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contributor authorAli Nejat; Saeed Moradi; Souparno Ghosh
date accessioned2019-03-10T12:15:09Z
date available2019-03-10T12:15:09Z
date issued2019
identifier other%28ASCE%29IS.1943-555X.0000471.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255206
description abstractReestablishment of housing is a crucial component of the recovery process and has a domino effect on the overall timing of recovery. Anchors of social networks, such as schools and churches, on the other hand, are perceived to be influential in housing recovery decisions. This study provides a model for indexing households’ anchors of social network awareness based on publicly available data. This model uses individual-level data to develop a county-level index of anchors of social network awareness. This allows devising recovery strategies that are tailored to the needs of residents within a given county. Data were collected through an internet survey targeting New York and Louisiana, which were highly impacted by Hurricanes Sandy and Katrina. The survey asked participants to draw a polygon around their perceived neighborhood area in Google Maps. Then, follow-up questions were asked to identify key anchors driving this perception. Latent class analysis (LCA) and regression revealed the existence of multiple latent classes, each corresponding to a certain demographic and socioeconomic group. Finally, a county-level index of anchors of social network awareness was developed using individual-level latent classes. This index can be used by policyholders as a decision support tool for prioritizing anchors that are deemed to be important in a given county for receiving recovery assistance, which can then lead to a more enhanced recovery.
publisherAmerican Society of Civil Engineers
titleAnchors of Social Network Awareness Index: A Key to Modeling Postdisaster Housing Recovery
typeJournal Paper
journal volume25
journal issue2
journal titleJournal of Infrastructure Systems
identifier doi10.1061/(ASCE)IS.1943-555X.0000471
page04019004
treeJournal of Infrastructure Systems:;2019:;Volume ( 025 ):;issue: 002
contenttypeFulltext


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