Precificação em orquestradores de informação: maximizando redes estáveis

• Ano de defesa: 2013
• Autor(a) principal: Lustosa, Bernardo Carvalho
• Orientador(a): Albertin, Alberto Luiz
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Palavras-chave em Português: Redes de inovação; Teoria dos jogos; Equilíbrio de Nash; Estabilidade de redes; Efeitos de redes
• Palavras-chave em Inglês: Innovation networks; Game theory; Nash equilibrium; Network stability; Network effects
• Link de acesso: https://hdl.handle.net/10438/11108

In innovation networks based on information exchange, the orchestrating actor, or hub, captures information from the peripherical actors, promotes innovation and then distributes it for the network in the form of added value. Orchestration comprises promoting the network’s stability in order to avoid negative growth rates. The credit and fraud agencies, for example, can be understood as orchestrating hubs, concentrating the historical information of the population generated by their clients and offering products that support decision making. Assuming all the companies of this ecosystem as rational agents, game theory emerges as an appropriate framework for the study of pricing as a mechanism to promote the network’s stability. The present work focuses on the identification of a relationship between the different pricing options that can be proposed by the orchestrating hub and the network’s stability and efficiency. Since the network power is given by the combined strength of its members, the innovation generated is a function of the isolated decision of each peripherical agent on whether to hire the orchestrating hub’s services for the price defined by the latter. Through the definition of a simplified theoretical game in which agents decide whether to connect or not to the network based on the pricing structure defined by the hub, the present study analyzes the equilibrium conditions and concludes that the Nash equilibrium entails the network’s stability. One of the conclusions is that in order to maximize the innovation power of the network, the agents should be charged a price that is proportional to the financial benefit obtained by the innovation generated by the net. The study presents as well a computer simulation of a fictitious market for a numerical demonstration of the observed effects. With these conclusions, the present study fills a gap in the literature on monopolistic orchestrated innovation in terms of the pricing structures of the network connection and its use. It can be used as a basis for decision making both on the supply and the demand sides of the services of the hub.