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Clustering Analysis of Classified Performance Evaluation of Higher Education in Shanghai Based on Topsis Model

Author

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  • Yan Xia

    (School of Economics and Management, Tongji University, Shanghai 200092, China
    Shanghai Joint Laboratory for Discipline Evaluation, Shanghai Education Evaluation Institute, Shanghai 200031, China)

  • Jianxin You

    (School of Economics and Management, Tongji University, Shanghai 200092, China)

  • Xiumeng Feng

    (Shanghai Joint Laboratory for Discipline Evaluation, Shanghai Education Evaluation Institute, Shanghai 200031, China
    School of Public Health, Shanghai Medical College, Fudan University, Shanghai 200032, China)

  • Yingjie Xu

    (Shanghai Joint Laboratory for Discipline Evaluation, Shanghai Education Evaluation Institute, Shanghai 200031, China)

  • Hui Feng

    (Shanghai Joint Laboratory for Discipline Evaluation, Shanghai Education Evaluation Institute, Shanghai 200031, China)

Abstract

Diversification is a fundamental attribute of higher education. With the continuous expansion of the scale, universities and colleges have paid more attention to developing in diversified ways. Diversification is an important way to promote sustainable development of universities and colleges. Sustainable development is the endogenous impetus for the long-term development of higher education. The implementation of classified performance evaluation on higher education is beneficial to optimize fund and resource allocation for different types of universities and colleges, to effectively promote the diversified construction and sustainable development of higher education. Therefore, it becomes extremely important in the reform of higher education in China. It classifies universities and colleges into different types and then implements performance evaluation on the objects of the same type. In this paper, a classified performance evaluation indicator system is established for different types of universities and colleges. Topsis model is used to calculate the relative adjacency between the evaluated objects and the optimal and inferior solutions of all objects. A systematic clustering algorithm is made to analyze and evaluate the performance of universities and colleges in the same type. An automatic system is developed to analyze data from 62 universities and colleges in Shanghai. It provides advice and guidance for the development strategy of higher education.

Suggested Citation

  • Yan Xia & Jianxin You & Xiumeng Feng & Yingjie Xu & Hui Feng, 2023. "Clustering Analysis of Classified Performance Evaluation of Higher Education in Shanghai Based on Topsis Model," Sustainability, MDPI, vol. 15(8), pages 1-18, April.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:8:p:6946-:d:1128446
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    References listed on IDEAS

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