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Valentin Bertsch, Otto Rentz, & Jutta Geldermann. (2007). Preference elicitation and sensitivity analysis in multi-criteria group decision support for nuclear remediation management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 395–404). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The resolution of complex decision situations in crisis and remediation management following a man-made or natural emergency usually requires input from different disciplines and fields of expertise. Contributing to transparency and traceability of decisions and taking subjective preferences into account, multi-criteria decision analysis (MCDA) is suitable to involve various stakeholder and expert groups in the decision making process who may have diverse background knowledge and different views, responsibilities and interests. The focus of this paper is to highlight the role of MCDA in nuclear emergency and remediation management on the basis of a hypothetical case study. Special emphasis is placed on the modelling of the decision makers' preferences. The aim is to explore the sensitivity of decision processes to simultaneous variations of the subjective preference parameters and consequently to contribute to a facilitation of the preference modelling process by comprehensibly visualising and communicating the impact of the preferential uncertainties on the results of the decision analysis.
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Camelia Bellepeau, Hugo Bergere, Corentin Thevenet, Frédérick Bénaben, Nafe Moradkhani, & Thibaut Cerabona. (2022). Use of Physics of Decision to Assess how COVID-19 Impacted Air Pollution. In Rob Grace, & Hossein Baharmand (Eds.), ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management (pp. 887–894). Tarbes, France.
Abstract: This article focuses on the question of the impact of the COVID-19 crisis on air pollution. The chosen approach is based on the principle of “Physics of Decision” (POD), which considers: (i) the performance of a system as a physical trajectory within the framework of its performance indicators, (ii) risks or opportunities (potentialities) as forces that may deviate that trajectory, and (iii) benefits or damages (actualities) as concrete deviations of the performance trajectory. The daily data about the air pollution in Paris area (France) has been gathered for eight years (2014-2021) and three main performance indicators have been chosen. Then, the performance trajectory of each year has been plotted and the expected trajectories of 2020 and 2021 have been guessed from the previous ones. The deviation between the expected and actual trajectories of 2020 and 2021 have been assessed, and using physics and motion laws, evaluated as a deviation force.
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Daniel Hahn. (2007). Non-restrictive linking in wireless sensor networks for industrial risk management. In K. Nieuwenhuis P. B. B. Van de Walle (Ed.), Intelligent Human Computer Systems for Crisis Response and Management, ISCRAM 2007 Academic Proceedings Papers (pp. 605–609). Delft: Information Systems for Crisis Response and Management, ISCRAM.
Abstract: The OSIRIS project addresses the disaster management workflow in the phases of risk monitoring and crisis management. Risk monitoring allows the continuous observation of endangered areas combined with sensor deployment strategies. The crisis management focuses on particular events and the support by sensor networks. Four complementary live demonstrations will validate the OSIRIS approach. These demonstrations include water contamination, air pollution, south European forest fire, and industrial risk monitoring. This paper focuses on the latter scenario: the industrial risk monitoring. This scenario offers the special opportunity to demonstrate the relevance of OSIRIS by covering all the aspects of monitoring, preparation and response phases of both environmental risk and crisis management. The approach focuses on non-restrictive linking in a wireless sensor network in order to facilitate the addition and removal of nodes providing open interaction primitives allowing the comfortable integration, exclusion, and modification. A management layer with an event-triggered and service-based middleware is proposed. A live lab with real fire is illustrated.
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Yongzhong Sha, Jinsong Yan, & Guoray Cai. (2014). Detecting public sentiment over PM2.5 pollution hazards through analysis of Chinese microblog. 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. 722–726). University Park, PA: The Pennsylvania State University.
Abstract: Decision-making in crisis management can benefit from routine monitoring of the (social) media to discover the mass opinion on highly sensitive crisis events. We present an experiment that analyzes Chinese microblog data (extracted from Weibo.cn) to measure sentiment strength and its change in relation to the recent PM 2.5 air pollution events. The data were analyzed using SentiStrength algorithm together with a special sentiment words dictionary tailored and refined for Chinese language. The results of time series analysis on detected sentiment strength showed that less than one percent of the posts are strong-positive or strong negative. Weekly sentiment strength measures show symmetric changes in positive and negative strength, but overall trend moved towards more positive opinions. Special attention was given to sharp bursts of sentiment strength that coincide temporally with the occurrence of extreme social events. These findings suggest that sentiment strength analysis may generate useful alert and awareness of pending extreme social events.
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Yiwei Li, Yu Guo, & Naoya Ito. (2015). The Role of Information Quality and Efficacy Beliefs in Predicting Chinese People?s Information Seeking about Air Pollution Risk. In L. Palen, M. Buscher, T. Comes, & A. Hughes (Eds.), ISCRAM 2015 Conference Proceedings ? 12th International Conference on Information Systems for Crisis Response and Management. Kristiansand, Norway: University of Agder (UiA).
Abstract: Information seeking is suggested as an important precursor of self-protective behavior. Therefore, ways of enhancing information seeking are expected to help individuals? precautionary action under conditions of risk. Builds upon previous efforts, a social-cognitive model of risk information seeking is constructed, presenting a new approach to meet the aforementioned expectation. Data were collected from a sample of Mainland Chinese people (N=1032). Results of path analysis demonstrated satisfactory model fit. Explanations on how the cognitive process resulted in information seeking may create a better understanding of individual behavior. Findings provide practical implications for communicating risks and for helping the public to make better decisions.
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