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Profitability decided by patent quality? An empirical study of the U.S. semiconductor industry

Author

Listed:
  • Yin-Hui Cheng

    (National Taichung University)

  • Fu-Yung Kuan

    (National Kaohsiung First University of Science and Technology)

  • Shih-Chieh Chuang

    (National Chung Cheng University)

  • Yun Ken

    (National Yunlin University of Science and Technology)

Abstract

The investment in research and development (R&D) for semiconductor industry is never small as the technology cycle time (TCT) is relatively short comparing to other industries, thus a semiconductor company requires lots of technological innovations and capital offerings to maintain. The semiconductor industry contributes primarily part of the micro-electronic industries. Advancing technology and patent application are the centre of attention within the semiconductor sector. This research examines the relationship between patent quality and the profits a patent creates for a company in this selected field. This study distinguishes itself from prior research by including cross-sectional data, time series data to simultaneously collect and analyze. The study result shows that some indicators of patent quality are statistically significant to return on assets.

Suggested Citation

  • Yin-Hui Cheng & Fu-Yung Kuan & Shih-Chieh Chuang & Yun Ken, 2010. "Profitability decided by patent quality? An empirical study of the U.S. semiconductor industry," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 175-183, January.
    • Handle: RePEc:spr:scient:v:82:y:2010:i:1:d:10.1007_s11192-009-0080-4
    DOI: 10.1007/s11192-009-0080-4
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    References listed on IDEAS

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    1. Hausman, Jerry, 2015. "Specification tests in econometrics," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 38(2), pages 112-134.
    2. Hagedoorn, John & Cloodt, Myriam, 2003. "Measuring innovative performance: is there an advantage in using multiple indicators?," Research Policy, Elsevier, vol. 32(8), pages 1365-1379, September.
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    Cited by:

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    2. Mónica Benito & Rosario Romera, 2012. "Modeling the enrollment demand of masters programs for the Spanish public university system," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 113-130, April.
    3. Toshiyuki Sueyoshi & Youngbok Ryu, 2020. "Performance Assessment of the Semiconductor Industry: Measured by DEA Environmental Assessment," Energies, MDPI, vol. 13(22), pages 1-24, November.
    4. Lee, Changyong & Cho, Yangrae & Seol, Hyeonju & Park, Yongtae, 2012. "A stochastic patent citation analysis approach to assessing future technological impacts," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 16-29.
    5. Ahmad Barirani & Bruno Agard & Catherine Beaudry, 2013. "Discovering and assessing fields of expertise in nanomedicine: a patent co-citation network perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1111-1136, March.
    6. Fiorenzo Franceschini & Domenico Maisano, 2012. "Publication and patent analysis of European researchers in the field of production technology and manufacturing systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(1), pages 89-100, October.
    7. Hsiao, Shu-Hua, 2014. "PTE, innovation capital and firm value interactions in the biotech medical industry," Journal of Business Research, Elsevier, vol. 67(12), pages 2636-2644.
    8. Chihmao Hsieh, 2011. "Explicitly searching for useful inventions: dynamic relatedness and the costs of connecting versus synthesizing," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 381-404, February.

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