Game theoretic approach of a novel decision policy for customers based on big data

Shasha Liu, Bingjia Shao (), Yuan Gao (), Su Hu, Yi Li and Weigui Zhou
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Shasha Liu: Chongqing University
Bingjia Shao: Chongqing University
Yuan Gao: Xichang Satellite Launch Center
Su Hu: University of Electronic Science and Technology of China
Yi Li: The High School Affiliated to Renmin University of China
Weigui Zhou: Xichang Satellite Launch Center

Electronic Commerce Research, 2018, vol. 18, issue 2, No 3, 225-240

Abstract: Abstract In recent days, big data based analysis in hotel industry become popular. Merchants are attracting clients using the accurate analysis of historic data and predicting the behavior of possible clients to perform proper marketing strategy. To study the principle of the game between clients and merchants, in this work, we propose a novel two-stage game theoretic approach of decision policy for clients when choosing the suitable hotel to stay among many candidates, the merchants will provide a non-cooperative game strategy to attract the attention of potential clients. Analysis of the non-cooperative game method based on big data has been given. Simulation results indicate that, by using our proposed novel method, the average price for clients to choose a satisfied hotel is reduced and the successful rate of stay is increased for merchants, which will bring the expected income to a higher level because of the sticky phenomena of users.

Keywords: Game theory; Big data; Accurate prediction; Non-cooperative game; Decision policy (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10660-017-9259-6

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