Pricing Algorithm

Pricing algorithms are computational methods designed to optimize price setting in various contexts, aiming to maximize revenue or profit while considering factors like demand, competition, and operational constraints. Current research emphasizes the potential for unintended consequences, such as algorithmic collusion leading to supra-competitive pricing, even without explicit communication or malicious intent, and investigates the role of different algorithm architectures (e.g., reinforcement learning) and recommender systems in shaping market outcomes. This field is significant due to its widespread application in e-commerce, ride-sharing, and other two-sided markets, with ongoing research focusing on improving algorithm efficiency, mitigating risks of collusion, and ensuring fair and transparent pricing practices.