全部树

China university patent statisticsNEW

China high-tech enterprise patent statisticsNEW

Digital economy patent application and authorization dataNEW

Patents and citation data of Little Giant and individual champion companiesNEW

Small giant and single champion enterprise design patent details table

Statistics on the entry and exit of Chinese industrial and commercial enterprisesNEW

Statistics on entry and exit information of Chinese partnershipsNEW

Basic information data of manufacturing industrial and commercial registered enterprisesNEW

Patent and citation data of A-share listed companiesNEW

Patent details of A-share listed companies
A-share listed companies' patent application details table
Details of Design Patents Authorized by A-share Listed Companies

Green patents and citation data of A-share listed companies

A-share listed companies green patent details table

Patent and citation data of Chinese industrial enterprisesNEW

Green patents and citation data of Chinese industrial enterprisesNEW

Details of Green Patents of Chinese Industrial Enterprises

Tax investigation of corporate patents and citation dataNEW

Cost of living data for global residentsNEW

China foreign trade index data

  Based on their positions in control relationships, listed companies can be categorized as parent companies, subsidiaries, associates, and joint ventures. The commonly referred "listed companies" typically encompass not only the parent entity but also its corporate group comprising subsidiaries, associates, and joint ventures. The composition of listed companies and their affiliated entities undergoes annual variations.

  CnOpenData's Extended Basic Information Data on A-Share Listed Companies and Their Subsidiaries integrates comprehensive multi-dimensional information about A-share listed companies and their subsidiaries, associates, and joint ventures. The dataset comprises two core modules:

  • List of Affiliated Entities: Systematically extracted from annual reports, this includes securities codes, affiliated entity names, and their relationship with the listed company;
  • Extended Business Registration Information: Utilizing both exact and fuzzy matching methodologies, this module bridges affiliated entities with business registration data (40+ fields including enterprise name, unified social credit code, taxpayer identification number, industry classification, registered address) to form a structured database detailing corporate business fundamentals.

Data Uniqueness

  • Exclusive Integration of "Relationship Network + Business Panorama": Uniquely combines disclosed affiliations (e.g., subsidiary/associate roles) from annual reports with business entity details (paid-up capital, operating period, industry classification), addressing the fragmentation between "relationship networks" and "entity attributes" in academic and commercial analyses.
  • Dual-Matching Methodology Ensures Coverage: Provides both exact and fuzzy matching results with confidence indicators (marked fields), mitigating omissions caused by name changes in traditional databases.
  • Granular Geographic and Industry Classification: Registered addresses are detailed to district/county level (province-to-district codes), while industry classifications span four tiers (broad category → subclass codes), supporting regional economic and industrial chain research.

Data Application Value

  • Academic Research: Constructs parent-subsidiary control maps via securities codes + affiliated entity names; analyzes policy diffusion paths to subsidiaries using province + industry subclass codes.
  • Commercial Decision-Making: Screens investment targets using paid-up capital (实缴资本) and operational risk fields (causes of deregistration/revocation); identifies competitors' affiliated networks via business scope + industry broad categories.
  • Policy Evaluation: Tracks corporate survival rates using registration year + region codes to assess regional business environments.

CnOpenData's dataset serves as a structured database deeply integrating listed companies' affiliations with fundamental business entity dimensions. With 34-year historical coverage, dual-matching technology, and 40+ fields for granular analysis, it provides one-stop infrastructure for academic research on corporate ecosystems, financial institution risk assessments, and governmental industrial policymaking.


Literature Citing This Dataset

  • Wen Wen, Sun Yajie, Niu Yuhao, 2025: "Open Public Data and Cross-Regional Development of Corporate Groups," Journal of Financial Research, No. 10.

Time Coverage

2000–2024


Field Display

A-Share Listed Companies and Subsidiary Name Data

Basic Information on A-Share Listed Companies and Their Subsidiaries


Sample Data

A-Share Listed Companies and Subsidiary Name Data

Basic Information on A-Share Listed Companies and Their Subsidiaries—Exact Match

Basic Information on A-Share Listed Companies and Their Subsidiaries—Fuzzy Match


Data Update Frequency

Annual Updates