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A Green Technological Innovation Efficiency Evaluation of Technology-Based SMEs Based on the Undesirable SBM and the Malmquist Index: A Case of Hebei Province in China

Author

Listed:
  • Yongfang Peng

    (School of Management, Hebei GEO University, Shijiazhuang 050031, China)

  • Yingying Fan

    (School of Art, Hebei GEO University, Shijiazhuang 050031, China
    Strategy and Management Base of Mineral Resources in Hebei Province, Hebei GEO University, Shijiazhuang 050031, China)

  • Yi Liang

    (School of Management, Hebei GEO University, Shijiazhuang 050031, China
    Strategy and Management Base of Mineral Resources in Hebei Province, Hebei GEO University, Shijiazhuang 050031, China)

Abstract

Small- and medium-sized technology-based enterprises (technology-based SMEs) are an important part of China’s scientific and technological development. To a certain extent, the green technological innovation level of technology-based SMEs plays a significant role in supporting the overall development of social green innovation. Carrying out research on green technology innovation efficiency evaluations of technology-based SMEs is helpful to find existing problems to provide references for managers. Therefore, this paper proposes an evaluation system based on the undesirable slack based model (SBM) and the Malmquist index model. Firstly, the evaluation index system of the green technological innovation efficiency of technology-based SMEs in Hebei Province was constructed from the perspectives of input and output, in which environmental pollution is included in the evaluation factors of green innovation activities. Then, the undesirable SBM and the Malmquist index model of green technology innovation efficiency evaluation were constructed. Finally, the technological innovation efficiency of technology-based SMEs in Hebei Province in different regions and time nodes was comprehensively calculated and combined with the Malmquist index model to analyze the efficiency changes of technology-based SMEs in Hebei Province over different years. The results show that the overall level of green technological innovation efficiency of technology-based SMEs in Hebei Province is low, and the regional differences in various cities are obvious, but the main trend is rising. The research in this paper can further improve the research results in the field of evaluation of technology-based SMEs and technological innovation efficiency, as well as play an important role in improving the ecological competitiveness and sustainable development capabilities of the products of Hebei’s technology-based SMEs.

Suggested Citation

  • Yongfang Peng & Yingying Fan & Yi Liang, 2021. "A Green Technological Innovation Efficiency Evaluation of Technology-Based SMEs Based on the Undesirable SBM and the Malmquist Index: A Case of Hebei Province in China," Sustainability, MDPI, vol. 13(19), pages 1-19, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11079-:d:651209
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    Cited by:

    1. Lihui Chen & Qiqi Xiao & Jianlin Wang & Zhong Fang, 2023. "Research on Dynamic Evolutionary Efficiency and Regional Differentiation of High-Tech Industrial Chain Networks," Sustainability, MDPI, vol. 15(24), pages 1-23, December.
    2. Xu Dong & Wensi Fu & Yali Yang & Chenguang Liu & Guizhi Xue, 2022. "Study on the Evaluation of Green Technology Innovation Efficiency and Its Influencing Factors in the Central Plains City Cluster of China," Sustainability, MDPI, vol. 14(17), pages 1-24, September.
    3. Mengchao Yao & Jinjun Duan & Qingsong Wang, 2022. "Spatial and Temporal Evolution Analysis of Industrial Green Technology Innovation Efficiency in the Yangtze River Economic Belt," IJERPH, MDPI, vol. 19(11), pages 1-20, May.
    4. Biao Hu & Kai Yuan & Tingyun Niu & Liang Zhang & Yuqiong Guan, 2022. "Study on the Spatial and Temporal Evolution Patterns of Green Innovation Efficiency and Driving Factors in Three Major Urban Agglomerations in China—Based on the Perspective of Economic Geography," Sustainability, MDPI, vol. 14(15), pages 1-28, July.
    5. Xiaonan Fan & Sainan Ren & Yang Liu, 2023. "The Driving Factors of Green Technology Innovation Efficiency—A Study Based on the Dynamic QCA Method," Sustainability, MDPI, vol. 15(12), pages 1-25, June.

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