ABSTRACT With the rise of COVID-19, decision support systems (DSS) increasingly display crowding information (CI) (e.g. how crowded a medical practice is) to encourage physical distancing when users select locations. Despite important implications for containing COVID-19, little is known about the causal effect of CI on user selection behaviour and how the immediacy of CI (e.g. “updated 2 minutes ago“) as well as users’ health anxiety further influence the effect of CI. Drawing on literature on digital choice environments and construal level theory, we conducted a multi-national online experiment to investigate the effect of CI on selecting differently crowded medical practices. Our results demonstrate that present (vs. absent) CI in DSS increases the likelihood of users selecting less crowded medical practices, while the effect is strongest when employed with real-time (vs. historical average) CI and, surprisingly, when users’ health anxiety is low (vs. high). Overall, our study adds to the growing body of research on IS in the age of pandemics and provides actionable insights for DSS providers and policymakers to endow users with information to identify and select less crowded locations, thus containing COVID-19 through improved physical distancing without paternalistically restricting users’ freedom of choice.

中文翻译：

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通过物理距离控制 COVID-19：实时拥挤信息的影响

摘要 随着 COVID-19 的兴起，决策支持系统 (DSS) 越来越多地显示拥挤信息 (CI)（例如医疗实践的拥挤程度），以鼓励用户在选择位置时保持身体距离。尽管对遏制 COVID-19 具有重要意义，但人们对 CI 对用户选择行为的因果影响以及 CI 的即时性（例如“2 分钟前更新”）以及用户的健康焦虑如何进一步影响 CI 的影响知之甚少. 借鉴有关数字选择环境和解释水平理论的文献，我们进行了一项跨国在线实验，以研究 CI 对选择不同拥挤的医疗实践的影响。我们的结果表明，DSS 中存在（与不存在）CI 增加了用户选择不那么拥挤的医疗实践的可能性，而当使用实时（与历史平均）CI 时效果最强，并且令人惊讶的是，当用户的健康焦虑较低（与较高）时。总体而言，我们的研究增加了大流行时代关于 IS 的越来越多的研究，并为 DSS 提供者和政策制定者提供了可行的见解，为用户提供信息以识别和选择不那么拥挤的地点，从而通过改善物理距离来控制 COVID-19，而无需家长式地限制用户的选择自由。