Digital Economy | Statistics on digital innovation of listed companies are new! Guangdong, Beijing, and Zhejiang rank among the top three!

For more details, please see the original article Digital Economy | Statistics on digital innovation of listed companies are new! Guangdong, Beijing, and Zhejiang rank among the top three!

Table of contents

Part1Foreword

Introduction to Part2 database

Part3 sample data

Part4Data Visualization

Part5 data acquisition guide

1 Institutional users download directly

2 individual user purchasing downloads


Part1Foreword _

In the tweet about the micro data of digital innovation of listed companies , we introduced the micro information of digital patents and software works of listed companies. Based on the above background, the digital economy special database launched the digital innovation (statistics) module, which analyzes the data of some commonly used patents and soft works. Statistics on indicators, such as the number of patent applications and authorizations, the number of software registrations, etc.

Introduction to Part2 database

The Digital Innovation (Statistics) module contains six statistical tables of digital patents and software works.

Based on the micro-data of the Digital Patent Information Table of Listed Companies (Old Edition), the number of patent applications and authorizations for invention patents and utility models are counted by year, region, and industry category . The statistical subjects are domestic A-share listed companies that are listed . ;

According to the micro-data of the Digital Patent Information Table of Listed Companies (New Edition), the number of applications and authorizations for invention patents and utility model patents of each listed company is calculated by year and patent type. The statistical subjects cover the types of securities issued : domestic A shares, domestic B shares shares and is a listed company.

According to the software copyright information table of listed companies, the number of software registrations is calculated by industry and region .

Among them, the digital patent information table of listed companies (old version) is constructed based on the "Reference Table of Strategic Emerging Industries Classification and International Patent Classification (2021)" [1], including "Digital Creative Industries" and "New Generation Information Technology Industry" "Patent information of the two major digital economy-related industries; the digital patent information table of listed companies (new version) is based on the "Digital Economy Core Industry Classification and International Patent Classification Reference Table (2023)" [2] issued by the State Intellectual Property Office" [2] in accordance with.

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The specific form fields are as follows:

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Part3 sample data

Due to limited space, only some fields of the tweet are displayed. For complete data, please log in to the Qiyan·Social Science Big Data Platform (https://r.qiyandata.com) for query!

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Table 1 Partial data on software copyright statistics of listed companies in various provinces and industries over the years (2002-2022)

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Table 2 Digital patent statistics of listed companies in various provinces and industries over the years - some data from the old version (1985-2022)

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Table 3 Statistics on the number of digital patent applications and authorizations of listed companies over the years - Partial data of the new version (2000-2022)

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Table 4 Statistics on the number of digital patents of listed companies in various provinces and cities over the years - part of the new version (2000-2022)

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Table 5 Statistics on the number of digital patents of listed companies in various provinces over the years - part of the new version (2000-2022)

Part4Data Visualization

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Figure 1 shows the application and authorization status of digital patents for listed companies in Zhejiang Province. Several important trends can be seen in the figure. First, from 2010 to 2015, the number of utility model patent applications exceeded the number of invention patent applications. However, since 2016, the number of invention patent applications began to exceed the number of utility model patent applications. Secondly, the number of applications for invention patents and utility model patents has been showing an increasing trend in the past few years. However, in 2022, the number of applications for invention patents dropped significantly, while the number of applications for utility model patents began to decline slightly in 2021. And there will be a significant decline in 2022. Finally, there is almost no significant downward trend in the number of digital patents granted.

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Figure 2 reveals the number of digital patent invention patent applications by listed companies in various provinces across the country in 2022. It is worth noting that Guangdong Province ranks first among all provinces in the country with the number of invention patent applications, accounting for almost a quarter of the number of digital patent applications from listed companies nationwide. Followed by Beijing City, Zhejiang Province, Shandong Province and Jiangsu Province in decreasing order. It is worth mentioning that the number of digital patent invention patent applications in most provinces only accounts for 2% or less of the total number of digital patent invention patents in the country.

Part5 data acquisition guide

This data has been launched on the Enterprise Research·Social Science Big Data Platform!

1 Institutional users download directly

The Enterprise Research·Social Science Big Data Platform is now open for trial periods ranging from 3 to 6 months for major domestic universities. It can be accessed through the school IP to query and download data. Welcome all readers and friends to recommend the Enterprise Research Social Science Big Data Platform (https://r.qiyandata.com) to your school/institutional library!

>>>Click here to view the list of colleges and universities that have opened trials

Reference articles for specific introduction:

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Download process:

  1. Enter the Enterprise Research·Social Science Big Data Platform website (https://r.qiyandata.com).

  2. Click on the upper right corner of the website and select "Institutional User (IP) Login".

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  3. Select the required thematic database in the navigation bar → data table → filter fields and other information → preview data or download.

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2 individual user purchasing downloads

If your university/institution has not opened a big data platform trial, you can directly purchase the data you need on the Qiyan·Social Science Big Data Platform (https://r.qiyandata.com/) - Data Supermarket !

Procurement path:

  1. Click "Login/Register" in the upper right corner and select "Individual User Login".

  2. After successfully logging in, click "Data Supermarket".

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References

[1] "Reference Table of Strategic Emerging Industries Classification and International Patent Classification (2021)":  https://www.cnipa.gov.cn/art/2021/2/10/art_2073_156808.html

[2] "Reference Table of Digital Economy Core Industry Classification and International Patent Classification (2023)":  https://www.cnipa.gov.cn/art/2023/3/23/art_543_183097.html

▍User Notes

Without the permission of Enterprise Research Data, no institution or individual may transfer, donate, sell or otherwise disseminate the above data to other third parties in any form. Violators will be held accountable in accordance with the law. During the use of data, the "Data Security Law of the People's Republic of China" and other relevant regulations must not be violated, otherwise the consequences will be borne by the user.

▍Citation specifications

This data is provided by Enterprise Research Data. Academic papers or research reports published using this database must indicate in the results “all (part) of the data used in this paper (report) come from the Enterprise Research·Digital Economy Industry Special Database”.

 For more information, please view the Enterprise Research·Social Science Big Data Platform , a big data distribution center, publishing platform and service window dedicated to promoting think tank construction and academic research. https://r.qiyandata.com/

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Origin blog.csdn.net/weixin_55633225/article/details/132182763