Preventing competition using side payments: when non-neutrality creates barriers to entry

Network neutrality is often advocated by content providers, stressing that side payments to Internet Service Providers would hinder innovation. However, we also observe some content providers actually paying those fees. This paper intends to explain such behaviors through economic modeling, illustrating how side payments can be a way for an incumbent content provider to prevent new competitors from entering the market. We investigate the conditions under which the incumbent can benefit from such a barrier-to-entry, and the consequences of that strategic behavior on the other actors: content providers, users, and the Internet Service Provider. We also describe how the Nash bargaining solution concept can be used to determine the side payment.     

Big content providers weighing on non-neutrality?

There is a trend for big content providers such as Netflix and YouTube to give grades to Internet Service Providers (ISPs), to incentivize those ISPs to improve at least the quality offered to their service. We design in this paper a model analyzing ISPs’ optimal allocation strategies in a competitive context and in front of quality-sensitive users. We show that the optimal strategy is non-neutral, that is, it does not allocate bandwidth proportionally to the traffic share of content providers. On the other hand, we show that non-neutrality does not benefit ISPs but is surprisingly favorable to the perceived quality for users.

     

The Progressive Second Price Mechanism in a Stochastic Environment

We consider in this paper an auction-based pricing scheme recently introduced by Lazar and Semret to allocate bandwidth among users. This mechanism, called Progressive Second Price, was studied using tools from noncooperative game theory, for a fixed set of players (i.e., users). We compare here the results obtained in that case with the more realistic situation when players randomly enter or leave the game. We assume that they enter according to a Poisson process, and leave it after an exponentially distributed sojourn time. We show that this stochastic assumption cannot be skipped since it can lead to very different results.     

Consumers’ preference modeling to price bundle offers in the telecommunications industry: a game with competition among operators

Network operators are merging their services, such as fixed or wireless telephony, internet or television, into single offers, called bundles. It is essential to understand consumers’ preferences to define the most profitable bundles, with their associated prices, especially in the fierce competitive current market. We start by defining a random linear utility model and then, analyze the competition between an integrated operator and new entrants proposing substitutable services. Each operator ignores the consumers’ reservation prices for his offers and has to deal with uncertainties about the marketing strategies of competitors, due to potential different size and cost structure. A two-level game is introduced and solved by backward induction. In the second level, the operators determine their optimal offer prices for each possible combination of marketing strategies while the consumers select their most profitable purchasing processes; the natural framework is that of Bayesian game theory. Finally at the top level, knowing the outcome of the other level, the operators identify which marketing strategy to use between market share expansion, segment targeting or multi-level price discrimination, to maximize their expected utilities conditionally to their private informations.