Supply and demand analysis for flood insurance by using logistic regression model: case study at Citarum watershed in South Bandung, West Java, Indonesia

The Indonesian Operations Research Association (IORA) - International Conference on Operations Research 2016

Sidi, P.^1 ; Mamat, M.^2 ; Sukono^3 ; Supian, S.^2

Department of Mathematics, Universitas Terbuka, Indonesia^1

Graduate School, Universiti Sultan Zainal Abidin, Malaysia^2

Department of Mathematics, Universitas Padjadjaran, Indonesia^3

关键词: Cost of repairs;    Economic circumstances;    Logistic Regression modeling;    Ordinal logistic regression;    Property damage;    Residential building;    Social organizations;    Supply and demand;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/166/1/012002/pdf
DOI  :  10.1088/1757-899X/166/1/012002

来源: IOP

【 摘 要 】

Floods have always occurred in the Citarum river basin. The adverse effects caused by floods can cover all their property, including the destruction of houses. The impact due to damage to residential buildings is usually not small. Indeed, each of flooding, the government and several social organizations providing funds to repair the building. But the donations are given very limited, so it cannot cover the entire cost of repair was necessary. The presence of insurance products for property damage caused by the floods is considered very important. However, if its presence is also considered necessary by the public or not? In this paper, the factors that affect the supply and demand of insurance product for damaged building due to floods are analyzed. The method used in this analysis is the ordinal logistic regression. Based on the analysis that the factors that affect the supply and demand of insurance product for damaged building due to floods, it is included: age, economic circumstances, family situations, insurance motivations, and lifestyle. Simultaneously that the factors affecting supply and demand of insurance product for damaged building due to floods mounted to 65.7%.