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Revenue distribution in streaming


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Título :
Revenue distribution in streaming
Autor :
Gonçalves Dosantos, Juan Carlos
Martínez, Ricardo
Sánchez Soriano, Joaquín
Editor :
Elsevier
Departamento:
Departamentos de la UMH::Estadística, Matemáticas e Informática
Fecha de publicación:
2025
URI :
https://hdl.handle.net/11000/40205
Resumen :
The streaming industry has experienced exponential growth over the past decade. Streaming platforms provide subscribers with unlimited access to a diverse range of services, including movies, TV shows, and music, in exchange for a subscription fee. We take an axiomatic approach to the problem of how to share the overall revenue obtained from subscription sales among services or content producers. In doing so, we provide normative justifications for several distribution rules. We formulate several axioms that convey ethical and operational principles. In the first group, we consider properties that guarantee equal and impartial treatment of services and subscribers. In the second group, we introduce requirements designed to safeguard allocation schemes from inconvenient alterations, namely, changes in the units of measurement of inputs, subscription sharing, or group decomposition. Our analysis reveals that different combinations of these axioms define two classes of rules that strike a balance between three focal schemes, each representing distinct perspectives on the egalitarian and proportional principles. To illustrate the practical implications of our theoretical model, we explore its potential application by assessing how various types of content impact the revenues of some of the most well-known Twitch streamers.
Palabras clave/Materias:
revenue distribution
proportional rule
equal division rule
axiom
streaming
Área de conocimiento :
CDU: Ciencias puras y naturales: Matemáticas
CDU: Ciencias sociales: Demografía. Sociología. Estadística: Estadística
CDU: Ciencias sociales: Economía
Tipo de documento :
info:eu-repo/semantics/article
Derechos de acceso:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI :
https://doi.org/10.1016/j.omega.2024.103233
Publicado en:
Omega: The International Journal of Management Science
Aparece en las colecciones:
Artículos - Estadística, Matemáticas e Informática



Creative Commons La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.