Assessing the competitiveness of insurance corporations using fuzzy correlation analysis and improved fuzzy modified TOPSIS

Abstract

To obtain greater profit, insurance firms not only need to provide attractive insurance products but also effectively promote their products. A growing number of insurance companies have thus heavily invested in marketing. Therefore, the proposed assessment framework integrates the fuzzy analytical hierarchy process and the improved fuzzy modified technique for order preference by similarity to the ideal solution (improved fuzzy modified TOPSIS) to acquire the efficiency scores of the alternatives (i.e. insurance companies) being evaluated. The improved fuzzy modified TOPSIS computes efficiency scores of insurance companies based on the Mahalanobis distances, taking into account the fuzzy correlations between the indicators and the weighted distance of fuzzy modified TOPSIS. The advantage of calculating the Mahalanobis distances over the Euclidean distances, which are typically used in the literature, is that the undulation of efficiency scores can be decreased. The assessment criteria have high correlations with each other. This assessment framework is applied to appraise the marketing performance of four major insurance companies in Taiwan. The assessment and comparison results are proved to be consistent with those published by an independent business survey institute.

DOI: 10.1111/exsy.12099

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Cite this paper

@article{Chen2015AssessingTC, title={Assessing the competitiveness of insurance corporations using fuzzy correlation analysis and improved fuzzy modified TOPSIS}, author={Shang-Yu Chen and Chung-Cheng Lu}, journal={Expert Systems}, year={2015}, volume={32}, pages={392-404} }