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Negotiation Game Model for Big Data Transactions

Given the surge around the research and development of models and tools for big data, businesses continue to improve their implementations to achieve their promised value. This paper proposes and evaluates a price negotiation game model for purchasing big data resources; the model utilizes a network for its structure. The key idea of this model is to consider big data transactions as a multi-player (data owners and consumers) game in which the players have access to imperfect information. The model embodies a deduction problem and proposes a game strategy for price negotiations. The model provides a new approach to evaluate the influences of various factors. We evaluate the influence of reservation prices, information completeness, and platform commission on the profit. The performance of the model is explored using thousands of simulated transactions. The success rate of the transactions, in addition to the rewards of the owners, consumers, and the platform are observed to assess the activity of network.