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Data Analysis of the Factors Influencing the Industrial Land Leasing in Shanghai Based on Mathematical Models

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  • Jing Cheng

Abstract

By analyzing the background of land leasing in Shanghai, the hypotheses of the mathematical models of industrial land leasing in Shanghai are proposed, and then, the mathematical models of the land price and land area are presented for analyzing the factors of industrial land leasing. Based on the mathematical models and the district data of Shanghai from 2007 to 2015, the factors influencing industrial land leasing by the district government are studied. It is shown that the influencing factors, such as the land area, GDP, tenure of district mayor, and the distance between the land and the nearest subway station, affect the government behavior on industrial land leasing.

Suggested Citation

  • Jing Cheng, 2020. "Data Analysis of the Factors Influencing the Industrial Land Leasing in Shanghai Based on Mathematical Models," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-11, April.
  • Handle: RePEc:hin:jnlmpe:9346863
    DOI: 10.1155/2020/9346863
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    Cited by:

    1. Linfang Shen & Kuoyu Liu & Jinfei Chai & Weibin Ma & Xiaoxiong Guo & Yao Li & Peng Zhao & Boying Liu, 2022. "Research on the Mathematical Model for Optimal Allocation of Human Resources in the Operation and Maintenance Units of a Heavy Haul Railway," Mathematics, MDPI, vol. 10(19), pages 1-18, October.
    2. Xiaoyan Du & Jinfei Chai, 2022. "Stability Evaluation of Medium Soft Soil Pile Slope Based on Limit Equilibrium Method and Finite Element Method," Mathematics, MDPI, vol. 10(19), pages 1-32, October.
    3. Jing Cheng, 2021. "Mathematical Models and Data Analysis of Residential Land Leasing Behavior of District Governments of Beijing in China," Mathematics, MDPI, vol. 9(18), pages 1-14, September.
    4. Cheng, Jing, 2022. "Analysis of the factors influencing industrial land leasing in Beijing of China based on the district-level data," Land Use Policy, Elsevier, vol. 122(C).
    5. Jing Cheng & Xiaowei Luo, 2022. "Analyzing the Land Leasing Behavior of the Government of Beijing, China, via the Multinomial Logit Model," Land, MDPI, vol. 11(3), pages 1-14, March.
    6. Wei, Jia & Wen, Jun & Wang, Xiao-Yang & Ma, Jie & Chang, Chun-Ping, 2023. "Green innovation, natural extreme events, and energy transition: Evidence from Asia-Pacific economies," Energy Economics, Elsevier, vol. 121(C).
    7. Jinfei Chai, 2021. "Research on Dynamic Response Characteristics for Basement Structure of Heavy Haul Railway Tunnel with Defects," Mathematics, MDPI, vol. 9(22), pages 1-23, November.
    8. Li Li & Jiahui Yu & Hang Cheng & Miaojuan Peng, 2021. "A Smart Helmet-Based PLS-BPNN Error Compensation Model for Infrared Body Temperature Measurement of Construction Workers during COVID-19," Mathematics, MDPI, vol. 9(21), pages 1-20, November.
    9. Zhijuan Meng & Xiaofei Chi & Lidong Ma, 2022. "A Hybrid Interpolating Meshless Method for 3D Advection–Diffusion Problems," Mathematics, MDPI, vol. 10(13), pages 1-21, June.
    10. Pei Yin & Miaojuan Peng, 2023. "Station Layout Optimization and Route Selection of Urban Rail Transit Planning: A Case Study of Shanghai Pudong International Airport," Mathematics, MDPI, vol. 11(6), pages 1-29, March.
    11. Jufeng Wang & Fengxin Sun & Rongjun Cheng, 2021. "A Dimension Splitting-Interpolating Moving Least Squares (DS-IMLS) Method with Nonsingular Weight Functions," Mathematics, MDPI, vol. 9(19), pages 1-22, September.
    12. Cheng, Jing, 2021. "Analysis of commercial land leasing of the district governments of Beijing in China," Land Use Policy, Elsevier, vol. 100(C).
    13. Fengxin Sun & Jufeng Wang & Xiang Kong & Rongjun Cheng, 2021. "A Dimension Splitting Generalized Interpolating Element-Free Galerkin Method for the Singularly Perturbed Steady Convection–Diffusion–Reaction Problems," Mathematics, MDPI, vol. 9(19), pages 1-15, October.

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