Exploring Probabilistic Network-Based Modeling of Multidimensional Factors Associated with Country Risk

Area of Science:

• Economics
• Risk Management
• Data Science

Background:

• Country risk assessment is crucial for global business expansion.
• Existing models lack a probabilistic network approach to evaluate individual factor contributions.
• Limited focus on identifying critical risk factors and their interdependencies.

Purpose of the Study:

• To develop a probabilistic network model for country risk assessment.
• To identify critical factors influencing country risk using real data.
• To provide insights for policy-makers and multinational enterprises.

Main Methods:

• Development of a probabilistic network model.
• Utilizing real-world data for analysis.
• Assessing network-wide vulnerability and resilience of factors.

Main Results:

• The model captures dependencies among multidimensional country risk factors.
• Identified critical factors influencing overall country risk.
• Quantified network-wide vulnerability and resilience potential.

Conclusions:

• The study offers a novel methodology for country risk assessment.
• Provides actionable insights for prioritizing risk mitigation strategies.
• Enables better prioritization of factors for regional stability and business environment analysis.