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Prioritization vs zero-rating: Discrimination on the internet.

ABSTRACT: 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.

SUBMITTER: Gautier A

PROVIDER: S-EPMC7495184 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Prioritization vs zero-rating: Discrimination on the internet.

Gautier Axel A Somogyi Robert R

International journal of industrial organization 20200917

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 ...[more]

PMID: 32958970

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Project description:The complement system is part of the innate immune system and plays an important role in the host defense against infectious pathogens. One of the main effects is the opsonization of foreign invaders and subsequent uptake by phagocytosis. Due to the continuous default basal level of active complement molecules, a tight regulation is required to protect the body's own cells (self cells) from opsonization and from complement damage. A major complement regulator is Factor H, which is recruited from the fluid phase and attaches to cell surfaces where it effectively controls complement activation. Besides self cells, pathogens also have the ability to bind Factor H; they can thus escape opsonization and phagocytosis causing severe infections. In order to advance our understanding of the opsonization process at a quantitative level, we developed a mathematical model for the dynamics of the complement system-termed DynaCoSys model-that is based on ordinary differential equations for cell surface-bound molecules and on partial differential equations for concentration profiles of the fluid phase molecules in the environment of cells. This hybrid differential equation approach allows to model the complement cascade focusing on the role of active C3b in the fluid phase and on the cell surface as well as on its inactivation on the cell surface. The DynaCoSys model enables us to quantitatively predict the conditions under which Factor H mediated complement evasion occurs. Furthermore, investigating the quantitative impact of model parameters by a sensitivity analysis, we identify the driving processes of complement activation and regulation in both the self and non-self regime. The two regimes are defined by a critical Factor H concentration on the cell surface and we use the model to investigate the differential impact of complement model parameters on this threshold value. The dynamic modeling on the surface of pathogens are further relevant to understand pathophysiological situations where Factor H mutants and defective Factor H binding to target surfaces results in pathophysiology such as renal and retinal disease. In the future, this DynaCoSys model will be extended to also enable evaluating treatment strategies of complement-related diseases.

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Prioritization vs zero-rating: Discrimination on the internet.

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Prioritization vs zero-rating: Discrimination on the internet.

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