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A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic

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  • Fatemeh Safara

    (Islamic Azad University, Islamshahr Branch)

Abstract

The knowledge-based economy has drawn increasing attention recently, particularly in online shopping applications where all the transactions and consumer opinions are logged. Machine learning methods could be used to extract implicit knowledge from the logs. Industries and businesses use the knowledge to better understand the consumer behavior, and opportunities and threats correspondingly. The outbreak of coronavirus (COVID-19) pandemic has a great impact on the different aspects of our daily life, in particular, on our shopping behaviour. To predict electronic consumer behaviour could be of valuable help for managers in government, supply chain and retail industry. Although, before coronavirus pandemic we have experienced online shopping, during the disease the number of online shopping increased dramatically. Due to high speed transmission of COVID-19, we have to observe personal and social health issues such as social distancing and staying at home. These issues have direct effect on consumer behaviour in online shopping. In this paper, a prediction model is proposed to anticipate the consumers behaviour using machine learning methods. Five individual classifiers, and their ensembles with Bagging and Boosting are examined on the dataset collected from an online shopping site. The results indicate the model constructed using decision tree ensembles with Bagging achieved the best prediction of consumer behavior with the accuracy of 95.3%. In addition, correlation analysis is performed to determine the most important features influencing the volume of online purchase during coronavirus pandemic.

Suggested Citation

  • Fatemeh Safara, 2022. "A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1525-1538, April.
    • Handle: RePEc:kap:compec:v:59:y:2022:i:4:d:10.1007_s10614-020-10069-3
    DOI: 10.1007/s10614-020-10069-3
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    References listed on IDEAS

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    1. María Teresa Ballestar & Pilar Grau-Carles & Jorge Sainz, 2019. "Predicting customer quality in e-commerce social networks: a machine learning approach," Review of Managerial Science, Springer, vol. 13(3), pages 589-603, June.
    2. Ming Zeng & Hancheng Cao & Min Chen & Yong Li, 2019. "User behaviour modeling, recommendations, and purchase prediction during shopping festivals," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 263-274, June.
    3. Erpeng Wang & Ning An & Zhifeng Gao & Emmanuel Kiprop & Xianhui Geng, 2020. "Consumer food stockpiling behavior and willingness to pay for food reserves in COVID-19," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 12(4), pages 739-747, August.
    4. Pantano, Eleonora & Pizzi, Gabriele & Scarpi, Daniele & Dennis, Charles, 2020. "Competing during a pandemic? Retailers’ ups and downs during the COVID-19 outbreak," Journal of Business Research, Elsevier, vol. 116(C), pages 209-213.
    5. Barua, Suborna, 2020. "Understanding Coronanomics: The economic implications of the coronavirus (COVID-19) pandemic," MPRA Paper 99693, University Library of Munich, Germany.
    6. Ivanov, Dmitry, 2020. "Predicting the impacts of epidemic outbreaks on global supply chains: A simulation-based analysis on the coronavirus outbreak (COVID-19/SARS-CoV-2) case," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    Full references (including those not matched with items on IDEAS)

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