TY - JOUR
T1 - Anchors of social network awareness index
T2 - A key to modeling postdisaster housing recovery
AU - Nejat, Ali
AU - Moradi, Saeed
AU - Ghosh, Souparno
N1 - Publisher Copyright:
© ASCE.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - 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.
AB - 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.
KW - Anchors of social network
KW - Decision support tool
KW - Latent class analysis
KW - Multilevel analysis
KW - Policymaking
KW - Postdisaster recovery
UR - http://www.scopus.com/inward/record.url?scp=85060441675&partnerID=8YFLogxK
U2 - 10.1061/(ASCE)IS.1943-555X.0000471
DO - 10.1061/(ASCE)IS.1943-555X.0000471
M3 - Article
AN - SCOPUS:85060441675
SN - 1076-0342
VL - 25
JO - Journal of Infrastructure Systems
JF - Journal of Infrastructure Systems
IS - 2
M1 - 04019004
ER -