IDEAS home Printed from https://ideas.repec.org/a/spr/apjors/v6y2022i3d10.1007_s41685-022-00247-6.html
   My bibliography  Save this article

Understanding mobility dynamics using urban functions during the COVID-19 pandemic: comparison of pre-and post-new normal eras

Author

Listed:
  • Gizem Hayrullahoğlu

    (Gazi University)

  • Çiğdem Varol

    (Gazi University)

Abstract

Several changes in urban mobility patterns have been observed in response to COVID-19 since March 2020 when the World Health Organization (WHO) declared COVID-19 a pandemic. However, whether mobility changes are entirely pandemic related has not been investigated for each urban function. This paper evaluates the potential determinants of urban mobility changes for six different urban functions during the COVID-19 pandemic via community mobility data collected by Google. Using artificial neural networks (ANN), the dynamics that affect mobility changes in the following urban functions; grocery/pharmacy, residential, parks, retail/recreation, transport stations, and workplaces, were analysed for Çankaya, one of the densest districts in the capital of Turkey. Results of the prediction model show that responses to the pandemic differed considerably by urban function. Before the new normal era, changes in urban mobility trends were strongly dependent on the pandemic as a public health threat and represented by restrictive government measures. However, impacts of the pandemic on intracity mobility decreased in the new normal era when rules were relaxed. These results are useful for developing proactive policies to ensure rapid post-pandemic recovery in urban economics and planning.

Suggested Citation

  • Gizem Hayrullahoğlu & Çiğdem Varol, 2022. "Understanding mobility dynamics using urban functions during the COVID-19 pandemic: comparison of pre-and post-new normal eras," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1087-1109, October.
    • Handle: RePEc:spr:apjors:v:6:y:2022:i:3:d:10.1007_s41685-022-00247-6
    DOI: 10.1007/s41685-022-00247-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s41685-022-00247-6
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s41685-022-00247-6?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Cavalcante da Silva, Gabriela & Monteiro de Almeida, Fernanda & Oliveira, Sabrina & Wanner, Elizabeth F. & Bezerra, Leonardo C.T. & Takahashi, Ricardo H.C. & Lima, Luciana, 2021. "Comparing community mobility reduction between first and second COVID-19 waves," Transport Policy, Elsevier, vol. 112(C), pages 114-124.
    2. Edward Coulson & Steven Brakman & Alessandra Faggian & Yasusada Murata, 2021. "COVID‐19 and regional economies: An introduction to the special issue," Journal of Regional Science, Wiley Blackwell, vol. 61(4), pages 691-695, September.
    3. Dominic Edelmann & Konstantinos Fokianos & Maria Pitsillou, 2019. "An Updated Literature Review of Distance Correlation and Its Applications to Time Series," International Statistical Review, International Statistical Institute, vol. 87(2), pages 237-262, August.
    4. Jing Xie & Shixian Luo & Katsunori Furuya & Dajiang Sun, 2020. "Urban Parks as Green Buffers During the COVID-19 Pandemic," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    5. Mendolia, Silvia & Stavrunova, Olena & Yerokhin, Oleg, 2021. "Determinants of the community mobility during the COVID-19 epidemic: The role of government regulations and information," Journal of Economic Behavior & Organization, Elsevier, vol. 184(C), pages 199-231.
    6. Fan, Jingting & Tang, Lixin & Zhu, Weiming & Zou, Ben, 2018. "The Alibaba effect: Spatial consumption inequality and the welfare gains from e-commerce," Journal of International Economics, Elsevier, vol. 114(C), pages 203-220.
    7. Sébastien Goudeau & Camille Sanrey & Arnaud Stanczak & Antony Manstead & Céline Darnon, 2021. "Why lockdown and distance learning during the COVID-19 pandemic are likely to increase the social class achievement gap," Nature Human Behaviour, Nature, vol. 5(10), pages 1273-1281, October.
    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. Tüzin Baycan & Suat Tuysuz, 2022. "Special Feature on social, economic, and spatial impacts of COVID-19 pandemic in Turkey," Asia-Pacific Journal of Regional Science, Springer, vol. 6(3), pages 1041-1051, October.

    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. Elif Bozkaya & Levent Eriskin & Mumtaz Karatas, 2023. "Data analytics during pandemics: a transportation and location planning perspective," Annals of Operations Research, Springer, vol. 328(1), pages 193-244, September.
    2. Yekaterina Chzhen & Jennifer Symonds & Dympna Devine & Júlia Mikolai & Susan Harkness & Seaneen Sloan & Gabriela Martinez Sainz, 2022. "Learning in a Pandemic: Primary School children’s Emotional Engagement with Remote Schooling during the spring 2020 Covid-19 Lockdown in Ireland," Child Indicators Research, Springer;The International Society of Child Indicators (ISCI), vol. 15(4), pages 1517-1538, August.
    3. Yue Du & Zan Zou & Yaodong He & Yongge Zhou & Shixian Luo, 2022. "Beyond Blue and Green Spaces: Identifying and Characterizing Restorative Environments on Sichuan Technology and Business University Campus," IJERPH, MDPI, vol. 19(20), pages 1-17, October.
    4. Ladan Rahbari, 2023. "COVID-19 Pandemic and the Crisis of Care: Wellness Discourses, Neoliberal Self-Care, and (Dis)Infodemic," Social Sciences, MDPI, vol. 12(3), pages 1-12, February.
    5. Dominic Edelmann & Tobias Terzer & Donald Richards, 2021. "A Basic Treatment of the Distance Covariance," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 12-25, May.
    6. Emmanuel Selorm Tsyawo, 2023. "Feasible IV regression without excluded instruments," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 235-256.
    7. Christoph Lambio & Tillman Schmitz & Richard Elson & Jeffrey Butler & Alexandra Roth & Silke Feller & Nicolai Savaskan & Tobia Lakes, 2023. "Exploring the Spatial Relative Risk of COVID-19 in Berlin-Neukölln," IJERPH, MDPI, vol. 20(10), pages 1-22, May.
    8. Emad B. Dawwas & Karen Dyson, 2021. "COVID-19 Changed Human-Nature Interactions across Green Space Types: Evidence of Change in Multiple Types of Activities from the West Bank, Palestine," Sustainability, MDPI, vol. 13(24), pages 1-21, December.
    9. Shixian Luo & Jing Xie & Katsunori Furuya, 2021. "“We Need such a Space”: Residents’ Motives for Visiting Urban Green Spaces during the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    10. Samuel-Azran, Tal & Hayat, Tsahi (Zack), 2020. "The geography of the Arab public sphere on Twitter," Technology in Society, Elsevier, vol. 62(C).
    11. Noszczyk, Tomasz & Gorzelany, Julia & Kukulska-Kozieł, Anita & Hernik, Józef, 2022. "The impact of the COVID-19 pandemic on the importance of urban green spaces to the public," Land Use Policy, Elsevier, vol. 113(C).
    12. Krishnan, Pramila & Gunning, Jan Willem & Mengistu, Andualem Telaye, 2018. "Fading Choice: Transport Costs and Variety in Consumer Goods," CEPR Discussion Papers 12910, C.E.P.R. Discussion Papers.
    13. Victor Couture & Benjamin Faber & Yizhen Gu & Lizhi Liu, 2021. "Connecting the Countryside via E-Commerce: Evidence from China," American Economic Review: Insights, American Economic Association, vol. 3(1), pages 35-50, March.
    14. Zdeněk Hlávka & Marie Hušková & Simos G. Meintanis, 2020. "Change-point methods for multivariate time-series: paired vectorial observations," Statistical Papers, Springer, vol. 61(4), pages 1351-1383, August.
    15. Sang-Jun Park & Kyung-Tae Lee & Jin-Bin Im & Ju-Hyung Kim, 2022. "The Need for Smart Architecture Caused by the Impact of COVID-19 upon Architecture and City: A Systematic Literature Review," Sustainability, MDPI, vol. 14(13), pages 1-20, June.
    16. Zhou Jiang & Maoxia Zeng & Mingming Shi, 2023. "E‐commerce and Consumption Inequality in China," China & World Economy, Institute of World Economics and Politics, Chinese Academy of Social Sciences, vol. 31(5), pages 61-86, September.
    17. Angelo Panno & Annalisa Theodorou & Giuseppe Alessio Carbone & Evelina De Longis & Chiara Massullo & Gianluca Cepale & Giuseppe Carrus & Claudio Imperatori & Giovanni Sanesi, 2021. "Go Greener, Less Risk: Access to Nature Is Associated with Lower Risk Taking in Different Domains during the COVID-19 Lockdown," Sustainability, MDPI, vol. 13(19), pages 1-17, September.
    18. Liu, Yajie & Cui, Lijuan & Xiong, Yanyan & Yao, Xianguo, 2023. "Does the development of the Internet improve the allocative efficiency of production factors? Evidence from surveys of Chinese manufacturing firms," Structural Change and Economic Dynamics, Elsevier, vol. 66(C), pages 161-174.
    19. Yuta Uchiyama & Ryo Kohsaka, 2020. "Access and Use of Green Areas during the COVID-19 Pandemic: Green Infrastructure Management in the “New Normal”," Sustainability, MDPI, vol. 12(23), pages 1-9, November.
    20. Mouratidis, Kostas, 2021. "How COVID-19 reshaped quality of life in cities: A synthesis and implications for urban planning," Land Use Policy, Elsevier, vol. 111(C).

    More about this item

    Keywords

    Community mobility; COVID-19; Urban functions; Artificial neural network;
    All these keywords.

    JEL classification:

    • C54 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Quantitative Policy Modeling
    • E27 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Forecasting and Simulation: Models and Applications
    • R14 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Land Use Patterns

    Statistics

    Access and download statistics

    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:spr:apjors:v:6:y:2022:i:3:d:10.1007_s41685-022-00247-6. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.