Resilience in Transportation Systems

Tamvakis, Pavlos; Xenidis, Yiannis

doi:10.1016/j.sbspro.2012.06.1308

Cited by 69 publications

(25 citation statements)

References 7 publications

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“…Current models primarily focus on a single type of infrastructure system. For example, these models include power system simulation (Eusgeld & Nan, 2009), water supply system simulation (Liu, Liu, Zhao & Tang, 2013), transportation systems (Tamvakis, Pavlos & Xenidis, 2012).…”

Section: Introductionmentioning

confidence: 99%

A composite policy tool to measure territorial resilience capacity

Pontarollo

Serpieri

2020

Socio-Economic Planning Sciences

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Section: Introductionmentioning

confidence: 99%

A composite policy tool to measure territorial resilience capacity

Pontarollo

Serpieri

2020

Socio-Economic Planning Sciences

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“…The socio-economic dimension of resilience and vulnerability requires that we analyze the conflicting interests of stakeholders. In particular, we must study the 1 Examples of systems studied from this perspective are transportation networks (Cantillo et al 2018;Tamvakis and Xenidis 2012), urban systems (Östh et al 2018) and electrical power systems (Holmgren 2007) among others. 2 This broad definition of social-ecological systems includes spatial economic systems, for the latter represent the spatial dimension of production and consumption (Nijkamp and Ratajczak 2013), which weave together social and natural elements.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability, Resilience and ‘Systemic Interest’: a Connectivity Approach

Cardinale

2019

Netw Spat Econ

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This paper analyzes the socioeconomic dimension of vulnerability and resilience from the viewpoint of connectivity. While no consensus has yet emerged on the definitions of vulnerability and resilience or on their relationship, it has been recognized that both have an important normative dimension, in that whether a system is considered vulnerable or resilient depends on the interests of the stakeholders involved. The paper proposes a dimension of resilience and vulnerability that is likely to be shared across a significant spectrum of stakeholders. To do so, the paper analyses connectivity within social-ecological systems from a BStructural Political Economy^viewpoint. A key concept in this regard is Bsystemic interest^, which is defined as the interest of stakeholders in keeping viable the system of connections within which they act. Systemic interest has desirable properties to conceptualize the normative dimension of vulnerability and resilience and leads to problematize their link with connectivity. In fact, it raises the question of what features of connectivity can be expected to lead to systemic interest, and how this impinges on vulnerability and resilience in different contexts. On the one hand, one might expect that a more interconnected system is more vulnerable to shocks, which propagate more easily throughout the system. On the other hand, such system might have a stronger systemic interest, so that a shock would trigger stakeholders' reaction to counteract its effects and avoid systemic consequences. The paper points to the institutional conditions that might make either outcome more likely in any given context.

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“…Rajesh and Ravi [4] considered that when choosing resilient suppliers, the key factors that should be considered include: vulnerability, collaboration, risk awareness, and supply chain continuity management. Baek et al [27] argued that the driving factor of resilient supply chain is flexibility, while Tamvakis et al [28] emphasize the role of transportation. Vugrin et al [29] define resilience from the perspectives of predisruption prevention and postdisruption recovery and considered that resilience includes absorptive, adaptive, and restorative capacities.…”

Section: Literature Reviewmentioning

confidence: 99%

Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment

Gan

Zhong

Liu

et al. 2019

Discrete Dynamics in Nature and Society

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Resilient suppliers can reduce supply chain risk, effectively avoid supply chain disruption, and bring profits to enterprises. However, there is no united measuring index system to evaluate the resilient supplier under supply chain environment, and the assessment language sets are usually crisp values. Therefore, in order to fill the research gap, this paper proposes a hybrid method, which combines triangular fuzzy number, the best-worst method (BWM), and the modular TOPSIS in random environments for group decision-making (GMo-RTOPSIS) to solve the above problem. Firstly, the weight of decision-maker is calculated by using fuzzy BWM which can deal with triangular fuzzy numbers. Secondly, triangular fuzzy number is introduced into GMo-RTOPSIS, and combined with fuzzy BWM, alternatives are sorted to select the best resilient supply chain partner. Finally, the feasibility and universality of this method are proved by illustrative examples.

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Resilience in Transportation Systems

Cited by 69 publications

References 7 publications

A composite policy tool to measure territorial resilience capacity

A composite policy tool to measure territorial resilience capacity

Vulnerability, Resilience and ‘Systemic Interest’: a Connectivity Approach

Resilient Supplier Selection Based on Fuzzy BWM and GMo-RTOPSIS under Supply Chain Environment

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