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How to Evaluate Smart Cities’ Construction? A Comparison of Chinese Smart City Evaluation Methods Based on PSF

Author

Listed:
  • Hongbo Shi

    (School of Economics and Management, Harbin Institute of Technology, Weihai 264209, China)

  • Sang-Bing Tsai

    (Zhongshan Institute, University of Electronic Science and Technology of China, Zhongshan 528402, China)

  • Xiaowei Lin

    (School of Economics and Management, Harbin Institute of Technology, Weihai 264209, China)

  • Tianyi Zhang

    (School of Economics and Management, Harbin Institute of Technology, Weihai 264209, China)

Abstract

With the rapid development of smart cities in the world, research relating to smart city evaluation has become a new research hotspot in academia. However, there are general problems of cognitive deprivation, lack of planning experience, and low level of coordination in smart cities construction. It is necessary for us to develop a set of scientific, reasonable, and effective evaluation index systems and evaluation models to analyze the development degree of urban wisdom. Based on the theory of the urban system, we established a comprehensive evaluation index system for urban intelligent development based on the people-oriented, city-system, and resources-flow (PSF) evaluation model. According to the characteristics of the comprehensive evaluation index system of urban intelligent development, the analytic hierarchy process (AHP) combined with the experts’ opinions determine the index weight of this system. We adopted the neural network model to construct the corresponding comprehensive evaluation model to characterize the non-linear characteristics of the comprehensive evaluation indexes system, thus to quantitatively quantify the comprehensive evaluation indexes of urban intelligent development. Finally, we used the AHP, AHP-BP (Back Propagation), and AHP-ELM (Extreme Learning Machine) models to evaluate the intelligent development level of 151 cities in China, and compared them from the perspective of model accuracy and time cost. The final simulation results show that the AHP-ELM model is the best evaluation model.

Suggested Citation

  • Hongbo Shi & Sang-Bing Tsai & Xiaowei Lin & Tianyi Zhang, 2017. "How to Evaluate Smart Cities’ Construction? A Comparison of Chinese Smart City Evaluation Methods Based on PSF," Sustainability, MDPI, vol. 10(1), pages 1-16, December.
    • Handle: RePEc:gam:jsusta:v:10:y:2017:i:1:p:37-:d:124274
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    References listed on IDEAS

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    1. Renata Paola Dameri & Camille Rosenthal-Sabroux (ed.), 2014. "Smart City," Progress in IS, Springer, edition 127, number 978-3-319-06160-3, June.
    2. Lombardi, P. & Giordano, S. & Caragliu, A. & Del Bo, C., 2011. "An advanced triple-helix network model for smart cities performance," Serie Research Memoranda 0045, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    3. Lazaroiu, George Cristian & Roscia, Mariacristina, 2012. "Definition methodology for the smart cities model," Energy, Elsevier, vol. 47(1), pages 326-332.
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    Cited by:

    1. Wang, Mengmeng & Zhou, Tao & Wang, Di, 2020. "Tracking the evolution processes of smart cities in China by assessing performance and efficiency," Technology in Society, Elsevier, vol. 63(C).
    2. Sławomira Hajduk, 2021. "Multi-Criteria Analysis of Smart Cities on the Example of the Polish Cities," Resources, MDPI, vol. 10(5), pages 1-23, May.
    3. Yi Tao & Shihang Wang & Jiang Wu & Mingsong Zhao & Zhen Yang, 2022. "Logistic Network Construction and Economic Linkage Development in the Guangdong-Hong Kong-Macao Greater Bay Area: An Analysis Based on Spatial Perspective," Sustainability, MDPI, vol. 14(23), pages 1-21, November.
    4. Wang, Mengmeng & Zhou, Tao, 2022. "Understanding the dynamic relationship between smart city implementation and urban sustainability," Technology in Society, Elsevier, vol. 70(C).
    5. Guijun Li & Yongsheng Wang & Jie Luo & Yulong Li, 2018. "Evaluation on Construction Level of Smart City: An Empirical Study from Twenty Chinese Cities," Sustainability, MDPI, vol. 10(9), pages 1-18, September.

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