Structural models for nonlinear pricing schemes
Nonlinear pricing schemes are present in many service industries. However, there is relatively little empirical research that models customers' choices of service options and their consumption decisions in the presence of such nonlinear pricing schemes. In this dissertation, we contribute by structurally modeling the impact of nonlinear pricing schemes employed by services on customers' choice of service options, their consumption patterns and their decision to stay or defect. We focus on the wireless industry.
Within the wireless industry, pricing schemes are typically characterized by an access fee, included free minutes and a per-minute marginal price for any consumption above the free minutes. Such pricing schemes are termed increasing block as the applicable marginal price increases with consumption. While this dissertation focuses on the wireless industry, increasing block schemes are used by other services and the modeling framework of this dissertation can be adapted to these contexts.
In the first part of the dissertation, we develop a structural model that incorporates the nonlinearity of the pricing scheme. This model gives several substantive results on how past consumption dynamics impact current consumer decisions. For instance, past under-utilization of free minutes either increases current consumption or influences customers to downgrade plans. We also use policy experiments to simulate the effects of price changes on plan switching and customer defection and link these changes to Customer Lifetime Value (CLV). We find that changes in access price have an overall greater impact on CLV as compared to that from changes in marginal prices. In addition, changes in access prices have greater impact on the CLV of “light users” while changes in marginal prices have a bigger influence on the long-term value of “heavy users”.
In the second part of the dissertation, we extend the structural model to incorporate consumer learning. In the current context, there can be two forms of consumer uncertainty. First, consumers can be uncertain about the benefits associated with different service options (for instance, customer service) and can learn more about these benefits after choosing a plan. We call this quality learning. Second, consumers can be uncertain about their consumption of minutes and learn about its distribution after observing their monthly usage of minutes. This type of learning is termed as quantity learning. We develop a structural model that incorporates these dual forms of uncertainty within a nonlinear pricing setting.
The results from this model gives insights about the effect of consumers' uncertainty on their consumption decisions. The results show that quantity learning is more important than quality learning. Policy experiments conducted to investigate the effects of changes in price and quality also give several interesting results. We find that “light users” are most sensitive to changes in quality and they respond to a decrease in quality by churning. Further, we find that the negative effects of a price increase can be offset by an increase in quality. Specifically, we estimate that a 3.3% increase in quality can nullify the effects of a 10% increase in access fee.
The insights gleaned from this dissertation will be useful for managers to understand the impact of nonlinear pricing schemes on consumers' decisions, particularly in the context of consumer uncertainty.