IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i23p13152-d689454.html
   My bibliography  Save this article

Spatiotemporal Trends and Driving Factors of Urban Livability in the Yangtze River Delta Agglomeration

Author

Listed:
  • Yichen Yang

    (State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Shifeng Fang

    (State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Hua Wu

    (State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Jiaqiang Du

    (Institute of Ecological Environment Research, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Haomiao Tu

    (College of Mining, Guizhou University, Guiyang 550025, China)

  • Wei He

    (State Key Laboratory of Resources and Environmental Information Systems, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

With the development of cities, the relationship between cities is becoming closer, and the study of urban livability based on a single city can no longer meet the guidelines and suggestions for urban agglomerations. A scientific evaluation of livability in urban agglomerations can better help cities to recognize the advantages and disadvantages. However, most studies on urban livability focus on its connotation and history and neglect simulations and analyses of the future. Based on the Yangtze River Delta agglomeration, this paper establishes an index system using data from 2011 to 2019 to simulate urban livability from 2020 to 2025 through the ARIMA model and analyzes the historical and future data by using GIS methods. The results show the following: (1) The ARIMA model has good simulation accuracy when applied to urban livability analysis and can provide a reference for future urban livability development. (2) The urban livability of the Yangtze River Delta agglomeration has obviously changed both on the whole and in subsystems. Cities in the upper ranking of livability have developed rapidly, and the difference in urban livability has increased. (3) The spatial autocorrelation of urban livability in the Yangtze River Delta agglomeration is obvious both on the whole and in subsystems. (4) The influencing factors of urban livability development are diverse. The general public budget expenditure for social security and employment, fixed assets investment in municipal public facilities, total retail sales of consumer goods, and education and medical expenditures have positive effects on the development of urban livability, while industrial SO 2 emissions have a negative effect. The results show that cities should strengthen inter-city relationships, promote the coordinated development of inter-regional cities, and formulate relevant policies to improve the level of urban environmental governance in the region.

Suggested Citation

  • Yichen Yang & Shifeng Fang & Hua Wu & Jiaqiang Du & Haomiao Tu & Wei He, 2021. "Spatiotemporal Trends and Driving Factors of Urban Livability in the Yangtze River Delta Agglomeration," Sustainability, MDPI, vol. 13(23), pages 1-19, November.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:23:p:13152-:d:689454
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/23/13152/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/13/23/13152/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hongzhong FAN & Shujahat Haider HASHMI & Yasir HABIB & Minhaj ALI, 2020. "How Do Urbanization and Urban Agglomeration Affect CO2 Emissions in South Asia? Testing Non-Linearity Puzzle with Dynamic STIRPAT Model," Chinese Journal of Urban and Environmental Studies (CJUES), World Scientific Publishing Co. Pte. Ltd., vol. 8(01), pages 1-37, March.
    2. Getis, Arthur, 2007. "Reflections on spatial autocorrelation," Regional Science and Urban Economics, Elsevier, vol. 37(4), pages 491-496, July.
    3. Huiping Huang & Qiangzi Li & Yuan Zhang, 2019. "Urban Residential Land Suitability Analysis Combining Remote Sensing and Social Sensing Data: A Case Study in Beijing, China," Sustainability, MDPI, vol. 11(8), pages 1-19, April.
    4. Gaetano Perone, 2020. "An ARIMA model to forecast the spread and the final size of COVID-2019 epidemic in Italy," Health, Econometrics and Data Group (HEDG) Working Papers 20/07, HEDG, c/o Department of Economics, University of York.
    5. Shi, Qian & Lai, Xiaodong, 2013. "Identifying the underpin of green and low carbon technology innovation research: A literature review from 1994 to 2010," Technological Forecasting and Social Change, Elsevier, vol. 80(5), pages 839-864.
    6. Bernd Resch & Anja Summa & Peter Zeile & Michael Strube, 2016. "Citizen-Centric Urban Planning through Extracting Emotion Information from Twitter in an Interdisciplinary Space-Time-Linguistics Algorithm," Urban Planning, Cogitatio Press, vol. 1(2), pages 114-127.
    7. Adam Okulicz-Kozaryn, 2013. "City Life: Rankings (Livability) Versus Perceptions (Satisfaction)," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 110(2), pages 433-451, January.
    8. Appio, Francesco Paolo & Lima, Marcos & Paroutis, Sotirios, 2019. "Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 1-14.
    9. Appio, Francesco Paolo & Lima, Marcos & Paroutis, Sotirios, 2019. "Understanding Smart Cities: Innovation ecosystems, technological advancements, and societal challenges," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 1-14.
    10. John Bongaarts, 2016. "World Health Organization Health in 2015: From MDGs, Millennium Development Goals, to SDGs, Sustainable Development Goals Geneva : WHO Press , 2016 . 212 p. $60.00 (pbk.)," Population and Development Review, The Population Council, Inc., vol. 42(3), pages 575-575, September.
    11. Fu, Bo & Yu, Danlin & Zhang, Yaojun, 2019. "The livable urban landscape: GIS and remote sensing extracted land use assessment for urban livability in Changchun Proper, China," Land Use Policy, Elsevier, vol. 87(C).
    Full references (including those not matched with items on IDEAS)

    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. Filippo Corsini & Rafael Laurenti & Franziska Meinherz & Francesco Paolo Appio & Luca Mora, 2019. "The Advent of Practice Theories in Research on Sustainable Consumption: Past, Current and Future Directions of the Field," Sustainability, MDPI, vol. 11(2), pages 1-19, January.
    2. Maria Vincenza Ciasullo & Orlando Troisi & Mara Grimaldi & Daniele Leone, 2020. "Multi-level governance for sustainable innovation in smart communities: an ecosystems approach," International Entrepreneurship and Management Journal, Springer, vol. 16(4), pages 1167-1195, December.
    3. Xiaoran Zheng & Yuzhuo Cai, 2022. "Transforming Innovation Systems into Innovation Ecosystems: The Role of Public Policy," Sustainability, MDPI, vol. 14(12), pages 1-26, June.
    4. Shami, Mohammad Reza & Rad, Vahid Bigdeli & Moinifar, Maryam, 2022. "The structural model of indicators for evaluating the quality of urban smart living," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    5. Anthea van der Hoogen & Ifeoluwapo Fashoro & Andre P. Calitz & Lamla Luke, 2024. "A Digital Transformation Framework for Smart Municipalities," Sustainability, MDPI, vol. 16(3), pages 1-28, February.
    6. Caprotti, Federico & Liu, Dong, 2020. "Emerging platform urbanism in China: Reconfigurations of data, citizenship and materialities," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    7. Kajikawa, Yuya & Mejia, Cristian & Wu, Mengjia & Zhang, Yi, 2022. "Academic landscape of Technological Forecasting and Social Change through citation network and topic analyses," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    8. Oleg Golubchikov & Mary J. Thornbush, 2022. "Smart Cities as Hybrid Spaces of Governance: Beyond the Hard/Soft Dichotomy in Cyber-Urbanization," Sustainability, MDPI, vol. 14(16), pages 1-12, August.
    9. Renata Biadacz & Marek Biadacz, 2021. "Implementation of “Smart” Solutions and An Attempt to Measure Them: A Case Study of Czestochowa, Poland," Energies, MDPI, vol. 14(18), pages 1-28, September.
    10. Aleksandra Jadach-Sepioło & Katarzyna Olejniczak-Szuster & Michał Dziadkiewicz, 2021. "Does Environment Matter in Smart Revitalization Strategies? Management towards Sustainable Urban Regeneration Programs in Poland," Energies, MDPI, vol. 14(15), pages 1-16, July.
    11. Richard Hu, 2019. "The State of Smart Cities in China: The Case of Shenzhen," Energies, MDPI, vol. 12(22), pages 1-18, November.
    12. Bencsik, Barbara & Palmié, Maximilian & Parida, Vinit & Wincent, Joakim & Gassmann, Oliver, 2023. "Business models for digital sustainability: Framework, microfoundations of value capture, and empirical evidence from 130 smart city services," Journal of Business Research, Elsevier, vol. 160(C).
    13. Tan Yigitcanlar & Bo Xia & Tatiana Tucunduva Philippi Cortese & Jamile Sabatini-Marques, 2023. "Understanding City 4.0: A Triple Bottom Line Approach," Sustainability, MDPI, vol. 16(1), pages 1-11, December.
    14. El Barachi, May & Salim, Taghreed Abu & Nyadzayo, Munyaradzi W. & Mathew, Sujith & Badewi, Amgad & Amankwah-Amoah, Joseph, 2022. "The relationship between citizen readiness and the intention to continuously use smart city services: Mediating effects of satisfaction and discomfort," Technology in Society, Elsevier, vol. 71(C).
    15. Leonardo Guevara & Fernando Auat Cheein, 2020. "The Role of 5G Technologies: Challenges in Smart Cities and Intelligent Transportation Systems," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    16. Ginevra Balletto & Mara Ladu & Federico Camerin & Emilio Ghiani & Jacopo Torriti, 2022. "More Circular City in the Energy and Ecological Transition: A Methodological Approach to Sustainable Urban Regeneration," Sustainability, MDPI, vol. 14(22), pages 1-18, November.
    17. Barrutia, Jose M. & Echebarria, Carmen & Aguado-Moralejo, Itziar & Apaolaza-Ibáñez, Vanessa & Hartmann, Patrick, 2022. "Leading smart city projects: Government dynamic capabilities and public value creation," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    18. Hazel Si Min Lim & Araz Taeihagh, 2019. "Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities," Sustainability, MDPI, vol. 11(20), pages 1-28, October.
    19. Kusumastuti, Ratih Dyah & Nurmala, N. & Rouli, Juliana & Herdiansyah, Herdis, 2022. "Analyzing the factors that influence the seeking and sharing of information on the smart city digital platform: Empirical evidence from Indonesia," Technology in Society, Elsevier, vol. 68(C).
    20. Mohammed Balfaqih & Soltan Abed Alharbi, 2022. "Associated Information and Communication Technologies Challenges of Smart City Development," Sustainability, MDPI, vol. 14(23), pages 1-27, December.

    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:jsusta:v:13:y:2021:i:23:p:13152-:d:689454. 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.