Platform Revenue Strategy Selection Considering Consumer Group Data Privacy Regulation

Xudong Lin, Shuilin Liu, Xiaoli Huang, Hanyang Luo and Sumin Yu
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Xudong Lin: Institute of Big Data Intelligent Management and Decision, College of Management, Shenzhen University, Shenzhen 518060, China
Shuilin Liu: College of Management, Shenzhen University, Shenzhen 518060, China
Xiaoli Huang: College of Management, Shenzhen University, Shenzhen 518060, China
Hanyang Luo: Institute of Big Data Intelligent Management and Decision, College of Management, Shenzhen University, Shenzhen 518060, China
Sumin Yu: Institute of Big Data Intelligent Management and Decision, College of Management, Shenzhen University, Shenzhen 518060, China

Mathematics, 2021, vol. 9, issue 22, 1-24

Abstract: In the era of big data, consumer group privacy has become an important source of revenue for the digital platform. Considering the situation that the platform collects consumer group data privacy to generate business revenue, we explore how the service matching level and commission rate affect the platform revenue, social welfare, and seller benefits. Based on the theory of group privacy, the three-party equilibrium evolution is solved by constructing a sequential game model including platform, seller, and consumer alliance. It is found that when the service matching level of the platform is greater than the threshold value, there are two main situations: on the one hand, if using the data privacy of a consumer group is subject to market regulation, the platform will set a high commission rate and service matching level in order to maximize profit. However, social welfare and seller’s business benefit both reach a minimum in this case, and the three-party game cannot attain equilibrium. On the other hand, when the market governor relaxes the platform’s regulation on the use of consumer group privacy data and data revenue efficiency is high enough, the platform can maximize the revenue by increasing the service matching level and reducing the commission rate. The optimal commission rate depends on the data revenue efficiency of the platform. Moreover, when the platform sets the highest commission rate and the service matching level is at a medium level, a stable partial equilibrium among the three-party will be achieved. These conclusions can give some insights into platform’s business model choice decision.

Keywords: group privacy data; service matching level; platform revenue strategy; data regulation (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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