1 citations · 1 across the 4 of their papers we have counts for
5 papers
Swimming in Dark Water: When Cartels Mimic Competition
David Imhof, Thierry Madiès, Martin Huber
This paper analyzes the internal organization and economic effects of a bid-rigging cartel in the road construction sector of the Swiss canton of Ticino, active from 1999 to 2005.…
Catching Bid-rigging Cartels with Graph Attention Neural Networks
David Imhof, Emanuel W Viklund, Martin Huber
We propose a novel application of graph attention networks (GATs), a type of graph neural network enhanced with attention mechanisms, to develop a deep learning algorithm for detec…
Detecting bid-rigging coalitions in different countries and auction formats
David Imhof, Hannes Wallimann
We propose an original application of screening methods using machine learning to detect collusive groups of firms in procurement auctions. As a methodical innovation, we calculate…
Deep learning for detecting bid rigging: Flagging cartel participants based on convolutional neural networks
Martin Huber, David Imhof
Adding to the literature on the data-driven detection of bid-rigging cartels, we propose a novel approach based on deep learning (a subfield of artificial intelligence) that flags…
A Machine Learning Approach for Flagging Incomplete Bid-rigging Cartels
Hannes Wallimann, David Imhof, Martin Huber
We propose a new method for flagging bid rigging, which is particularly useful for detecting incomplete bid-rigging cartels. Our approach combines screens, i.e. statistics derived…