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Disruption in the Chinese E-Commerce During COVID-19

Authors :
Yuan, Yuan
Guan, Muzhi
Zhou, Zhilun
Kim, Sundong
Cha, Meeyoung
Jin, Depeng
Li, Yong
Publication Year :
2020

Abstract

The recent outbreak of the novel coronavirus (COVID-19) has infected millions of citizens worldwide and claimed many lives. This paper examines its impact on the Chinese e-commerce market by analyzing behavioral changes seen from a large online shopping platform. We first conduct a time series analysis to identify product categories that faced the most extensive disruptions. The time-lagged analysis shows that behavioral patterns seen in shopping actions are highly responsive to epidemic development. Based on these findings, we present a consumer demand prediction method by encompassing the epidemic statistics and behavioral features for COVID-19 related products. Experiment results demonstrate that our predictions outperform existing baselines and further extend to the long-term and province-level forecasts. We discuss how our market analysis and prediction can help better prepare for future pandemics by gaining an extra time to launch preventive steps.<br />Comment: 10 pages, 7 figures, 6 tables

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2009.14605
Document Type :
Working Paper