We analyze the ongoing price war among major mobile data carriers. Understanding better the underlying mechanisms of the noticed price war in the wireless ecosystem is imperative to develop better techno-economical models for future technologies and to plan possible necessary regulatory actions, e.g. in the case of mergers and acquisitions.
The detailed analysis requires us to consider the goals and requirements of the key stakeholders, including mobile service providers (MSPs) and end-users. In this paper, we analyze this situation by using game-theoretical models under general techno-economical conditions. We consider an oligopoly market where the MSPs aim to attract a pool of undecided users.
The revenue generation of MSPs is usually based on the monthly data plans. Three dominant pricing models are:
(i) flat-rate pricing where each user pays a fixed fee for unlimited data usage,
(ii) volume-based pricing where the fee increases with the data consumption,
(iii) cap-based pricing where the MSP charges a fixed fee up to a point and if the user exceeds this cap, there is an additional charge per unit of volume.
We quantify the cost of MSPs including marginal costs associated with each user, variable costs based on the data consumption per user and fixed costs generated by CAPEX and OPEX. We note that fixed costs include debt payments that may make a MSP risk-averse to high revenue volatility.
Key novelties of our model are the examination of these dominant pricing schemes under the same framework along with the quantification of the variable cost per user and the introduction of a weighted-metric for the users’ MSP selection where we do not consider only the price but also brand attraction. We analyze the outcome of these interactions by introducing a two-stage sequential game instead of a simultaneous game which, for simplicity, is adopted in earlier studies. In the first stage, each MSP announces its data pricing plans, and, in the second stage, each user chooses one of them.
In technical sense we explore the division of market shares and respective revenues under different selection of parameters. In the regulatory domain this is an interesting question as it shows how much there is true differentiation possibilities between MSPs. In this paper we are particularly interested in to study if the lower market share imply lower profits as is often claimed. Another important regulatory and techno-economical question is, if MSPs have motivation to unilaterally update their data pricing schemes. We also touch the question if it is rational for MSPs to offer all three pricing plans simultaneously. Apart of studying these issues, our work is aiming at to provide formal tools and related discussion to understand motivations for different pricing schemes, and asking if there is any motivation for MSPs to collude – and if so how to design markets to be robust against collusion.
