A Study On Insured Farmer Satisfaction Measurement For New Rural Pension Insurance Based On Rough Set Theory

Rural residents is an important part of our society, is the backbone of socialistmodernization with Chinese characteristics. Establish a blameless rural old-agesecurity system, improve rural production and living initiative is a key to improvepeople’s livelihood, keep social stability, and promote social harmony. In recent years,with the population aging trend, our government have paid more and more attentionsto build a perfect old-age security system and regard it as the important beginning toimprove people’s livelihood, provide our elderly with a sense of security. This articlefrom the insured farmer rural resident point of view, established the insured farmersatisfaction measurement model for new rural pension insurance based on rough settheory. Based on our new pilot agricultural insurance policy, analyzes the currentsituation and the pilot facing major problems.The main contents of the paper are as follows:First, the article start with the research background, indicate the research purposeof the article and combine the theory and practice of the analysis of the studysignificance on insured farmer satisfaction measurement for new rural pensioninsurance based on rough set theory.Explaining the related concepts about the mainidea of the article and analysing the connotation of the new rural pension insuredfarmer satisfaction,then introducing basis of the rough set theory and the introductionof new rural pension insured farmers satisfaction measurementSecondly, building the insured farmer satisfaction measurement model for newrural pension insurance based on rough set theory, through combining with its owncharacteristics of new rural pension insured farmer satisfaction measurement with theclassic Customer Satisfaction Index Model, Choosing the relevant variables andpointing out that the structure of related variables.Finally, the article choose the research object of ten villages from Yuan JiangCity of Hunan province and make a questionnaire according to the model, collectingdata by field sampling, And using rough set information entropy method to determinethe weight of the data analysis and processing, eliminate redundant indicators, putforward the corresponding countermeasures and suggestions from the empiricalresults.