Anying Chen, Zhongliang Huang, Manchun Liang, & Guofeng Su. (2020). Empirical Study of Individual Evacuation Decision-making in Fire Accidents: Evacuate Intention and Herding Effect. In Amanda Hughes, Fiona McNeill, & Christopher W. Zobel (Eds.), ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management (pp. 200–209). Blacksburg, VA (USA): Virginia Tech.
Abstract: People's decision of evacuating or not could greatly influence the final losses in fire accidents. In order to study people's response under emergent occasions, a fire accident evacuation drill experiment was conducted in an office building without advance notice. 113 Participants' response and their decision-making process were collected by questionnaire survey right after the experiment. In this study, we mainly focused on two aspects of people's response, including participants' evacuate intention and their herding tendency during evacuate decision-making. It is found that the classical Expected Utility Theory (EUT) has certain limitation in explaining individual's evacuation intention, but the relationship between the expected utility and the evacuation intention could be represented with a modified model based on EUT. Furthermore, the herding tendency is found to be different for the two groups of people who intend to evacuate and not to evacuate. People who firstly intend not to evacuate are more easily to form herding behavior and change their minds to evacuate. Based on these findings, models of individual evacuation intention and herding tendency for two groups of people are put forward. Simulation is conducted to investigate the effect of these two changes in people's evacuation decision-making process, and results show that they both increase the final evacuation rate, reflecting the majority's risk aversion characteristics.
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Qing Gu, & David Mendonça. (2005). Patterns of group information-seeking in a simulated emergency response environment. In B. C. B. Van de Walle (Ed.), Proceedings of ISCRAM 2005 – 2nd International Conference on Information Systems for Crisis Response and Management (pp. 109–116). Brussels: Royal Flemish Academy of Belgium.
Abstract: Groups in emergency response environment may be confronted with problems that cannot be solved by following predefined procedures. They must therefore engage in a collective search for relevant information, cooperating and collaborating as they move towards the deadline. Information technologies and expertise may help shape group information seeking and determine its effectiveness. By understanding how response personnel search for information in emergencies and extending the findings to determine demands on information systems, we may begin to understand how to support and train for skillful information seeking in emergency situations. Accordingly, this research evaluates the impact of decision support systems and member expertise on group information-seeking behavior in a simulated emergency response environment. The results of the evaluation are then used to identify how information technologies may further support information seeking in emergency response.
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Sigmund Kluckner, Johannes Sautter, Matthias Max, Wolf Engelbach, & Tina Weber. (2012). Impacting factors on human reactionsto alerts. In Z.Franco J. R. L. Rothkrantz (Ed.), ISCRAM 2012 Conference Proceedings – 9th International Conference on Information Systems for Crisis Response and Management. Vancouver, BC: Simon Fraser University.
Abstract: Crisis response authorities have to deal with the unpredictability of their population's behavior. One of the complex challenges is to understand the people's reaction after an official alert in a crisis situation has been issued. This paper elaborates a knowledge base to describe impacting factors on human reactions in alerting situations. For this purpose, a literature review in the theme of human behavior after warnings was conducted and augmented with information gathered in a series of interviews in German-speaking countries. The outcome is phrased as factors that might impact the human reaction to a warning. This knowledge base shall support crisis management practitioners in the elaboration of alerting strategies as well as allow researchers to systematically structure human behavior aspects for the purpose of modeling and simulating alert effects. © 2012 ISCRAM.
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Ma Ma, Shengcheng Yuan, H. Zhang, & Yi Liu. (2013). Framework design for operational scenario-based emergency response system. In J. Geldermann and T. Müller S. Fortier F. F. T. Comes (Ed.), ISCRAM 2013 Conference Proceedings – 10th International Conference on Information Systems for Crisis Response and Management (pp. 332–337). KIT; Baden-Baden: Karlsruher Institut fur Technologie.
Abstract: The present paper introduces a scenario-based framework design for connecting emergency response system with human behavior analysis and social information processing, which aims at improving its comprehensive capability in dealing with unexpected situations caused by physical, social and psychological factors during a crisis. The overall framework consists of four function modules: Scenario awareness, scenario analysis, scenario evolvement and scenario response. A detailed function design for each module is presented as well as the related methodologies used for integration of four modules. The contribution of this paper includes two aspects. One is realizing the integration of incident evolution, information-spreading and decision-making by taking account of physical, social and psychological effects during emergency. The other is improving the efficiency of decisionmaking through dynamic optimization process.
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Maude Arru, & Elsa Negre. (2017). People Behaviors in Crisis Situations: Three Modeling Propositions. In eds Aurélie Montarnal Matthieu Lauras Chihab Hanachi F. B. Tina Comes (Ed.), Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management (pp. 139–149). Albi, France: Iscram.
Abstract: Warnings can help to prevent damages and harm if they are issued timely and provide information that help responders and population to adequately prepare for the disaster to come. Today, there are many indicator and sensor systems that are designed to reduce disaster risks. These systems have proved to be eective. Unfortunately, as all systems including human beings, a part of unpredictable remains. Indeed, each person behaves dierently when a problem arises. In this paper, we focus on people behaviors in crisis situations: from the definition of factors that impact human behavior to the integration of these behaviors, with three dierent modeling propositions, into a warning system in order to have more and more eÿcient crisis management systems.
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Babajide Osatuyi, & David Mendonça. (2010). Requirements for modeling collaborative information foraging behavior: An application to emergency response organizations. In C. Zobel B. T. S. French (Ed.), ISCRAM 2010 – 7th International Conference on Information Systems for Crisis Response and Management: Defining Crisis Management 3.0, Proceedings. Seattle, WA: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: Collaborative information foraging refers to the collective activities of seeking and handling information in order to meet information needs. This paper delineates requirements for modeling salient factors that shape collaborative information foraging behavior of groups. Existing modeling approaches are assessed based on their adequacy for measuring identified salient factors that shape collaborative information foraging behavior. A view of information foraging behavior as a dynamic process is presented. Consequently, this paper purports that modeling methods employed to aid understanding of foraging behavior must allow for plausible explanation of the inherent dynamism in foraging activities. This work therefore provides an initial roadmap to defining salient factors that need to be addressed in order to adequately model collaborative information foraging behavior within teams that operate in extreme environments. Implications of this work in practice and research are discussed.
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Philip Fei Wu. (2009). User acceptance of emergency alert technology: A case study. In S. J. J. Landgren (Ed.), ISCRAM 2009 – 6th International Conference on Information Systems for Crisis Response and Management: Boundary Spanning Initiatives and New Perspectives. Gothenburg: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The purpose of the study is to investigate the factors affecting the user acceptance of emergency alert systems. By studying the adoption of a SMS-based alert system at a large public university in the United States, this paper explores the research question: How are different motivational factors related to the intention and behavior of using emergency alert technology? Through a mixed-methods approach, the study demonstrates a “deepening” effort in applying the technology acceptance model (TAM) to emergency response system, drawing attention to the holistic nature of motivation-behavior in technology acceptance. Results of this research show that: The concept of usefulness has multiple levels of meanings to its intended users; the ease of use is more about the users' ability to control the system behavior; and subjective norm need to be examined with relation to its originating source.
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Yiewi Li., Yu Guo, & Naoya Ito. (2014). An exploration of a social-cognitive framework for improving the human-centric risk communication. In and P.C. Shih. L. Plotnick M. S. P. S.R. Hiltz (Ed.), ISCRAM 2014 Conference Proceedings – 11th International Conference on Information Systems for Crisis Response and Management (pp. 394–398). University Park, PA: The Pennsylvania State University.
Abstract: With the aim of improving human-centric risk communication, this research in progress paper argues for a social-cognitive perspective focusing on the interaction between laypeople and the information environment. A model is designed to predict laypeople's environmental risk perception and information seeking behavior. Using data from a national online survey (N=1,032), our research is an effort to test the predictive power of the socialcognitive model. Practical implications are also discussed in this paper.
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Yudi Chen, Angel Umana, Chaowei Yang, & Wenying Ji. (2021). Condition Sensing for Electricity Infrastructures in Disasters by Mining Public Topics from Social Media. In Anouck Adrot, Rob Grace, Kathleen Moore, & Christopher W. Zobel (Eds.), ISCRAM 2021 Conference Proceedings – 18th International Conference on Information Systems for Crisis Response and Management (pp. 598–608). Blacksburg, VA (USA): Virginia Tech.
Abstract: Timely and reliable sensing of infrastructure conditions is critical in disaster management for planning effective infrastructure restorations. Social media, a near real-time information source, has been widely used in the disaster domain for building timely, general situational awareness, such as urgent public needs and donations. However, the employment of social media for sensing electricity infrastructure conditions has yet been explored. This study aims to address the research gap to sense electricity infrastructure conditions through mining public topics from social media. To achieve this purpose, we proposed a systematic and customized approach wherein (1) electricity-related social media data is extracted by the classifier developed based on Bidirectional Encoder Representations from Transformers (BERT); and (2) public topics are modeled with unigrams, bigrams, and trigrams to incorporate the formulaic expressions of infrastructure conditions in social media. Electricity infrastructures in Florida impacted by Hurricane Irma are studied for illustration and demonstration. Results show that the proposed approach is capable of sensing the temporal evolutions and geographic differences of electricity infrastructure conditions.
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