
This paper analyzes two business practices on the mobile internet market, paid prioritization and zero-rating. These practices allow the internet service provider to discriminate different content types. With prioritization, the ISP delivers content at different speeds; with zero-rating, the ISP charges different prices. In recent years these practices have attracted considerable media attention and regulatory interest. When the asymmetry between content providers is limited, in particular with regard to their ability to attract traffic or to monetize it, we first show that the ISP can extract more surplus from consumers by privileging the relatively weaker content and restoring symmetry between content providers. Next, we show that the ISP chooses prioritization when traffic is highly valuable for content providers and congestion is severe, and zero-rating in all other cases. Finally, we find that a policy banning prioritization can lead to zero-rating and a reduction in consumer surplus.
Article, Microéconomie, Zero-rating;, D, sponsored data, data ccap, Microeconomics, Data Cap;, data cap, Sponsored Data;, L51, Sciences économiques & de gestion, paid prioritization, Net Neutrality; Paid Prioritization; Zero-rating; Sponsored Data; Data Cap; Congestion, L12, Business & economic sciences, ddc:330, L96, congestion, Paid Prioritization;, Net Neutrality;, zero-rating, net neutrality, Congestion, D21
Article, Microéconomie, Zero-rating;, D, sponsored data, data ccap, Microeconomics, Data Cap;, data cap, Sponsored Data;, L51, Sciences économiques & de gestion, paid prioritization, Net Neutrality; Paid Prioritization; Zero-rating; Sponsored Data; Data Cap; Congestion, L12, Business & economic sciences, ddc:330, L96, congestion, Paid Prioritization;, Net Neutrality;, zero-rating, net neutrality, Congestion, D21
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| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
