Agent-based computational modelling of social risk responses

Abstract

Please cite this article as: J.S. Busby , B.S.S. Onggo , Y. Liu , Agent-based computational modelling of social risk responses, European Journal of Operational Research (2015Research ( ), doi: 10.1016Research ( /j.ejor.2015 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. 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.

Modelling security risk in critical utilities: The system at risk as a three player game and agent society

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Applications of agent-based modelling and simulation in the agri-food supply chains

“…Furthermore, the dynamics in ASC are often influenced by social factors (e.g. lifestyles, personal values, safety concerns) (Busby and Onggo, 2013, Busby et al, 2016, Chebolu-Subramanian and Gaukler, 2015, economic factors (e.g. price) and the environment (e.g.…”