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How Has the COVID-19 Pandemic Affected the Perceptions of Public Space Employees?

Author

Listed:
  • Soyoung Han

    (College of Architecture and Urban Studies, Virginia Tech, Blacksburg, VA 24060, USA)

  • Cermetrius Lynell Bohannon

    (College of Architecture and Urban Studies, Virginia Tech, Blacksburg, VA 24060, USA)

  • Yoonku Kwon

    (Department of Landscape Architecture, Chonnam National University, Gwangju 61186, Korea)

Abstract

The purpose of this study is to derive the subjective perception about COVID-19 of public space employees and to identify the characteristics of COVID-19 related issues. By using the Q-method, 24 workers in four public spaces located in Blacksburg, Virginia, USA were selected as P-Sample and Q-Sorting was conducted. Three types of perceptions were identified; Type 1 (Expansion of Non-Face-To-Face Service), Type 2 (Expansion of Professional Labor), and Type 3 (Expansion of Welfare Service Type). All three types recognized that when a confirmed case occurs in a public space, the right and safety of users or communities to know is important, and accurate information must be provided, because it is necessary to prevent the spread of infection. Above all, these results show another side of the COVID-19 situation, as the participants in this study are currently in charge of various tasks such as quarantine and service provision in public spaces. This study can be used as basic data for policy response and system improvement of public spaces in the event of an infectious disease such as COVID-19 in the future.

Suggested Citation

  • Soyoung Han & Cermetrius Lynell Bohannon & Yoonku Kwon, 2021. "How Has the COVID-19 Pandemic Affected the Perceptions of Public Space Employees?," Land, MDPI, vol. 10(12), pages 1-16, December.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:12:p:1332-:d:694653
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    References listed on IDEAS

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    5. Armatas, Christopher A. & Venn, Tyron J. & Watson, Alan E., 2014. "Applying Q-methodology to select and define attributes for non-market valuation: A case study from Northwest Wyoming, United States," Ecological Economics, Elsevier, vol. 107(C), pages 447-456.
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    Cited by:

    1. Mateusz Ciski & Krzysztof Rząsa, 2023. "Multiscale Geographically Weighted Regression in the Investigation of Local COVID-19 Anomalies Based on Population Age Structure in Poland," IJERPH, MDPI, vol. 20(10), pages 1-23, May.
    2. Krzysztof Rząsa & Mateusz Ciski, 2022. "Influence of the Demographic, Social, and Environmental Factors on the COVID-19 Pandemic—Analysis of the Local Variations Using Geographically Weighted Regression," IJERPH, MDPI, vol. 19(19), pages 1-26, September.

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