Universidad del Pacífico, Lima, Peru.
Laboratory SAMOVAR, Telecom SudParis, Institut Polytechnique de Paris, Palaiseau, France.
PLoS One. 2021 Jan 28;16(1):e0244409. doi: 10.1371/journal.pone.0244409. eCollection 2021.
El Niño is an extreme weather event featuring unusual warming of surface waters in the eastern equatorial Pacific Ocean. This phenomenon is characterized by heavy rains and floods that negatively affect the economic activities of the impacted areas. Understanding how this phenomenon influences consumption behavior at different granularity levels is essential for recommending strategies to normalize the situation. With this aim, we performed a multi-scale analysis of data associated with bank transactions involving credit and debit cards. Our findings can be summarized into two main results: Coarse-grained analysis reveals the presence of the El Niño phenomenon and the recovery time in a given territory, while fine-grained analysis demonstrates a change in individuals' purchasing patterns and in merchant relevance as a consequence of the climatic event. The results also indicate that society successfully withstood the natural disaster owing to the economic structure built over time. In this study, we present a new method that may be useful for better characterizing future extreme events.
厄尔尼诺是一种极端天气现象,其特征是赤道东太平洋表面水温异常升高。这种现象的特点是暴雨和洪水,对受影响地区的经济活动产生负面影响。了解这种现象如何在不同的粒度级别上影响消费行为,对于推荐策略以使情况正常化至关重要。为此,我们对与信用卡和借记卡交易相关的数据进行了多尺度分析。我们的研究结果可以总结为两个主要结果:粗粒度分析揭示了给定地区厄尔尼诺现象的存在及其恢复时间,而细粒度分析则表明由于气候事件,个人购买模式和商家相关性发生了变化。结果还表明,由于随着时间的推移而建立的经济结构,社会成功地抵御了自然灾害。在这项研究中,我们提出了一种新方法,该方法可能有助于更好地描述未来的极端事件。