Natural disaster management mechanisms for probabilistic earthquake loss

High rates of urbanization, environmental degradation, and industrial development have affected all nations worldwide, but in disaster-prone areas, the impact is even greater serving to increase the extent of damage from natural catastrophes. As a result of the global nature of environmental change, modern economies have had to adapt, and sustainability is an extremely important issue. Clearly, natural disasters will affect the competitiveness of an enterprise. This study focuses on natural disaster management in an area in which the direct risks are posed by the physical effects of natural disasters such as floods, droughts, tsunamis, and rising sea levels. On a local level, the potential impact of a disaster on a company and how much damage (loss) it causes to facilities and future business are of concern. Each company must make plans to mitigate predictable risk. Risk assessments must be completed in a timely manner. Disaster management is also very important to national policy. Natural disaster management mechanisms can include strategies for disaster prevention, early warning (prediction) systems, disaster mitigation, preparedness and response, and human resource development. Both governmental administration (public) and private organizations should participate in these programs. Participation of the local community is especially important for successful disaster mitigation, preparation for, and the implementations of such measures. Our focus in this study is a preliminary proposal for developing an efficient probabilistic approach to facilitate design optimization that involves probabilistic constraints.

[1]  John N. Warfield,et al.  Developing Interconnection Matrices in Structural Modeling , 1974, IEEE Trans. Syst. Man Cybern..

[2]  R. Shankar,et al.  An interpretive structural modeling of knowledge management in engineering industries , 2003 .

[3]  W. Chiang,et al.  An integrated flood risk assessment model for property insurance industry in Taiwan , 2011 .

[4]  Chung-Hung Tsai,et al.  The establishment of a rapid natural disaster risk assessment model for the tourism industry , 2011 .

[5]  A. Sohal,et al.  RESISTANCE: A CONSTRUCTIVE TOOL FOR CHANGE , 1998 .

[6]  David Etkin,et al.  People and community as constituent parts of hazards: the significance of societal dimensions in hazards analysis , 2007 .

[7]  Chun-Pin Tseng,et al.  A new viewpoint on risk control decision models for natural disasters , 2011 .

[8]  Anne van der Veen,et al.  Flood risk perceptions and spatial multi-criteria analysis: an exploratory research for hazard mitigation , 2008 .

[9]  Chung-Hung Tsai,et al.  An earthquake disaster management mechanism based on risk assessment information for the tourism industry-a case study from the island of Taiwan , 2010 .

[10]  Huicong Jia,et al.  Resilience to natural hazards: a geographic perspective , 2010 .

[11]  A. Sohal,et al.  Critical success factors in agile supply chain management ‐ An empirical study , 2001 .

[12]  Hiroshi Katayama Agility, Adaptability and Leanness: A Comparison of Concepts and a Study of Practice , 2001 .

[13]  M. Bar-Hillel The base-rate fallacy in probability judgments. , 1980 .

[14]  Cheng-Wu Chen,et al.  RETRACTED: Risk control allocation model for pressure vessels and piping project , 2012 .

[15]  C. Yi,et al.  GIS-based distributed technique for assessing economic loss from flood damage: pre-feasibility study for the Anyang Stream Basin in Korea , 2010 .

[16]  Markus Biehl,et al.  International supply chain agility ‐ Tradeoffs between flexibility and uncertainty , 2001 .

[17]  Angappa Gunasekaran,et al.  Agile supply chain capabilities: Determinants of competitive objectives , 2004, Eur. J. Oper. Res..

[18]  Prem Vrat,et al.  Impact of indirect relationships in classification of variables—a micmac analysis for energy conservation , 1990 .