Analysis of Online Consumer Purchasing Behavior Typology After the COVID-19 Pandemic

Zongkang Yang, Xiao Li and Qiwei Wang

SAGE Open, 2024, vol. 14, issue 3, 21582440241279684

Abstract: The COVID-19 pandemic has significantly impacted global society and economies, prompting a shift in online consumer purchasing behavior (OCPB). This study aims to explore the evolving typologies of OCPB in the context of post-pandemic retail transformations. Utilizing data from a leading Chinese e-commerce platform, this study employed data mining techniques and the Bidirectional Encoder Representations from Transformers (BERT) model to analyze OCPB typologies. The BERT model, known for its advanced multi-task capabilities, demonstrated high reliability in classifying OCPB into three distinct types, as evidenced by robust performance metrics including accuracy, precision, recall, and F1-score. However, the BERT model alone did not fully capture the nuanced concept of OCPB typology. To address this, this study integrated grounded theory to further delineate OCPB typologies, identifying key dimensions such as social and economic adaptation, product attributes, and user experience. Our findings offer a comprehensive understanding of OCPB typologies and provide valuable insights for retailers navigating the post-COVID-19 landscape. This research not only contributes to the academic discourse on consumer behavior but also offers practical guidance for enhancing retail strategies in a rapidly changing environment.

Keywords: post-COVID-19; consumer behavior; typology; data mining; data analysis (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:14:y:2024:i:3:p:21582440241279684

DOI: 10.1177/21582440241279684

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