Ricerc@Sapienza

Although group-related uncertainties have been shown to drive subgroups’ pursuit of autonomy, it is unclear whether all group-related uncertainties motivate subgroup autonomy. We hypothesized that social identity-uncertainty, not politico-economic uncertainty, about one’s subgroup is a key driver of support for subgroup autonomy.

In the present chapter an overview of the notion of uncertainty in statistical matching is given. New measures of uncertainty are introduced, and new proposals for the construction of a methcing distribution are formulated.

Literature suggests that checking behaviors are aimed at reducing feelings of uncertainty both in clinical samples with obsessive-compulsive disorder and in general population. Previous studies also showed that deontological guilt is an emotion often associated with obsessive-compulsive disorder. Thus, the aim of the current study was to investigate the differences in checking behaviors in the condition of high versus low uncertainty, by exploring the moderating role of deontological versus altruistic guilt.

Why are people (de)motivated to mobilize in favor of immigrants? Addressing this question, we investigated the role of individuals' epistemic motivation (i.e., need for closure) in influencing the process of becoming motivated to participate in collective action in favor of immigrants in Italy. Specifically, the mediational role of binding moral foundations and political conservatism in explaining the relationship between need for closure and collective action in favor of immigrants was examined in three studies.

Management can be considered the science of decisions. Different researchers and practitioners have analysed the contents and boundaries of this vibrant domain, proposing multiple contributions and several perspectives. After a short overview of the principles of scientific management and their contribution to the definition of the modern idea of business management, this chapter briefly introduces the topics of subjectivity, complexity and uncertainty as relevant challenges to face in decision-making processes.

Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories,and avoiding inappropriate decision-making.

In the process of scientific discovery, knowledge ampliation is pursued by means of non-deductive inferences. When ampliative reasoning is performed, probabilities cannot be assigned objectively. One of the reasons is that we face the problem of the unconceived alternatives: we are unable to explore the space of all the possible alternatives to a given hypothesis, because we do not know how this space is shaped.

We estimate different MS-SBVARs with U.S. data from 1978 to 2015 and we adopt a final model with two variance regimes and two monetary policy regimes: The variance regimes capture periods of high or low uncertainty of the system. The monetary policy regimes are hawkish or dovish. The hawkish regime captures mainly the Volcker mandate, in which the conduct of monetary policy followed the dynamics of inflation, whereas the dovish regime is active under Greenspan and Bernanke, when the central banker focused mainly on real activity.