Welcome to Francis Academic Press

The Frontiers of Society, Science and Technology, 2023, 5(8); doi: 10.25236/FSST.2023.050806.

Research on Correlation Control of Subjective Patent Indicators Based on Progressive Constraint

Author(s)

Bingxiu Gui, Wen Jiang, Huyuan Zhang

Corresponding Author:
Wen Jiang
Affiliation(s)

China Center for Information Industry Development, Beijing, China

Abstract

Patent indicator evaluation is a relatively objective patent quality evaluation method recognized by academia. Some subjective patent indicators are often related, which to some extent interferes with the objectivity of patent evaluation. This study selects five commonly used subjective patent indicators that are directly related to the compilers of patent documents, which includes patent forward citations, patent family, four digit international patent classifications, patentees, and patent inventors. Through the progressive limitation of the three constraints of patentees, patent priority countries, and patent disclosure years, the correlation between the subjective patent indicators is compared. The research results show that under the control of progressive constraint conditions, the positive correlation between subjective patent indicators is increasingly strengthened as a whole and has strong controllability. Further verification shows that the direct compilers of patent documents can affect the results of patent indicator evaluation by controlling the subjective patent indicator data, thus interfering with the evaluation of patent quality. It is recommended that researchers carefully select multiple subjective patent indicators with strong correlation before using patent indicators to evaluate patent quality, and complete the correlation analysis and screening of subjective patent indicators in advance.

Keywords

Subjective patent indicators; Correlation control; Progressive constraint; Influence factor

Cite This Paper

Bingxiu Gui, Wen Jiang, Huyuan Zhang. Research on Correlation Control of Subjective Patent Indicators Based on Progressive Constraint. The Frontiers of Society, Science and Technology (2023) Vol. 5, Issue 8: 39-46. https://doi.org/10.25236/FSST.2023.050806.

References

[1] Oh J H, Hong J W, You Y Y, et al. Effects of patent indicators on national technological level: concentrated on mobile communication, network, and convergence technologies. Cluster Computing, 2016, 19(1): 519-528.

[2] Harhoff D, Hoisl K. Institutionalized incentives for ingenuity—patent value and the German Employees’ Inventions Act. Research Policy, 2007, 36(8): 1143-1162.

[3] Sohn S Y, Lee W S, Ju Y H. Valuing academic patents and intellectual properties: Different perspectives of willingness to pay and sell. Technovation, 2013, 33(1): 13-24.

[4] Wang Qingshi. Introduction to Statistical Indicators. Northeast University of Finance and Economics Press, 1994.

[5] Zhou Guofu. The Best Method for Evaluating Regional Economic Levels. Zhejiang Statistics, 1998, (6): 9-11.

[6] Hu Yonghong, He Sihui. Comprehensive Evaluation Methods. Science Press, 2000.

[7] Zhang Chongfu, Hu Xiling, Chen Shuyun. Statistical Analysis Methods and Their Applications. Chongqing University Press, 1995.

[8] Liu Jifei. Research on the Treatment Methods of Evaluation Index Correlation. Management Observation, 2006, (12): 50-51.

[9] Banerjee, P., B.M. Gupta, and K.C. Garg. Patent statistics as indicators of competition an analysis of patenting in biotechnology. Scientometrics, 2000. 47(1): 95-116.

[10] Bryant K. and L. Lombardo. Broad-level indicators for national systems of science and innovation: A new approach. Proceedings of 8th International Conference on Scientometrics and Informetrics, 2001, (1): 75-88.

[11] Lai K.K., S.M. Chang, and S.B. Chang. Using patent citation to explore knowledge flow between different industries. Proceedings of PICMET '07-2007 Portland International Conference on Management of Engineering & Technology, 2007, (6): 1777-1783.

[12] de la Potterie, B.V. and N. van Zeebroeck. A brief history of space and time: The scope-year indicator as a patent value indicator based on families and renewals. Scientometrics, 2008. 75(2): 319-338.

[13] Guan J.C. and X. Gao. Exploring the h-indicator at Patent Level. Journal of the American Society for Information Science and Technology, 2009, 60(1): 35-40.

[14] Zhang X., et al. Study on Indicator System for Core Patent Documents Evaluation. Proceedings of ISSI 2009 - 12th International Conference of the International Society for Scientometrics and Informetrics, 2009, 1(1): 154-164.

[15] Chang S.B. Using patent analysis to establish technological position: Two different strategic approaches. Technological Forecasting and Social Change, 2012, 79(1): 3-15.

[16] Trappey A.J.C., et al. A patent quality analysis for innovative technology and product development. Advanced Engineering Informatics, 2012, 26(1): 26-34.

[17] Kuan C.H., M.H. Huang, and D.Z. Chen. Ranking patent assignee performance by h-indicator and shape descriptors. Journal of Informetrics, 2011. 5(2): 303-312.

[18] Bakker J., et al. Patent citation indicators: One size fits all. Scientometrics, 2016, 106(1): 187-211.

[19] Yang Yang, Liu Wenfei, Ding Kun. Construction and Empirical Study on Evaluation Indicators of Patent Technology Transfer Performance in Universities. Science Research Management, 2022, 43(07): 189-199. DOI: 10.19571/j.cnki.1000-2995.2022.07.022.

[20] Hua Zhilei, Liu Yajuan. Hierarchical Evaluation of Patents in Chinese Universities. Science and Technology Management Research, 2022, 42(16): 45-54.

[21] Liu Yun, Gui Bingxiu, An Yuan, Cheng Yijie. Comparison of competitiveness of high-speed rail equipment manufacturers and China's high-speed rail "going out" countermeasures. Scientific Research Management, 2016, (S1):346-355.