TY - JOUR
T1 - Spatio-Temporal Variability of the Impact of Population Mobility on Local Business Sales in Response to COVID-19 in Seoul, Korea
AU - Koo, Hyeongmo
AU - Lee, Soyoung
AU - Lee, Jiyeong
AU - Cho, Daeheon
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/10
Y1 - 2022/10
N2 - Social distancing is an effective method for controlling the COVID-19 pandemic by decreasing population mobility, but it has also negatively affected local business sales. This paper explores the spatio-temporal impact of population mobility on local business sales in response to COVID-19 in Seoul, South Korea. First, this study examined the temporal variability by analyzing statistical interaction terms in linear regression models. Second, the spatio-temporal variability was captured using Moran eigenvector spatial filtering (MESF)-based spatially varying coefficients (SVC) models with additional statistical interaction terms. Population mobility and local business sales were estimated from public transportation ridership and restaurant sales, respectively, which were both obtained from spatial big datasets. The analysis results show the existence of various relationships between changes in the population mobility and local business sales according to the corresponding period and region. This study confirms the usability of spatial big datasets and spatio-temporal varying coefficients models for COVID-19 studies and provides support for policy-makers in response to infectious disease.
AB - Social distancing is an effective method for controlling the COVID-19 pandemic by decreasing population mobility, but it has also negatively affected local business sales. This paper explores the spatio-temporal impact of population mobility on local business sales in response to COVID-19 in Seoul, South Korea. First, this study examined the temporal variability by analyzing statistical interaction terms in linear regression models. Second, the spatio-temporal variability was captured using Moran eigenvector spatial filtering (MESF)-based spatially varying coefficients (SVC) models with additional statistical interaction terms. Population mobility and local business sales were estimated from public transportation ridership and restaurant sales, respectively, which were both obtained from spatial big datasets. The analysis results show the existence of various relationships between changes in the population mobility and local business sales according to the corresponding period and region. This study confirms the usability of spatial big datasets and spatio-temporal varying coefficients models for COVID-19 studies and provides support for policy-makers in response to infectious disease.
KW - COVID-19
KW - Moran eigenvector spatial filtering
KW - spatially varying coefficients
KW - spatio-temporal analysis
UR - http://www.scopus.com/inward/record.url?scp=85140721592&partnerID=8YFLogxK
U2 - 10.3390/ijgi11100532
DO - 10.3390/ijgi11100532
M3 - Article
AN - SCOPUS:85140721592
SN - 2220-9964
VL - 11
JO - ISPRS International Journal of Geo-Information
JF - ISPRS International Journal of Geo-Information
IS - 10
M1 - 532
ER -