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

Auteur(s):



Médium: article de revue
Langue(s): en 
Publié dans: Advances in Civil Engineering, , v. 2020
Page(s): 1-14
DOI: 10.1155/2020/6612848
Abstrait:

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.

Copyright: © Jiwei Zhu et al. et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

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  • Reference-ID
    10535953
  • Publié(e) le:
    01.01.2021
  • Modifié(e) le:
    19.02.2021