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On suspicious tracks: Machine-learning based approaches to detect cartels in railway-infrastructure procurement

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  • Wallimann, Hannes
  • Sticher, Silvio

Abstract

In railway infrastructure, construction and maintenance is typically procured using competitive procedures such as auctions. However, these procedures only fulfill their purpose – using (taxpayers’) money efficiently – if bidders do not collude. Employing a unique dataset of the Swiss Federal Railways, we present two methods in order to detect potential collusion: First, we apply machine learning to screen tender databases for suspicious patterns. Second, we establish a novel category-managers’ tool, which allows for sequential and decentralized screening. To the best of our knowledge, our study represents the first attempt to adapt and implement machine-learning-based price screens within the context of a railway-infrastructure market.

Suggested Citation

  • Wallimann, Hannes & Sticher, Silvio, 2023. "On suspicious tracks: Machine-learning based approaches to detect cartels in railway-infrastructure procurement," Transport Policy, Elsevier, vol. 143(C), pages 121-131.
    • Handle: RePEc:eee:trapol:v:143:y:2023:i:c:p:121-131
    DOI: 10.1016/j.tranpol.2023.09.010
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    References listed on IDEAS

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