Application of the perception model
In what concerns the model’s application in a threat analysis context, the threat is the undesirable behaviour, while the three components of the TPB (attitudes,
This section focuses on explaining the current state-of-the-art in identifying perception-derived threats and it is divided into two main sub-sections. The first sub-section will provide a theoretical background on how perceptions are shaped and how they are translated into behaviour and will therefore tackle the following topics: What is the information that is most likely to influence people’s beliefs? How are perceptions formed and what is the link between perceptions and beliefs? and What is the process by which beliefs influence behaviour? The second sub-section will be focused on linking the theoretical background into a methodology that would enable both security practitioners and humanitarian workers to identify and (hopefully) prevent threats derived from perceptions. This will be achieved through the analysis of different migration-related case studies, which will illustrate what are the types of perceptual beliefs that are relevant from a security/humanitarian perspective due to the risks they can generate for both the host country and the migrants themselves. Another important topic explored in this sub-section is the way in which perception-derived threats and especially the methodology for identifying perception-derived threats could be integrated into existing threat analysis methodologies.
In what concerns the model’s application in a threat analysis context, the threat is the undesirable behaviour, while the three components of the TPB (attitudes,
In order to successfully identify perception derived threats, one must understand which ‘perceptions’ fuel certain behaviours that could potentially be classified as ‘threatening.’ Whereas in
MIRROR has received funding from the European Union’s Horizon 2020 research and innovation action program under grant agreement No 832921.
CRiTERIA has received funding from the European Union’s Horizon 2020 research and innovation action program under grant agreement No 101021866.
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