Rights statement: This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 251, 3, 2016 DOI: 10.1016/j.ejor.2015.12.034
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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Agent-based computational modelling of social risk responses
AU - Busby, Jeremy Simon
AU - Onggo, Bhakti Satyabuhdi Stephan
AU - Liu, Yun
N1 - This is the author’s version of a work that was accepted for publication in European Journal of Operational Research. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in European Journal of Operational Research, 251, 3, 2016 DOI: 10.1016/j.ejor.2015.12.034
PY - 2016/6/16
Y1 - 2016/6/16
N2 - A characteristic aspect of risks in a complex, modern society is the nature and degree of the public response – sometimes significantly at variance with objective assessments of risk. A large part of the risk management task involves anticipating, explaining and reacting to this response. One of the main approaches we have for analysing the emergent public response, the social amplification of risk framework, has been the subject of little modelling. The purpose of this paper is to explore how social risk amplification can be represented and simulated. The importance of heterogeneity among risk perceivers, and the role of their social networks in shaping risk perceptions, makes it natural to take an agent-based approach. We look in particular at how to model some central aspects of many risk events: the way actors come to observe other actors more than external events in forming their risk perceptions; the way in which behaviour both follows risk perception and shapes it; and the way risk communications are fashioned in the light of responses to previous communications. We show how such aspects can be represented by availability cascades, but also how this creates further problems of how to represent the contrasting effects of informational and reputational elements, and the differentiation of private and public risk beliefs. Simulation of the resulting model shows how certain qualitative aspects of risk response time series found empirically – such as endogenously-produced peaks in risk concern – can be explained by this model.
AB - A characteristic aspect of risks in a complex, modern society is the nature and degree of the public response – sometimes significantly at variance with objective assessments of risk. A large part of the risk management task involves anticipating, explaining and reacting to this response. One of the main approaches we have for analysing the emergent public response, the social amplification of risk framework, has been the subject of little modelling. The purpose of this paper is to explore how social risk amplification can be represented and simulated. The importance of heterogeneity among risk perceivers, and the role of their social networks in shaping risk perceptions, makes it natural to take an agent-based approach. We look in particular at how to model some central aspects of many risk events: the way actors come to observe other actors more than external events in forming their risk perceptions; the way in which behaviour both follows risk perception and shapes it; and the way risk communications are fashioned in the light of responses to previous communications. We show how such aspects can be represented by availability cascades, but also how this creates further problems of how to represent the contrasting effects of informational and reputational elements, and the differentiation of private and public risk beliefs. Simulation of the resulting model shows how certain qualitative aspects of risk response time series found empirically – such as endogenously-produced peaks in risk concern – can be explained by this model.
KW - OR in societal problem analysis
KW - Multiagent systems
KW - Risk management
U2 - 10.1016/j.ejor.2015.12.034
DO - 10.1016/j.ejor.2015.12.034
M3 - Journal article
VL - 251
SP - 1029
EP - 1042
JO - European Journal of Operational Research
JF - European Journal of Operational Research
SN - 0377-2217
IS - 3
ER -