The Effects of Autoscaling in Cloud Computing - Fazli, Amir; Sayedi, Amin; Shulman, Jeffrey D. (Management Science, 2018)
Web-based firms often rely on cloud-based computational resources to serve customers, but the number of customers they will serve is rarely known at the time of product launch. A recent innovation in cloud computing, known as autoscaling, allows companies to automatically scale their computational load up or down to match customer demand. We build a game theory model to examine how autoscaling will affect firms’ decisions to enter a new market and the resulting equilibrium prices, profitability, and consumer surplus. The model produces novel results depending on the likelihood of a firm’s success in the new market, differentiation among potential entrants, and the cost of computational capacity. For instance, in contrast to previous capacity commitment models with demand certainty, we show that autoscaling can mitigate price competition if the likelihood of a firm’s success in the market is moderate and the cost of capacity is sufficiently low. This is because without autoscaling, the firms’ uncertainty about demand would lead to excessive computational capacities and thus aggressive price competition. We also find that when the likelihood of success is sufficiently high, autoscaling facilitates entry for one firm yet deters a second firm from simultaneously entering the market. The online appendix is available at https://doi.org/10.1287/mnsc.2017.2891 . This paper was accepted by Juanjuan Zhang, marketing.