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

Abstract

Assessment of country risk provides a vital source of information to organizations for expanding and globalizing their operations. Various rating agencies are involved in developing models for assessing country risk, which utilize different statistical techniques for establishing the overall impact of individual factors on country risk. The main limitation of existing studies on country risk is their limited focus on exploring the relative contribution of individual factors to country risk in a probabilistic network setting. Utilizing real data, we develop a probabilistic network model that captures dependencies among multidimensional factors associated with country risk. Further, we assess the network‐wide vulnerability and resilience potential of individual factors to identify critical factors. The findings of this study provide policy‐makers with some unique insights into prioritizing strategies to mitigate country risk. Further, this study provides the context for multinational enterprises to utilize the proposed methodology for prioritizing key factors associated with the relative variables of interest such as regional stability and business environment among others.

Adoption of a Data‐Driven Bayesian Belief Network Investigating Organizational Factors that Influence Patient Safety

“…We also conducted the Spearman's correlation test to establish the association between the two ranking schemes relative to the realization of the extreme states of individual factors (see Table VII ). The two ranking schemes can help establish whether these organizational factors possess the same relative importance in relation to their vulnerability and resilience potential (Qazi & Khan, 2020 ). The association is found to be statistically nonsignificant, which implies that the optimal choice of risk mitigation strategies is contingent on individual factors’ vulnerability and resilience potential.…”

Nexus between drivers of COVID-19 and country risks

“…This study yields a unique set of relative importance weights for different risk drivers in relation to COVID-19 and country risks simultaneously, thereby providing valuable information to decision-makers regarding resource allocation. Few studies [ 22 , 23 , 28 ] have explored the relative importance of different drivers of the two risks separately, but none of the studies have investigated this problem while accounting for interactions among various drivers of the two risks in a unified probabilistic network setting. Without adopting this approach, it may not be possible to establish an optimal resource allocation scheme for managing different risk drivers related to the two risks.…”

“…Country risk assessment is an active area of research due to the significant impact of country risk on regional development and prosperity [ 34 ]. Several studies have explored the assessment of country risk using financial, economic and political factors [ 28 , 35 , 36 ] and investigated the impact of country risk on regional stability, national development and businesses [ 27 , 37 , 38 ].…”

“…Exploring dependencies among risk factors in a network setting is critical for effective decision-making under risk and uncertainty [ 25 , 26 ]. However, it is quite challenging to capture cause-effect relations among various drivers in the context of country risk assessment [ 27 , 28 ]. On the other hand, studies that ignore the interdependence of risk factors can yield sub-optimal decisions regarding prioritizing risk factors and allocating resources for managing critical risks [ 26 , 29 ].…”

Risk perception and cost of capital in emerging market projects using dynamic conditional correlation model

“…Investor risk perception strategically relies on country risk and its computation. Consequently, country risk is influential to determine the investment decisions of private investors involved in PPP-based projects (Qazi and Khan, 2020). In this study, country risk is being taken as an important factor for shaping investor's perception.…”