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    Anchors of Social Network Awareness Index: A Key to Modeling Postdisaster Housing Recovery

    Source: Journal of Infrastructure Systems:;2019:;Volume ( 025 ):;issue: 002
    Author:
    Ali Nejat; Saeed Moradi; Souparno Ghosh
    DOI: 10.1061/(ASCE)IS.1943-555X.0000471
    Publisher: American Society of Civil Engineers
    Abstract: Reestablishment 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.
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      Anchors of Social Network Awareness Index: A Key to Modeling Postdisaster Housing Recovery

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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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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
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