Big data and disaster management: a systematic review and agenda for future research

• Published in: Annals of operations research Vol. 283; no. 1-2; pp. 939 - 959
• Main Authors: Akter, Shahriar, Wamba, Samuel Fosso
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2019; Springer; Springer Nature B.V
• Subjects: Applications of OR in Disaster Relief Operations; Big Data; Business and Management; Combinatorics; Data management; Disaster management; Disasters; Documents; Emergency management; Literature reviews; Methods; Operations research; Operations Research/Decision Theory; Part II; Technology application; Theory of Computation; Australia; Big data analytics; Emergency services; Humanitarian services; Disaster management; Systematic literature review
• ISSN: 0254-5330; 1572-9338
• DOI: 10.1007/s10479-017-2584-2

The era of big data and analytics is opening up new possibilities for disaster management (DM). Due to its ability to visualize, analyze and predict disasters, big data is changing the humanitarian operations and crisis management dramatically. Yet, the relevant literature is diverse and fragmented, which calls for its review in order to ascertain its development. A number of publications have dealt with the subject of big data and its applications for minimizing disasters. Based on a systematic literature review, this study examines big data in DM to present main contributions, gaps, challenges and future research agenda. The study presents the findings in terms of yearly distribution, main journals, and most cited papers. The findings also show a classification of publications, an analysis of the trends and the impact of published research in the DM context. Overall the study contributes to a better understanding of the importance of big data in disaster management.