Library and Information Service

Library and Information Service >

2026 , Vol. 70 >Issue 18: 3 - 22

DOI: https://doi.org/10.13266/j.issn.0252-3116.2026.18.001

INVITED ARTICLE

Research on Patent Value Evaluation System Integrating Policy Semantic Mining and Rule Engine: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area

  • Zhang Yang ,
  • Wang Yizhu ,
  • Li Danyang
Expand
  • 1 School of Information Management, Sun Yat-sen University, Guangzhou 510006;
    2 School of Information Management, Wuhan University, Wuhan 430072
Zhang Yang, Dean, Professor, PhD, Doctoral Supervisor; Wang Yizhu, Master's Candidate; Li Danyang, Associate Researcher, PhD,Corresponding Author, E-mail: whusimldy@163.com.

Received date: 2025-09-02

  Revised date: 2026-02-27

  Online published: 2026-09-08

Supported by

This work is supported by National Social Science Fund Major Project of China (Grant No. 23&ZD226) and the National Social Science Fund Youth Project of China (Grant No. 23CTQ018).

Fold

Abstract

[Purpose/Significance] Against the backdrop of the profound shifts of the global innovation landscape and China's accelerated implementation of the innovation-driven development strategy, patents have evolved beyond legal instruments into core carriers of innovation and key indicators of regional competitiveness. While existing evaluation systems generally rely on a solid tripartite framework—comprising legal, technological, and economic values—they frequently struggle with dynamic adaptability in complex macro-strategic contexts. Traditional endogenous indicators fail to capture the forward-looking strategic orientation embedded in dynamic policy adjustments. Grounded in the Technological Innovation System (TIS) theory, this study argues that high-value patents should not only fulfill technical and legal criteria but also demonstrate alignment with macro-strategic needs. Therefore, this study aims to construct a quantitative analytical framework and an evaluation system for patent value that can dynamically adapt to macro contexts and integrate strategic perspectives. [Method/Process] Taking the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) —characterized by cross-institutional, cross-regional, and cross-industrial collaborative innovation—as an empirical case, this study designs a research path of "knowledge discovery—rule mapping—dynamic weighting—empirical validation. " Specifically, in the knowledge discovery phase, the study combines the BERTopic model with rule-engine technology to mitigate the semantic sparsity problem of traditional bag-of-words models, effectively extracting latent strategic themes from exogenous policy texts. In the rule mapping phase, these themes are mapped into five supplementary categories of strategic value: industrial policy responsiveness, regional collaborative radiation, policy empowerment intensity, sustainable-development drive, and technical-rule dominance, which are further refined into ten secondary indicators. Finally, in the dynamic weighting phase, utilizing exogenous policy texts as the core benchmark, the study couples the rule engine with a time-decay coefficient to design a dynamic entropy-weight model. This process addresses static lag issues and constructs a comprehensive evaluation system encompassing legal, technological, economic, and strategic values. [Result/Conclusion] Multiple empirical and robustness tests based on the GBA patent samples indicate that the proposed evaluation system possesses demonstrates strong construct validity and criterion-related predictive validity. The empirical results verify the significant marginal explanatory power of strategic value as a supplementary dimension. Furthermore, heterogeneity analysis reveals distinct institutional constraints: strategic value exhibits a negative impact on patent transfer rates across all samples, but the magnitude is significantly stronger for non-enterprise entities (e. g., universities and research institutes) due to constraints regarding risks of state-owned asset losses and maturity levels, whereas enterprises tend to adopt defensive strategies to maintain core competitiveness. Overall, this measurement paradigm can identify core patent assets highly aligned with macro-strategic orientations, effectively broadening the measurement dimensions of traditional evaluation systems and enhancing their dynamic adaptability in complex policy contexts, thereby providing a quantitative decision-making reference for innovation-resource allocation. [Innovation/Value] This study makes three main contributions. First, theoretically, it breaks through the traditional micro-level evaluation perspective by establishing a structural mapping between macro-policy semantics and micro-patent evaluation. By introducing "Strategic Value" based on the TIS theory, it extends the evaluation dimension to macro-strategic alignment. Second, methodologically, it integrates the BERTopic model with a customized rule engine to achieve a rigorous and objective mapping from unstructured policy intentions to structured indicator weights. Third, in terms of evaluation logic, by adopting exogenous policy texts as the core benchmark for weighting rather than excessively relying on endogenous data, the study mitigates homological endogeneity bias. This creates a highly transparent, traceable, and dynamic measurement paradigm capable of objectively responding to macro-strategic guidance. [Insufficient/Improvement] Despite these theoretical and methodological advancements, certain limitations remain to be addressed in future research. First, the spatial generalizability of the evaluation system requires further verification. Future studies could apply this measurement paradigm to other strategic regions, such as the Yangtze River Delta and the Beijing-Tianjin-Hebei region, to confirm the generalizability and robustness of the evaluation logic through cross-regional horizontal comparisons. Second, due to the long lifecycle of patent value realization, current cross-sectional data cannot fully capture dynamic value trajectories. Subsequent research should establish long-term panel databases and employ methodologies such as survival analysis to conduct full-life-cycle tracking tracking of high-value patents' conversion rates, implementation rates, and ultimate economic benefits.

Key words： patent value evaluation; technological innovation system; BERTopic; rule engine; strategic value

Cite this article

Zhang Yang , Wang Yizhu , Li Danyang . Research on Patent Value Evaluation System Integrating Policy Semantic Mining and Rule Engine: A Case Study of the Guangdong-Hong Kong-Macao Greater Bay Area[J]. Library and Information Service, 2026 , 70(18) : 3 -22 . DOI: 10.13266/j.issn.0252-3116.2026.18.001

References

[1] 国家知识产权局.《专利评估指引》国家标准正式发布[EB/OL].[2026-05-15]. https://www.cnipa.gov.cn/art/2023/9/1/art_ 53_187168. html. (State Intellectual Property Office of China. National standard“Guidelines for Patent Valuation” officially released[EB/OL].[2026-05-15]. https://www.cnipa.gov.cn/art/2023/9/1/art_53_187168.html.)
[2] 冉从敬,李旺,黄文俊.高校高价值专利技术机会识别研究——以“生成式人工智能”领域为例[J].信息资源管理学报, 2024, 14(4): 103-116. (RAN C J, LI W, HUANG W J. Identifying technology opportunities from high-value patents in universities: the case of generative artificial intelligence[J]. Journal of information resources management, 2024, 14(4): 103-116.)
[3] 祝瑜晗,程彩娟,徐蔼婷.经济集聚下的专利“含金量”与产业结构优化——基于276个城市的实证研究[J].统计研究, 2023, 40(12): 62-76. (ZHU Y H, CHENG C J, XU A T. Patent “gold content” and industrial structure optimization under economic agglomeration: based on an empirical study of 276 cities in China[J]. Statistical research, 2023, 40(12): 62-76.)
[4] SANDERS B S, ROSSMAN J, HARRIS L J. The economic impact of patents[J]. Patent, trademark and copyright journal, 1958, 2(2): 340-362.
[5] 郑素丽,宋明顺.专利价值由何决定?——基于文献综述的整合性框架[J].科学学研究, 2012, 30(9): 1316-1323, 1332. (ZHENG S L, SONG M S. Review on the determinants of patent value: an integrate framework[J]. Studies in science of science, 2012, 30(9): 1316-1323, 1332.)
[6] 王子焉,刘文涛,倪渊,等.专利价值评估研究综述[J].科技管理研究, 2019, 39(16): 181-190. (WANG Z Y, LIU W T, NI Y, et al. A review of patent value evaluation[J]. Science and technology management research, 2019, 39(16): 181-190.)
[7] 张玉蓉,祝靖雨.基于中国专利金奖的高价值专利影响因素研究——模糊集定性比较分析[J].科学学与科学技术管理, 2025, 46(2): 109-119. (ZHANG Y R ZHU J Y. Research on the influencing factors of high-value patents based on China patent gold award: the fuzzy set qualitative comparative analysis method[J]. Science of science and management of S.& T., 2025, 46(2): 109-119.)
[8] 方曦,田梦婷,刘云.基于熵权—突变级数法与专利组合策略的高价值专利培育研究[J].中国科技论坛, 2023(11): 108-119. (FANG X, TIAN M T, LIU Y. Research on high-value patent cultivation based on entropy weight-catastrophe progression method and patent portfolio strategy[J]. Forum on science and technology in China, 2023(11): 108-119.)
[9] 唐恒,黄文,程龙,等.技术—组织—环境三维视角下企业专利价值提升路径研究[J].中国科技论坛, 2024(7): 132-142, 163. (TANG H, HUANG W, CHENG L, et al. Research on paths for enhancing patent value in enterprises from the perspective of TOE (technology-organization-environment)[J]. Forum on science and technology in China, 2024(7): 132-142, 163.)
[10] 刘妍.专利价值评估研究综述与趋势展望[J].图书情报工作, 2022, 66(15): 127-139. (LIU Y. Review and trend prospect of the research on patent value evaluation[J]. Library and information service, 2022, 66(15): 127-139.)
[11] 洪群业,汪志波,王乐,等.基于熵权法的我国烟草行业高价值专利评价分析[J].烟草科技, 2024, 57(11): 106-112. (HONG Q Y, WANG Z B, WANG L, et al. Evaluation of high-value patents held by the tobacco industry of China based on entropy weight method[J]. Tobacco science & technology, 2024, 57(11): 106-112.)
[12] 张亚峰,李黎明.专利价值再认识：大学专利转让的实证研究[J].科学学研究, 2022, 40(9): 1608-1620. (ZHANG Y F, LI L M. Reexamination of patent value: empirical analysis on assigned university patents[J]. Studies in science of science, 2022, 40(9): 1608-1620.)
[13] CARLSSON B, STANKIEWICZ R. On the nature, function and composition of technological systems[J]. Journal of evolutionary economics, 1991, 1(2): 93-118.
[14] HEKKERT M P, SUURS R A A, NEGRO S O, et al. Functions of innovation systems: a new approach for analysing technological change[J]. Technological forecasting and social change, 2007, 74(4): 413-432.
[15] 余明桂,范蕊,钟慧洁.中国产业政策与企业技术创新[J].中国工业经济, 2016(12): 5-22. (YU M G, FAN R, ZHONG H J. Chinese industrial policy and corporate technological innovation[J]. China industrial economics, 2016(12): 5-22.)
[16] 余长林,杨国歌,杜明月.产业政策与中国数字经济行业技术创新[J].统计研究, 2021, 38(1): 51-64. (YU C L, YANG G G, DU M Y. Industrial policy and technological innovation of China’ s digital economy industries[J]. Statistical research, 2021, 38(1): 51-64.)
[17] 廖筠,轩辕明雪,朱晗荞.国家级大数据综合试验区试点政策对企业开放式创新的影响研究[J].工业技术经济, 2025, 44(8): 78-87. (LIAO Y, XUANYUAN M X, ZHU H Q. Research on the impact of national big data comprehensive experimental zone pilot policies on enterprise open innovation[J]. Journal of industrial technological economics, 2025, 44(8): 78-87.)
[18] 成程,王一出,田轩,等.对外开放制度创新、全球创新网络嵌入与中国科技国际影响力[J].管理世界, 2024, 40(10): 16-43. (CHENG C, WANG Y C, TIAN X, et al. Institutional innovation in opening-up, global innovation network integration, and international influence of Chinese science and technology[J]. Journal of management world, 2024, 40(10): 16-43.)
[19] BERGEK A, JACOBSSON S, CARLSSON B, et al. Analyzing the functional dynamics of technological innovation systems: a scheme of analysis[J]. Research policy, 2008, 37(3): 407-429.
[20] SCHOT J, STEINMUELLER W E. Three frames for innovation policy: R&D, systems of innovation and transformative change[J]. Research policy, 2018, 47(9): 1554-1567.
[21] WILKERSON J, CASAS A. Large-scale computerized text analysis in political science: opportunities and challenges[J]. Annual review of political science, 2017, 20(1): 529-544.
[22] 肖华斌,朱琳霄,盛硕,等.山东省黄河流域生态保护与高质量发展战略模式比较与路径实践——基于政策文本分析视角[J].现代城市研究, 2025(3): 52-59. (XIAO H B, ZHU L X, SHENG S, et al. Path practice and pattern comparison of ecological protection and high quality development strategy models in the Yellow River Basin of Shandong province: based on the perspective of policy text analysis[J]. Modern urban research, 2025(3): 52-59.)
[23] 陈美,孙瑞乾.政策工具视域下我国省级数字经济政策文本的量化分析——基于LDA的主题社会网络分析[J].情报杂志, 2023, 42(11): 174-182. (CHEN M, SUN R Q. Quantitative analysis of China's provincial digital economy policies from the perspective of policy tools: based on LDA topic social network analysis[J]. Journal of intelligence, 2023, 42(11): 174-182.)
[24] 叶杨,徐洁,黄章龙,等.中国地市级人才政策时空演进与新质生产力——基于2002-2021年3308项政策文本的量化分析[J].科学学研究, 2026, 44(2): 255-269, 372. (YE Y, XU J, HUANG Z L, et al. The spatiotemporal evolution of talent policies and their impact on new quality productive forces in Chinese prefecture-level cities: based on quantitative analysis of 3308 policy texts from 2002 to 2021[J]. Studies in science of science, 2026,44(2): 255-269,372.)
[25] 金燕,陈登建,曹玲静.中国数据要素政策主题的嬗变逻辑及扩散动向分析[J].现代情报, 2026, 46(4): 123-135. (JIN Y, CHEN D J, CAO L J. Analysis of the evolutionary logic and diffusion trends of China’ s data element policy themes[J]. Journal of modern information, 2026, 46(4): 123-135.)
[26] 杨长进,罗仁杰,黄俊,等.产业政策对新能源汽车企业技术创新的影响——基于政策文本的LDA模型分析[J].科技进步与对策, 2025, 42(14): 114-126. (YANG C J, LUO R J, HUANG J, et al. The impact of industrial policies on the technological innovation of new energy vehicle enterprises: An analysis of the LDA model based on policy texts[J]. Science & technology progress and policy, 2025, 42(14): 114-126.)
[27] EGGER R, YU J. A topic modeling comparison between LDA, NMF, Top2Vec, and BERTopic to demystify Twitter posts[J]. Frontiers in sociology, 2022, 7: 886498.
[28] GROOTENDORST M. BERTopic: Neural topic modeling with a class-based TF-IDF procedure[PP/OL]. arXiv (2022-03-11)[2026-05-15]. https://doi.org/10.48550/arXiv.2203.05794.
[29] 苗宏慧,全情爽,舒心.基于BERTopic的科技人才政策文本主题识别与量化分析——以东北三省为例[J].现代情报, 2025, 45(4): 110-121. (MIAO H H, QUAN Q S, SHU X. Topic identification and quantitative analysis of science and technology talent policy texts based on BERTopic: a case study of three northeast provinces in China[J]. Journal of modern information, 2025, 45(4): 110-121.)
[30] 王益成,蒋星宇,秦晴,等.基于投融资事件的技术主题识别研究——以生物技术领域为例[J].情报学报, 2025, 44(2): 234-245. (WANG Y C, JIANG X Y, QIN Q, et al. Research on technology theme identification based on investment and financing events: using biotechnology as an example[J]. Journal of the China Society for Scientific and Technical Information, 2025, 44(2): 234-245.)
[31] 刘苇,刘勇.基于Spring的业务规则引擎[J].计算机工程, 2008, 34(23): 56-58, 81. (LIU W, LIU Y. Business rule engine based on Spring[J]. Computer engineering, 2008, 34(23): 56-58, 81.)
[32] 刘宝林,莫海峰,冯磊,等.规则引擎驱动的配电网问题诊断[J].电力系统及其自动化学报, 2023, 35(7): 151-158. (LIU B L, MO H F, FENG L, et al. Diagnosis of distribution network problems driven by rule engine[J]. Proceedings of the CSUEPSA, 2023, 35(7): 151-158.)
[33] FRIEDMAN-HILL E. Jess in action: Java rule-based systems[M]. Greenwich: Manning Publications, 2003: 3-40.
[34] 新华社.中共中央国务院印发《粤港澳大湾区发展规划纲要》[EB/OL]. (2019-02-18)[2026-05-15]. https://www.gov.cn/zhengce/2019-02/18/content_5366593.htm#1. (Xinhua News Agency. CPC Central Committee and State Council issue the “Outline Development Plan for the Guangdong-Hong KongMacao Greater Bay Area”[EB/OL]. (2019-02-18)[2026-05-15]. https: //www.gov.cn/zhengce/2019-02/18/content_5366593.htm#1.)
[35] 陈伟,张永超,田世海.区域装备制造业产学研合作创新网络的实证研究——基于网络结构和网络聚类的视角[J].中国软科学, 2012(2): 96-107. (CHEN W, ZHANG Y C, TIAN S H. An empirical study on the innovation network of industryuniversity-research cooperation in regional equipment manufacturing industry: from the perspectives of network structure and network clustering[J]. China soft science, 2012(2): 96-107.)
[36] HILLMAN A J, WITHERS M C, COLLINS B J. Resource dependence theory: a review[J]. Journal of management, 2009, 35(6): 1404-1427.
[37] 施学哲,杨晨,蔡芸.专利政策融入产业经济发展路径分析:来自江苏专利政策的实证研究[J].科技进步与对策, 2018, 35(2): 129-133. (SHI X Z, YANG C, CAI Y. A study on patent policy path integrated into the industrial economic development: based on the empirical research about Jiangsu[J]. Science & technology progress and policy, 2018, 35(2): 129-133.)
[38] 央视新闻客户端.《国家标准化发展纲要》发布为未来15年我国标准化发展设定目标蓝图[EB/OL]. (2021-10-10)[2026-05-15]. https://m.news.cctv.com/2021/10/10/ARTIDBvsAKGUkNRva111q03r211010.shtml. (CCTV News client.“National Standardization Development Outline” released, setting target blueprint for China’ s standardization development over next 15 years[EB/OL]. (2021-10-10)[2026-05-15]. https://m.news.cctv.com/2021/10/10/ARTIDBvsAKGUkNRva111q03r211010.shtml.)
[39] TOMBROS A, RUTHVEN I, JOSE J M. How users assess web pages for information seeking[J]. Journal of the American Society for Information Science and Technology, 2005, 56(4): 327-344.
[40] EL HAMDANI R, MUSTAPHA M, RESTREPO AMARILES D, et al. A combined rule-based and machine learning approach for automated GDPR compliance checking[C/OL] //Proceedings of the eighteenth international conference on artificial intelligence and law, 2021: 40-49. https://doi.org/10.1145/3462757.3466081.DOI:10.1145/3462757.3466081.
[41] REIMERS N, GUREVYCH I. Sentence-BERT: Sentence embeddings using Siamese BERT-Networks[C/OL] //Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP), 2019: 3982-3992. https://aclanthology.org/D19-1410/.DOI:10.18653/v1/D19-1410.
[42] COE D T, HELPMAN E. International R&D spillovers[J]. European economic review, 1995, 39(5): 859-887.
[43] 冉从敬,李旺.校企合作视角下高校高价值专利推荐模型构建——以“新能源汽车”为例[J].图书情报工作, 2023, 67(11): 115-126. (RAN C J, LI W. The construction of high-value patent recommendation model for universities from the perspective of university-enterprise cooperation: taking“new energy vehicles” as the case[J]. Library and information service, 2023, 67(11): 115-126.)
[44] 刘运华,刘兴华,李晶.建立有利于科技成果转化的专利质量评价体系研究[J].科学管理研究, 2022, 40(2): 65-72. (LIU Y H, LIU X H, LI J. Research on patent quality analysis to promote the transformation of scientific and technological achievements[J]. Scientific management research, 2022, 40(2): 65-72.)
[45] 文豪,胡晓阳.基于质量评价模型的专利质押价值评估体系修正研究[J].科技管理研究, 2022, 42(21): 168-175. (WEN H, HU X Y. Research on the modification of patent pledge evaluation system based on quality evaluation model[J]. Science and Technology Management Research, 2022, 42(21): 168-175.)
[46] 宋凯,冉从敬.基于主题挖掘与专利评估的技术机会识别研究——以智慧农业为例[J].图书情报工作, 2023, 67(3): 61-71. (SONG K, RAN C J. Research on technology opportunity identification based on topic mining and patent evaluation: a case study of smart agriculture[J]. Library and information service, 2023, 67(3): 61-71.)
[47] 刘澄,雷秋原,张楠,等.基于BP神经网络的专利价值评估方法及其应用研究[J].情报杂志, 2021, 40(12): 195-202. (LIU C LEI Q Y, ZHANG N, et al. Research on patent value evaluation method based on BP neural network and its application[J]. Journal of Intelligence, 2021, 40(12): 195-202.)
[48] 王舒,马新宇,彭博,等.高校高价值专利评估的理论探讨[J].中国高校科技, 2020(S1): 15-18. (WANG S, MA X Y, PENG B, et al. Theoretical discussion on evaluation of high-value patents in universities[J]. China university science & technology, 2020(S1): 15-18.)
[49] BAKKER J. The log-linear relation between patent citations and patent value[J]. Scientometrics, 2017, 110(2): 879-892.
[50] 国家知识产权局办公室.关于印发《战略性新兴产业分类与国际专利分类参照关系表（2021）（试行）》的通知[EB/OL]. (2021-02-10)[2026-05-15]. https://www.cnipa.gov.cn/art/2021/2/10/art_75_156716.html. (National Intellectual Property Administration (CNIPA). Notice on printing and distributing the "Reference Relationship Table between Strategic Emerging Industry Classification and International Patent Classification (2021) (Trial)"[EB/OL]. (2021-02-10)[2026-05-15]. https://www.cnipa.gov.cn/art/2021/2/10/art_75_156716.html.)
[51] 华南师范大学,肇庆市龙乾农业科技发展有限公司.水产养殖环境智能病害预警系统及存储介质： CN120526554B[P]. 2025-09-16. (South China Normal University, Zhaoqing Longqian Agricultural Technology Development Co., Ltd. Intelligent disease early warning system for aquaculture environment and storage medium: CN120526554B[P]. 2025-09-16.)
[52] 腾讯科技(深圳)有限公司,中国人民大学.一种信息推荐方法、装置、设备及计算机可读存储介质： CN113761355B[P]. 2025-12-16. (Tencent Technology (Shenzhen) Co., Ltd., Renmin University of China. Information recommendation method, device, equipment and computer readable storage medium: CN113761355B[P]. 2025-12-16.)
[53] 华为技术有限公司.道路信息的识别方法、装置、电子设备、车辆及介质： CN116206278B[P]. 2025-01-28. (Huawei Technologies Co., Ltd. Road information identification method and device, electronic equipment, vehicle and medium: CN116206278B[P]. 2025-01-28.)
[54] 华为技术有限公司.基于多任务学习的决策方法、决策模型训练方法及装置： CN111950726B[P]. 2025-03-25. (Huawei Technologies Co., Ltd. Decision method based on multitask learning, decision model training method and device: CN111950726B[P]. 2025-03-25.)
[55] SOMAYA D. Patent strategy and management: an integrative review and research agenda[J]. Journal of management, 2012, 38(4): 1084-1114.
[56] NOVELLI E. An examination of the antecedents and implications of patent scope[J]. Research policy, 2015, 44(2): 493-507.
[57] HARHOFF D, SCHERER F M, VOPEL K. Citations, family size, opposition and the value of patent rights[J]. Research policy, 2003, 32(8): 1343-1363.
[58] 肖莉娜,杨武.基于核心专利的固态电池产业技术安全评估——以中美日韩为例[J/OL].科学学研究: 1-21[2026-05-15]. https://doi.org/10.16192/j.cnki. 1003-2053.20251206.002. (Xiao Lina, Yang Wu. Technological safety assessment of the solidstate battery industry based on core patents: taking China, the United States, Japan and Korea as examples[J/OL]. Studies in science of science: 1-21[2026-05-15]. https://doi.org/10.16192/j.cnki.1003-2053.20251206.002.)
[59] SERRANO C J. The dynamics of the transfer and renewal of patents[J]. The RAND journal of economics, 2010, 41(4): 686-708.
[60] TRAJTENBERG M. A penny for your quotes: patent citations and the value of innovations[J]. The RAND Journal of Economics, 1990, 21(1): 172-187.
[61] BLIND K, CREMERS K, MUELLER E. The influence of strategic patenting on companies’ patent portfolios[J]. Research policy, 2009, 38(3): 428-436.
[62] HALL B H, JAFFE A B, TRAJTENBERG M. The NBER patent citation data file: Lessons, insights and methodological tools: Working Paper 8498[R/OL]. 2001. https://www.nber.org/system/files/working_papers/w8498/w8498.pdf.
[63] TEECE D J. Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy[J]. Research Policy, 1986, 15(6): 285-305.
[64] 黄宁.国有资产管理制度与科技成果转化制度的冲突和协调[J].科技管理研究, 2023, 43(16): 22-30. (HUANG N. Conflict and coordination between the state-owned assets management system and the transformation system of scientific and technological achievements[J]. Science and technology management research, 2023, 43(16): 22-30.)
[65] 张慧慧.高校科技成果转化的促进机制研究[J].科研管理, 2025, 46(9): 136-144. (ZHANG H H. Research on the promotion mechanism of universities' on the transformation of S&T achievements[J]. Science research management, 2025, 46(9): 136-144.)
Options
Outlines

/

〈 〉

    Copyrights © LIS Press Co., Ltd. Reproduction is prohibited without permission.