Understanding the impact of COVID-19 on consumer mobility and recovery from a distance perspective: a mobile phone data application

Abstract

Purpose

In this study, to investigate tourist mobility (i.e. hotel visits) during the COVID-19 pandemic, the authors developed three objectives with reference to protection motivation theory: (1) to examine changes in travel distances in the USA before and during the pandemic, (2) to identify distinct travel patterns across different regions during the pandemic; and (3) to explore threat- and coping-related factors influencing tourist mobility.

Design/methodology/approach

The authors used two primary sources of data. First, smartphone data from SafeGraph provided hotel-specific variables (e.g. location and visitor counts) and travel distances for 63,610 hotels in the USA. Second, state-level data representing various factors associated with travel distance were obtained from COVID-19 Data Hub and the US Census Bureau. The authors analyzed changes in travel distances over time at the state and regional levels and investigated clinical, policy and demographic factors associated with such changes.

Findings

The findings reveal actual travel movements and intraregional variances across different stages of the pandemic, as well as the roles of health-related policies and other externalities in shaping travel patterns amid public health risks.

Originality/value

To the best of the authors’ knowledge, this study is the first to empirically examine changes in travel distances to hotels as destinations using smartphone data along with state-level data on COVID-19 and demographics. The findings suggest that tourism enterprises and stakeholders can proactively adapt their strategies by considering threat appraisals and coping mechanisms, both of which are influenced by externalities such as health-related policies.

研究目的

在我们的研究中, 为了调查COVID-19大流行期间的旅游出行（例如：酒店访问）, 我们根据保护动机理论制定了三个目标：（1）研究在COVID-19大流行前后美国的旅行距离的变化, （2）在大流行期间识别不同地区的不同旅行模式; 以及（3）探讨影响旅游出行的威胁和应对因素。

研究方法

我们利用了两个主要数据源。首先, 来自SafeGraph的智能手机数据提供了63,610家美国酒店的酒店特定变量（例如位置和访客计数）以及旅行距离数据。其次, 代表与旅行距离相关的各种因素的州级数据来自COVID-19数据中心和美国人口普查局。我们分析了州级和地区级的旅行距离随时间的变化, 并调查了与这些变化相关的临床、政策和人口因素。

研究发现

我们的研究结果揭示了不同阶段的实际旅行动态和地区内的差异, 以及在公共卫生风险中塑造旅行模式的健康相关政策和其他外部因素的作用。

研究创新

我们的研究是第一个利用智能手机数据以及与COVID-19和人口统计数据相关的州级数据, 经验性地研究了旅行距离到酒店作为目的地的变化。我们的研究结果表明, 旅游企业和利益相关者可以通过考虑威胁评估和应对机制来主动调整他们的策略, 这两者都受到健康相关政策等外部因素的影响。

Citation

Kim, W.-H., Park, E.(O). and Chae, B.(K). (2024), "Understanding the impact of COVID-19 on consumer mobility and recovery from a distance perspective: a mobile phone data application", Journal of Hospitality and Tourism Technology, Vol. 15 No. 1, pp. 104-122. https://doi.org/10.1108/JHTT-10-2022-0284