{"title":"家庭对灾害引起的长期停电易感性的实证评估","authors":"Amir Esmalian, Shangjia Dong, A. Mostafavi","doi":"10.1061/9780784482858.100","DOIUrl":null,"url":null,"abstract":"The objective of this study is to empirically assess household susceptibility to the power disruptions during disasters. In this study, a service gap model is utilized to characterize household susceptibility to infrastructure service disruptions. The empirical household survey data collected from Harris County, Texas, in the aftermath of Hurricane Harvey was employed in developing an appropriate empirical model to specify the significance of various factors influencing household susceptibility. Various factors influencing households’ susceptibility were implemented in developing the models. The step-wise algorithm was used to choose the best subset of variables, and availability of substitutes, previous hazards experience, level of need, access to reliable information, race, service expectations, social capital, and residence duration were selected to be included in the models. Among three classes of models, accelerated failure time (AFT)-loglogistic model yielded the best model fitness for estimating households’ susceptibility to disaster-induced power disruption. The model showed that having a substitute, households’ need for the service, race, and access to reliable information are the most significant factors influencing household susceptibility to the power disruptions. Understanding households’ susceptibility to infrastructure service disruptions provides useful insights for prioritizing infrastructure resilience improvements in order to reduce societal impacts.","PeriodicalId":322194,"journal":{"name":"Construction Research Congress 2020","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Empirical Assessment of Household Susceptibility to Hazards-Induced Prolonged Power Outages\",\"authors\":\"Amir Esmalian, Shangjia Dong, A. Mostafavi\",\"doi\":\"10.1061/9780784482858.100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The objective of this study is to empirically assess household susceptibility to the power disruptions during disasters. In this study, a service gap model is utilized to characterize household susceptibility to infrastructure service disruptions. The empirical household survey data collected from Harris County, Texas, in the aftermath of Hurricane Harvey was employed in developing an appropriate empirical model to specify the significance of various factors influencing household susceptibility. Various factors influencing households’ susceptibility were implemented in developing the models. The step-wise algorithm was used to choose the best subset of variables, and availability of substitutes, previous hazards experience, level of need, access to reliable information, race, service expectations, social capital, and residence duration were selected to be included in the models. Among three classes of models, accelerated failure time (AFT)-loglogistic model yielded the best model fitness for estimating households’ susceptibility to disaster-induced power disruption. The model showed that having a substitute, households’ need for the service, race, and access to reliable information are the most significant factors influencing household susceptibility to the power disruptions. Understanding households’ susceptibility to infrastructure service disruptions provides useful insights for prioritizing infrastructure resilience improvements in order to reduce societal impacts.\",\"PeriodicalId\":322194,\"journal\":{\"name\":\"Construction Research Congress 2020\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Construction Research Congress 2020\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1061/9780784482858.100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Construction Research Congress 2020","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1061/9780784482858.100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Empirical Assessment of Household Susceptibility to Hazards-Induced Prolonged Power Outages
The objective of this study is to empirically assess household susceptibility to the power disruptions during disasters. In this study, a service gap model is utilized to characterize household susceptibility to infrastructure service disruptions. The empirical household survey data collected from Harris County, Texas, in the aftermath of Hurricane Harvey was employed in developing an appropriate empirical model to specify the significance of various factors influencing household susceptibility. Various factors influencing households’ susceptibility were implemented in developing the models. The step-wise algorithm was used to choose the best subset of variables, and availability of substitutes, previous hazards experience, level of need, access to reliable information, race, service expectations, social capital, and residence duration were selected to be included in the models. Among three classes of models, accelerated failure time (AFT)-loglogistic model yielded the best model fitness for estimating households’ susceptibility to disaster-induced power disruption. The model showed that having a substitute, households’ need for the service, race, and access to reliable information are the most significant factors influencing household susceptibility to the power disruptions. Understanding households’ susceptibility to infrastructure service disruptions provides useful insights for prioritizing infrastructure resilience improvements in order to reduce societal impacts.