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Design of industrial clusters and optimization of land use in an airport economic zone

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  • Wang, Dan
  • Gong, Zhiguang
  • Yang, Zhongzhen

Abstract

To increase the land utility and efficiency in an airport economic zone (AEZ) and to manage the corresponding transport demands, we propose a method to determine the structure and scale of the basic airport industry cluster based on the airport scale and its relationships to industries. The correlation coefficients between industries are calculated by the strengths of the logistical and non-logistical relationships. We use the system layout planning (SLP) approach to determine the location pattern of basic industries with the objective of maximizing the correlation coefficient of a unit distance. Finally, the employees’ housing locations and service industries in the AEZ are determined using the Lowry model based on employees’ choice behaviors regarding housing and consumer services. This study is helpful for planning the development of industrial clusters and optimizing the land use patterns in an AEZ.

Suggested Citation

  • Wang, Dan & Gong, Zhiguang & Yang, Zhongzhen, 2018. "Design of industrial clusters and optimization of land use in an airport economic zone," Land Use Policy, Elsevier, vol. 77(C), pages 288-297.
    • Handle: RePEc:eee:lauspo:v:77:y:2018:i:c:p:288-297
    DOI: 10.1016/j.landusepol.2018.05.048
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    References listed on IDEAS

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    1. Stevens, Nicholas & Baker, Douglas & Freestone, Robert, 2010. "Airports in their urban settings: towards a conceptual model of interfaces in the Australian context," Journal of Transport Geography, Elsevier, vol. 18(2), pages 276-284.
    2. Wang, Kung-Jeng & Hong, Wan-Chung & Chen, Shin-Hua & Jiang, Jyun-Ting, 2011. "Strategic development trend and key factors analysis of Airport City in Taiwan," Journal of Transport Geography, Elsevier, vol. 19(4), pages 807-820.
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    Citations

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    Cited by:

    1. Chich-Ping Hu, 2022. "Urban Land-Use Allocation with Resilience: Application of the Lowry Model," Sustainability, MDPI, vol. 14(23), pages 1-15, November.
    2. Huafei Yu & Yaolong Zhao & Yingchun Fu, 2019. "Optimization of Impervious Surface Space Layout for Prevention of Urban Rainstorm Waterlogging: A Case Study of Guangzhou, China," IJERPH, MDPI, vol. 16(19), pages 1-28, September.
    3. Jie Li & Ninghui Pan & Xin Ma & Zhiyuan Cheng & Yao Yao & Guang Li & Jianyu Yuan & Guorong Xu, 2024. "Mutual Causality Between Urban Transport Superiority Degree and Urban Land Use Efficiency: Insights from County Cities in Gansu Province Under the Belt and Road Initiative," Land, MDPI, vol. 13(11), pages 1-25, October.
    4. Yingnan Niu & Gaodi Xie & Yu Xiao & Keyu Qin & Shuang Gan & Jingya Liu, 2021. "Spatial and Temporal Changes of Ecosystem Service Value in Airport Economic Zones in China," Land, MDPI, vol. 10(10), pages 1-16, October.
    5. Pi, Jianhua & Li, Dong & Liu, Xingjian & Freestone, Robert, 2021. "The spatial distribution of employment around major Chinese airports," Journal of Transport Geography, Elsevier, vol. 91(C).
    6. Masilonyane Mokhele & Tholang Mokhele, 2022. "Spatial Configuration of Logistics Firms Relative to Cape Town International Airport, South Africa," Logistics, MDPI, vol. 6(3), pages 1-22, July.
    7. Sergi, S. Bruno & D’Aleo, Vittorio & Arbolino, Roberta & Carlucci, Fabio & Barilla, David & Ioppolo, Giuseppe, 2020. "Evaluation of the Italian transport infrastructures: A technical and economic efficiency analysis," Land Use Policy, Elsevier, vol. 99(C).
    8. Wang, Dan & Zhao, Xu & Shen, Lixin & Yang, Zhongzhen, 2020. "Industry choice for an airport economic zone by multi-objective optimization," Journal of Air Transport Management, Elsevier, vol. 88(C).

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