Structural Relationship between COVID-19, Night-Time Economic Vitality, and Credit-Card Sales: The Application of a Formative Measurement Model in PLS-SEM
Autor(en): |
Seong-a Kim
Heungsoon Kim |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Buildings, 20 September 2022, n. 10, v. 12 |
Seite(n): | 1606 |
DOI: | 10.3390/buildings12101606 |
Abstrakt: |
Cities worldwide are actively promoting their Night-Time Economies (NTEs) to recover from the economic crisis caused by COVID-19. However, in the case of Seoul, Korea, the interest in the NTE from an urban perspective remains insufficient. Therefore, this study was performed with the following two objectives: (1) To empirically identify the characteristics of Korea’s NTE and derive an indicator of the nighttime economic vitality (NTEV) by considering the NTE in urban regions; (2) to explore the structural relationship between NTEV, COVID-19, and credit-card sales in Seoul, to which operational restrictions were stringently applied according to the COVID-19 policy of Korea. The NTEV was evaluated using indicators of the nightly floating population, night-lighting value, and number of entertainment facilities. Moreover, to identify the structural relationship between COVID-19, NTEV, and credit-card sales based on abnormal analysis data, a formative measurement model of the partial least squares structural equipment modeling framework was used. The results highlighted that the effect of COVID-19 differed depending on the density of facilities to which the “social distancing policy” was applied, and the NTEV boosted the consumption economy of the entire city. Moreover, we empirically confirmed that an increase in the number of confirmed COVID-19 patients directly or indirectly decreased credit-card sales, which deteriorated the urban economy. |
Copyright: | © 2022 by the authors; licensee MDPI, Basel, Switzerland. |
Lizenz: | Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden. |
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10700194 - Veröffentlicht am:
11.12.2022 - Geändert am:
15.02.2023