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RETRACTED ARTICLE: Assessing the efficiency of innovation entities in China: evidence from a nonhomogeneous data envelopment analysis and Tobit

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This article was retracted on 15 April 2024

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Abstract

Universities, research institutes, and firms are the main entities in the national innovation system. Owing to the heterogeneity of their outputs, prior studies have focused on their independent efficiency evaluation. This study adopts the nonhomogeneous data envelopment analysis model to assess the efficiency of three innovation entities in 30 provinces in China on a common platform. Results show that firms have the highest efficiency, and research institutes have the lowest efficiency. Innovation entities perform poorly due to the inefficiency of their subunits. Additionally, the 30 provinces are divided into three clusters by using the hierarchical clustering method. Moreover, Tobit regressions are used to estimate the impact of five environmental factors on the innovation efficiency of the three entities. The regression results show that the more open the region, the stronger the positive impact on the innovation efficiency of research institutes and firms. The regional economic environment has different degrees of negative impact on the three innovation entities. The direction and intensity of the impact of education input, government support, and information infrastructure on the three entities exhibit a large dispersion. The results provide important information for improving the efficiency of innovation entities.

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Abbreviations

DEA:

Data envelopment analysis

IT:

Information technology

MIMO:

Multiple input, multiple output

DMU:

Decision-making unit

R&D:

Research and development

RDP:

R&D personnel

RDE:

R&D expenditures

NPA:

Number of patent applications

CSYS:

China Statistical Yearbook on Science and Technology

SPI:

Scientific papers issued

NPG:

Number of Postgraduates

SRN:

Sales revenue of new products

FTE:

Full-time equivalent

USPTO:

United States patent and trademark office

ESYC:

Educational Statistics Yearbook of China

CPI:

Consumer price index

SPSS:

Statistical package for social sciences

GDP:

Gross domestic product

CSY:

China Statistical Yearbook

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Acknowledgements

This research was supported by the National Natural Science Foundation of China (71991464, 71921001, and 71671001), and Department of Education of Zhejiang Province (Y202147829).

Author information

Authors and Affiliations

  1. School of Economics and Management, Anhui Polytechnic University, Wuhu, 241000, Anhui, People’s Republic of China

    Yu Zhu & Bengang Gong

  2. School of Management, University of Science and Technology of China, Hefei, 230026, Anhui, People’s Republic of China

    Yu Zhu & Feng Yang

  3. School of Mechanical Engineering and Automation, Zhejiang Sci-Tech University, Hangzhou, 310000, Zhejiang, People’s Republic of China

    Wei Zeng

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  1. Yu Zhu
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Correspondence to Wei Zeng.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s10660-024-09844-3

Appendix

Appendix

See Tables 9,

Table 9 Innovation efficiency of universities in 30 provinces of China from 2012–2019
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Table 10 Innovation efficiency of research institutes in 30 provinces of China from 2012–2019
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10,

Table 11 Innovation efficiency of firms in 30 provinces of China from 2012–2019
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11,

Table 12 Estimation result of the Tobit regressions
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12.

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Zhu, Y., Yang, F., Gong, B. et al. RETRACTED ARTICLE: Assessing the efficiency of innovation entities in China: evidence from a nonhomogeneous data envelopment analysis and Tobit. Electron Commer Res 23, 175–205 (2023). https://doi.org/10.1007/s10660-022-09599-9

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