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Agent-based computational modelling of social risk responses

Agent-based computational modelling of social risk responses
Agent-based computational modelling of social risk responses
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.
OR in societal problem analysis, Multiagent systems, Risk management
0377-2217
1029-1042
Busby, Jeremy Simon
58ad9a6a-0450-4cc3-a68b-12cc74796cce
Onggo, Bhakti Satyabuhdi Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Liu, Yun
103d136a-822d-468a-854d-5198f461a0f1
Busby, Jeremy Simon
58ad9a6a-0450-4cc3-a68b-12cc74796cce
Onggo, Bhakti Satyabuhdi Stephan
8e9a2ea5-140a-44c0-9c17-e9cf93662f80
Liu, Yun
103d136a-822d-468a-854d-5198f461a0f1

Busby, Jeremy Simon, Onggo, Bhakti Satyabuhdi Stephan and Liu, Yun (2016) Agent-based computational modelling of social risk responses. European Journal of Operational Research, 251 (3), 1029-1042. (doi:10.1016/j.ejor.2015.12.034).

Record type: Article

Abstract

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.

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More information

Accepted/In Press date: 16 December 2015
e-pub ahead of print date: 23 December 2015
Published date: 16 June 2016
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
Keywords: OR in societal problem analysis, Multiagent systems, Risk management

Identifiers

Local EPrints ID: 425082
URI: https://eprints.soton.ac.uk/id/eprint/425082
ISSN: 0377-2217
PURE UUID: 447212d1-0e9b-4197-bc8f-41c5108a61f8
ORCID for Bhakti Satyabuhdi Stephan Onggo: ORCID iD orcid.org/0000-0001-5899-304X

Catalogue record

Date deposited: 10 Oct 2018 16:30
Last modified: 15 Jul 2019 16:56

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