We analyze maximal cartel prices in infinitely-repeated oligopoly models under leniency where fines are linked to illegal gains, as often outlined in existing antitrust regulation, and detection probabilities depend on the degree of collusion. We introduce cartel culture that describes how...

We develop a novel model of price-fee competition in bilateral oligopoly markets with non-expandable infrastructures and costly transportation. The model captures a variety of real market situations and it is the continuous quantity version of the assignment game with indivisible goods on a .xed...

We analyze how leniency affects cartel pricing in an infinitely-repeated oligopoly model where the fine rates are linked to illegal gains and detection probabilities depend on the degree of collusion. A novel aspect of this study is that we focus on the worst possible outcome. We investigate the...

Data-driven AI pricing algorithms in on-line markets collect consumer information and use it in their pricing technologies. In the simplest symmetric Hotellingís model such technologies reduce prices and proÖts. We extend Hotellingís model with vertically di§erentiated products, cost...

Data-driven AI pricing algorithms in on-line markets collect consumer information and use it in their pricing technologies. In the simplest symmetric Hotelling's model such technologies reduce prices and profits. We extend Hotelling's model with vertically differentiated products, cost...

We analyze maximal cartel prices in infnitely-repeated oligopoly models under leniency where fines are linked to illegal gains, as often outlined in existing antitrust regulation, and detection probabilities depend on the degree of collusion. We introduce cartel culture that describes how likely...