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

Abstract

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.

Cross-sector humanitarian–business partnerships in managing humanitarian logistics: an empirical verification

“…In the preparedness phase, humanitarian organisations can pre-establish emergency supplies, and pre-position vital equipment that will be needed in times of crisis (Salmerón and Apte 2010;Tomasini and Van Wassenhove 2009;Oloruntoba and Gray 2006;Tatham and Pettit 2010). In fact, any improvement in preparedness will in turn be translated into better performance during response (Akter and Wamba 2017;Chandes and Paché 2010;Ergun et al 2014;Tatham and Pettit 2010). This finding calls for the establishment of more partnerships that focus on preparedness, especially those that help humanitarian organisations to improve their inventory capacity, human resource capabilities and information systems.…”

“…The use of tools such as IT tools may be very helpful in fostering collaborative relations (Ergun et al 2014), which is an area where the commercial sector has considerable experience. The amount of data becoming available in case of disasters is growing, making data integration that ensures proper data gathering, modelling and notification systems a key area of attention (Akter and Wamba 2017). In fact, big data analytics may support disaster relief considerably (Swaminathan 2017).…”

Designing business models in circular economy: A systematic literature review and research agenda

“…In addition, the Internet of Things—although its practical effects are still unclaimed and under experimentation—can support the monitoring, analysis, and control of products' data in order to support their lifecycle and extend their replacement along the entire supply chain (Da Xu, He, & Li, ). Moreover, the Internet of Things can be used as a digital enabler of circular economy together with (a) system optimization models, (b) real‐time measurement, (c) big data analysis and process control, (d) smart integration of tools and methods, and (5) data mining techniques, to help quantify resource efficiency (Akter & Wamba, ; Marconi et al, ; Witkowski, ). In addition, additive manufacturing technologies (also known as 3D printing) can be used to support the design for assembly and re‐assembly, by producing modular and customized products for customers in places that are close to them, thus exploiting a localization advantage.…”

Big Data for Natural Disasters in an Urban Railroad Neighborhood: A Systematic Review

“…Based on a systematic literature review, the research by [35] examined BD in disaster management, presenting the main contributions, gaps, challenges, and an agenda for future research. [36] affirms that in the era of the BD revolution, there is potential to mitigate the effects of disaster events, allowing access to live critical information.…”