Public Infrastructure Procurement: Detecting Collusion in Capped First-Priced Auctions

Signor, Regis; Love, Peter E.D.; Oliveira, Acir; Lopes, Alan de Oliveira; Oliveira, Pedro

doi:10.1061/(asce)is.1943-555x.0000543

Cited by 14 publications

(10 citation statements)

References 28 publications

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“…Those methods were explored on several Federal Police's studies and were based on joint behavior analysis of competitors who act to achieve bid-rigging. It was successfully applied to oil-related contracts using Operation Car Wash 1 information (Signor et al, 2019(Signor et al, , 2020a and for infrastructure projects (Signor et al, 2020b) with capped first-price auctions.…”

Section: Related Workmentioning

confidence: 99%

Inferring about fraudulent collusion risk on Brazilian public works contracts in official texts using a Bi-LSTM approach

Lima¹,

Silva

Mendes

et al. 2020

Findings of the Association for Computational Linguistics: EMNLP 2020

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Public works procurements move US$ 10 billion yearly in Brazil and are a preferred field for collusion and fraud. Federal Police and audit agencies investigate collusion (bid-rigging), over-pricing, and delivery fraud in this field and efforts have been employed to early detect fraud and collusion on public works procurements. The current automatic methods of fraud detection use structured data to classification and usually do not involve annotated data. The use of NLP for this kind of application is rare. Our work introduces a new dataset formed by public procurement calls available on Brazilian official journal (Diário Oficial da União), using by 15,132,968 textual entries of which 1,907 are annotated risky entries. Both bottleneck deep neural network and Bi-LSTM shown competitive compared with classical classifiers and achieved better precision (93.0% and 92.4%, respectively), which signs improvements in a criminal fraud investigation.

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Section: Related Workmentioning

confidence: 99%

Inferring about fraudulent collusion risk on Brazilian public works contracts in official texts using a Bi-LSTM approach

Lima¹,

Silva

Mendes

et al. 2020

Findings of the Association for Computational Linguistics: EMNLP 2020

View full text Add to dashboard Cite

show abstract

“…An adjacency matrix of the kfactional community structure is obtained, and the connected part of the adjacency matrix represents the divided kfactional community. In general, the value of k in the CPM faction filtering algorithm is [4,6][45].…”

Section: Community Division Based On the Cpmmentioning

confidence: 99%

“…For example, the United States [1], the Netherlands [2], Japan [3], Italy [4], South Africa [5], and other countries have been battling with and suffering from corruption. Governments of all countries attach great importance to the problem of collusion and adopt a series of policies to prevent collusion (e.g., National Research Council 2011, European Commission 2013, and Australian Government Competition Policy Review 2015) [6]. Not only the national government, other stakeholders have also taken actions to manage and regulate bidding behavior.…”

Section: Introductionmentioning

confidence: 99%

Bidder Network Community Division and Collusion Suspicion Analysis in Chinese Construction Projects

Zhu

Wang

Liang³

et al. 2020

Advances in Civil Engineering

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Bidder collusion seriously undermines the fair competition of the construction project market, and effective identification of collusion behaviors is of vital importance to the implementation of proactive regulation and supervision. In this paper, the data of construction project bidders from 2011 to 2018 are selected in Shaanxi Province, China, and a bidder network of construction projects is constructed. The collusion suspicion of bidders is analyzed from the macro-, meso-, and microlevels. The results show that the bidder network has features as small world at macrolevels, and it is easy for bidders to involve in collusion. The network community formed by construction, supervision, and survey and design bidding enterprises is analyzed at the mesolevel, and the collusion of supervision enterprises is found to have the highest suspicion At the microlevel, the characteristic value judgment and community division are adopted to analyze the collusion suspicion, which is divided into high, medium, and low according to the possibility. Through a comparison with the actual data, it is found that the method proposed in this paper can effectively identify the collusion behavior of construction project bidders. This paper proposes red, yellow, and green warning mechanism and formulates hierarchical accurate management preparedness, which can provide some suggestions to help prevent bidders from colluding.

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“…On the other hand, relevant scholars have found laws by summarizing the characteristics of the collusion behaviors that have occurred. Signoret et al [6] summarized the laws of 187 maximum price auctions and found collusion by comparing with the expected behavior of noncolluding bidders. Kwasnica and Sherstyuk [7] discussed the behavioral rules in multiunit auctions, Imhof et al [8] detected collusion based on the systematic correlation between bids, and David [9] compared the behavioral characteristics of bidding with noncolluding bidders.…”

Section: Introductionmentioning

confidence: 99%

Analysis on the Types and Characteristics of Collusion Behavior of Government Investment Project Tenderees

Nie

Chen

et al. 2022

Complexity

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The classification of collusion behaviors of government-invested project tenderers is one of the important methods to describe the characteristics and laws of collusion behaviors and strengthen the governance of collusion. Firstly, the variables that affect the type of collusion behavior are selected and cluster analysis is carried out on the cases of collusion in government investment project bidding. Then use the social network to mine the types and characteristics of the collusion behavior of the tenderee. Finally, a BP neural network automatic identification model is established to quickly discriminate the types of collusion, which can effectively overcome the subjectivity of traditional methods. As a result, three typical types of collusion of tenderees can be obtained: intervention type, opportunity type, and cooperation type. The study found that the three types of collusion behavior have their own characteristics and laws, and the relationship between the variables that affect the type of collusion behavior is complex and affects each other.

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Public Infrastructure Procurement: Detecting Collusion in Capped First-Priced Auctions

Cited by 14 publications

References 28 publications

Inferring about fraudulent collusion risk on Brazilian public works contracts in official texts using a Bi-LSTM approach

Inferring about fraudulent collusion risk on Brazilian public works contracts in official texts using a Bi-LSTM approach

Bidder Network Community Division and Collusion Suspicion Analysis in Chinese Construction Projects

Analysis on the Types and Characteristics of Collusion Behavior of Government Investment Project Tenderees

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