Abstract
“Net neutrality” often refers to the policy dictating that an Internet service provider (ISP) cannot charge content providers (CPs) for delivering their content to consumers. Many past quantitative models designed to determine whether net neutrality is a good idea have been rather equivocal in their conclusions. Here we propose a very simple two-sided market model, in which the types of the consumers and the CPs are power-law distributed — a kind of distribution known to often arise precisely in connection with Internet-related phenomena. We derive mostly analytical, closed-form results for several regimes: (a) Net neutrality, (b) social optimum, (c) maximum revenue by the ISP, or (d) maximum ISP revenue under quality differentiation. One unexpected conclusion is that (a) and (b) will differ significantly, unless average CP productivity is very high.
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Notes
- 1.
Possibly negative prices: recall that in the first two examples the practice includes subsidies.
- 2.
Power law distributions have been called “the signature of human activity,” even though they also appear in life and the cosmos, and they are easy to confuse with the lognormal distribution.
- 3.
More formally, of types between x and \(x+dx\), etc.
- 4.
This is because \(\frac{1}{2}(\frac{\gamma -2}{\gamma -1}\phi '(\bar{Y}x_0)+\lambda )\bar{X} < \frac{1}{2}(\int _{x_0}^{\infty }\phi '(x\bar{Y})x^{1-\gamma }dx+\lambda \bar{X})\) when \(\phi \) is a fractional power function.
- 5.
Perhaps what is most striking in this figure (especially to somebody trained in approximation algorithms and the price of anarchy) is that, in all three cases and for these parameters and model, neither of the two extreme regimes (revenue maximization and net neutrality) is catastrophically suboptimal in social welfare.
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Acknowledgement
Research results reported in this work are partially supported by the National Natural Science Foundation of China (Grant No. 61632017) and a Project 985 grant of Shanghai Jiao Tong University. This work was done while the authors were visiting the Simons Institute for the Theory of Computing, Berkeley.
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Deng, X., Feng, Z., Papadimitriou, C.H. (2016). Power-Law Distributions in a Two-Sided Market and Net Neutrality. In: Cai, Y., Vetta, A. (eds) Web and Internet Economics. WINE 2016. Lecture Notes in Computer Science(), vol 10123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-54110-4_5
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