Resilience: Theory and Application.

Carlson, Jennifer; Haffenden, R.A.; Bassett, G. W.; Buehring, W.A.; Collins, Michael J.; Folga, S.; Petit, Frédéric; Phillips, Julia; Verner, Duane; Whitfield, R. G.

doi:10.2172/1044521

Cited by 145 publications

(88 citation statements)

References 7 publications

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“…Also, Levin et al (1998) argued that flexibility and adaptivity were necessary in a response system dealing with shocks. Carlson et al (2012) reinforces the adaptivity concept by defining resilience as the capacity of an entity to absorb, adapt to, anticipate, recover from, resist, and respond to a shock.…”

Section: General Definitions Of Resiliencementioning

confidence: 94%

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Spatial Economic Resilience: Overview and Perspectives

2014

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The concept of resilience has been receiving both theoretical and empirical attention in recent years, from different disciplinary fields, including spatial economics where resilience is becoming a 'popular' term. In particular, the concept of spatial economic resilience seems to assume slightly different interpretations. Starting from the basic definitions of resilience, which stem from ecology, this paper aims to highlight the similarities and the differences in the various analyses of resilience, in order to offer some insights into its use in the spatial economics literature.

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Section: General Definitions Of Resiliencementioning

confidence: 94%

“…Given these premises, the concept of resilience might be understood as a multifaceted notion that can be managed differently according to different objectives (Carlson et al 2012). Readers interested in investigating the concept of resilience more deeply might be hindered by the range of definitions, classifications and uses of resilience.…”

Section: Introductionmentioning

confidence: 99%

Spatial Economic Resilience: Overview and Perspectives

2014

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“…Extensive research on system resilience has still not resulted in a standard definition of resilience, or a consistent approach for quantifying resilience [Sheard and Mostashari, ]. We quote and paraphrase the following definitions of resilience: The ability to restore a system from a disrupted state to a stable recovered state [Henry and Ramirez‐Marquez, ]. A time‐dependent ratio of recovery over maximum loss [Barker, Ramirez‐Marquez, and Rocco, ]. Resilience is that of emergence, which means that simple entities, because of their interaction and feedback, their cross‐adaptation, and cumulative change, can produce far more complex behaviors as a collective, and produce effects across scales different from those along which the entities themselves operate [Dekker et al., ]. “…ability of an entity—for example, asset, organization, community, region—to anticipate, resist, absorb, respond to, adapt to, and recover from a disturbance” [Carlson et al., ]. Resilience is the ability of an architecture to support the functions necessary for mission success in spite of hostile action or adverse conditions [DOD, ]. …”

Section: Introductionmentioning

confidence: 99%

Resilience in Complex Systems: An Agent‐Based Approach

Pumpuni-Lenss

Blackburn

Garstenauer

2017

Systems Engineering

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This paper presents results from a research project on the behavior of complex systems after they experience disruptive events that impact their performance. As systems become more complex, the probability increases that they will exhibit emergent behavior that could lead to system failures or widespread and prolonged service interruptions. A complex adaptive system (CAS) approach is used to conceptualize a complex network system that has been impacted by disruptions and perturbations. A combination of network analysis and agent-based modeling is used to measure the performance of the system as it responds to disruptive events and restoration efforts. This system-level behavior is an emergent property of the complex network and represents system resilience. Various resilience measures are used to quantify system resilience and assess the effectiveness of strategies system owners employ to restore the system. We illustrate our techniques by characterizing a critical infrastructure system network as a CAS, and applying an agent-based simulation with an adaptive algorithm. C⃝ 2017 Wiley Periodicals, Inc. Syst Eng

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“…From a modeling perspective, the question is, of course, critical: How we frame resilience directly affects the approach we use to identify, assess, and address the key factors influencing how our most important systems respond to disruptive events. Numerous authors have codified, contrasted, and commented upon the variety of resilience definitions existing in the scientific and technical literature (e.g., Brand and Jax 2007;Martin-Breen and Anderies 2011;Bhamra et al 2011;Carlson et al 2012). These definitions of resilience vary but are based upon the same core concept: Resilience is the capacity of a system to cope with disruptions while maintaining or rapidly reestablishing the system's functionality.…”

Section: Defining Resilience: Implications For Modelingmentioning

confidence: 99%

Risk management is not enough: a conceptual model for resilience and adaptation-based vulnerability assessments

et al. 2015

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The US government has focused considerable attention on enhancing our society's ability to protect critical systems and services from disruptive events. Over the past decade, federal agencies have bolstered their efforts to identify and minimize threats using traditional risk-based approaches such as continuity of operations and disaster risk reduction processes. However, these valuable risk identification and management tools are limited because they rely upon foreseeable factor analyses of steady-state systems with predictable hazard frequencies and severities. In assessing the capability of complex adaptive systems to cope with disruptions, an overemphasis upon engineering resilience through risk management and planning for what is predictable may cloud or detract from our efforts to better understand a system's emergent capabilities to withstand disruptions that are unforeseeable. This article contends that augmenting traditional risk approaches through the incorporation of methodologies grounded in socio-ecological system (SES) resilience principles offers a potential avenue for improving our agencies' abilities to assess and manage both known and unknown risks. We offer a notional rationale for broadening our examination of system vulnerabilities and present a conceptual model that combines engineering and SES resilience paradigms to facilitate the identification, assessment, and management of system vulnerabilities. The Military Installation Resilience Assessment model described herein applies risk and resilience principles to evaluate whole systems, focusing on interconnections and their functionality in facilitating response and adaptation.

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Resilience: Theory and Application.

Cited by 145 publications

References 7 publications

Spatial Economic Resilience: Overview and Perspectives

Spatial Economic Resilience: Overview and Perspectives

Resilience in Complex Systems: An Agent‐Based Approach

Risk management is not enough: a conceptual model for resilience and adaptation-based vulnerability assessments

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