[Chengze Observation · Platform Economy 40 Evaluation 37] Shen Yan et al.: Challenge and response of data circulation

Zhongxin Jingwei September 28th. Question: Challenge and response of data circulation

Author Shen Yan, Professor of Peking University National Development Academy, and Deputy Director of Peking University Digital Finance Research Center

Zhang Junni Peking University National Development Research Dean hired associate professor

Introduction: Accelerating the cultivation of data factor markets is one of the key issues at the moment, but the development of the existing factors is not satisfactory. The high cost of data transaction and high compliance costs are important reasons. Breaking the situation requires the particularity of the production factors of data to achieve the "two -way go" of the market and the government: the market leads to form a multi -level data trading market system. effect.

Data plays an increasingly important role in economic development, and China also attaches great importance to the construction of the data element market. The expression of "accelerating the cultivation of the data element market", the "Opinions on the Construction of a more complete factor market -based configuration system and mechanism" issued by the State Council in April 2020, and the "Action Plan for the Construction of High Standard Market System" in January 2021, The "Fourteenth Five -Year Plan" Big Data Industry Development Plan released by the Ministry of Industry and Information Technology in November 2021 was repeatedly mentioned. Correspondingly, various places have made positive efforts to cultivate the data element market. For example, as of the end of August 2022, there have been 46 data exchanges built in various places. However, the current development of the data factor market is not satisfactory. How to promote the circulation of data elements has become one of the key issues of the healthy and sustainable development of the digital economy.

The research team of the National Development Research Institute of Peking University sorted out the current development of the Chinese data element market and found three main phenomena. First, the size of Chinese data output is large, but the data trading market is small. Digital China Development Report (2021) shows that China ’s data output ranked second in the world from 2017-2021, accounting for 9.9%of the world's; The scale of labeling, trading, etc.) was about 54.5 billion yuan, about 3.1%of the United States, 10.5%in Europe, and 17.5%of Japan. Second, although many data exchanges are quickly established, the on -site transactions are insufficient: data transactions in 2020 accounted for only 4% of the overall trading market scale, and less than 5% in 2021 (calculated by the National Industrial Information Security Development Research Center). Insufficient transactions on the venue are also reflected in the duration capacity of data exchanges. According to the statistics of the research team of the National Development Research Institute of Peking University, as of August 2022, 30 data exchanges for the existence or industry in industrial and commercial registration were as 30, and some data exchanges have withdrawn from operations. Third, in off -site transactions, the scale of data transactions in the black market cannot be ignored. Some experts estimate that in 2021, the size of the Chinese data black market trading market exceeds 150 billion yuan, and the industrial chain has been formed.

Why is the data factor market unsatisfactory? We first think about problems from the perspective of the characteristics of the production factors of data. Whether it is "data" in Chinese or English Data, the common point of its dictionary meaning is that the data emphasizes that data is the carrier of recording information. This determines that the element of data must be different from the traditional factor market in terms of ownership, value, security, and supervision.

From the perspective of the ownership, the data of the information carrier has the characteristics of the public product. Its non -competitive and some exclusive determine that the data cannot completely define its belonging in accordance with the method of property rights. "The pattern will not be completely applicable. From the perspective of value, the data can be copied infinitely. Among them, big data has ecological characteristics, which determines that the value of the data has changed greatly with the use of people, use scenarios and specific purposes, and it is difficult to standardize the value of the same data. At the same time, due to improper data use may cause privacy and data security issues, and problems caused by improper use of production factors such as labor, capital, land, and land, are also very different in nature and solutions. Finally, from the perspective of supervision, the construction of the Chinese data factor market is still in the initial stage, and some trading entities in the market also have certain social governance and even regulatory functions. Challenge. Therefore, the particularity of the data production factors determines that the development logic of the traditional production factor market cannot be applied to the data factor market. This point is Huang Yiping, a professor of the National Development Research Institute of Peking University National Development Research Institute, in "How to share big data?" "One article is also mentioned.

Specifically, the particularity of data elements determines that in data supply, demand, and even specific transactions and circulation links, they all face the same problems as the traditional factors market. On the supply side, the main problem is insufficient supply. We divide the main data suppliers into three categories: government departments, data -rich enterprises, and data collection suppliers to discuss this. Government departments have high demand for open public data, but operating costs, low income, and high potential risks; data -rich enterprises (such as large platforms and state -owned enterprises) have insufficient data income. In competition with itself, there is no enough motivation to do it; for data suppliers, in addition to standard data products, in all links with ecological characteristics, Chinese suppliers generally face lack of technical capabilities and cost -effectiveness. High, less data products.

The problem of demand is not that the demand is not strong, but to convert demand into effective demand at least five difficulties. The first is to identify the demand difficult, that is, the data demand party may have fuzzy data needs, but it is not clear what kind of data can meet their needs; It is more difficult than the three households. Because many data are non -standard products, the goods need to be accurately identified by the three units of different data quality. Fourth, it is difficult to integrate internal and external integration. Integration and use are also a lot of challenges; fifth is that security guarantee is difficult. This means that some data demand may not have good data security guarantee. Entering external data may increase the hidden dangers of data security, which makes the demand discouraged. Finally, the problem in the completion of the data transaction is that because many data products are non -standard products, they also lack recognized standards, and there is a phenomenon of difficulty in pricing, rights protection and compliance. Here, the reason for the difficulty of pricing is that due to the lack of consistent standards for assessing and identifying data products, it is not easy to find prices through a large number of repeated transactions in the market, and it is difficult to evaluate whether the price is reasonable. It is difficult to defend their rights in the case of failure to follow the contract. fine.

In simple terms, the development of the data factor market is not satisfactory. It is closely related to the high transaction cost of the production factors in China's existing technical capabilities and system supervision environment. Therefore, it is necessary to speed up the cultivation of the data factor market, which needs to reduce transaction costs as the starting point, and efforts are made from the supply and needs of the specific transaction. We divide data transactions into two types: point -to -point data transactions and data intermediary transactions, and data intermediaries are divided into data collection, development and selling vendors, data marketplace, and data trusts. The data trading market structure of the United States, Europe, and Japan provides some development experience that can be used for reference.

Generally speaking, in the global data intermediary trading market, data collection, development and selling vendors (or data brokers Data Broker) play a positive role in reducing data transaction costs as the mainstream model. Data collection, development and selling vendors obtain various types of data such as individuals, enterprises, geographical location, interconnected physical equipment, weather and other types of data from the government, commercial institutions and open channels. Proper needs. Many US data collection, development and selling vendors occupy a leading position in different industries, such as CoreLogic covering more than 99%of residential and commercial real estate data in the United States; Liveramp (called ACXIOM before 2018, Anke Cheng) has 700 million people around the world for markets for the market. Marketing analysis, etc.

It is worth noting that although the data market also has excellent enterprises (such as DataRade), in general, the proportion of small data suppliers and the demand party's data market is not large. According to the statistics of Maximize Market Research, the size of the global data intermediary trading market in 2021 was about $ 257.2 billion, and the market size of the data market was US $ 780 million. In addition, there are many examples of failure or closing of data markets, such as Microsoft's Azure DataMarket closed in 2018.

Another important reason for the development of the data factor market is that the compliance cost of data transactions is high. China's "Personal Information Protection Law" is similar to the "Data Security Law" and Europe's "General Data Protection Regulations" (GDPR), which takes the protection of the main equity of the data as its core. Because the data circulation may violate relevant regulations, in many cases, the enrichment of data companies not only dare not sell data, but even data circulation among different departments in the same enterprise has concerns.

In terms of reducing the cost of compliance, some methods of Europe, America and Japan can also learn from. Among them, in addition to the use of the data party to obtain the clear consent of the consumer, GDPR also has five other legal basis for handling personal data. Among them In possibilities, the regulatory authorities also have corresponding evaluation templates to help enterprises work in compliance. The United States takes the development of the digital economy as its core. Generally, it adopts the consent of selection, and the requirements for privacy protection and data security will be more satisfied from the perspective of development technology. For example, the privacy Japanese rules are similar to GDPR, and in practice, it emphasizes the cooperation between public forces and market forces, and plays more about the role of industry associations and personal data trust banks.

Accelerate the cultivation of the data factor market, the government has something to do. Internationally data intermediary transactions, data collection, development and selling vendors, supplemented by data stadiums, supplemented by data markets, providing some reference experience for the development of Chinese data exchanges. We must avoid the last place of the data exchanges and the last place. With market -led specific transaction models, the development of data trading market systems combined with high -quality data collection, development and selling vendors, point -to -pairs, data markets, and data trusts may be a road worth exploring.

In terms of reducing transaction costs and compliance costs, the government has great promise. First, relevant departments can actively participate in the formulation of data and technical standards: how to distinguish and store sensitive data and unsightly data, or participate in technical standards and qualification certifications (such as grading cord licenses) and other aspects. Privacy protection and data security, to change the passive situation of data without data, and increase the breakthrough of the core technology bottleneck by guiding funds, etc.; the third is to supervise it to help enterprises form a stable expectations for compliance costs. On the one hand, it can be committed to helping both supply and demand to solve the data dispute; on the other hand, you can consider the feasibility of setting up data transaction supervision sandboxes early, and minimize regulatoryness behind innovation. Finally, the government can also encourage leader companies and related industry associations to play more leading role. (Zhongxin Jingwei APP) Editor in charge: Song Yafen

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