection-of-collusive-tenders-in-infrastructure-projects-learning-from-operation-car-wash
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