Consumers' Dynamic Switching Decisions in the Cellular Service Industry

Abstract

This paper develops an empirical framework to analyze consumer's dynamic switching decision in the cellular service industry. It first incorporates the sequential problem of quantity, plan and firm subscription choice in the presence of switching costs into a dynamic structural model, which allows for fully heterogeneous consumers and multiple switching possibilities across networks. The model is estimated using the data set on the number of switching consumers and the evolution of observed plan/firm characteristics over time. Based on the BLP-style estimation methods, we combine a nested technique that uses parametric assumptions with the structural estimation algorithm. The magnitude of switching costs is estimated and it turns out that switching costs vary across networks. A dynamic model with restricted number of switching is likely to underestimate the switching costs. Lower switching costs encourage consumers to switch relatively early. Change in the variety of optional plans and plan characteristics also play a great role in the consumers' switching decision