TY - GEN
T1 - Identification, Categorization, and Weighting of Barriers to Timely Post-Disaster Recovery Process
AU - Rouhanizadeh, Behzad
AU - Kermanshachi, Sharareh
AU - Nipa, Thahomina Jahan
N1 - Publisher Copyright:
© 2019 American Society of Civil Engineers.
PY - 2019
Y1 - 2019
N2 - Different aspects of disaster recovery have been studied in recent years through which a variety of barriers relative to different perspectives were determined. However, the barriers causing delays in the process of post-disaster recovery have not been studied in detail. Some of these barriers are related to pre-disaster conditions, and some relate to post-disaster situation. In this study, post-disaster recovery barriers causing delay have been studied comprehensively. Based on the existing literature, the barriers were identified, categorized, ranked, and weighted. The 33 identified barriers are presented in economic, social, environment, policy and politics, infrastructure, and transportation categories. Furthermore, social and economic categories had the highest weight, 35% and 25% respectively, among all the categories. The found preventives in this study can be used by researchers for later studies. In addition, the decision-makers can use the results for making proper disaster recovery planning.
AB - Different aspects of disaster recovery have been studied in recent years through which a variety of barriers relative to different perspectives were determined. However, the barriers causing delays in the process of post-disaster recovery have not been studied in detail. Some of these barriers are related to pre-disaster conditions, and some relate to post-disaster situation. In this study, post-disaster recovery barriers causing delay have been studied comprehensively. Based on the existing literature, the barriers were identified, categorized, ranked, and weighted. The 33 identified barriers are presented in economic, social, environment, policy and politics, infrastructure, and transportation categories. Furthermore, social and economic categories had the highest weight, 35% and 25% respectively, among all the categories. The found preventives in this study can be used by researchers for later studies. In addition, the decision-makers can use the results for making proper disaster recovery planning.
UR - http://www.scopus.com/inward/record.url?scp=85068770954&partnerID=8YFLogxK
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U2 - 10.1061/9780784482445.006
DO - 10.1061/9780784482445.006
M3 - Conference contribution
AN - SCOPUS:85068770954
T3 - Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2019
SP - 41
EP - 49
BT - Computing in Civil Engineering 2019
A2 - Cho, Yong K.
A2 - Leite, Fernanda
A2 - Behzadan, Amir
A2 - Wang, Chao
PB - American Society of Civil Engineers (ASCE)
T2 - ASCE International Conference on Computing in Civil Engineering 2019: Smart Cities, Sustainability, and Resilience, i3CE 2019
Y2 - 17 June 2019 through 19 June 2019
ER -