According to statistics from the Ministry of Commerce, China's invention patent applications have ranked first globally for eight consecutive years as of 2018. However, quantity does not equate to quality. Just as citation counts measure academic paper quality, patent citations serve as a core indicator for assessing patent quality.
Patent citations occur when later patent applicants or examiners reference prior patents, indicating technological connections between inventions. Originating from the Science Citation Index (SCI), this concept evolved into patent citations through knowledge networks formed by technical document references. Around February 1947, the USPTO first implemented listing relevant references on granted patents to evaluate technical solutions. Modern patent citation information primarily comes from two sources:
- Disclosures by inventors in patent specifications (e.g., "Background Technology" sections) to differentiate their inventions from prior art and demonstrate novelty. For instance, the Chinese patent system mandates applicants to submit all relevant technical materials through Information Disclosure Statements (IDS) during application processes.
- References added by patent examiners during substantive examinations to assess novelty and inventiveness through prior art searches.
Patent citation data serves two critical academic purposes:
- Tracing technological evolution and knowledge flows. Since Narin (1994) introduced bibliometrics into patent analysis, citations have been recognized as objective indicators of knowledge linkages. Citation networks reveal innovation dynamics and cross-sectoral knowledge transfer patterns.
- Measuring innovation quality and value. Citation counts help evaluate patent significance beyond mere quantity metrics, addressing the heterogeneity in innovation outputs.
The seminal work Patents, Citations and Innovations by Adam Jaffe and Manuel Trajtenberg established methodologies for analyzing patent value and technological trends through citation relationships.
Compared with the domestic version, USDataverse's Chinese Patent and Citation/Cited Data features unique characteristics as outlined below.
Data Characteristics
- Covers both domestic citations and international citations to Chinese patents from foreign-filed applications
- Includes comprehensive citation-out (patents cited) and citation-in (citing patents) information
- Tracks current legal status of patents across jurisdictions
- Identifies examiner-added citations during prosecution
Citing Publications
- Peng Yuanhuai, 2023: "Value Creation of Government Data Openness: Perspective of Enterprise Total Factor Productivity", Journal of Quantitative & Technical Economics 9.
- Shang Yuping, Pan Zhou, Meng Meixia, 2023: "Innovation Performance of Polycentric Urban Spatial Strategy in China: Agglomeration Economy and Amenities Perspectives", China Economic Quarterly 3.
Application Guides
Repost: Research Applications of Patent Citation Data
Repost: Understanding the Relationship Between Citation Counts and Patent Value
Repost: Mining High-Value University Patents Through Inventor Citation Analysis
Repost: Proper Use and Common Misuses of Patent Data in Finance and Economics Research
Repost: Chinese Patent Numbering System
Time Range
- Invention applications: 1985-2024 (by publication date)
- Granted patents/Utility models/Designs: 1985-2024 (by grant date)
Field Description
Sample Data
Chinese Patent Basic Information Table
Chinese Patent Citation Information Table
Chinese Patent Cited Information Table
Chinese Patent Event Table
Chinese Patent Cited Literature Information Table
Chinese Patent Classification Number Table
References
- Jan Bena, Hernán Ortiz-Molina, Elena Simintzi, 2022, “Shielding firm value: Employment protection and process innovation”, Journal of Financial Economics.
- Moser, P., J. Ohmstedt and P. W. Rhode, 2018, “Patent Citations-an Analysis of Quality Differences and Citing Practices in Hybrid Corn”, Management Science.
- Jaffe, A. B., M. Trajtenberg and R. Henderson, 1993, “Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations”, The Quarterly Journal of Economics.
- Roach, M. and W. M. Cohen, 2013, “Lens or Prism? Patent Citations as a Measure of Knowledge Flows from Public Research”, Management Science.
- Josh L , Amit S., 2021, "The Use and Misuse of Patent Data: Issues for Finance and Beyond", The Review of Financial Studies.
Update Frequency
Annual Update