scholarly journals Do Combinatorial Procurement Auctions Lower Cost? - An Empirical Analysis of Public Procurement of Multiple Contracts

2011 ◽  
Author(s):  
Sofia Lundberg ◽  
Anders Lunander
Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-20
Author(s):  
Manuel J. García Rodríguez ◽  
Vicente Rodríguez Montequín ◽  
Francisco Ortega Fernández ◽  
Joaquín M. Villanueva Balsera

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.


2015 ◽  
Vol 17 (4) ◽  
pp. 487-520 ◽  
Author(s):  
Sofia Lundberg ◽  
Per-Olov Marklund ◽  
Elon Strömbäck ◽  
David Sundström

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

2020 ◽  
Vol 12 (3) ◽  
pp. 1261
Author(s):  
Chunling Yu ◽  
Toru Morotomi ◽  
Haiping Yu

Green public procurement (GPP) is a policy tool aiming to achieve environmental protection and resource reservation via public procurement. After decades of adaptation, what promotes and hinders its uptake in public contracting remains difficult to discern. This research explores factors that influence the adoption of green award criteria, covering features of procurement procedures, purchasers, tenderers, and the business sectors through empirical analysis of Probit regression combined with a fixed term method. The data is contract award notices (CAN) from 33 countries in Europe in 2018. Our findings suggest that framework agreements, the medical products sector, the health and social services sector, and the business services sector are negatively correlated with whether a contract is green. On the other hand, the contract value, Government Procurement Agreement (GPA)coverage, joint procurement, competitive dialogue, negotiation with competition (with a call for competition), restricted procedure, transport equipment sector, and food sector can positively correlate with green contracts, or these factors increase the possibility of a contract being green. Explicit explanations on these relations are provided. This research identifies factors relating with and influencing the application of green award criteria in public contracts, which would inform public sectors on efficient resources allocation in terms of increasing green public procurement performance.


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