Agent-based computational modelling of social risk responses

Busby, Jeremy Simon and Onggo, Bhakti Satyabuhdi Stephan and Liu, Yun (2016) Agent-based computational modelling of social risk responses. European Journal of Operational Research, 251 (3). pp. 1029-1042. ISSN 0377-2217

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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.

Item Type:
Journal Article
Journal or Publication Title:
European Journal of Operational Research
Additional Information:
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
Uncontrolled Keywords:
?? or in societal problem analysismultiagent systemsrisk managementmodelling and simulationmanagement science and operations researchinformation systems and management ??
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Deposited On:
22 Jan 2016 14:02
Last Modified:
31 Dec 2023 00:38