UC Irvine

Chapter 1 introduces a continuous-time monopoly model that considers a return policy allowing consumers to return purchased products within a specified period. The model shows that an easy return policy, allowing for no-questions-asked returns, reduces consumer surplus compared to a stricter policy that only refunds under specific conditions. This decrease in consumer surplus happens when consumers are not highly price-sensitive. The study also explores how product quality affects the return policy and finds that lower quality products result in longer return periods. Additionally, lower quality products can lead to higher market prices if the value of the defective item is high enough.

In Chapter 2, a duopoly model is developed to study competition between an online seller and a local store seller in the presence of a return policy. The model finds that offering returns after sales increases the sellers' market power. The local store targets consumers with lower utility by offering a shorter return period and a lower price. The study also shows that an increase in the information cost at the local store increases market price dispersion and gives the online store more market share.

Chapter 3 uses economic theory and experiments with AI-based pricing algorithms to analyze the impact of consumer search friction on collusion, market prices, and consumer welfare. The chapter develops an oligopoly model where consumers search sequentially for the best product with advertised prices. The study finds that collusion is easier to sustain with lower search costs. However, increasing search costs can reduce the collusive price, but this does not increase consumer surplus if the collusion sustains. The experiments show that simple reinforcement learning algorithms (Q-learning) can adopt a trigger-price strategy to keep prices above the competitive level in a frictional market.