Disruption in the Chinese E-Commerce During COVID-19

• URL: http://arxiv.org/abs/2009.14605v2
• Date: Tue, 27 Oct 2020 14:17:52 GMT
• Title: Disruption in the Chinese E-Commerce During COVID-19
• Authors: Yuan Yuan and Muzhi Guan and Zhilun Zhou and Sundong Kim and Meeyoung Cha and Depeng Jin and Yong Li
• Abstract summary: 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 present a consumer demand prediction method by encompassing the epidemic statistics and behavioral features for COVID-19 related products.
• Score: 27.593450217418777
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• 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.

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