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A novel approach for urbanization level evaluation based on information entropy principle: A case of Beijing

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  • Zhao, Jingjing
  • Chai, Lihe

Abstract

Urbanization level evaluation (ULE) is an important scientific basis for guiding urban managers to make decisions. By introducing information entropy to describe the interactions between all indicators, a holistic structural parameter ξ, its dynamic equation and self-organizing feature map simulation technique are derived to describe the structural evolution of the indicator network. In this way, a novel ULE model is universally proposed. Then, we use the model to assess the evolutionary urbanization level of Beijing during 2005–2012. We calculate structural parameter ξ values of the indicator network with 35 microscopic indicators as nodes. The results show Beijing’s urbanization level has ever kept increasing. Large increase of ξ values in 2008 and 2012 represented significant improvements of urbanization level in these two years, while a rapid adjustment of urbanization development occurred in 2010. Five meso-scopic subsystems as urban construction, economic development, social development, ecological environment and urban–rural development affected Beijing’s urbanization level in different ways. The radar chart of the model shows the contributions of economic development and urban–rural development to Beijing’s urbanization changed most, while poor coordination of urban–rural development largely existed. By showing Beijing’s ULE based on two analytical ways, we further discuss the objectivity and flexibility in choosing indicator network. Finally, beyond the application case, we discuss the universality and superiority of the new model.

Suggested Citation

  • Zhao, Jingjing & Chai, Lihe, 2015. "A novel approach for urbanization level evaluation based on information entropy principle: A case of Beijing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 430(C), pages 114-125.
  • Handle: RePEc:eee:phsmap:v:430:y:2015:i:c:p:114-125
    DOI: 10.1016/j.physa.2015.02.039
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    References listed on IDEAS

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    1. Du, Huibin & Xia, Qiongqiong & Ma, Xuan & Chai, Lihe, 2014. "A new statistical dynamic analysis of ecological niches for China’s financial centres," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 476-486.
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    5. Deng Chen & Yanxia Wang & Fu Ren & Qingyun Du, 2016. "Spatio-Temporal Differentiation of Urban-Rural Equalized Development at the County Level in Chengdu," Sustainability, MDPI, vol. 8(5), pages 1-17, April.
    6. Wei Qi & Ying Gao & Qian Zhang, 2017. "Spatiotemporal Dynamics of Beijing’s Urbanization Efficiency from 2005 to 2014," Sustainability, MDPI, vol. 9(12), pages 1-17, November.
    7. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2020. "Effects of urbanization on energy efficiency in China: New evidence from short run and long run efficiency models," Energy Policy, Elsevier, vol. 147(C).
    8. Lin Ding & Zhenfeng Shao & Hanchao Zhang & Cong Xu & Dewen Wu, 2016. "A Comprehensive Evaluation of Urban Sustainable Development in China Based on the TOPSIS-Entropy Method," Sustainability, MDPI, vol. 8(8), pages 1-23, August.
    9. Yanjing Zhang & Zhengguo Su & Guan Li & Yuefei Zhuo & Zhongguo Xu, 2018. "Spatial-Temporal Evolution of Sustainable Urbanization Development: A Perspective of the Coupling Coordination Development Based on Population, Industry, and Built-Up Land Spatial Agglomeration," Sustainability, MDPI, vol. 10(6), pages 1-20, May.
    10. Cheng, Zhuo & Kai, Zhe & Zhu, Shouwenjun, 2023. "Does green finance regulation improve renewable energy utilization? Evidence from energy consumption efficiency," Renewable Energy, Elsevier, vol. 208(C), pages 63-75.
    11. Cong Xu & Shixin Wang & Yi Zhou & Litao Wang & Wenliang Liu, 2016. "A Comprehensive Quantitative Evaluation of New Sustainable Urbanization Level in 20 Chinese Urban Agglomerations," Sustainability, MDPI, vol. 8(2), pages 1-19, January.
    12. Lina Zhong & Xiaonan Li & Rob Law & Sunny Sun, 2020. "Developing Sustainable Urbanization Index: Case of China," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    13. Lv, Yulan & Chen, Wei & Cheng, Jianquan, 2019. "Modelling dynamic impacts of urbanization on disaggregated energy consumption in China: A spatial Durbin modelling and decomposition approach," Energy Policy, Elsevier, vol. 133(C).
    14. Jing Bian & Hong Ren & Ping Liu & Yu Zhang, 2018. "Sustainable Urbanization Performance Evaluation Based on “Origin” and “Modernization” Perspectives: A Case Study of Chongqing, China," IJERPH, MDPI, vol. 15(8), pages 1-17, August.
    15. Pang, Jingru & Li, Nan & Mu, Hailin & Jin, Xin & Zhang, Ming, 2022. "Asymmetric effects of urbanization on shadow economy both in short-run and long-run:New evidence from dynamic panel threshold model," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    16. Liudan Jiao & Liyin Shen & Chenyang Shuai & Bei He, 2016. "A Novel Approach for Assessing the Performance of Sustainable Urbanization Based on Structural Equation Modeling: A China Case Study," Sustainability, MDPI, vol. 8(9), pages 1-16, September.

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