知识产权保护社会共治问题与建议
Issues and Suggestions on Social Co-governance of Intellectual Property Rights Protection
刘晓峰 1闫艳丽 2马箫笛 2李娇娇1
作者信息
- 1. 郑州商标审查协作中心,河南 郑州 450000
- 2. 河南财经政法大学,河南 郑州 450046
- 折叠
摘要
[目的]强有力的知识产权保护是数字时代创新和经济持续增长的保障,知识产权保护社会共治治理模式,是适应日益变化的互联网时代知识产权保护的需要.[方法]采用比较研究法,阐述美国和日本在知识产权保护社会共治方面的举措,借鉴其先进经验,提出针对性建议.[结果]我国知识产权保护社会共治还存在司法保护机制具有局限性、中小企业知识产权保护缺乏系统性、行业组织知识产权保护自律和信息沟通有待提高、社会公众参与知识产权保护社会共治动力不足等问题.[结论]结合我国国情,提出引入技术专家证人制度、强化中小企业知识产权保护支撑、提升行业组织知识产权保护与服务能力、发挥社会公众参与知识产权社会共治主体作用等建议,以期为完善我国知识产权保护社会共治治理模式提供参考价值.
Abstract
[Purposes]Strong intellectual property protection is the guarantee of innovation and sustained economic growth in the digital era.Therefore,the social co-governance model of intellectual property protection is to meet the needs of intellectual property protection in the changing Internet era.[Methods]This paper adopts the comparative research method to expound the measures of the United States and Ja-pan in the protection of intellectual property rights in social co-governance,learns from their advanced experience,and puts forward targeted suggestions.[Findings]There are still shortcomings in the judicial protection mechanism,the intellectual property protection of small and medium-sized enterprises,the self-discipline and communication link of intellectual property protection in industry organizations,and the role of the public in the public.[Conclusions]Combined with China's national conditions,sugges-tions are made such as improving the judicial protection mechanism,strengthening the intellectual prop-erty protection support of small and medium-sized enterprises,improving the intellectual property pro-tection and service capabilities of industry organizations,and giving full play to the main role of the pub-lic in the social co-governance of intellectual property,in order to provide reference for the improvement of China's intellectual property protection and social co-governance model.
关键词
知识产权保护/社会共治/对策建议Key words
intellectual property protection/social co-governance/countermeasure and recommendation引用本文复制引用
出版年
2024
NETL
NSTL
万方数据