Academic Journal of Business & Management, 2024, 6(11); doi: 10.25236/AJBM.2024.061137.
Hao Yue1, Han Zhang2, Senping Gou3
1Department of Intelligent Networking and New Energy Vehicles, Geely University of China, Chengdu, 641423, China
2Business School, Geely University of China, Chengdu, 641423, China
3School of Intelligent Manufacturing, Geely University of China, Chengdu, 641423, China
With the frequent occurrence of extreme weather, it brings huge losses to the economy and increases the pressure on insurance companies to pay out. However, globally, there are still many shortcomings in natural disaster insurance that need to be addressed. Therefore, the problems related to insurance modelling and building protection modelling are explored. Firstly, a natural disaster risk assessment model based on AHP-entropy weighting method and TOPSISI was established, and natural disasters in the US and China were risk assessed into three risk levels. Secondly, an insurance breakeven model was established, breakeven validation was carried out, insurance schemes for two regions were designed, the relationship between the breakeven point and the four benchmark factors was clarified, and sensitivity analysis was carried out. Finally, an insurance decision model was developed to determine risk thresholds, and it was concluded that areas where extreme weather occurs should be included in insurance coverage.
Extreme weather, AHP-Entropy Weight-TOPSIS, Insurance
Hao Yue, Han Zhang, Senping Gou. Research on insurance decision problem based on break-even model. Academic Journal of Business & Management (2024) Vol. 6, Issue 11: 250-261. https://doi.org/10.25236/AJBM.2024.061137.
[1] Xu H,Ge Z,Ao W .Research on Climate Change Prediction based on ARIMA Model and its Impact on Insurance Industry Decision-Making[J].Frontiers in Computing and Intelligent Systems,2024,8(1):1-5.
[2] Huang Yujie. Moment and insurance pricing problem of natural disaster risk model [D]. Dalian University of Technology, 2010.
[3] Zhou J,Bu Y .Research on Natural Disaster Risk Assessment and Insurance Decision-Making Using EWM-TOPSIS and ARIMA Models[J].Frontiers in Computing and Intelligent Systems,2024,8(2):1-6.
[4] Deng Xue, Li Jiaming, Zeng Haojian, et al. Analysis and application of the weight calculation method of hierarchical analysis method [J]. The Practice and Understanding of Mathematics, 2012, 42 (07): 93-100.
[5] Cheng Qiyue. Evaluation the structure entropy weight method determined by index weight [J]. System Engineering Theory and Practice, 2010,30 (07): 1225-1228.
[6] Huo Guozhi, Li Shikui, Wang Suyan, et al. Research on the risk assessment techniques of major agrometeorological disasters and their application [J]. Journal of Natural Resources, 2003 (06): 692-703.
[7] C.J. N,N.P. D,N.P. R, et al. Risk evaluation and remedial measures for heavy metal contamination in lagoonal sediments of the Negombo Lagoon, Sri Lanka after the X-Press Pearl maritime disaster[J]. Regional Studies in Marine Science, 2023,67.
[8] Vilcu A, Verzea I,Chaib R . Dependability breakeven point mathematical model for production - quality strategy support[J]. IOP Conference Series: Materials Science and Engineering, 2016, 145(2).
[9] Apeagyei E A, Sahu M . Claims data from health insurance programmes in sub-Saharan Africa: an untapped resource to promote Universal Health Coverage.[J]. BMJ global health, 2024, 9(7).
[10] Samuel R, J PR,WJ WB. Insights into the complementarity of natural disaster insurance purchases and risk reduction behavior. [J].Risk analysis : an official publication of the Society for Risk Analysis, 2023, 44(1):141-154.