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Assessing the relative efficiency of Chinese high-tech industries: a dynamic network data envelopment analysis approach

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Abstract

The high-tech industry in China has largely developed in recent decades. To provide a basis for the sustainable development of high-tech industry, the government should evaluate its performance to find out its strengths and weaknesses that are critical for the future improvement of business operations. Dynamic network data envelopment analysis has received considerable attention from researchers evaluating the performance of a system during long-term production. However, studies on the issue of shared outputs caused by the lagged production effect of inputs are rare. In a real high-tech industry, the outputs during a production period are derived from the inputs in that production period and also from the inputs in the previous period. These intertemporal shared outputs in a system cannot be easily divided into different periods. Thus, a new dynamic two-stage data envelopment analysis approach is proposed to measure the efficiency of such system with a two-stage structure and shared outputs. We divide a high-tech activity system into two stages: technology research and development stage and technology digestion and absorption stage, where intertemporal shared outputs occur. Empirical results from our approach indicate that Chinese high-tech industries are weak in the technology digestion and absorption stage. Finally, suggestions are provided to improve the overall efficiency of Chinese high-tech industries.

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Acknowledgements

The research is supported by National Natural Science Foundation of China (No. 71501189; 71571192), Natural Science Foundation of Hunan Province (2017JJ3397), the open project of “Mobile Health” Ministry of Education-China Mobile Joint Laboratory of Central South University, the Innovation-Driven Project of Central South University (No. 2018CX039), the State Key Program of National Natural Science of China (Nos. 71431006, 71631008). Major Project for National Natural Science Foundation of China (71790615). Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Hunan University of Commerce (2017TP1026).

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Authors and Affiliations

  1. School of Business, Central South University, Changsha, 410083, China

    Qingxian An, Fanyong Meng, Zongrun Wang & Xiaohong Chen

  2. Industrial Systems Optimization Laboratory, Charles Delaunay Institute and UMR CNRS 6281, University of Technology of Troyes, 10004, Troyes, France

    Qingxian An & Beibei Xiong

  3. School of Management, University of Science and Technology of China, Hefei, 230026, China

    Beibei Xiong

  4. Key Laboratory of Hunan Province for Mobile Business Intelligence, Hunan University of Commerce, Changsha, 410205, China

    Xiaohong Chen

  5. Mobile E-business 2011 Collaborative Innovation Center of Hunan Province, Hunan University of Commerce, Changsha, 410205, China

    Xiaohong Chen

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  1. Qingxian An
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Correspondence to Beibei Xiong.

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An, Q., Meng, F., Xiong, B. et al. Assessing the relative efficiency of Chinese high-tech industries: a dynamic network data envelopment analysis approach. Ann Oper Res 290, 707–729 (2020). https://doi.org/10.1007/s10479-018-2883-2

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