Analyzing Efficiency of Indian Life Insurance Companies using DEA and SEM

Insurance companies play a significant role in the economic growth of an economy. This paper explores the performance of the life insurance companies working in India during the period 2010 to 2017. Each of the selected insurance companies has been recognized as a separate Decision Making Unit (DMU)...

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Published inTurkish journal of computer and mathematics education Vol. 12; no. 12; pp. 3897 - 3919
Main Authors Ghosh, Arijit, Sarkar, Anirban, Dey, Munmun, Guha, Banhi, Jana, Subrata, Ghorui, Neha
Format Journal Article
LanguageEnglish
Published Gurgaon Ninety Nine Publication 01.01.2021
Subjects
Comparative Analysis
Data envelopment analysis
Decision analysis
Decision making
Economic development
Economics
Efficiency
Insurance
Life insurance companies
Mathematical models
Multivariate statistical analysis
Performance measurement
Structural Equation Models
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Summary:Insurance companies play a significant role in the economic growth of an economy. This paper explores the performance of the life insurance companies working in India during the period 2010 to 2017. Each of the selected insurance companies has been recognized as a separate Decision Making Unit (DMU) and their performance has been analyzed with respect to their peers in the industry. Data Envelopment Analysis (DEA) is carried out to estimate the efficiency of these insurance companies using a set of inputs and outputs. An input oriented model has been used to identify the DMU that is able to minimize input while maintaining the same or more output. The efficiency scores measure the efficiency of the DMUs in minimizing the costs. In input oriented DEA. it becomes important to differentiate between multiple efficient DMUs with an efficiency score of 1. Hence super efficiency score has been used to rank the DMUs. The model has been validated through Structural Equation Modeling (SEM) before performance measurement using DEA. In this paper. comparative analysis has been carried out with other Multi Criteria Decision Making techniques(MCDM) such as Simple Additive Weighting (SAW). Weighted Aggregated Sum Product Assessment (WASPAS).Weighted Sum Method (WSM). Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).Range of value method (ROVM). The Additive Ratio Assessment (ARAS). Measurement Alternatives and Ranking according to the COmpromise Solution (MARCOS) to show the correlation between different methods and to uphold the reliability of the proposed methodology._
ISSN:1309-4653