This study employs the bibliometric method to analyse a sample of 936 core journal articles obtained from Chinese Social Sciences Citation Index(CSSCI)during the period 1998–2014,with a view to outlining the situatio...This study employs the bibliometric method to analyse a sample of 936 core journal articles obtained from Chinese Social Sciences Citation Index(CSSCI)during the period 1998–2014,with a view to outlining the situation,characteristics and trends of Chinese research on disaster economics.Our analysis shows that Chinese research on disaster economics is characterised by marked shortterm fluctuations,non-mainstream tendency,localisation and noncollaboration.In terms of content,the major concerns of Chinese scholars are post-disaster construction,agricultural natural disasters,as well as disaster insurance and securitisation.In terms of methodology,these researches have entered into a quantitative phase of establishing the evaluation index system,and mathematical model analysis.With regard to the path,researches in the Chinese language have expanded from analyses of causes and natures of disasters to those of institutional response to disasters(e.g.disaster insurance and finance).展开更多
Earth observation(EO) technologies,such as very high-resolution optical satellite data available from Maxar,can enhance economic consequence modeling of disasters by capturing the fine-grained and real-time behavioral...Earth observation(EO) technologies,such as very high-resolution optical satellite data available from Maxar,can enhance economic consequence modeling of disasters by capturing the fine-grained and real-time behavioral responses of businesses and the public.We investigated this unique approach to economic consequence modeling to determine whether crowd-sourced interpretations of EO data can be used to illuminate key economic behavioral responses that could be used for computable general equilibrium modeling of supply chain repercussions and resilience effects.We applied our methodology to the COVID-19 pandemic experience in Los Angeles County,California as a case study.We also proposed a dynamic adjustment approach to account for the changing character of EO through longer-term disasters in the economic modeling context.We found that despite limitations,EO data can increase sectoral and temporal resolution,which leads to significant differences from other data sources in terms of direct and total impact results.The findings from this analytical approach have important implications for economic consequence modeling of disasters,as well as providing useful information to policymakers and emergency managers,whose goal is to reduce disaster costs and to improve economic resilience.展开更多
文摘This study employs the bibliometric method to analyse a sample of 936 core journal articles obtained from Chinese Social Sciences Citation Index(CSSCI)during the period 1998–2014,with a view to outlining the situation,characteristics and trends of Chinese research on disaster economics.Our analysis shows that Chinese research on disaster economics is characterised by marked shortterm fluctuations,non-mainstream tendency,localisation and noncollaboration.In terms of content,the major concerns of Chinese scholars are post-disaster construction,agricultural natural disasters,as well as disaster insurance and securitisation.In terms of methodology,these researches have entered into a quantitative phase of establishing the evaluation index system,and mathematical model analysis.With regard to the path,researches in the Chinese language have expanded from analyses of causes and natures of disasters to those of institutional response to disasters(e.g.disaster insurance and finance).
基金funded by the NASA Disasters Program grant#NH18ZDA001N001N.
文摘Earth observation(EO) technologies,such as very high-resolution optical satellite data available from Maxar,can enhance economic consequence modeling of disasters by capturing the fine-grained and real-time behavioral responses of businesses and the public.We investigated this unique approach to economic consequence modeling to determine whether crowd-sourced interpretations of EO data can be used to illuminate key economic behavioral responses that could be used for computable general equilibrium modeling of supply chain repercussions and resilience effects.We applied our methodology to the COVID-19 pandemic experience in Los Angeles County,California as a case study.We also proposed a dynamic adjustment approach to account for the changing character of EO through longer-term disasters in the economic modeling context.We found that despite limitations,EO data can increase sectoral and temporal resolution,which leads to significant differences from other data sources in terms of direct and total impact results.The findings from this analytical approach have important implications for economic consequence modeling of disasters,as well as providing useful information to policymakers and emergency managers,whose goal is to reduce disaster costs and to improve economic resilience.
