Entry and Subcontracting in Public Procurement Auctions

2015 ◽  
Vol 61 (12) ◽  
pp. 2945-2962 ◽  
Author(s):  
Nicola Branzoli ◽  
Francesco Decarolis
Keyword(s):  
Public Procurement ◽  
Procurement Auctions

scholarly journals Bidders Recommender for Public Procurement Auctions Using Machine Learning: Data Analysis, Algorithm, and Case Study with Tenders from Spain

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Manuel J. García Rodríguez ◽  
Vicente Rodríguez Montequín ◽  
Francisco Ortega Fernández ◽  
Joaquín M. Villanueva Balsera
Keyword(s):  
Machine Learning ◽  
Public Procurement ◽  
Public Information ◽  
Random Forest Classifier ◽  
Procurement Auctions ◽  
Machine Learning Method ◽  
Test Conditions ◽  
A Company ◽  
Learning Data

Recommending the identity of bidders in public procurement auctions (tenders) has a significant impact in many areas of public procurement, but it has not yet been studied in depth. A bidders recommender would be a very beneficial tool because a supplier (company) can search appropriate tenders and, vice versa, a public procurement agency can discover automatically unknown companies which are suitable for its tender. This paper develops a pioneering algorithm to recommend potential bidders using a machine learning method, particularly a random forest classifier. The bidders recommender is described theoretically, so it can be implemented or adapted to any particular situation. It has been successfully validated with a case study: an actual Spanish tender dataset (free public information) which has 102,087 tenders from 2014 to 2020 and a company dataset (nonfree public information) which has 1,353,213 Spanish companies. Quantitative, graphical, and statistical descriptions of both datasets are presented. The results of the case study were satisfactory: the winning bidding company is within the recommended companies group, from 24% to 38% of the tenders, according to different test conditions and scenarios.

Corruption in delegated public procurement auctions

2014 ◽  
Vol 35 ◽  
pp. 122-127 ◽  
Author(s):  
Krishnendu Ghosh Dastidar ◽  
Diganta Mukherjee
Keyword(s):  
Public Procurement ◽  
Procurement Auctions

scholarly journals Design of public procurement auctions: evidence from cleaning contracts

2018 ◽  
Vol 49 (2) ◽  
pp. 398-426 ◽  
Author(s):  
Ari Hyytinen ◽  
Sofia Lundberg ◽  
Otto Toivanen
Keyword(s):  
Public Procurement ◽  
Procurement Auctions

scholarly journals Detecting Bid-Rigging in Public Procurement. A Cluster Analysis Approach

2021 ◽  
Vol 11 (1) ◽  
pp. 13
Author(s):  
Mihail Busu ◽  
Cristian Busu
Keyword(s):  
Cluster Analysis ◽  
Public Procurement ◽  
Nonparametric Tests ◽  
Procurement Auctions ◽  
Statistical Hypothesis ◽  
Limited Participation ◽  
The Public ◽  
Nonparametric Statistical Methods ◽  
Nonparametric Statistical ◽  
Bid Rigging

This paper analyses the public procurement auctions for snow removal contracts to find out whether bid-rigging occurred. Due to the limited participation in the auction processes, detection of anticompetitive agreements was possible. The econometric analysis used in our study supported the findings of a cartel agreement. Cluster analysis, statistical hypothesis, normality and symmetry and nonparametric tests reveal two types of auctions: competitive and noncompetitive bids. The aim of this paper is to analyze the public procurement auctions with nonparametric statistical methods. Our findings are in line with the literature in the field.

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