The COVID-19 pandemic is a new phenomenon and has affected the population’s lifestyle in many ways, such as panic buying (the so-called “hamster shopping”), adoption of home-office, and decline in retail shopping. For transportation planners and operators, it is interesting to analyze the spatial factors’ role in the demand patterns at a POI (Point of Interest) during the COVID-19 lockdown viz-a-viz before lockdown. This study illustrates a use-case of the POI visitation rate or popularity data and other publicly available data to analyze demand patterns and spatial factors during a highly dynamic and disruptive event like COVID-19. We develop regression models to analyze the correlation of the spatial and non-spatial attributes with the POI popularity before and during COVID-19 lockdown in Munich by using lockdown (treatment) as a dummy variable, with main and interaction effects. In our case-study for Munich, we find consistent behavior of features like stop distance and day-of-the-week in explaining the popularity. The parking area is found to be correlated only in the non-linear models. Interactions of lockdown with POI type, stop-distance, and day-of-the-week are found to be strongly significant. The results might not be transferable to other cities due to the presence of different city-specific factors. The findings from our case-study provide evidence of the impact of the restrictions on POIs and show the significant correlation of POI-type and stop distance with POI popularity. These results suggest local and temporal variability in the impact due to the restrictions, which can impact how cities adapt their transport services to the distinct demand and resulting mobility patterns during future disruptive events.

中文翻译：

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使用机会数据解释 COVID-19 期间的需求模式：慕尼黑市的案例研究


COVID-19 大流行是一种新现象，在很多方面影响了人们的生活方式，例如恐慌性购买（所谓的“仓鼠购物”）、家庭办公的采用以及零售购物的下降。对于交通规划者和运营商来说，在 COVID-19 封锁期间（即封锁之前）分析空间因素在 POI（兴趣点）需求模式中的作用是很有趣的。本研究阐释了 POI 访问率或受欢迎程度数据以及其他公开数据的用例，用于分析像 COVID-19 这样的高度动态和破坏性事件期间的需求模式和空间因素。我们开发了回归模型，通过使用锁定（治疗）作为虚拟变量，并具有主效应和交互效应，来分析慕尼黑 COVID-19 封锁之前和期间的空间和非空间属性与 POI 受欢迎程度的相关性。在我们对慕尼黑的案例研究中，我们发现停车距离和星期几等特征在解释受欢迎程度方面具有一致的行为。发现停车区域仅在非线性模型中相关。研究发现，锁定与 POI 类型、停止距离和星期几的交互作用非常显着。由于存在不同的城市特定因素，结果可能无法转移到其他城市。我们的案例研究结果提供了 POI 限制影响的证据，并显示 POI 类型和停止距离与 POI 受欢迎程度之间存在显着相关性。这些结果表明，由于限制而造成的影响存在局部和时间上的变化，这可能会影响城市在未来破坏性事件期间如何调整其交通服务以适应不同的需求以及由此产生的流动模式。