| Summary: | 碩士 === 國立東華大學 === 企業管理學系 === 100 === In accordance with the statistics of the Life Insurance Association, the total amount of the Republic of China 2011’s annual “premium income” includes 377,495 million dollars from self-marketing system performance of life insurance company (accounting for 41.14%), 508,147 one million dollars from bank channel performance (accounting for 55.38%), and 31,945 million dollars from traditional insurance broker and insurance agent performance (accounting for 3.48%). The above information shows that insurance competition is getting fierce and cross-industry marketing makes traditional life insurance marketing system performance drop to 41.14%. Traditional life insurance team is still very important. According to the statistics, the life insurance salespersons are still main forces of health insurance and injury insurance. Traditional life insurance team still has the important responsibility to strengthen the protection-type insurance markets. Therefore, this study mainly focuses on the critical success factors for the life insurance team educational trainings. It is hoped to provide professional advice to industry, government agencies and the academics.
In this study, the main method is to use of the Analytic Hierarchy Process (AHP) and KASH suggested by the United States Life Insurance Marketing Association. This paper also applies expert interviews to find the performance indicators for life insurance team educational trainings. Questionnaires for experts and scholars with Likert five-point scale are used to filter out the evaluation indicators which are used to establish the hierarchical structure measurement. Critical success factors affecting the educational training performance are identified via Analytical Hierarchy Process’ questionnaire collected information. Expertise, working attitude, marketing skills, and working habits are learned in the second layer of key factors. “Working habits” is accounted for 41% as the most important, followed by “working attitude" accounted for 31.8%, “marketing skills” accounted for 13.9%, and “Expertise" accounted for 13.3% as the least important. 29 research variables are listed and sorted according to their importance.
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