A New Approach to Investigate the Performance of Insurance Branches in Iran Using Best-Worst Method and Fuzzy Inference System

Ali Reza Torbati, Mohammad Kazem Sayadi

Abstract


The purpose of this study is to present a fuzzy expert model to examine the performance of insurance branches in Iran. The aim is to weight the criteria for measuring the performance of insurance branches and according to the experts’ perspectives. Our method is developed by the use of Best-Worst Method (BWM) and Fuzzy Inference System (FIS). BWM is used to    determine the importance of each criteria and FIS to evaluate and rank the insurance branches. The data for this study was collected from the managers of 52 Dana insurance companies in Iran. By analyzing the data obtained by the questionnaire, it was determined that the criteria such as insurance costs, administrative, general and personnel costs, premium income, deferred claims, marketing and advertising costs, market share of number in issued insurance policies, degree of customer satisfaction, level of employee education, amount of investment, facility to employees, cost of education, research and development costs and manpower skills are the most important criteria for senior executives in measuring the performance of Dana insurance company. In addition, the results of BWM showed that the insurance costs criteria is the most important criteria among others. The results concluded that the proposed model is superior to other methods in the literature in terms of convenience and accuracy.


Keywords


Fuzzy Inference System, Best-Worst method, Performance, Insurance branches

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References


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