Design of IPR evaluation system based on linear regression model

Author:

Zhang Qihang1,Jiang Jie1,Feng Bo12,Feng Junwen12

Affiliation:

1. 1 School of Intellectual Property , Nanjing University of Science and Technology , Nanjing , Jiangsu , , China

2. 2 Nanjing Audit University Jinshen College , Nanjing , Jiangsu , , China

Abstract

Abstract This paper first defines the conceptual scope of intellectual property, and the intellectual property evaluation system analyzes the special characteristics of enterprise intellectual property evaluation and compares the differences between several intellectual property management models. Secondly, an open adaptive enterprise IPR evaluation system is constructed based on a linear regression model, and the system structure and the relationship between subsystems are analyzed in depth. Finally, based on the theory of adaptive evaluation management, the adaptive IPR evaluation system is constructed. The adaptive enterprise IPR evaluation model based on linear regression was constructed mainly from three dimensions, and the method to determine the development coordination index and early warning degree of the three dimensions was deduced. The results show that the average efficiency of the typical enterprise IPR evaluation system calculated based on the linear regression model is 0.86, which is 21.3% more efficient than the traditional model. Four of the decision units’ DEA is effective, 63% of the inputs are effective, and 37% of the input resources are wasted, which aligns with the actual enterprise. The adaptive IPR evaluation system based on the linear regression model proposed in this paper has theoretical innovation value and practical significance for enterprises to realize the transformation of IPR achievements.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

Reference18 articles.

1. Gaikwad, A. H. (2020). A Study of Intellectual Property Rights and Its Significance for Business. Journal of Computational Acoustics, 10(2), 552-561.

2. Leonid, Kogan, Dimitris, Papanikolaou, Amit, & Seru, et al. (2017). Technological innovation, resource allocation, and growth*. Quarterly Journal of Economics..

3. Mazzola, E., Acur, N., Piazza, M., et al. (2018). “To Own or Not to Own?” A Study on the Determinants and Consequences of Alternative Intellectual Property Rights Arrangements in Crowdsourcing for Innovation Contests. Journal of Product Innovation Management.

4. Xiang, W. (2015). China’s Intellectual Property Protection Strength and Its Evaluation - Based on the Accession to TRIPS Agreement (Agreement On Trade-Related Aspects of Intellectual Property Rights). R & D Management: Research and Development Management.

5. Liu, X. (2021). Evaluation of Influencing Factors of Intellectual Property Protection Based on Fuzzy Analytic Hierarchy Process. Journal of Intelligent and Fuzzy Systems, 2021(3), 1-10.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3