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The R&D value-chain efficiency measurement for high-tech industries in China

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  • Yung-ho Chiu
  • Chin-wei Huang
  • Yu-Chuan Chen

Abstract

This study constructs the research and development (R&D) and operation processes as a value-chain framework, in which R&D results in the successful applications of patents. These patents are then used to generate final outputs in the operation. We introduce an empirical model extended from the value-chain model to compute the R&D and the operation efficiencies for 21 of China’s high-tech businesses in a single implementation. The findings are presented as follows. First, R&D efficiency is not related to operation efficiency. Second, communication businesses have relatively higher performance in R&D and operation efficiencies, whereas electronics and computer businesses have high operation efficiency, but low R&D efficiency. Finally, for improving the efficiencies, the patents that do not effectively create value should be reduced. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Yung-ho Chiu & Chin-wei Huang & Yu-Chuan Chen, 2012. "The R&D value-chain efficiency measurement for high-tech industries in China," Asia Pacific Journal of Management, Springer, vol. 29(4), pages 989-1006, December.
    • Handle: RePEc:kap:asiapa:v:29:y:2012:i:4:p:989-1006
    DOI: 10.1007/s10490-010-9219-3
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    7. Lin, Shoufu & Lin, Ruoyun & Sun, Ji & Wang, Fei & Wu, Weixiang, 2021. "Dynamically evaluating technological innovation efficiency of high-tech industry in China: Provincial, regional and industrial perspective," Socio-Economic Planning Sciences, Elsevier, vol. 74(C).
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    13. Wang, Qunwei & Hang, Ye & Sun, Licheng & Zhao, Zengyao, 2016. "Two-stage innovation efficiency of new energy enterprises in China: A non-radial DEA approach," Technological Forecasting and Social Change, Elsevier, vol. 112(C), pages 254-261.
    14. Liu, Hui-hui & Yang, Guo-liang & Liu, Xiao-xiao & Song, Yao-yao, 2020. "R&D performance assessment of industrial enterprises in China: A two-stage DEA approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    15. Dongphil Chun & Yanghon Chung & Chungwon Woo & Hangyeol Seo & Hyesoo Ko, 2015. "Labor Union Effects on Innovation and Commercialization Productivity: An Integrated Propensity Score Matching and Two-Stage Data Envelopment Analysis," Sustainability, MDPI, vol. 7(5), pages 1-19, April.
    16. Wan, Qunchao & Chen, Jin & Yao, Zhu & Yuan, Ling, 2022. "Preferential tax policy and R&D personnel flow for technological innovation efficiency of China's high-tech industry in an emerging economy," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    17. Ebersberger, Bernd & Feit, Margarita & Mengis, Helen, 2023. "International knowledge interactions and catch-up. Evidence from European patent data for Chinese latecomer firms," International Business Review, Elsevier, vol. 32(2).

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