Kondraganti Abhilash, Narayanamurthy Gopalakrishnan, Sharifi Hossein
University of Liverpool Management School, Chatham Street, Liverpool, L69 7ZH UK.
Ann Oper Res. 2022 Nov 21:1-38. doi: 10.1007/s10479-022-04904-z.
At the start of this review, 168 million individuals required humanitarian assistance, at the conclusion of the research, the number had risen to 235 million. Humanitarian aid is critical not just for dealing with a pandemic that occurs once every century, but more for assisting amid civil conflicts, surging natural disasters, as well as other kinds of emergencies. Technology's dependability to support humanitarian and disaster operations has never been more pertinent and significant than it is right now. The ever-increasing volume of data, as well as innovations in the field of data analytics, present an incentive for the humanitarian sector. Given that the interaction between big data and humanitarian and disaster operations is crucial in the coming days, this systematic literature review offers a comprehensive overview of big data analytics in a humanitarian and disaster setting. In addition to presenting the descriptive aspects of the literature reviewed, the results explain review of existent reviews, the current state of research by disaster categories, disaster phases, disaster locations, and the big data sources used. A framework is also created to understand why researchers employ various big data sources in different crisis situations. The study, in particular, uncovered a considerable research disparity in the disaster group, disaster phase, and disaster regions, emphasising how the focus is on reactionary interventions rather than preventative approaches. These measures will merely compound the crisis, and so is the reality in many COVID-19-affected countries. Implications for practice and policy-making are also discussed.
在本次综述开始时，有1.68亿人需要人道主义援助，而在研究结束时，这一数字已升至2.35亿。人道主义援助不仅对于应对百年一遇的大流行病至关重要，更重要的是在内部冲突、自然灾害激增以及其他各类紧急情况中提供援助。技术在支持人道主义和救灾行动方面的可靠性，从未像现在这样相关且重要。不断增长的数据量以及数据分析领域的创新，为人道主义部门提供了动力。鉴于大数据与人道主义和救灾行动之间的相互作用在未来几天至关重要，本系统文献综述全面概述了人道主义和灾难背景下的大数据分析。除了介绍所审查文献的描述性方面，结果还解释了对现有综述的回顾、按灾害类别、灾害阶段、灾害地点以及所使用的大数据来源划分的研究现状。还创建了一个框架，以了解研究人员在不同危机情况下使用各种大数据来源的原因。该研究尤其发现，在灾害类别、灾害阶段和灾害地区存在相当大的研究差距，强调重点在于应对性干预而非预防性方法。这些措施只会使危机更加复杂，许多受新冠疫情影响的国家的现实情况就是如此。还讨论了对实践和政策制定的影响。
