Developing a Framework for Future Mobile Data Pricing

Abstract

<p><strong>Purpose:</strong> The revenues for mobile data transmission overtook the revenue of voice calls for the first time in 2014 in the USA. It can be observed that demand for mobile data – largely driven by video and cloud - is increasing exponentially, while overall data revenue is rising only moderately. This will lead to insufficient revenues stream to increase investments into mobile networks and ensure quality service. Consequently, hereof network performance will deteriorate sharply. At the heart of the problem is the current global pricing regime of fixed multiple MB/GB bundles, irrespective of time of the day, intensity of usage (e.g. video vs. email) and underlying economic value of the data. A new framework is proposed as to optimize and align network capacity and implicit data value/utility, which is crucial to ensure customer satisfaction and access justice.</p><p><strong>Methodology/Approach:</strong> The fundamental differences in pricing voice and data in voice and/or data centric networks are analysed in detail. Information has been synthesized as to develop insights into the impact of different devises and type of digital traffic for the overall performance of mobile networks. Based hereupon, a new framework for mobile data has been proposed to address the increasing misalignment between network capacity, usage and underlying data value/utility. Initial solutions have been proposed and discussed.</p><p><strong>Findings:</strong> While voice calls are easily quantifiable and are largely predictable in its occurrence and network load implications, mobile data traffic shows very large variations depending on type of traffic. While social media messaging by many customers consumes very little capacity, consumption of video streaming by relatively few customers can lead already to network saturation.</p><p><strong>Research Limitation/implication:</strong> Carriers set prices for a fixed amount of data – irrespective of intensity and time of data traffic - which leads to sharp spiky type of traffic patterns essentially signalling sharp overuse during busy hours coexist with large period of underused times.</p><strong>Originality/Value of paper:</strong> A new framework for proposition building and particularly pricing of mobile data services is provided.