Cargando…

Decision-Making under Risk: Conditions Affecting the Risk Preferences of Politicians in Digitalization

Public officials are constantly facing decisions under risk, particularly in digitalization policies, the consequences of which are hard to predict given their multiple dimensional nature. Since scholarly research has not yet addressed this phenomenon, we do not know what influences the risk prefere...

Descripción completa

Detalles Bibliográficos
Autor principal: Roisse Rodrigues Ferreira, Jean
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8910726/
https://www.ncbi.nlm.nih.gov/pubmed/35270728
http://dx.doi.org/10.3390/ijerph19053036
Descripción
Sumario:Public officials are constantly facing decisions under risk, particularly in digitalization policies, the consequences of which are hard to predict given their multiple dimensional nature. Since scholarly research has not yet addressed this phenomenon, we do not know what influences the risk preferences of politicians in digitalization policies. Prospect theory—widely used to explain political decisions—can help us describe politicians’ potential risk references and the conditions affecting their decisions. Accordingly, this paper aims to answer the following question: what are the conditions affecting the risk preferences of politicians in digitalization policies? I address this question by employing two important assumptions of prospect theory: the value function and the probability weighting function. Particularly, I discuss the effects of loss/gain frames and probability weighting on the risk preferences of politicians in digitalization with outcomes in multiple dimensions (e.g., data privacy and economy). I argue that whether an outcome is perceived as a gain or as a loss depends on how the situation is framed and how the probabilities are weighted. I conclude with a brief discussion of how prospect theory can leverage our understanding of political decisions in highly complex policy environments.