Campuses:

Revenue Management and Pricing with Strategic (Forward-looking) Customers

Wednesday, December 5, 2018 - 3:00pm - 4:00pm
Lind 305
Yiwei Chen (University of Cincinnati)
We study a canonical revenue management problem wherein a monopolist seller seeks to maximize revenue from selling a fixed inventory of a product to customers who arrive over time. We assume that customers are forward-looking and rationally strategize the timing of their purchases. We allow customer delay disutilities to be heterogeneous and possibly correlated with valuations.
Chen et al. (2018) show that the so-called fixed price policy is asymptotically optimal in the high-volume regime where both the seller's initial inventory and the length of the selling horizon are proportionally scaled. Specifically, the revenue loss of the fixed price policy is O(k^{1/2}), where k is the system's scaling parameter.
Based on Chen et al. (2018), Chen and Jasin (2018) propose a novel real-time pricing policy. This policy repeatedly updates the fixed price policy in Chen et al. (2018) by taking into account the volatility of the historic sales. We force the price process under this policy to be non-decreasing over time. Therefore, our policy incentivizes strategic customers to behave myopically. We show that if the seller updates the price for only a single time, then the revenue loss of our policy can be arbitrarily close to O(k^{1/3} ln k). If the seller updates the prices with a frequency O(ln k/ ln ln k), then the revenue loss of our policy can be arbitrarily close to O((ln k)^3).