专利收益影响因素实证研究

科学学研究 ›› 2021, Vol. 39 ›› Issue (10): 1850-1859.

专利收益影响因素实证研究

乔永忠¹,刘睿²

1. 厦门大学知识产权研究院
2. 同济大学上海国际知识产权学院

收稿日期:2020-10-15 修回日期:2021-03-01 出版日期:2021-10-15 发布日期:2021-11-05
通讯作者: 刘睿

Research on Influencing Factors of the Patent Profit Based on the Logistic Regression-BP Neural Network Model

Received:2020-10-15 Revised:2021-03-01 Online:2021-10-15 Published:2021-11-05

摘要/Abstract

摘要： 专利收益具有动态性、随机性、不平衡性、相对性和隐蔽性等特征，是专利创造、运用、保护、管理和服务等的核心，与专利数量、质量和价值等关系密切。以中国授权、国内居民拥有的法定保护期于2019年届满的专利为研究对象，基于逻辑回归-BP神经网络模型对专利收益影响因素分析发现：专利主体特征对专利收益的影响程度最大，专利客体特征和专利事件特征对专利收益的影响程度相对较弱，且比较接近；主体特征中专利权人类型、专利权人所在地区经济状况和发明人数对专利收益的影响程度依次递减；客体特征中同族专利数、独立权利要求数和专利引证数对专利收益的影响依次递减；事件特征中专利审查时间、诉讼涉案数和专利被引数对专利收益的影响程度依次递减。

Abstract: The patent profit has characteristics of dynamic, random, unbalanced, relative and hidden, which is the core of patent creation, application, protection, management and service, and is closely related to patent quantity, quality and value. Taking patents granted by China and owned by domestic residents whose legal protection period expires in 2019 as the research object, based on the logistic regression-BP neural network model, the empirical analysis of influencing factors of the patent profit shows that: the patent subject characteristics have the greatest influence on the patent profit; the patent object characteristics and the patent event characteristics have a relatively weak influence on the patent profit and are relatively close; the influence degree of the patentee type, the economic status of the patentee’s region, and the inventor number in the patent subject characteristics on the patent profit orderly decreases; the influence degree of the patent family number, the independent claim number, and the patent citation in the patent object characteristics on the patent profit orderly decreases; the influence degree of the patent examination time, the litigation case number, and the patent cited number in the patent event characteristics on the patent profit orderly decreases.

乔永忠刘睿. 专利收益影响因素实证研究[J]. 科学学研究, 2021, 39(10): 1850-1859.

参考文献

[1] Fernando J. Leiva Bertran, John L. Turner. Welfare-optimal patent royalties when imitation is costly [J]. Journal of Economic Behavior & Organization, 2017, 137(5): 457-475. [2] Jheng-Long Wu, et al. A patent quality analysis and classification system using self-organizing maps with support vector machine [J]. Applied Soft Computing, 2016, 41(C): 305-316. [3] Danguy, J., de Rassenfosse, G., van Pottelsberghe de la Potterie, B. On the origins of the worldwide surge in patenting: an industry perspective on the R&D-patent relationship [J]. Industrial and Corporate Change, 2014, 23(2): 535-572. [4] 国家知识产权局.国新办举行2019年中国知识产权发展状况发布会[EB/OL]. https://www.cnipa.gov.cn/art/2020/4/23/art_53_118141.html. 2020–04–23/2020–10–010. [5] James Bessen. Estimates of patent rents from firm market value [J]. Research Policy, 2009, 38(10): 1604-1616. [6] Chen, Y.-M., Ni, Y.-T., Liu, H.-H., & Teng, Y.-M. Information and rivalry-based perspectives on reactive patent litigation strategy [J]. Journal of Business Research, 2015, 68(4): 788-792. [7] Fragiskos Archontakis, Nikos C. Varsakelis. Patenting abroad: Evidence from OECD countries [J]. Technological Forecasting & Social Change, 2017, 116(6): 62-69. [8] 时奇, 沈芳. 债券投标专利拍卖：均衡策略与期望收益[J]. 中国管理科学, 2020. 10.16381/j.cnki.issn1003-207x.2019.2035. [9] 毛昊, 刘澄, 林瀚. 基于调查的中国企业非实施专利申请动机实证研究[J]. 科研管理，2014, 35(1): 73-81. [10] Lin H, Wang H, Du D, et al. Patent Quality Valuation with Deep Learning Models [C]//International Conference on Database Systems for Advanced Applications. Springer, Cham, 2018: 474-490. [11] Haupt R, Kloyer M, Lange M. Patent indicators for the technology life cycle development [J]. Research Policy, 2007, 36(3): 387-398. [12] Han E J, Sohn S Y. Patent valuation based on text mining and survival analysis [J]. The Journal of Technology Transfer, 2015, 40(5): 821-839. [13] Ooi K B, Lee V H, Tan G W H, et al. Cloud computing in manufacturing: The next industrial revolution in Malaysia [J]. Expert Systems with Applications, 2018, 93: 376-394. [14] Sharma S K, Al-Badi A H, Govindaluri S M, et al. Predicting motivators of cloud computing adoption: A developing country perspective [J]. Computers in Human Behavior, 2016, 62: 61-69. [15] Tu J V. Advantages and disadvantages of using artificial neural networks versus logistic regression for predicting medical outcomes [J]. Journal of clinical epidemiology, 1996, 49(11): 1225-1231. [16] Ing E B, Miller N R, Nguyen A, et al. Neural network and logistic regression diagnostic prediction models for giant cell arteritis: development and validation [J]. Clinical Ophthalmology (Auckland, NZ), 2019, 13: 421. [17] Larasati A, DeYong C, Slevitch L. The application of neural network and logistics regression models on predicting customer satisfaction in a student-operated restaurant [J]. Procedia-Social and Behavioral Sciences, 2012, 65: 94-99. [18] Talukder M S, Sorwar G, Bao Y, et al. Predicting antecedents of wearable healthcare technology acceptance by elderly: A combined SEM-Neural Network approach [J]. Technological Forecasting and Social Change, 2020, 150: 119793. [19] 蒋仁爱, 张路路, 石皓月. 专利发明人合作对中国专利质量的影响研究[J]. 科学学研究 2020, 38 (7):1215-1226. [20] 乔永忠.不同类型创新主体发明专利维持信息实证研究[J]. 科学学研究，2011, 29 (3):442-447. [21] Kim, N. Kim, W. Kim. The effect of patent protection on firms’ market value: The case of the renewable energy sector [J]. Renewable and Sustainable Energy Reviews, 2018, 82(2): 4309-4319. [22] Rainer Frietsch, PeterNeuh?usler, Taehyun Jung, Bart Van Looy. Patent indicators form acroeconomic growth-the value of patents estimated by export volume [J]. Technovation, 2014, 34(9): 546-558. [23] Yu-Shan Chen, Ke-Chiun Chang. The relationship between a firm's patent quality and its market value: The case of US pharmaceutical industry [J]. Technological Forecasting & Social Change, 2010, 77(1): 20-33. [24] Jerak A, Wagner S. Modeling probabilities of patent oppositions in a Bayesian semiparametric regression framework [J]. Empirical Economics, 2006, 31(2): 513-533. [25] Chia-Yi Liu, Hsueh-Liang Wu, Cheng-Yu Lee. The relationship between patent attributes and patent litigation: Considering the moderating effects of managerial characteristics [J]. Asia Pacific Management Review, 2017, 24(5): 1-9.