Applying Complex Network Theory to the Assessment of Organizational Resilience

Ruiz-Martín, Cristina; Paredes, Adolfo López; Wainer, Gabriel

doi:10.1016/j.ifacol.2015.06.251

Cited by 30 publications

(10 citation statements)

References 14 publications

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“…For example, Ruiz-Martin et al (2017) proposed to apply the Viable System Model to design resilient organizations. Ruiz-Martin et al (2015) remarked the importance of communication systems in organizational resilience and suggested evaluating the communication system using network theory. Tolk & Johnson IV (2013) proposed to develop antifragile systems focusing on their components and interactions and Jones (2014) stated that a change in the way we design systems is needed.…”

Section: Discussion About Organizational Resilience Assessmentmentioning

confidence: 99%

What we know and do not know about organizational resilience

Ruiz-Martín

López-Paredes

Wainer

2018

Int. J. Prod. Manag. Eng.

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134

124

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We present a literature review about organizational resilience, with the goal of identifying how organizational resilience is conceptualized and assessed. The two research questions that drive the review are: (1) how is organizational resilience conceptualized? and (2) how is organizational resilience assessed? We answer the first question by analyzing organizational resilience definitions and the attributes or characteristics that contribute to develop resilient organizations. We answer the second question by reviewing articles that focus on tools or methods to measure organizational resilience. Although there are three different ways to define organizational resilience, we found common ideas in the definitions. We also found that organizational resilience is considered a property, ability or capability that can be improved over time. However, we did not find consensus about the elements that contribute to improving the level of organizational resilience and how to assess it. Based on the results of the review, we propose a conceptualization of organizational resilience that integrates the three views found in the literature. We also propose a four-level Maturity Model for Organizational Resilience -MMOR. Using this model, the organization can be in one of the following levels based on its ability and capacity to handle disruptive events: fragile, robust, resilient or antifragile.

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Section: Discussion About Organizational Resilience Assessmentmentioning

confidence: 99%

What we know and do not know about organizational resilience

Ruiz-Martín

López-Paredes

Wainer

2018

Int. J. Prod. Manag. Eng.

Self Cite

134

124

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“…Interference to a node in the system may cause a domino effect, which will affect the partial cascade of the network [20]. The relevant literature has mostly used single indicators to measure resilience, such as transmissibility, diversity, or connectivity [53][54][55]. We simulated changes in the network from the perspectives of transmissibility and diversity under scenarios of node failure and maximum load attack in order to evaluate structural resilience.…”

Section: Assessment Of Network Structure Resiliencementioning

confidence: 99%

Resilience of Urban Network Structure in China: The Perspective of Disruption

Wei

Pan

2021

IJGI

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In light of the long-term pressure and short-term impact of economic and technological globalization, regional and urban resilience has become an important issue in research. As a new organizational form of regional urban systems, the resilience of urban networks generated by flow space has emerged as a popular subject of research. By gathering 2017 data from the Baidu search index, the Tencent location service, and social statistics, this study constructs information, transportation, and economic networks among 344 cities in China to analyze the spatial patterns of urban networks and explore their structural characteristics from the perspectives of hierarchy and assortativity. Transmissibility and diversity were used to represent the resilience of the network structure in interruption scenarios (node failure and maximum load attack). The results show the following: The information, transportation, and economic networks of cities at the prefecture level and higher in China exhibit a dense pattern of spatial distribution in the east and a sparse pattern in the west; however, there are significant differences in terms of hierarchy and assortativity. The order of resilience of network transmissibility and diversity from strong to weak was information, economic, transportation. Transmissibility and diversity had nearly identical scores in response to the interruption of urban nodes. Moreover, a highly heterogeneous network was more likely to cause shocks to the network structure, owing to its cross-regional urban links in case of disturbance. We identified 12 dominant nodes and 93 vulnerable nodes that can help accurately determine the impetus behind network structure resilience. The capacity of regions for resistance and recovery can be improved by strengthening the construction of emergency systems and risk prevention mechanisms.

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“…Presently, the increasingly complex social environment, urban connectivity, and diverse economic structures have made it essential to enhance the capability of urban networks to cope with shocks for maintaining sustainable regional development [23]. Existing studies have shown that indicators such as network efficiency, diversity, and connectivity can effectively characterize the resilience of urban network structures [24][25][26]. Unpredictable, uncertain, and frequent natural and man-made disasters can affect urban nodes to a certain extent or can even fail, which can lead to the failure of urban networks and affect the sustainable development of a region [27].…”

Section: Introductionmentioning

confidence: 99%

Research on the Evaluation of Resilience and Influencing Factors of the Urban Network Structure in the Three Provinces of Northeast China Based on Multiple Flows

Liu

Tian

et al. 2022

Buildings

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An important indicator for measuring the resilience and ability of urban networks to recover under external environmental shock, which is essential for the healthy development of the region, is urban network structure resilience. Herein we analyzed the resilience of the urban network structure and explored the influencing factors of resilience in the three provinces of Northeast China. We accomplished this by utilizing the Gephi profiling social network analysis tools based on the Baidu Index, road mileage, statistical data, other multi-source data, construction information, and the transportation, innovation, and economic multiple linkage network. This analysis enabled us to propose relevant suggestions and strategies to optimize urban network structure resilience. Our results indicate that (1) in 2019, the multi-city network structure in the three provinces of Northeast China contains both commonalities and characteristics. Overall, each network demonstrates a spatial distribution pattern of “dense in the north and sparse in the south.” (2) There exist evident hierarchical differences in the resilience characteristics of the multi-city network structure in the three provinces; each provincial capital city and sub-provincial city possesses greater advantages, the innovation network exhibits the most evident hierarchy, the mismatch of the information network is the highest, and the transmission and agglomeration of the economic network are the most prominent. (3) The resilience of the urban network structure of the three provinces is the result of the interaction of several factors. Political and economic factors such as government capacity, economic status, and urban vitality are the main factors affecting the resilience of the network structure.

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Applying Complex Network Theory to the Assessment of Organizational Resilience

Cited by 30 publications

References 14 publications

What we know and do not know about organizational resilience

What we know and do not know about organizational resilience

Resilience of Urban Network Structure in China: The Perspective of Disruption

Research on the Evaluation of Resilience and Influencing Factors of the Urban Network Structure in the Three Provinces of Northeast China Based on Multiple Flows

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