Agent-based modelling of social risk amplification during product crises
Creators: name: Liu, Yun
Publisher: name: Lancaster University
Year: 2018
Subjects: social risk amplification
agent-based modelling
product recall
recreancy
media

description: Public response to risk is socially shaped in a way that often over- or
      under-estimates expert risk assessments. One of the main theoretical tools
      to examine public risk perception is the social amplification of risk
      framework (SARF). This framework proposes a mechanism through which risk
      responses arise from interactions among various social actors, but past
      empirical work has been mainly concerned with correlations between
      structural variables rather than the mechanism of amplification and the
      process over time by which it develops. And more importantly, there has
      been quite limited modelling of risk amplification to date. This study
      aims to discover a way of formalising social risk amplification, to find
      out what are the necessary assumptions for modelling risk amplification,
      and to work out what consequences this modelling would predict. It is an
      attempt to model collective response to risks that are significant at a
      societal level but which materialise in a distributed way across a
      population. The natural heterogeneity of individual risk perceivers, the
      emergence of behaviour through interactions of social actors, and the
      complex feedback loops linking risk perception with risk related behaviour
      point to using an agent-based model as a modelling medium.
      
      The study is developed in the context of product contamination scandals
      such as the recent cases in China of contaminated milk products. One of
      the important features of contamination crises is that product recall has
      become an increasingly inevitable part and is often a key element in risk
      communication during such crises. Yet recalls send ambiguous signals about
      the misconduct of the organization in question: they clearly indicate some
      kind of failure, and possibly negligence, in the product that are
      associated with a risk of significant harm; but they also suggest that the
      organization is concerned with consumers’ welfare. 
      
      The model that was developed is based on the principle that risk
      perceivers have to assimilate risk through the risk beliefs of others,
      their direct experience of a risk, and communications about the risk from
      organizations (including their product recall decisions) and the media.
      And it is based on the principle that, as well as discovering the nature
      of a risk, risk perceivers also make judgments about wrongfulness (which
      Freudenburg called recreancy) – and this also shapes the strength of risk
      responses.
      
      The model is partially calibrated with a consumer survey carried out in
      the context of a Chinese milk contamination scandal that took place in
      recent years. Simulation results from the model show that public risk
      perception grows progressively toward an exogenous peak before it
      immediately decays, and that there is a relatively high residue of concern
      after the crisis is resolved. The objectivity of media coverage appears to
      be inversely related to risk amplification: a media that simply follows
      public opinion is associated more strongly with exaggerated risk
      perceptions than an objective one. A sensitivity analysis indicates that
      the initial conditions, objective risk level, duration of contamination,
      and variation of recreancy perception are the most significant influences
      on the degree of social amplification. This knowledge helps prioritize
      data collection for future research and identify important aspects that
      particularly require managerial attention.
      
      The main contribution of this study is to develop a process of modelling
      social risk amplification that consists of three steps of increasing
      contextualisation. The first step involves a basic model that captures
      social risk amplification as a general theory relative to all kinds of
      risk event. The second step contextualises this model specifically for
      product recall crises. It involves extracting agent decision rules from
      the literature on product recall, based on statistical associations found
      in empirical work on recall crises. And the third step contextualises the
      model for a specific population. It involves calibrating the relative
      importance of different information sources for the heterogeneous agent
      population using a survey of Chinese consumers responding to a milk
      contamination crisis. One important insight from the process of modelling
      risk amplification is that SARF is not sufficient for modelling particular
      crises. It seems essential that modelling of SARF should involve a clearly
      defined context in which risk responses arise.