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【学术通知】南方科技大学副研究员李少波:Racial Discrimination and Anti-Discrimination: The COVID-19 Pandemic's Impact on Chinese Restaurants in North American

  • 发布日期:2023-10-16
  • 点击数:

  

喻园管理论坛2023年第78期(总第901期)

演讲主题: Racial Discrimination and Anti-Discrimination: The COVID-19 Pandemic’s Impact on Chinese Restaurants in North American

主 讲 人: 李少波,南方科技大学副研究员

主 持 人: 王梦阳,工商管理系副教授

活动时间2023年10月17日(周二) 10:00-11:30

活动地点管理大楼121室

主讲人简介:

李少波博士,南方科技大学商学院副研究员、博士生导师。新加坡南洋理工大学南洋商学院市场营销博士,美国西弗吉尼亚大学硕士,兰州大学学士。研究成果发表于Journal of Consumer Research, Information System Research, Production and Operations Management 和Organizational Behavior and Human Decision Processes 等 UTD/FT 国际顶尖商科期刊。Journal of Business Research 编委会成员。主持国家自然科学基金,广东省自然科学基金等科研项目。研究兴趣为数字时代的消费行为、消费者福祉。

活动简介:

The COVID-19 pandemic has led to an increase in cases of racial discrimination against Asians, especially Chinese people. Despite an emerging stream of studies investigating various aspects of the COVID-19 pandemic, research on the behavioral consequences of racial discrimination during the pandemic remains scarce. In this work, we examined how racial discrimination stemming from the COVID-19 pandemic and subsequent anti-discrimination were manifested on online platforms. By combining difference-in-differences analyses on two large-scale panel datasets from Yelp.com and SafeGraph and two controlled experiments, we explored the impact of COVID-19 on Chinese restaurants, relative to non-Chinese restaurants, at different phases of the COVID-19 pandemic. We found that the COVID-19 pandemic led to an immediate increase in racial discrimination, which was reflected in a significant drop in the customer patronage frequency of Chinese restaurants as compared to that of non-Chinese restaurants. Furthermore, analyses using multiple behavioral indicators generated by text mining and machine learning techniques consistently suggested that increased discrimination triggered anti-discrimination actions of customers on online platforms after the COVID-19 outbreak. This study contributes to the literature on racial discrimination by investigating a subtle but more factual form of racial discrimination evidenced by the customer patronage of Chinese restaurants, as well as user-generated content, by demonstrating that consumers can fight discrimination on online platforms.

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