法学院知识库

The rapid change of the Internet and the innovative development of artificial intelligence technologies such as big data and cloud computing have promoted the vigorous rise of the digital economy, and the traditional economic field has been gradually eroded by the digital economy. The price discrimination behavior under the background of big data is a product of the rapid change and melting of data technology and market economic activities, derived from "big data killing", and is currently widely used in various fields such as online shopping, transportation, and online tourism. The field of big data naturally has monopolies, and price discrimination behavior implemented by operators based on big data and algorithms may not only expand output and improve market allocation efficiency, but also cause consumer damage and linkage with first line damage, disrupt market competition order, and other risks. The report of the 20th National Congress of the Communist Party of China pointed out the need to strengthen anti-monopoly and anti unfair competition. As a tool to promote market competition and protect consumer rights, it is necessary and legitimate to regulate price discrimination behavior in the context of big data. Therefore, within the existing framework of anti-monopoly laws, competition analysis and legal justification should be conducted on big data price discrimination behavior.

This article analyzes the mechanism and behavioral characteristics of price discrimination in the context of big data, defines the behavior of price discrimination in big data, and analyzes how such behavior can bring competitive damage such as disrupting market fair competition order and weakening innovation driving force. It traces the basic theory of anti-monopoly law and clarifies the necessity of regulating anti-monopoly law. Further summarizing the current situation and practical cases of China's system, drawing on the American model based on civil rights protection and the EU model focusing on personal data empowerment, this study attempts to explore the problems and optimization paths of anti-monopoly law regulation of price discrimination behavior in the context of big data. Firstly, in terms of market definition, the digital economy competition strategy and free behavior model make it difficult to ensure the accuracy of traditional market definition methods. To this end, relevant market definition methods should be improved, gradually shifting from price factors to non price factors, using multi factor judgment methods for demand substitution analysis, and innovating the SSNIP testing method based on transfer costs. Secondly, in response to the weakening of market share and the strengthening of market barriers in the context of big data, factors for determining market dominance should be transformed, and the consideration of data barriers should be strengthened. Furthermore, it