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Faculty & Research


Optimal Pricing and Introduction Timing of New Virtual Machines

Working Paper
In the context of subscription-based services, many technologies improve over time, and service providers can provide increasingly powerful service upgrades to their customers but at a launching cost and the expense of the sales of existing products. The authors propose a model of technology upgrades and characterize the optimal pricing and timing of technology introductions for a service provider who price-discriminates among customers based on their upgrade experience in the face of customers who are averse to switching to improved offerings. The authors first characterize optimal discriminatory pricing for the infinite horizon pricing problem with fixed introduction times. The authors reduce the optimal pricing problem to a tractable optimization problem and propose an efficient algorithm for solving it. The authors' algorithm computes optimal discriminatory prices within a fraction of a second even for large problem instances. The authors then show that periodic introduction times, combined with optimal pricing, enjoy optimality guarantees. In particular, the authors first show that, as long as the introduction intervals are constrained to be nonincreasing, it is optimal to have periodic introductions after an initial warm-up phase. When allowing general introduction intervals, the authors show that periodic introduction intervals after some time are optimal in a more restricted sense. Numerical experiments suggest that it is generally optimal to have periodic introductions after an initial warm-up phase. Finally, the authors focus on a setting in which the firm does not price-discriminate based on customers’ experience. The authors show both analytically and numerically that in the nondiscriminatory setting, a simple policy of Myerson (i.e., myopic) pricing and periodic introductions enjoys good performance guarantees.

Associate Professor of Decision Sciences