Research On The Anti-monopoly Regulation Of Abusing Algorithm Personalized Pricing From The Perspective Of American Law

With the advent of the era of big data,the platform economy has become a mainstream digital economy model.Especially since the outbreak of the new crown epidemic,many offline transactions have been hindered and restricted,while the online platform economy has developed rapidly.However,there are also many problems in the platform economy.Among them,the behavior of platforms using algorithms to implement personalized pricing for consumers is considered to be a manifestation of platform companies having a market monopoly position and infringing on consumers’ rights,and this behavior has also caused widespread social concerns.In this regard,my country has promulgated the Anti-Monopoly Guidelines of the Anti-Monopoly Committee of the State Council on Platform Economy which stipulates and explains new issues in the platform economy,but it is not platform operators who implement the guidelines in the Guidelines.The actions listed are abuses of market dominance.Therefore,how to determine the behavior of platform companies in specific cases and how to solve the real personalized pricing problem is very important.As one of the more advanced countries in the development of the platform economy,the United States started early in the research on the role of anti-monopoly law in the platform economy,and has rich theoretical and practical experience in regulating algorithmic personalized pricing behavior.Therefore,by clarifying the nature and logic of algorithmic personalized pricing,combined with the experience in regulating algorithmic personalized behavior in the United States,this paper provides a solution to the algorithmic personalized pricing implemented by platform companies in my country.This article first introduces the topic through a case and draws out the issues to be discussed in this article through the analysis of the case of SC Innovations,Inc.v.Uber Techs.Then,the algorithm personalized pricing is studied through five parts,in order to provide a reference for our country to better solve the algorithm personalized pricing problem.The first part shows the dilemma of regulating algorithmic personalized pricing:because the nature and connotation of algorithmic personalized pricing are not clear,the attitude of antimonopoly law to regulating this behavior is also ambiguous,which leads to the application of antimonopoly law in the application of Some problems occurred during the process.Secondly,algorithmic personalized pricing involves multiple values.When identifying relevant economic behaviors,there are also correlations and conflicts between various values.It is precise because when there is a conflict between values,there is no corresponding rank relationship,so the principle of case analysis is often adopted,which leads to the randomness of illegal knowledge.The second part is the monopoly evaluation of algorithmic personalized pricing:first,it analyzes the concept of algorithmic personalized pricing and its internal technical logic.Pricing.Secondly,it analyzes the nature of algorithmic personalized pricing and points out that it should be second-degree price discrimination or third-degree price discrimination,not the first-degree price discrimination advocated by some scholars.Finally,the monopoly value of algorithmic personalized pricing is analyzed,and it is believed that it has both negative and positive effects.The third part is the identification strategy of the anti-monopoly law to regulate algorithmic personalized pricing:because the behavior of platform companies to implement algorithmic personalized pricing conforms to the appearance of differential treatment in the anti-monopoly law to regulate the abuse of market dominance Behavior identification logic to regulate algorithmic personalized pricing.This chapter uses this logic to analyze the basic identification principles of algorithmic personalized pricing,the identification of monopoly behavior,and the identification of damage effects.The fourth part analyzes the defense reasons for the anti-monopoly law to regulate algorithmic personalized pricing:the public generally believes that personalized pricing is a violation of consumer rights and a challenge to fair competition in the market.However,we should also see the other side of this behavior:this behavior not only does not infringe on fair value but instead achieves a kind of substantial equality;secondly,algorithm-based personalized pricing also conforms to traditional pricing rules,which satisfies platform companies’ comprehensive data requirements.In addition,algorithmic personalized pricing is a normal business behavior for companies to deal with competition,and its purpose is to maintain existing users while expanding new users,preventing competing companies from implementing low-price strategies to plunder their users.The fifth part is to summarize the enlightenment to our country by sorting out the behavior of algorithmic personalized pricing in the US anti-monopoly law:first,define the concept and connotation of the behavior through the type analysis of algorithmic personalized pricing;The dynamic analysis principle of algorithmic personalized pricing is used to identify the behavior;finally,the identification framework for identifying algorithmic personalized pricing behavior is analyzed,and it is believed that the principle of proportionality should be used as an analysis tool,and on the basis of balancing multiple values.conduct comprehensive consideration.The innovations of this paper are:first,to correctly understand the personalized pricing behavior of algorithms,from the perspectives of technical logic,essence,and type of research,to conduct rational research on the personalized pricing behavior of algorithms regulated by anti-monopoly laws;second,to use Economic analysis and proportionality principle analysis,combined with the existing practice standards for the regulation of abuse of dominant market position,solve the shortcomings of randomness and unpredictability in case-by-case specific analysis,and build a general identification standard for personalized pricing of anti-monopoly laws and regulations.