Using Mobile Phone Data for Emergency Management: a Systematic Literature Review

Wang, Yanxin; Li, Jian; Zhao, Xi; Feng, Gengzhong; Luo, Xin

doi:10.1007/s10796-020-10057-w

Cited by 27 publications

(15 citation statements)

References 109 publications

(100 reference statements)

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“…• Virtual conferencing systems, virtual togetherness (Hacker et al, 2020) • Experience and adjusting to working from home (Carillo et al, 2021;Waizenegger et al, 2020) • Misconceptions of digital work (Richter, 2020) • Knowledge management and collaboration systems and technologies (Kodama, 2020;Marks, 2020) • The future of knowledge work (Wang et al, 2020) Digital transformation and digitalisation…”

Section: Remote Working Working From Homementioning

confidence: 99%

“…This pushes the limits of IT management models and knowledge on digital work, as is evident in the papers that outline challenges experienced in the early stages of COIVD-19 related lockdowns. It is also evident in the differing future visions of remote work, ranging from 'digital Taylorism' to 'worker autonomy' (Wang et al, 2020). Future research should examine the different models of working from home used by organisations, the challenges in reversing this trend (Kelly, 2021), and how these may spur new models of work.…”

Section: The Immediate Response: Contributions and Looking Forwardmentioning

confidence: 99%

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The pursuit of relevance and impact: A review of the immediate response of the information systems field to COVID‐19

Karanasios

2021

Information Systems Journal

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The COVID-19 pandemic demanded an immediate response from the research community, including adjustment to how researchers undertake research. As in many fields, information systems scholars attempted 'rapid response' research that addresses the immediate crisis. This paper reviews the state of the immediate research and scholarly discussion in the information systems field. Seventy-one journal papers are reviewed. The review categorises nine thematic areas and one broad area of discussion. The methods by which information systems scholars address immediate research questions are identified. The contributions are discussed, future research directions are outlined and a model is proposed that traces the pathway from initiation of research/ generation of new knowledge to practice impact. A further model is proposed to help information systems scholars clearly establish the link between the study of information systems phenomena and COVID-19.

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Section: Remote Working Working From Homementioning

confidence: 99%

Section: The Immediate Response: Contributions and Looking Forwardmentioning

confidence: 99%

The pursuit of relevance and impact: A review of the immediate response of the information systems field to COVID‐19

Karanasios

2021

Information Systems Journal

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“…We measure the impact of drone strikes on civilian lives by utilizing changes in real-time call volume during drone strikes. In the broader literature, call volume has been frequently leveraged as a proxy to measure the scale and duration of an emergency among the general population (Wang et al ., 2020). It has been used in diverse contexts ranging from natural disasters (Tomaszewski, 2014), to the spread of disease (Baldo and Closas, 2013; Lima et al ., 2015; Tompkins and McCreesh, 2016; Mari et al ., 2017), and population displacement (Bozcaga et al ., 2019).…”

Section: Theorymentioning

confidence: 99%

The effect of drone strikes on civilian communication: evidence from Yemen

Christia

Zoumpoulis

Freedman

et al. 2021

PSRM

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Although covert warfare does not readily lend itself to scientific inquiry, new technologies are increasingly providing scholars with tools that enable such research. In this note, we examine the effects of drone strikes on patterns of communication in Yemen using big data and anomaly detection methods. The combination of these analytic tools allows us to not only quantify some of the effects of drone strikes, but also to compare them to other shocks. We find that on average drone strikes leave a footprint in their aftermath, spurring significant but localized spikes in communication. This suggests that drone strikes are not a purely surgical intervention, but rather have a disruptive impact on the local population.

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“…As climate change induces more frequent extreme weather events, populated areas are at greater risk to destruction and disruption due to floods at many scales and at every facet of society. Floods cause significant social and physical impacts on communities, such as property loss, loss of life, damage to infrastructure, and disrupted access to critical facilities (Wang et al 2020;Choi and Bae 2015;Huang et al 2008;Downton and Pielke 2005). In the aftermath of a flood, rapid assessment of either inundated areas or damages could facilitate rapid identification of hotspots with more severe flood impacts (Kryvasheyeu et al 2016) during flood event stages.…”

Section: Introductionmentioning

confidence: 99%

Unraveling the Temporal Importance of Community-scale Human Activity Features for Rapid Assessment of Flood Impacts

Yuan¹,

Yang²,

Li³

et al. 2021

Preprint

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The objective of this research is to explore the temporal importance of community-scale human activity features for rapid assessment of flood impacts. Ultimate flood impact data, such as flood inundation maps and insurance claims, becomes available only weeks and months after the floods have receded. Crisis response managers, however, need near-real-time data to prioritize emergency response. This time lag creates a need for rapid flood impact assessment. Accordingly, communityscale big data (such as satellite imagery) has been utilized for the early estimation of end flood impacts. Some recent studies have shown promising results for using human activity fluctuations as indicators of flood impacts. Existing studies, however, used mainly a single community-scale activity feature for the estimation of flood impacts and have not investigated their temporal importance for indicating flood impacts. Hence, in this study, we examined the importance of heterogeneous human activity features (such as human mobility, visits to points-of-interest, and social media posts) in different flood event stages. Using four community-scale big data categories we derived ten features related to the variations in human activity (e.g., travel, credit card transactions, and online communications) and evaluated their temporal importance for rapid assessment of flood impacts. Using multiple random forest models, we examined the temporal importance of each feature in indicating the extent of flood impacts (measured by the flood insurance claims and flood inundations) in the context of the 2017 Hurricane Harvey in Harris County, Texas. Our findings reveal that 1) fluctuations in human activity index and percentage of congested roads are the most important indicators for rapid flood impact assessment during response and recovery stages; 2) variations in credit card transactions assumed a middle ranking in both response and recovery stages; and 3) patterns of geolocated social media posts (Twitter) were of low importance across flood stages. Insights derived from data analysis reveal the potential for harnessing community-scale data characterizing human activity fluctuations for rapid assessment of flood impacts. The results of this research could rapidly forge a multi-tool enabling crisis managers to identify hotspots with severe flood impacts at various stages then to plan and prioritize effective response strategies.Keywords smart resilience • urban flood • machine learning • big data • rapid flood impact assessment

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Using Mobile Phone Data for Emergency Management: a Systematic Literature Review

Cited by 27 publications

References 109 publications

The pursuit of relevance and impact: A review of the immediate response of the information systems field to COVID‐19

The pursuit of relevance and impact: A review of the immediate response of the information systems field to COVID‐19

The effect of drone strikes on civilian communication: evidence from Yemen

Unraveling the Temporal Importance of Community-scale Human Activity Features for Rapid Assessment of Flood Impacts

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