Estimating potential losses of the client in public procurement in case of collusion utilizing a MLP neural networks

Hubert Anysz,

Andrzej Foremny,

Janusz Kulejewski

Abstrakt

There are two types of collusion which can harm Clients. This paper proposes two methods of detecting collusion’s and estimation a clients’ potential losses. The first is based on officially recommended factors for collusion detecting. The second one utilizes MLP artificial neural networks. Results are compared and discussed.

Słowa kluczowe: collusion MLP artificial neural networks public procurements
References

Urząd Ochrony Konkurencji i Konsumentów, Zmowy przetargowe, Warszawa 2012.

The Organisation for Economic Co-operation and Development (OECD), Detecting bid rigging in public procurement.

European Commision, Proposal for a Directive of the European Parliament and of the Councilon certain rules governing actions for damages under national law for infringements ofthe competition law provisions of the Member States and of the European Union, Strasbourg, 11.06.2013.

European Commision, Commission staff working document practical guide quantifying harm in actions for damages based on breaches of article 101 or 102 of the treaty on the functioning of the European Union accompanying the communication from the commission on quantifying harm in actions for damages based on breaches of Article 101 or 102 of the Treaty on the Functioning of the European Union, Strasbourg, 11.6.2013.

Porter R.H., Zona J.D., Detection of bid rigging in procurement auctions, Journal of Political Economy, Vol. 101, No. 3, 1993.

Zona, Douglas J., Bid-Rigging and the Competitive Bidding Process: Theory and Evidence. Ph.D. Dissertation, State University, New York 1986.

Baldwin M.R., Collusion at forest timber sales, Journal of Political Economy, Vol. 105, No. 4, 1997, 657-699.

Howard, J.H., Kaserman D.L., Proof of Damages in Construction Industry Bid-Rigging Cases, Antitrust Bulletin, 34, 1989, 359-393.

Nelson J.P., Comparative Antitrust Damages in Bid-Rigging Cases: Some Find-ings from a Used Car Auction, The Antitrust Bulletin, 38, 1993, 369-394.

McMillan J., Dango: Japan’s Price Fixing Conspiracies, Economics andPolitics, 3, 1991, 201-218.

Pesendorfer M., A study of collusion in first price auctions, Review of Economies Studies Limited 2000.

Tadeusiewicz R., Elementarne wprowadzenie do techniki sieci neuronowych z przykładowymi programami, Akademicka Oficyna Wydawnicza PLJ, Warsaw 1998.

Osowski S., Sieci neuronowe do przetwarzania informacji, Oficyna Wydawnicza Politechniki Warszawskiej, Warsaw 2006.

Zieliński J.S., Inteligentne systemy w zarządzaniu, Teoria i praktyka, Wydawnictwo Naukowe PWN, Warszawa 2000.

Computer program for Artificial Neural Network downloaded from Angshuman Saha (http://web.archive.org/web/20091026214344/http://www.geocities.com/adotsaha/index.html, accessed January 2014).