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Patent value assessment and commercialization strategy

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  • Hsieh, Chih-Hung

Abstract

It is difficult to assess the value of a patent before it is commercialized in the market. In this study, the author presents a hybrid method of assessing patent value and determining strategy in the early stage of commercialization. The author uses empirical data from Yuan Ze University to test the method. As a result of his analysis, the author categorized patents into four groups according to benefits and risk factors extracted from a factor analysis, and for each group of patents the author offers possible strategies for further commercialization. The method, which uses fuzzy measurement to pinpoint the location of a patent in a matrix with great precision, is more accurate than traditional technology portfolio planning models that rely on Likert scales. The method can highlight change in the meaning and strategic grouping of a patent. Furthermore, it can be used for long-term strategic planning, such as strategic foresight and corporate foresight.

Suggested Citation

  • Hsieh, Chih-Hung, 2013. "Patent value assessment and commercialization strategy," Technological Forecasting and Social Change, Elsevier, vol. 80(2), pages 307-319.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:2:p:307-319
    DOI: 10.1016/j.techfore.2012.09.014
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    Citations

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    Cited by:

    1. Su, Hsin-Ning, 2017. "Collaborative and Legal Dynamics of International R&D- Evolving Patterns in East Asia," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 217-227.
    2. Shen, Huijun & Coreynen, Wim & Huang, Can, 2023. "Prestige and technology-transaction prices: Evidence from patent-selling by Chinese universities," Technovation, Elsevier, vol. 123(C).
    3. Liu, Li-jun & Cao, Cong & Song, Min, 2014. "China's agricultural patents: How has their value changed amid recent patent boom?," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 106-121.
    4. Santiago, Leonardo P. & Martinelli, Marcela & Eloi-Santos, Daniel T. & Hortac, Luciana Hashiba, 2015. "A framework for assessing a portfolio of technologies for licensing out," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 242-251.
    5. Hsueh, Chao-Chih & Chen, Dar-Zen, 2015. "A taxonomy of patent strategies in Taiwan's small and medium innovative enterprises," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 84-98.
    6. Yuan Zhou & Meijuan Pan & Frauke Urban, 2018. "Comparing the International Knowledge Flow of China’s Wind and Solar Photovoltaic (PV) Industries: Patent Analysis and Implications for Sustainable Development," Sustainability, MDPI, vol. 10(6), pages 1-34, June.
    7. Lee, Pei-Chun & Su, Hsin-Ning, 2014. "How to forecast cross-border patent infringement? — The case of U.S. international trade," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 125-131.
    8. Grimaldi, Michele & Cricelli, Livio & Di Giovanni, Martina & Rogo, Francesco, 2015. "The patent portfolio value analysis: A new framework to leverage patent information for strategic technology planning," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 286-302.
    9. Hong-Hua Qiu & Jing Yang, 2018. "An Assessment of Technological Innovation Capabilities of Carbon Capture and Storage Technology Based on Patent Analysis: A Comparative Study between China and the United States," Sustainability, MDPI, vol. 10(3), pages 1-20, March.
    10. Hu, Jiangfeng & Pan, Xinxin & Huang, Qinghua, 2020. "Quantity or quality? The impacts of environmental regulation on firms’ innovation–Quasi-natural experiment based on China's carbon emissions trading pilot," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    11. Youngjae Choi & Sanghyun Park & Sungjoo Lee, 2021. "Identifying emerging technologies to envision a future innovation ecosystem: A machine learning approach to patent data," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5431-5476, July.
    12. Verónica Sansabas-Villalpando & Iván Juan Carlos Pérez-Olguín & Luis Asunción Pérez-Domínguez & Luis Alberto Rodríguez-Picón & Luis Carlos Mendez-González, 2019. "CODAS HFLTS Method to Appraise Organizational Culture of Innovation and Complex Technological Changes Environments," Sustainability, MDPI, vol. 11(24), pages 1-28, December.
    13. Bi, Kexin & Huang, Ping & Ye, Hui, 2015. "Risk identification, evaluation and response of low-carbon technological innovation under the global value chain: A case of the Chinese manufacturing industry," Technological Forecasting and Social Change, Elsevier, vol. 100(C), pages 238-248.
    14. Hu, Zewen & Zhou, Xiji & Lin, Angela, 2023. "Evaluation and identification of potential high-value patents in the field of integrated circuits using a multidimensional patent indicators pre-screening strategy and machine learning approaches," Journal of Informetrics, Elsevier, vol. 17(2).
    15. Xipeng Liu & Xinmiao Li, 2022. "Early Identification of Significant Patents Using Heterogeneous Applicant-Citation Networks Based on the Chinese Green Patent Data," Sustainability, MDPI, vol. 14(21), pages 1-27, October.
    16. Mohd Shadab Danish & Pritam Ranjan & Ruchi Sharma, 2022. "Assessing the Impact of Patent Attributes on the Value of Discrete and Complex Innovations," Papers 2208.07222, arXiv.org.
    17. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    18. Huang, Kenneth Guang-Lih & Huang, Can & Shen, Huijun & Mao, Hao, 2021. "Assessing the value of China's patented inventions," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    19. Mohd Shadab Danish & Pritam Ranjan & Ruchi Sharma, 2021. "Identification of “Valuable” Technologies via Patent Statistics in India: An Analysis Based on Renewal Information," BASE University Working Papers 13/2021, BASE University, Bengaluru, India.
    20. Erzurumlu, S. Sinan & Pachamanova, Dessislava, 2020. "Topic modeling and technology forecasting for assessing the commercial viability of healthcare innovations," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    21. Wang, Benjamin & Hsieh, Chih-Hung, 2015. "Measuring the value of patents with fuzzy multiple criteria decision making: insight into the practices of the Industrial Technology Research Institute," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 263-275.
    22. Cheng, Yu & Huang, Lucheng & Ramlogan, Ronnie & Li, Xin, 2017. "Forecasting of potential impacts of disruptive technology in promising technological areas: Elaborating the SIRS epidemic model in RFID technology," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 170-183.
    23. Noh, Heeyong & Lee, Sungjoo, 2020. "What constitutes a promising technology in the era of open innovation? An investigation of patent potential from multiple perspectives," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    24. Yuya Kajikawa, 2022. "Reframing evidence in evidence-based policy making and role of bibliometrics: toward transdisciplinary scientometric research," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(9), pages 5571-5585, September.

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