The figure shows the analytical model of business output change ratio (BOCR) of an individual business, including the production capacity and final demand as determinants of BOCR and the impact factors on them.
The figure shows the relationship between BCL of sample manufacturing businesses and downtimes of various operation factors in a case of Mianzhu County suffered from 2008 Wenchuan Earthquake, indicates manufacturing production relies on all these operation factors, and validates the BCL model.
The figure shows the analytical model of business closure length (BCL) of an individual business, including the downtimes of various operation factors as determinants of BCL and the impact factors of these downtimes.
Predicting business interruption losses (BIL) could support the development of informed post-disaster recovery strategies and the decision-making of pre-disaster prevention and insurance. However, the current knowledge lacks of sufficient understanding in the cause and mechanism of BIL, and meanwhile the relevant prediction methods are not comprehensive. Based on the production theory and demand theory, this research aims to identify the impact factors and paths of BIL, then establish the models of business closure length (BCL), business output change ratio (BOCR) and business output recovery, and finally propose the method of predicting BIL. The method could be used to enhance the capacity of disaster response and recovery of economic systems, and further improve the regional economic resilience.
Quan Mao
National Key R&D Program of China: 2017YFC0803300, 2017.07-2020.06
National Natural Science Foundation of China (NSFC): U1709212, 2018.01-2021.12
Beijing Natural Science Foundation (BJNSF): 8202027, 2020.01-2022.12
