Flood Risk and Preventive Choices: A Framework for Studying Human Behaviors.
agent-based framework
climate change
cognitive modeling
floods
hydrogeological phenomena
natural risk
social simulation
Journal
Behavioral sciences (Basel, Switzerland)
ISSN: 2076-328X
Titre abrégé: Behav Sci (Basel)
Pays: Switzerland
ID NLM: 101576826
Informations de publication
Date de publication:
20 Jan 2024
20 Jan 2024
Historique:
received:
27
12
2023
revised:
17
01
2024
accepted:
18
01
2024
medline:
26
1
2024
pubmed:
26
1
2024
entrez:
26
1
2024
Statut:
epublish
Résumé
The topic of flood phenomena has always been of considerable importance due to the high risks it entails, both in terms of potential economic and social damage and the jeopardizing of human lives themselves. The spread of climate change is making this topic even more relevant. This work aims to contribute to evaluating the role that human factors can play in responding to critical hydrogeological phenomena. In particular, we introduce an agent-based platform for analyzing social behaviors in these critical situations. In our experiments, we simulate a population that is faced with the risk of a potentially catastrophic event. In this scenario, citizens (modeled through cognitive agents) must assess the risk they face by relying on their sources of information and mutual trust, enabling them to respond effectively. Specifically, our contributions include (1) an analysis of some behavioral profiles of citizens and authorities; (2) the identification of the "dissonance between evaluation and action" effect, wherein an individual may behave differently from what their information sources suggest, despite having full trust in them in situations of particular risk; (3) the possibility of using the social structure as a "social risk absorber", enabling support for a higher level of risk. While the results obtained at this level of abstraction are not exhaustive, they identify phenomena that can occur in real-world scenarios and can be useful in defining general guidelines.
Identifiants
pubmed: 38275357
pii: bs14010074
doi: 10.3390/bs14010074
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : European Union
ID : Next Generation EU, PE 0000013, 931 FAIR-Future Artificial Intelligence Research