Big Data Analytics for Rapid, Impactful, Sustained, and Efficient (RISE) Humanitarian Operations

• 成果类型: Article
• 署名作者: Swaminathan, Jayashankar M.
• 署名单位: University of North Carolina; University of North Carolina Chapel Hill
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12840
• 发表日期: 2018
• 页码: 1696-1700
• 关键词: big data; humanitarian operations; analytics

摘要

There has been a significant increase in the scale and scope of humanitarian efforts over the last decade. Humanitarian operations need to berapid, impactful, sustained, and efficient (RISE). Big data offers many opportunities to enable RISE humanitarian operations. In this study, we introduce the role of big data in humanitarian settings and discuss data streams which could be utilized to develop descriptive, prescriptive, and predictive models to significantly impact the lives of people in need.