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

Hannes Wallimann and Silvio Sticher

Papers from arXiv.org

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, we pioneer illustrating the adaption and application of machine-learning based price screens to a railway-infrastructure market.

Date: 2023-04
New Economics Papers: this item is included in nep-big, nep-cmp, nep-com, nep-reg and nep-tre
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Citations: View citations in EconPapers (2)

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