Characterization of consumers’ behavior in medical insurance market with agent parameters’ Estimation process using Bayesian network

In medical insurance market as well as other markets, it is not straightforward for an institution to develop effective marketing strategies because consumers’ preferences and the environment surrounding consumers are constantly changing. This paper develops an agent-based model (ABM) of consumer’s behavior in purchasing medical insurance products and analyzes the characterization of consumers’ behavior to establish effective marketing strategies for the products. In general, the information propagation model of purchasing behavior has difficulty estimating the values of parameters only from ordinary marketing surveys, especially in the case of products that require a person to conduct advanced information processing, such as an insurance policy. To tackle this problem, this paper developed a method of estimating the probability parameters of agent’s behavior using Bayesian network based on questionnaire survey data, and then evaluated the effectiveness of the method by applying it to the actual insurance market. In the analysis using ABM constructed, we mainly focus on the power of influence of the sales activity using word-of-mouth communication between consumers. As the result we obtained several key findings regarding marketing strategies that can be utilized in the real marketing of insurance products.