| 王 铮 孙 林 孟春艳.基于区位熵的关键技术点识别模型[J].中国科技资源导刊,2025,(5):77~86 |
| 基于区位熵的关键技术点识别模型 |
| Identification Model of Key-Technical-Points Based on Location Entropy |
| 投稿时间:2025-06-16 |
| DOI: |
| 中文关键词: 专利分析;区位熵;关键技术点;特定研发主体 |
| 英文关键词: patent analysis, Location Entropy, key-technical-points, specific R&D entities |
| 基金项目: |
| 作者 | 单位 | | 王 铮 孙 林 孟春艳 | (中核工程咨询有限公司,北京 100089) |
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| 摘要点击次数: 23 |
| 全文下载次数: 22 |
| 中文摘要: |
| 经济学中的“区位熵”用于识别区域优势产业。基于区位熵构建关键技术点识别模型,可以将此定量分析的研究方法应用于专利分析之中,识别关键技术点,解决传统的依赖定性分析或单纯的专利数量统计而引发分析结论客观性、可靠性欠佳等问题。按照专利技术分解图谱确定的各条目,采用涵盖专利技术、法律和经济属性的专利质量作为总量指标,计算特定研发主体的专利质量与对应条目下全国专利质量之间的比例关系,从而识别出相对于该主体而言的关键技术点,特别是能够区分技术优势点与劣势点;引入动态指标,即10年期复合年均增长率(CAGR10)的指标,构建四象限矩阵,进一步判断关键技术点的发展现状,引导该主体对各关键技术点采取差异化发展路径。实证分析发现,此模型的分析结果与现实情况更加吻合,能够根据特定研发主体现实情况与市场趋势,明晰关键技术点的发展策略。 |
| 英文摘要: |
| Location Entropy (LE) is used to identify regional advantageous industries in field of economics. This quantitative analysis method is introduced into patent analysis for identifying key-technical-points (KTPs). By using this, issues such as the lack of objectivity and reliability in analytical conclusions can be solved, which are arisen from traditional reliance on qualitative analysis or mere patent quantity statistics. Specifically, based on the entries defined by patent technical decomposition map, patent quality—covering technical, legal, and economic attributes—is adopted as the aggregate indicator. The ratio of patent quality between a specific R&D entity and the whole nation for each item is calculated, thereby identifying KTPs relative to the entity. This approach can particularly distinguish between technical strengths and weaknesses. By introducing a dynamic indicator of CAGR10 and constructing a four-quadrant matrix, it is possible to further assess the development status of KTPs and guide the entity in adopting differentiated development paths for each key technology. An empirical analysis reveals that the results of this model align more closely with real-world scenarios, enabling the formulation of development strategies for KTPs based on the specific circumstances of the R&D entity and market trends. |
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