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Evaluation of Scientific and Technological Innovation Capability in Guangzhou Based on Cross-Efficiency DEA

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Application of Intelligent Systems in Multi-modal Information Analytics (MMIA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1233))

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Abstract

With the rapid development of the society, scientific and technological innovation has become a hot topic. This paper firstly constructs an evaluation index system for Guangzhou’s scientific and technological innovation ability. As we know that the traditional DEA model only pays attention to its own superiority index, ignoring the problem that there are too many effective units, which lead to the inability to give accurate ranking results of effective decision-making units. In order to overcome the limitations of the DEA model, this paper uses three types of cross-efficiency DEA models, including the friendly, confrontational and neutral type, to obtain the efficiency values and precise ranking of each decision-making unit. The results show that the three methods have differences, but they all passed the Kendall’s W test. In addition, this paper uses the vertical analysis to classify the scientific and technological innovation ability of each district of Guangzhou.

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Acknowledgements

This research was supported by the “Humanities and Social Sciences Research and Planning Fund of the Ministry of Education of China, No. x2lxY9180090”, “Natural Science Foundation of Guangdong Province, No. 2019A1515011038”, “Soft Science of Guangdong Province, and No. 2018A070712002, 2019A101002118”, and “Fundamental Research Funds for the Central Universities of China, No. x2lxC2180170”. The authors are highly grateful to the referees and editor in-chief for their very helpful comments.

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Authors and Affiliations

  1. School of Mathematics, South China University of Technology, Guangzhou, 510640, Guangdong, China

    Xue Deng, Ying Liang & Chuangjie Chen

  2. School of Finance, Shandong University, Jinan, 250100, Shandong, China

    Luyao Feng

  3. Department of Mechanical Engineering, Guangdong College of Industry and Commerce, Guangzhou, 510510, Guangdong, China

    Junfeng Zhao

Authors
  1. Xue Deng
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  2. Ying Liang
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  3. Luyao Feng
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  4. Chuangjie Chen
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  5. Junfeng Zhao
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Corresponding author

Correspondence to Junfeng Zhao .

Editor information

Editors and Affiliations

  1. Department of Decision and Information Sciences, and Center for Data Science and Big Data Analytics, Oakland University, School of Business Administration, Rochester, MI, USA

    Vijayan Sugumaran

  2. Shanghai University of Medicine and Health Sciences, Shanghai, China

    Zheng Xu

  3. Department of Informatics, University of Leicester, Leicester, UK

    Huiyu Zhou

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Deng, X., Liang, Y., Feng, L., Chen, C., Zhao, J. (2021). Evaluation of Scientific and Technological Innovation Capability in Guangzhou Based on Cross-Efficiency DEA. In: Sugumaran, V., Xu, Z., Zhou, H. (eds) Application of Intelligent Systems in Multi-modal Information Analytics. MMIA 2020. Advances in Intelligent Systems and Computing, vol 1233. Springer, Cham. https://doi.org/10.1007/978-3-030-51431-0_108

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