普惠保购买意愿研究——基于集成DEMATEL-ISM分析

A Study on the Willingness to Purchase Universal Insurance--Based on Integrated DEMATEL-ISM Analysis

2015年推出惠民保至今年各省市反响不尽相同,本文基于从购保者、政府、保险公司和第三部门四个维度构建惠民保购买意愿的影响因素指标体系,利用决策试验和评价实验室法(DEMATEL)计算22个影响因素的影响度、被影响度、中心度和原因度,结合解释结构模型法(ISM),建构惠民保购买影响因素的多层递阶结构模型,从而实现对系统中各因素重要性、因果属性以及因素间逻辑和层次结构的全面把握。研究表明:18个影响因素中包含7个原因指标和11个结果指标,其中赔付率、精算能力等7个指标是影响惠民保的关键因素,在多层递阶结构模型中,收入是表面因素层最为关键的指标,医保个人账户使用是中间因素层最为关键的指标,精算能力是次深因素层最为关键的指标,政策支持是本质因素层最为关键的指标。

Since the introduction of beneficiary insurance in 2015,the response of each province and city this year has been different,this paper is based on the construction of the indicator system of the influencing factors of the willingness to purchase beneficiary insurance from the policy buyers,the government,the insurance company,the third party sector,four dimensions,the use of decision-making experiments and the evaluation of the laboratory method(DEMATEL)to calculate the degree of influence,influenced,centered and the degree of cause of 22 influencing factors,combined with the method of explanatory structural modeling(ISM),the multilayer recursive structural model of the influencing factors of beneficiary insurance purchase is constructed,so as to realize a comprehensive grasp of the importance of the factors in the system,the causal attributes as well as the logical and hierarchical structure among the factors.The study shows that the 18 influencing factors include 7 cause indicators and 11 effect indicators,among which 7 indicators,such as payout rate and actuarial ability,are the key factors affecting beneficiary insurance.In the multilayered hierarchical structural model,income is the most critical indicator at the surface factor layer,the use of individual account of medical insurance is the most critical indicator at the intermediate factor layer,the actuarial ability is the most critical indicator at the second deepest factor layer,and the policy support is the most critical indicator at the essential factor layer.support is the most critical indicator in the essential factor layer.