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The Study On Forest Insurance Participants’ Behavior Based On Complex Adaptive System Theory

Posted on:2016-09-23Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZuoFull Text:PDF
GTID:2309330461959658Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
The government, insurance companies, and forest farmers are the most important participants in the market of forest insurance in China. Their activities can bring mutual promotion and restrained to each other. Currently, how to coordinate agents’ activities, mobilize the enthusiasm in participation and then to maximize social welfare is one of the important topics in the research field of forest insurance.This paper firstly analyzes the behavior characteristics and interactive relationships of participants, and verifies the complex adaptability of forest insurance based on the seven basic concepts of complex adaptive system theory. Secondly, this study analyzes the game relationship between the government, insurance companies and forest farmers by establishing the static game model and dynamic game model thus, proves the necessity of government’s participation and obtains the equilibrium probability under the condition of participants’ benefit maximization. Then, this study focuses on the research of forest farmers’ insurance purchasing behavior by multi-agent simulation modeling method to construct the forest insurance simulation system. The run results of simulation system show that the premium, insurance amount, subsidy rate, disaster probability, forest land area, forestry income and other factors all have effects on the purchasing behavior of forest farmers, and find that the sensitivity of forest farmers to premium subsidies will reduce when the forest land area and forestry income increase,. Finally, this paper puts forward relevant policy suggestions from aspect of government and insurance companies, combining with the implementation status and research results of forest insurance in our country.
Keywords/Search Tags:forest insurance, complex adaptive system, multi-agent simulation, game theory
PDF Full Text Request
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