Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Community Detection in Actor Collaboration Networks of Resilience Planning and Management in Interdependent Infrastructure Systems
This paper presents community detection in actor collaboration networks to understand patterns of collective actions in resilience planning and management in interdependent infrastructure systems (IISs) prior to Hurricane Harvey in Harris County, Texas. Resilience in IISs is influenced by the collective actions of actors involved in planning, operating, and maintaining of physical systems. Hence, evaluating the patterns of collective actions in actor networks is important for understanding and improving the resilience planning and management in IISs. This study mapped four bipartite actor collaboration networks at different frequency levels in Harris County, Texas, prior to Hurricane Harvey based on a stakeholder survey. Then, the patterns of collective actions were assessed using the bi-Louvain community detection algorithm. The results show that, prior to Hurricane Harvey: 1) actor communities were segregated based on their government and non-government type in the network at yearly collaboration frequency level, 2) with the increase of the collaboration frequency, the network cohesion in the actor network became weaker. The results imply segregation between different communities and insufficient coordination across government and non-government actors. The study provides a new way to examine collective actions based on evaluation of communities in actor networks in IIS. The results could provide new insights into increasing cohesion in actor collaboration networks to improve the resilience planning and management in IISs.
Community Detection in Actor Collaboration Networks of Resilience Planning and Management in Interdependent Infrastructure Systems
This paper presents community detection in actor collaboration networks to understand patterns of collective actions in resilience planning and management in interdependent infrastructure systems (IISs) prior to Hurricane Harvey in Harris County, Texas. Resilience in IISs is influenced by the collective actions of actors involved in planning, operating, and maintaining of physical systems. Hence, evaluating the patterns of collective actions in actor networks is important for understanding and improving the resilience planning and management in IISs. This study mapped four bipartite actor collaboration networks at different frequency levels in Harris County, Texas, prior to Hurricane Harvey based on a stakeholder survey. Then, the patterns of collective actions were assessed using the bi-Louvain community detection algorithm. The results show that, prior to Hurricane Harvey: 1) actor communities were segregated based on their government and non-government type in the network at yearly collaboration frequency level, 2) with the increase of the collaboration frequency, the network cohesion in the actor network became weaker. The results imply segregation between different communities and insufficient coordination across government and non-government actors. The study provides a new way to examine collective actions based on evaluation of communities in actor networks in IIS. The results could provide new insights into increasing cohesion in actor collaboration networks to improve the resilience planning and management in IISs.
Community Detection in Actor Collaboration Networks of Resilience Planning and Management in Interdependent Infrastructure Systems
Li, Qingchun (Autor:in) / Dong, Shangjia (Autor:in) / Mostafavi, Ali (Autor:in)
Construction Research Congress 2020 ; 2020 ; Tempe, Arizona
Construction Research Congress 2020 ; 675-683
09.11.2020
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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