CONSIDERACIONES BIOÉTICAS

Given the long-standing ambiguities of SARF, for example about what defines an ‘amplified’ risk response, this study uses an agent-based model to reason about risk amplification from the standpoint of an organization attempting to influence public response. This illustrates issues that have been explored only to a limited extent, such as Freudenburg’s (1993) general idea of recreancy, and explores an important context that has received little or no attention as a social risk amplification problem: product risk and recall events. It intends to provide a more precise understanding of social risk amplification and thereby contribute to the broader field of risk perception research. It synthesizes factors obtained from past work on SARF and past product recall studies into a coherent model and explores the implications of simulating this model. The concrete contributions of this thesis are mainly identified in the following two aspects.

First, this thesis provides a pathway to formalising social risk amplification in an organizational context of a recall event. Recall events, although not treated as problems of social risk amplification in the past, are important risk amplification events because the scale of the public response is important to the degree of risk that actually arises. If a public attenuates a product risk it will fail to respond adequately to the recall, and will consequently bear a higher objective risk. Recall events are also inherently interesting as risk amplification issues because there are two, basically opposing effects of the recall. The first is to inform the public of some risk they were probably not aware of before, but the second is to demonstrate to the public that the producer is concerned about the public’s welfare and is taking steps to protect it. These steps are likely to be costly to the firm. The aim in formalising our understanding of recall cases is to construct a process in which rules and interactions that determine agents’ behaviours are specified. The formalisation developed in this research is achieved by three main steps:

1) developing decision rules behind social risk amplification generally, 2) developing decision rules behind a specific crisis involving product recall, 3) calibrating the weights for the decision rules.

Within these three steps are certain essential aspects:

1) how to operationalize risk perception – an agent’s risk belief is shaped by three essential processes: risk discovery, recreancy, and media,

2) how to represent organizational decision making – product recall involves a decision about voluntariness and timing of when to recall a product,

3) how to represent media communication – media potentially plays different roles in shaping risk beliefs,

4) how to perform calibration of certain parameter distributions – by means of a consumer survey asking people to evaluate relative importance of risk information.

Overall, the modelling involves a process of progressively contextualising social risk amplification, integrating qualitative knowledge about decision rules and the connections between the rules of different decision makers with empirical data about the relative importance to decision makers of different information sources. Although the representation of risk decisions and calibration of the model are simple, the model reveals insight into the mechanism of risk amplification (e.g. the model produces a residue of concern after the crisis is terminated) and indicates critical variables (e.g. sensitivity analysis identifies recreancy as an influential factor of risk amplification).

Second, this thesis gives guidance on carrying out research concerning risk amplification: it proposes a method of extracting critical elements from the literature as well as a way of calibrating an agent model using a consumer survey. The procedure of developing decision rules of consumers as they respond to an organizational crisis (see Chapter 5) illustrates how to select factors from statistical findings of studies in a specific domain and to build these factors into an agent-based model. This approach, in principle, applies to situations in which a relatively large number of empirical studies are available in a particular area. It allows researchers to turn from a statistical correlation between two variables to a representation of agents whose decision rules express these relationships. This allows us to go from a model in which relationships are central to a model in which interactions of agents are central. This in turn allows us to model not average effects and average outcomes, but the dynamics of how effects and outcomes evolve over time within a population.

After this formulation of decision rules, the numerical priorities of heterogeneous agents still need to be determined. This comes from a calibration process. The calibration process can serve as a template for building a model of social risk amplification that can be made specific to a particular population and particular product crisis – for example the Chinese population buying infant milk products during a contamination event. A survey was employed as an instrument of calibration for a model of SARF for what is believed to be the first time, and it used a simple and straightforward way of gathering data to design survey questions to assess

calibration is that it encourages modellers to include only decision rules that are accessible to the decision makers using them, and to leave out those decision rules about which decision makers do not have insight. In other words, the calibration method only examines parameters and relationships that people are able to judge. The recreancy variation (by which recreancy can change when a firm makes a voluntary or an involuntary recall), for example, was not calibrated by the survey, because consumers’ recreancy perceptions of a firm represents a psychological state with respect to their belief in misconduct of the firm and it is hard for consumers to quantitatively evaluate the change in such state. Other approaches are needed to identify decision rules when people do not have access to their own rules, involving implied rather than stated priorities. Nonetheless, the calibration presented in this thesis offers a new perspective in micro-validation of SARF models.