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.
@article{arxiv.2009.14605,
title = {Disruption in the Chinese E-Commerce During COVID-19},
author = {Yuan Yuan and Muzhi Guan and Zhilun Zhou and Sundong Kim and Meeyoung Cha and Depeng Jin and Yong Li},
journal= {arXiv preprint arXiv:2009.14605},
year = {2020}
}