Artificial Intellingence and Algorithmic Price Collusion in Two-sided Markets
Cristian Chica, Yinglong Guo and Gilad Lerman
(Submitted)
PDF (2024)
Increased network externalities significantly enhance collusion, suggesting AI algorithms exploit them to maximize profits.
Higher user heterogeneity or greater utility from outside options generally reduce collusion, while higher discount rates increase it. Tacit collusion remains feasible even at low discount rates.
Dynamic Competition for Customer Memberships
Cristian Chica, Julian Jimenez-Cardenas and Jorge Tamayo
Journal of Economics & Management Strategy, 34, 525-556 (2025).
https://doi.org/10.1111/jems.12605
PDF Working Paper (2024) Codes: Subgames.nb Limits.nb Old Draft: HBS Working Paper (2021)
If firms can choose between long- and short-term memberships, the latter are offered in equilibrium. This result is robust to various extensions, including switching coupons or discounts, naive consumers, sunk costs, and asymmetric differentiation parameters.
Firms are indifferent between long- and short-term memberships only when the customer's switching coupon or discount is high relative to the transportation cost.
Competition and Collusion in Two-Sided Markets with an Outside Option
Cristian Chica, Yinglong Guo and Gilad Lerman
R&R International Journal of Industrial Organization
PDF (2023)
We introduce pricing formulas for competition and collusion models of two-sided markets with an outside option.
Comparing collusion to competition, we find that in cases of small cross-side externalities, collusion results in decreased normalized net deterministic utilities, reduced market participation and increased price, on both sides of the market.
Exclusive Dealing and Entry by Competing Two-Sided Platforms
Cristian Chica, Kenneth Chuk and Jorge Tamayo
R&R International Journal of Industrial Organization
HBS Working Paper (2021) New Draft Coming Soon
The introduction of non-exclusive contracts in addition to exclusive contracts softens the competition for content providers between platforms, as they have more tools to extract content providers’ surplus.
Cristian Chica, Fernando Morales, Carlos Osorio, Daniel Cabarcas (2025). A Big Data Based Method for Pass Rates Optimization in Mathematics University Lower Division Courses, SN COMPUT. SCI. 6, 330 (2025). https://doi.org/10.1007/s42979-025-03809-5
Mery Tamayo, Cristian Chica and Gustavo Canavire (2020). "Analysis of the offshoring network: Empirical evidence of the implied comparative advantage in offshoring", The Journal of International Trade & Economic Development.
(2020) Some Aspects of the Obstacle Problem, Universidad Nacional de Colombia Sede Medellín
Advisor: Carlos Augusto Vélez López. Co-Advisor: Luis Felipe Duque Álvarez.