Investigating Interbank Contagion with Agent-Based Modeling and Functional Dependency Network Analysis (FDNA)

Costa, Amy; McShane, Michael K.; Pinto, C. Ariel

doi:10.2139/ssrn.2608937

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…In other words, FDNA focuses on how the operability loss of a supplier causes cascading effects on its receiver systems (Garvey & Pinto, 2009). FDNA has been applied in various domains including space infrastructure (Guariniello & DeLaurentis, 2013), the security of Global Navigation Satellite Systems (Wang, Zhang, & Li, 2014), data dependency modeling (Cole, 2017), cyberspace (Servi & Garvey, 2017), power systems (Garvey, Pinto, & Santos, 2014), and finance (e.g., interbank lending) (Costa, McShane, & Pinto, 2015).…”

Section: Interdependency Modeling For Network Riskmentioning

confidence: 99%

Managing Physical and Economic Risk for Systems with Multidirectional Network Interdependencies

2021

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Critical infrastructure networks, such as transportation and supply chains, are becoming increasingly interdependent. As the operability of network nodes relies on the operability of connected nodes, network disruptions have the potential to spread across entire networks, having catastrophic consequences in the realms of physical network performance and also economic performance. While risk‐informed physical network models and economic models have been well‐studied in the literature, there is limited study of how physical features of network performance interact with sector‐specific economic performance, particularly as these physical networks recover from disruptions of varying durations. In this article, we create a generalizable framework for integrating Functional Dependency Network Analysis (FDNA) and Dynamic Inoperability Input–Output Models (DIIM), to assess the extent to which disruptions to critical infrastructure could degrade its functionality over a period of time. We demonstrate the framework using disruptive scenarios for a critical transportation network in Virginia, USA. We consider scenarios involving: (a) mild case that is relatively more frequent such as recurring traffic conditions; (b) moderate case involving an incident with a multihour delay, and (c) severe case that is relatively less frequent such as evacuation after a major hurricane. The results will be useful for network managers, policymakers, and stakeholders who are seeking to invest in risk mitigation for network functionality and economic activity.

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Section: Interdependency Modeling For Network Riskmentioning

confidence: 99%

Managing Physical and Economic Risk for Systems with Multidirectional Network Interdependencies

2021

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“…Improving counterfire operations with enhanced command and… they reflected the concepts of price dispersion, price dynamics, production costs, and so on. Costa et al (2015) modeled banks as agents and addressed the impact of bank failure, the failure factors, and the spreading complexion caused by the failure. Table 3 lists some of these joint analyses of M&S and network analysis by comparing them to our work.…”

Section: Joint Analysis Of Mands and Network Analysis On Organizationsmentioning

confidence: 99%

Improving counterfire operations with enhanced command and control structure

Shin

Kang

Kim

et al. 2018

Comput Math Organ Theory

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The success of military operations depends on soldiers' execution of the operation as well as resources used for the operation. However, this does not mean that more men and firepower will ensure victory. Military units, just like any other organization, are collections of distributed elements, and improving the organization or command and control (C2) structure of such elements will ultimately show the true power of more men and resources. This paper presents a case study comparing two C2 structures in a counterfire operation, which is a very realistic scenario in some parts of the world. We modeled each structure with meta-networks and agent-based simulations, and then determined why one structure has a better outcome in the simulation. In particular, we jointly analyze the virtual experiment and network metrics, i.e., centralities, to identify the important resources and human factors. This research provides critical insight and suggestions to reform the C2 structure based on quantitative findings. In terms of the C2 structure, assigning detection units to the decentralized echelon brings about the reduction of the time for the targeting process, while the strengthened gun power for multiple targets is proved to have strong influence from the operational perspective.

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Exploring Functional Dependency Network Based Order-Degree Analysis for Resilient System-of-Systems Architecture Design

Liu

Fang

Qin

et al. 2022

2022 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

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Investigating Interbank Contagion with Agent-Based Modeling and Functional Dependency Network Analysis (FDNA)

Cited by 3 publications

References 26 publications

Managing Physical and Economic Risk for Systems with Multidirectional Network Interdependencies

Managing Physical and Economic Risk for Systems with Multidirectional Network Interdependencies

Improving counterfire operations with enhanced command and control structure

Exploring Functional Dependency Network Based Order-Degree Analysis for Resilient System-of-Systems Architecture Design

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