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Research on Technological Innovation Efficiency of China’s High-Tech Industry Based on Network SBM Model and DEA Window Analysis

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Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013)

Abstract

The paper combines network SBM model with DEA window analysis to measure the technological innovation efficiency of China’s high-tech industry during 2000–2011. The research indicates that the overall efficiency of technological innovation of the high-tech industry shows a rising trend in the past 10 years, and the outbreak of the financial crisis has a negative impact on the efficiency of technological innovation in the short term. The efficiency values of technological innovation are still not high, and there is structural imbalance between R&D efficiency and conversion efficiency in the long term. The difference of the conversion efficiency among the industry segments shows trend of convergence, but the difference of R&D efficiency expands after the financial crisis.

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References

  1. Sexton TR, Lewis HF (2003) Two-stage DEA: an application to major league baseball. J Prod Anal 19(2–3):227–249

    Article  Google Scholar 

  2. Xiao ZL, Feng SX, Han SHF (2012) Calculation on high-tech industry’ two stage efficiency and analysis on its improving path in China-based on the SBM directional distance function (in Chinese). Ind Econ Res 11(4):10–18

    Google Scholar 

  3. Yu YZ (2009) Research on then technological innovation efficiency and influence factors of Chinese high-tech industry—two-stage analysis based on the perspective of value chain (in Chinese). Econ Sci 31(4):62–74

    Google Scholar 

  4. Liu HD, Chen C (2011) Evaluation research on the innovation efficiency of high-tech industry in China—two-stage analysis based on the perspective of innovation chain (in Chinese). Sci Technol Prog Policy 28(12):119–124

    Google Scholar 

  5. Chen W, Feng ZJ, Jiang HM, Kang X (2010) Evaluation research on the innovation efficiency of regional innovation systems of China—a new view based on chain relational network DEA model (in Chinese). J Intell 29(12):24–29

    Google Scholar 

  6. Qian L, Chen ZW, Xiao RQ (2012) Research on innovation efficiency of high-tech industry in Anhui Province: from perspective of value chain with two stages (in Chinese). Technol Econ 31(8):50–57

    Google Scholar 

  7. Yin WH (2012) The research on technological innovation efficiency of China’s regional high-tech industries: based on objective weighted NSBM model (in Chinese). Stat Info Forum 27(8):99–106

    Google Scholar 

  8. Feng F, Ma L, Zhang LY (2011) Research on efficiency of China’s S&T input-output in two-stage chain perspective: based on the data from 17 sub-industries of high-tech industry (in Chinese). Sci Sci Manage S & T 32(10):21–26

    Google Scholar 

  9. Kao C (2009) Efficiency decomposition in network data envelopment analysis: a relational model. Eur J Oper Res 192(3):949–962

    Article  Google Scholar 

  10. Wei QL, Pang LY (2010) Chain network DEA model (in Chinese). Math Pract Theory 40(1):213–221

    Google Scholar 

  11. Yu MM (2010) Assessment of airport performance using the SBM-NDEA model. Omega 38(6):440–452

    Article  Google Scholar 

  12. Lozano S, Gutiérrez E, Moreno P (2013) Network DEA approach to airports performance assessment considering undesirable outputs. Appl Math Model 37(4):1665–1676

    Article  Google Scholar 

  13. Tone K, Tsutsui M (2009) Network DEA: a slacks-based measure approach. Eur J Oper Res 197(5):243–252

    Article  Google Scholar 

  14. Klopp G (1985) The analysis of the efficiency of production system with multiple inputs and outputs. Master thesis, Chicago University of Illinois

    Google Scholar 

  15. Zhang YH, Feng XM (2009) Efficiency analysis of regional economy in Jiangsu Province with DEA window analysis (in Chinese). J Syst Manage 18(4):428–431

    Google Scholar 

  16. Cheng LW, Sun W, Wang JY (2011) High-tech innovation efficiency under the condition of incomplete factor market—on the perspective of scale and allocation efficiency based on three-stage DEA-window (in Chinese). Stud Sci Sci 29(6):930–938

    Google Scholar 

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Correspondence to Jian-li Chen .

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Chen, Jl., Meng, Lj. (2014). Research on Technological Innovation Efficiency of China’s High-Tech Industry Based on Network SBM Model and DEA Window Analysis. In: Qi, E., Shen, J., Dou, R. (eds) Proceedings of 2013 4th International Asia Conference on Industrial Engineering and Management Innovation (IEMI2013). Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40060-5_86

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