IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v11y2022i2p149-d727535.html
   My bibliography  Save this article

Evaluation of Public Service Facilities in 19 Large Cities in China from the Perspective of Supply and Demand

Author

Listed:
  • Wei Wei

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
    China Institute of Development Strategy and Planning, Wuhan University, Wuhan 430072, China)

  • Xiwen Ren

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Shiyi Guo

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

Abstract

The equalization of urban public service facilities is important to the daily lives of urban residents. Spatial quantification of the supply and demand of public service facilities can reveal relationships between supply and demand agents and provide a foundation for the planning of urban public service facilities. This study proposed a comprehensive framework to assess the current state of supply (accessibility of facilities) and demand (population carrying pressure) of various public services in cities and determine patterns between different public service facilities. This framework contains three elements: (a) multi-scale spatial quantification of the matching of supply and demand, (b) spatial matching of supply and demand, and (c) spatial clustering analysis of the supply and demand balance. This study analyzed 19 major cities in China from a supply and demand perspective and examined implications for matching the supply and demand of public service facilities. The results indicated that education service facilities had the most appropriate supply and demand relationship. Areas where public service facilities had a good matching of supply and demand demonstrated a strong pattern of clustering. There were significant differences in the level of matching of the supply and demand of public service facilities among various regions in China. The limitations of the framework and future directions are discussed.

Suggested Citation

  • Wei Wei & Xiwen Ren & Shiyi Guo, 2022. "Evaluation of Public Service Facilities in 19 Large Cities in China from the Perspective of Supply and Demand," Land, MDPI, vol. 11(2), pages 1-18, January.
    • Handle: RePEc:gam:jlands:v:11:y:2022:i:2:p:149-:d:727535
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/11/2/149/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/11/2/149/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hu, Lirong & He, Shenjing & Luo, Yun & Su, Shiliang & Xin, Jing & Weng, Min, 2020. "A social-media-based approach to assessing the effectiveness of equitable housing policy in mitigating education accessibility induced social inequalities in Shanghai, China," Land Use Policy, Elsevier, vol. 94(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jing Xu & Zhiming Yan & Sai Hu & Chunling Pu, 2022. "The Spatial Distribution and Optimization of Medical and Health Land from the Perspective of Public Service Equalization: A Case Study of Urumqi City," Sustainability, MDPI, vol. 14(13), pages 1-18, June.
    2. Yingzi Chen & Yaqi Hu & Lina Lai, 2022. "Demography-Oriented Urban Spatial Matching of Service Facilities: Case Study of Changchun, China," Land, MDPI, vol. 11(10), pages 1-22, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kangxu Wang & Weifeng Wang & Tongtong Li & Shengjun Wen & Xin Fu & Xinhao Wang, 2023. "Optimizing Living Service Amenities for Diverse Urban Residents: A Supply and Demand Balancing Analysis," Sustainability, MDPI, vol. 15(16), pages 1-24, August.
    2. Chucai Peng & Yang Xiang & Luxia Chen & Yangyang Zhang & Zhixiang Zhou, 2023. "The Impact of the Type and Abundance of Urban Blue Space on House Prices: A Case Study of Eight Megacities in China," Land, MDPI, vol. 12(4), pages 1-27, April.
    3. Yingzi Chen & Yaqi Hu & Lina Lai, 2022. "Demography-Oriented Urban Spatial Matching of Service Facilities: Case Study of Changchun, China," Land, MDPI, vol. 11(10), pages 1-22, September.
    4. Ding, Kangzhe & Itoh, Ryo, 2023. "JUE Insight: The impact of the school admission restriction policy on the housing market in Shanghai," Journal of Urban Economics, Elsevier, vol. 136(C).
    5. Cyprian Chwiałkowski & Adam Zydroń, 2021. "Socio-Economic and Spatial Characteristics of Wielkopolski National Park: Application of the Hedonic Pricing Method," Sustainability, MDPI, vol. 13(9), pages 1-17, April.
    6. Wei Lu & Yuechen Li & Rongkun Zhao & Bo He & Zihua Qian, 2022. "Spatial Pattern and Fairness Measurement of Educational Resources in Primary and Middle Schools: A Case Study of Chengdu–Chongqing Economic Circle," IJERPH, MDPI, vol. 19(17), pages 1-23, August.
    7. Song, Jinbo & Nie, Rong & Yuan, Hehui & Gao, Jingxin, 2023. "Does the renovation of waste-to-energy incineration plants attenuate the housing price gradient? Evidence from a quasi-natural experiment in Shenzhen, China," Energy Economics, Elsevier, vol. 120(C).
    8. Alboqami, Hassan, 2023. "Trust me, I'm an influencer! - Causal recipes for customer trust in artificial intelligence influencers in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    9. Shihang Fu & Yaolin Liu & Ying Fang, 2021. "Measuring the Differences of Public Health Service Facilities and Their Influencing Factors," Land, MDPI, vol. 10(11), pages 1-15, November.
    10. Zekun Li & Shenjing He & Shiliang Su & Guie Li & Fei Chen, 2020. "Public Services Equalization in Urbanizing China: Indicators, Spatiotemporal Dynamics and Implications on Regional Economic Disparities," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 152(1), pages 1-65, November.
    11. Mathur, Shishir, 2022. "Non-linear and weakly monotonic relationship between school quality and house prices," Land Use Policy, Elsevier, vol. 113(C).
    12. Yizhou Wu & Xiaohong Zheng & Li Sheng & Heyuan You, 2020. "Exploring the Equity and Spatial Evidence of Educational Facilities in Hangzhou, China," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 151(3), pages 1075-1096, October.
    13. Guie Li & Zhongliang Cai & Yun Qian & Fei Chen, 2021. "Identifying Urban Poverty Using High-Resolution Satellite Imagery and Machine Learning Approaches: Implications for Housing Inequality," Land, MDPI, vol. 10(6), pages 1-16, June.
    14. Cong Liao & Teqi Dai, 2022. "Is “Attending Nearby School” Near? An Analysis of Travel-to-School Distances of Primary Students in Beijing Using Smart Card Data," Sustainability, MDPI, vol. 14(7), pages 1-12, April.
    15. Sheng Li & Yi Jiang & Shuisong Ke & Ke Nie & Chao Wu, 2021. "Understanding the Effects of Influential Factors on Housing Prices by Combining Extreme Gradient Boosting and a Hedonic Price Model (XGBoost-HPM)," Land, MDPI, vol. 10(5), pages 1-15, May.
    16. Sun, Wenwen & Jin, Hongyu & Chen, Yan & Hu, Xin & Li, Zhuoran & Kidd, Akari & Liu, Chunlu, 2021. "Spatial mismatch analyses of school land in China using a spatial statistical approach," Land Use Policy, Elsevier, vol. 108(C).
    17. Wu, Chao & Du, Yihao & Li, Sheng & Liu, Pengyu & Ye, Xinyue, 2022. "Does visual contact with green space impact housing pricesʔ An integrated approach of machine learning and hedonic modeling based on the perception of green space," Land Use Policy, Elsevier, vol. 115(C).
    18. Zhenchao Zhang & Weixin Luan & Chuang Tian & Min Su & Zeyang Li, 2021. "Spatial Distribution Equilibrium and Relationship between Construction Land Expansion and Basic Education Schools in Shanghai Based on POI Data," Land, MDPI, vol. 10(10), pages 1-17, October.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:11:y:2022:i:2:p:149-:d:727535. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.