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电子商务平台价格歧视规制

时间:2022-09-03 来源:未知 编辑:梦想论文 阅读:
As of December 2017, the number of Internet users in China had reached 772 million, with a penetration rate of 55.8%. The revenue of e-commerce platforms in January November 2017 was 218.8 billion yuan, an increase of 43.4% year-on-year [1]. A large number of Internet users have quantified their online behavior into a large amount of data, and big data has become a new way of people's life, work and thinking. As far as e-commerce is concerned, with the support of database service and algorithm technology, the e-commerce platform is gradually improving personalized recommendation service to better meet the needs of users in products and services. E-commerce platforms use advanced data control technology to provide personalized recommendations for users. They track every behavior of buyers on relevant platforms, such as the time the mouse stays on the page, and analyze the correlation and purchase preferences among customers' historical behaviors, consumption records and purchase behaviors, so as to help customers buy products that meet their needs in the shortest time. The e-commerce platform establishes a customer information database. Through data mining, the interest and preference data of customers are intelligently classified and modeled. The system can automatically process and obtain these data. Predict the needs of customers, and carry out one-to-one intelligent marketing to customers [2], meet customer needs, improve customer loyalty, and deploy resources through intelligent analysis of customer needs to maximize resource utilization. For the seller, it reduces costs and increases profit margin; As far as customers are concerned, they can buy goods of the same quality at a low price that traditional transactions can not provide, intuitively obtain a large amount of commodity information, reduce the time and energy of shopping around, and match resources and consumption capacity as much as possible. This is a win-win situation that cannot be realized in traditional trade and can only appear in the era of big data.
 
At the same time, there are many problems in e-commerce. In December 2017, articles about "killing familiarity with big data" were hot in the circle of friends, and e-commerce platforms with dynamic pricing such as "Ctrip", "qunar" and "dangdang.com" were pushed to the forefront for a while. The reason is that there is a phenomenon of "different prices for the same product for the same person". Netizens say that they search for the same product on the same software as old customers, and the pricing of the same product is very different from that of a friend's new account. The price of the same commodity and the same consumption platform varies from person to person. This phenomenon, known as "price discrimination" in economics, has aroused consumers' concern and dissatisfaction. How to identify the price discrimination behavior of network operators, how consumers should safeguard their rights, and how to lift the "curtain" of deepening information asymmetry pulled by big data on e-commerce trading platforms need to be solved urgently. Analyzing and solving the problem of price discrimination in the era of big data is conducive to safeguarding the rights of consumers, alleviating the trust crisis between merchants and customers of e-commerce platforms, guiding rational sales of e-commerce merchants, and promoting the steady development of e-commerce platforms.
 
(1) current situation analysis of online consumer price discrimination
 
In February 2018, it was reported that "master Liao", a Weibo user who often booked a room in a specific hotel through "Ctrip" software, and whose annual price was between 380 yuan and 400 yuan, once learned through the front desk that his price of ordering a room in the off-season was around 300 yuan. After a friend's inquiry, it was indeed 300 yuan, but it was still 380 yuan when he checked it with his own account [3]. Old customers set high prices and new customers charge low prices, which is a widespread phenomenon. Different pricing for different users is actually the concrete implementation of the concept of "price discrimination" in economics.
 
Hidden behind the operation process is that Ctrip company determined that the netizen was very acceptable to set the room price at 380 yuan by collecting the historical consumption behavior of the netizen and the analysis of the hotel room price, and he bought it many times. He was not sensitive to the price, and the acceptable price was 380 yuan to 400 yuan. Based on the operator's pursuit of maximizing profits, Ctrip's pricing system was naturally willing to charge high prices. However, his friend is a new user of this product, and it happens to be in the off-season. In order to establish contacts with customers and attract new users, the pricing system adopts aggressive price discrimination to encourage new users, and sets it at a low price. Price discrimination is a common price strategy in economics. Ctrip accurately distinguishes users and makes differential pricing through the information it has, so as to maximize its profits. This is a new way to implement price discrimination based on cloud computing technology and data mining technology in the era of big data.
 
Theoretically, price discrimination can be divided into three categories, i.e. primary price discrimination, secondary price discrimination and tertiary price discrimination.
 
First level price discrimination refers to charging a different price for each unit of goods, such as dynamic pricing on e-commerce platforms.
 
First level price discrimination requires accurate and complete consumer information. So the information cost is relatively high. In traditional transactions, due to the limitations of information and technology, first-class price discrimination is not common. However, in the Internet era, with the development of big data technology, complete price discrimination has gradually increased and intensified. Ctrip's differentiated pricing based on users' historical consumption behavior is a first-class price discrimination behavior of pricing by accurately predicting users' highest willingness to pay. First class price discrimination is complete price discrimination, which completely deprives consumers of their surplus value and brings huge profits to operators. But it is not conducive to social welfare in general, and it is an illegal act that should be regulated by law.
 
Secondary price discrimination refers to charging different prices for different consumption quantity segments when selling the same commodity, such as "second half price", "group purchase price" and "peak valley electricity".
 
Three level price discrimination refers to charging different prices to different user groups when selling the same commodity, such as "Member treatment".
 
Second level price discrimination and third level price discrimination are incomplete price discrimination. In traditional trade, market information is asymmetric, not only consumers do not know operators, but operators are also unfamiliar with consumers. Price discrimination is usually of these two kinds. Due to the lack of information, the user groups can only be roughly divided, the implementation of price discrimination is limited, and the consumer surplus value obtained is limited. Therefore, although price discrimination has always existed, it has not caused much impact. On the contrary, as a business strategy, it can promote the improvement of social welfare and is a legal act. What this paper wants to discuss is the regulation of first-class price discrimination promoted by information technology in the Internet era.

(2) reasons for rampant online consumer price discrimination in the era of big data
 
2.1 technical reasons
 
The development of big data technology, on the one hand, makes it possible for network operators to realize large-scale price discrimination; On the other hand, it makes it more difficult for consumers to safeguard their rights, makes it difficult to regulate price discrimination, and leads to the proliferation of price discrimination.
 
Network operators have the inherent advantage of getting first-hand initial information and establishing their own databases. Through screening, analyzing and summarizing information, the information is quantified into data. The data are constantly crossed, and the information collected is endless, eliminating the previous information restrictions.
 
Computer algorithms and cloud computing technology can divide consumers in a data ladder, use data to deduce information that affects consumer behavior, grasp consumer psychology, and guide consumers to passively choose goods; On the one hand, accurately predict consumers' maximum purchase intention and maximum price tolerance, so that they are willing to spend the most money. Implement complete price discrimination and reap high profits, so that prices are no longer the sum of costs and profits in line with the principle of supply, but are set by the highest price consumers are willing to pay.
 
The existence of data and the whole cycle of data generation, use, transmission, transformation and destruction involve multiple participants such as government information controllers and information processors. The subject of data use is complex and it is difficult to identify the subject of responsibility.
 
2.2 market reasons
 
The competition in the network market is becoming increasingly fierce, and network operators have gained an advantageous position in the "information market" by some means, creating favorable conditions for the implementation of complete price discrimination. This advantage creates opportunities for the implementation of price discrimination by big data holders, that is, network operators.
 
In terms of big data, a single enterprise relies on its own strength to obtain information at a slow speed and at a high cost. Its dynamic market competition structure may also lose market opportunities due to its slow access to data and information. Therefore, merging with other big data enterprises has become the strategic choice of operators.
 
In recent years, through predatory price discrimination and low-cost competition, enterprises have merged and acquired leading e-commerce companies in various industries to gain a stable position in relevant fields. For example, the merger of Ctrip and qunar.com has given it greater market dominance in the tourism trade industry. The merger of e-commerce enterprises has intensified the large proportion of operators in data information.
 
Price coordination in the context of big data refers to the behavior that operators collect relevant pricing information of competitors through big data technology and both sides reach a unified and tacit understanding on price formulation. There is nothing wrong with the pricing behavior of normal business strategy implementation, but if the data information is deliberately released by competitors, it is to reach a unified pricing between the two sides, thus raising the price and infringing on the rights and interests of consumers. In fact, the two operators reached a "consensus" and used their dominant position in data information to monopolize prices. The price coordination behavior is hidden and difficult to find, which is harmful to the market order and should be regulated by law.
 
2.3 reasons for government supervision
 
 
Macro-control is the main means by which China's price management departments supervise market price behavior, mainly through price hearings, government pricing, supervision and inspection procedures to supervise improper price behavior. The objects of the price hearing are mainly natural monopoly products such as heating and gas supply, and the unfair price discrimination of different single commodities subdivided by electronic trade will not be regulated. And the hearing procedure involves the fairness of the hearing, and lacks the relief procedure of the hearing. Government pricing, because of the flexibility and autonomy of the market, the government and market information are not connected, and pricing is often composed of costs and profits. Rigid government pricing will inhibit free competition in the market, which is not conducive to the development of the market, and it is also unable to regulate, supervise and inspect price behavior. The government's supervision procedure often goes through multi-step procedures out of strict consideration, It is obvious that the diverse price discrimination behaviors under the big data mode will not be hindered by the cumbersome regulatory procedures.
 
(3) suggestions on strengthening the legal regulation of online consumer price discrimination in China
 
3.1 improvement of relevant legislation
 
Consumer rights and interests protection law: consumers' price discrimination in online consumption ultimately requires assistance from the consumer rights and interests protection law, and its relevant provisions should have more explicit provisions. As for the provisions of the right to know, the process of price discrimination of network operators is complex, and the pricing basis involves many dynamic factors, which is obviously not suitable for being included in the scope of the right to know. However, operators can be required to be more proactive about the price of goods and the cost of services, which can enable consumers to obtain more information to jointly judge.
 
With regard to the right to fair trade, there are more explicit provisions on "reasonable price" in online consumption, and there is a general basis for judging it, which can be a percentage limit or a limit on the proportion of consumers' surplus value obtained by operators through price discrimination. In addition, in the process of consumer private relief, the establishment of a system of inversion of the burden of proof, the absolute weakness of consumers in information, and the opacity of operators' operational processes in the data age make it difficult for consumers to obtain evidence.
 
Personal information protection law: the information adoption agreement of "inform consent" in advance can no longer protect the leakage of consumers' personal information. China's personal information protection law (Draft) has been proposed. The provisions on the right to decide information and the right to be forgotten restrict the purpose of data use of information holders, that is, network operators. However, there is no clear provision on the principle of transparency of information use by information holders, and the principle of transparency should be added. The information subject can exercise the right to be forgotten only by announcing which information is collected and shared with whom. And the use of information data in computer technology should be restricted. The information subject has the right to ask for an explanation of the data decision-making before exercising the information decision-making power. Transparency and the obligation to inform are the most important to protect the right to personal information, which can regulate price discrimination in online consumption from the source.
 
3.2 construction of multi party governance mechanism
 
3.2.1 information sharing between government and e-commerce platform
 
Most of China's information resources are in the hands of the government, and the rest of the data information of consumer behavior such as market transactions are occupied by network operators. The government will reach an agreement with the platform to share data information with the government platform, and set up a special price supervision department to be responsible for the collection, analysis and disclosure of information, so that information can be fully displayed on the government platform and all equal subjects can obtain information fairly. Buffer the phenomenon that consumers do not know about infringement and it is difficult to safeguard their rights caused by asymmetric information.
 
3.2.2 refine the regulatory responsibilities of relevant government departments
 
China's price supervision department is a comprehensive department, which integrates the functions of price supervision. Clearly divide the responsibilities of rule making, specific law enforcement, information processing, illegal punishment, etc. in terms of price supervision, price supervision can be divided into specific industrial departments, such as daily chemicals, food and drugs. Strengthen the flexibility of the administrative departments to reflect prices and the reliability of the implementation of specific policies through professionalism.
 
3.3 platform autonomy rules
 
In terms of data information, the platform should change the current default agreement to agree to the use of information. The data sharers should be clearly publicized and options should be set up. Users can choose whether to agree to the sharing of information. The collection of information data and which information should be collected should be publicized, and there should be hints about data use information before each user uses it.
 
Through the setting of the algorithm system, the pricing of the automatic pricing system does not exceed the limit of "reasonable price" stipulated by law.
 
The industry association plays an overall role and sets up a special price supervision organization to conduct dynamic supervision in combination with the cloud computing technology of each platform. We also set up complaint agencies, public feedback platforms and publicity platforms to publicize the platforms subject to punishment, investigate in the first time through public feedback, and set up punishment rules in the industry.

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