A Taxonomy of Communications Demand

Abstract

Demand forecasts are an essential tool for planning capacity and formulating policy. Traffic estimates are becoming increasingly unreliable, however, as accelerating rates of use and new communications applications invalidate conventional forecasting assumptions. This paper presents an alternative approach to the study of telecommunications demand: build aggregate estimates for demand based on the elasticity of demand for bandwidth. We argue that price elasticity models are necessary to grasp the interaction between Moore-type technological progress and non-linear demand functions. Traditional marketing models are premised on existing or, at best, foreseeable services. But in a period of sustained price declines, applications-based forecasts will be unreliable. Dramatically lower prices can cause fundamental changes in the mix of applications and, hence, the nature of demand. We consider the option of posing demand theoretically in terms of service attributes. Our conclusion is that the positive feedback loop of technology-driven price decreases and high-elasticity demand will quickly make it possible to base forecasts on bandwidth elasticity alone. Industry analysts and policymakers need models of consumer demand applicable under dynamic conditions. We conclude by drawing implications of our demand model for network planning, universal service policies, and the commoditization of communications carriage.