Looking Back and Moving Forward: How psychological and demographic factors affect consumer behaviors amid the COVID-19 pandemic

Ming-Yi Wu
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引用次数: 1

Abstract

By analyzing survey data collected from 857 U.S. adults, and applying the decision tree analysis, this study explores how psychological and demographic factors may affect consumer behaviors amid the COVID-19 pandemic. Protection motivation theory (PMT) and consumer demographics theory provide the theoretical foundation for this study. Decision tree is used for data analysis because it is a powerful predictive analytics method. There are a number of important findings. First, the result of decision tree analysis suggests that perceived threat/concern is the most important demographic factor that predicts consumers’ overall online shopping behavior. Second, education is the most important predictor for consumers’ online grocery shopping behavior. Third, perceived threat/concern is the most important predictor for consumers’ panic buying/hoarding behavior. Fourth, age is the most important predictor for consumers’ work from home behavior. Finally, race is the most important predictor for consumers’ spending more time watching TV behavior. The results support PMT and consumer demographics theory. This study brings additional insights into consumer behaviors amid the pandemic.
回顾与前进:心理和人口因素如何影响COVID-19大流行期间的消费者行为
通过分析从857名美国成年人中收集的调查数据,并应用决策树分析,本研究探讨了心理和人口因素如何影响COVID-19大流行期间的消费者行为。保护动机理论和消费者人口统计学理论为本研究提供了理论基础。决策树是一种功能强大的预测分析方法,因此被用于数据分析。有一些重要的发现。首先,决策树分析的结果表明,感知威胁/关注是预测消费者整体在线购物行为的最重要的人口统计学因素。其次,教育程度是消费者在线购物行为最重要的预测因素。第三,感知威胁/担忧是消费者恐慌性购买/囤积行为最重要的预测因子。第四,年龄是消费者在家办公行为最重要的预测因子。最后,种族是消费者花更多时间看电视行为的最重要预测因素。结果支持PMT和消费者人口统计学理论。这项研究为大流行期间的消费者行为提供了额外的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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