scholarly journals Relative Technical Efficiency of Life Insurance Companies DEA and Interval DEA Methods

2020 ◽  
Vol 8 (4S5) ◽  
pp. 101-105
Keyword(s):  
Decision Making ◽  
Life Insurance ◽  
Relative Efficiency ◽  
Interval Data ◽  
Vital Role ◽  
Insurance Companies ◽  
Data Envelopment ◽  
Parametric Linear Programming ◽  
Decision Making Unit ◽  
Dea Models

Insurance industries in India have taken a huge shape especially after privatization and introduction of Insurance Regulatory & Development Authority (IRDA). It plays an vital role in the growth of financial sector in all developed and developing countries. Insurance may be a sort of risk management and primarily used hedge against the danger of a contingent or uncertain loss. In this paper the author analyses the relative efficiency of life insurance companies in India using DEA and Interval Data Envelopment Approach (Interval DEA). DEA is a non parametric linear programming problem used for measuring the relative efficiency of decision making units (DMU) which utilize several identical inputs to produce a set of identical outputs. Interval DEA model is used in efficiency measurement of the life insurance companies under imprecise inputs and outputs. The empirical results of the conventional DEA models and Interval DEA models are computed to trace the performance of decision making unit at a possibility level.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

scholarly journals Efficiency Bounds for Two-Stage Production Systems

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Xiao Shi
Keyword(s):  
Production Systems ◽  
Efficiency Score ◽  
Insurance Companies ◽  
Practical Case ◽  
Data Envelopment ◽  
Production Structure ◽  
Two Stage ◽  
Decision Making Unit ◽  
Real World Applications ◽  
Dea Models

Traditional data envelopment analysis (DEA) models find the most desirable weights for each decision-making unit (DMU) in order to estimate the highest efficiency score as possible. These efficiency scores are then used for ranking the DMUs. The main drawback is that the efficiency scores based on weights obtained from the standard DEA models ignore other feasible weights; this is due to the fact that DEA may have multiple solutions for each DMU. To overcome this problem, Salo and Punkka (2011) deemed each DMU as a “Black Box” and developed models to obtain the efficiency bounds for each DMU over sets of all its feasible weights. In many real world applications, there are DMUs that have a two-stage production system. In this paper, we extend the Salo and Punkka’s (2011) model to a more common and practical case considering the two-stage production structure. The proposed approach calculates each DMU’s efficiency bounds for the overall system as well as efficiency bounds for each subsystem/substage. An application for nonlife insurance companies has been discussed to illustrate the applicability of the proposed approach and show the usefulness of this method.

Evaluation of Supplier Performance and Efficiency

2017 ◽  
pp. 184-216
Author(s):  
Chandra Sekhar Patro
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Efficient Frontier ◽  
Business Environment ◽  
Vital Role ◽  
Data Envelopment ◽  
Supplier Performance ◽  
Decision Making Units

In the present competitive business environment, it is essential for the management of any organisation to take wise decisions regarding supplier evaluation. It plays a vital role in establishing an effective supply chain for any organisation. Most of the experts agreed that there is no one best way to evaluate the suppliers and different organizations use different approaches for evaluating supplier efficiency. The overall objective of any approach is to reduce purchase risk and maximize overall value to the purchaser. In this paper Data Envelopment Analysis (DEA) technique is developed to evaluate the supplier efficiency for an organisation. DEA is a multifactor productivity technique to measure the relative efficiency of the decision making units. The super efficiency method of DEA provides a way, which indicates the extent to which the efficient suppliers exceed the efficient frontier formed by other efficient suppliers. A case study is undertaken to evaluate the supplier performance and efficiency using DEA approach.

Evaluation of Heuristics Using Data Envelopment Analysis

2014 ◽  
Vol 13 (04) ◽  
pp. 795-810 ◽  
Author(s):  
Chung-Cheng Jason Lu ◽  
Yen-Chun Jim Wu
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Data Envelopment Analysis ◽  
Statistical Tests ◽  
Data Envelopment ◽  
Decision Making Unit ◽  
Dea Models ◽  
Using Data ◽  
Inputs And Outputs

This paper focuses on identifying relatively efficient configurations of algorithmic operators among a set of configurations in the development of heuristics or meta-heuristics. Each configuration is considered as a decision-making unit with multiple inputs and outputs. Then, data envelopment analysis (DEA) is adopted to evaluate relative and cross-efficiencies of a set of algorithmic configurations. The proposed approach differs from existing methods based on statistical tests in that multiple inputs and outputs are simultaneously considered in an integrated framework for the evaluation of algorithmic efficiency. A case study is presented to demonstrate the application of DEA for determining the efficient configurations of genetic algorithm operators. The evaluation results of two DEA models are also compared. The DEA evaluation results are consistent with those obtained by a commonly used statistical method.

scholarly journals Data Envelopment Analysis - Basic Models and their Utilization

Organizacija ◽  
2009 ◽  
Vol 42 (2) ◽  
pp. 37-43 ◽  
Author(s):  
Milan Martić ◽  
Marina Novaković ◽  
Alenka Baggia
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Efficiency Frontier ◽  
Dea Models ◽  
Decision Making Tool ◽  
Inputs And Outputs

Data Envelopment Analysis - Basic Models and their UtilizationData Envelopment Analysis (DEA) is a decision making tool based on linear programming for measuring the relative efficiency of a set of comparable units. Besides the identification of relatively efficient and inefficient units, DEA identifies the sources and level of inefficiency for each of the inputs and outputs. This paper is a survey of the basic DEA models. A comparison of DEA models is given. The effect of model orientation (input or output) on the efficiency frontier and the effect of the convexity requirements on returns to scale are examined. The paper also explains how DEA models can be used to assess efficiency.

scholarly journals Dealing with Interval DEA Based on Error Propagation and Entropy: A Case Study of Energy Efficiency of Regions in China Considering Environmental Factors

2015 ◽  
Vol 3 (6) ◽  
pp. 538-548 ◽  
Author(s):  
Jianping Fan ◽  
Weizhen Yue ◽  
Meiqin Wu
Keyword(s):  
Energy Efficiency ◽  
Environmental Factors ◽  
Error Propagation ◽  
Interval Data ◽  
Data Envelopment ◽  
Exact Data ◽  
Dea Models ◽  
Traditional Approaches ◽  
Decision Making Units

AbstractThe conventional data envelopment analysis (DEA) measures the relative efficiency of decision making units (DMUs) consuming multiple inputs to produce multiple outputs under the assumption that all the data are exact. In the real world, however, it is possible to obtain interval data rather than exact data because of various limitations, such as statistical errors and incomplete information, et al. To overcome those limitations, researchers have proposed kinds of approaches dealing with interval DEA, which either use traditional DEA models by transforming interval data into exact data or get an efficiency interval by using the bound of interval data. In contrast to the traditional approaches above, the paper deals with interval DEA by combining traditional DEA models with error propagation and entropy, uses idea of the modified cross efficiency to get the ultimate cross efficiency of DMUs in the form of error distribution and ranks DMUs using the calculated ultimate cross efficiency by directional distance index. At last we illustrate the feasibility and effectiveness of the proposed method by applying it to measure energy efficiency of regions in China considering environmental factors.

scholarly journals Analisis Efisiensi Relatif di Unit Pelaksana Teknis Badan Pengawas Obat dan Makanan Tahun 2019

2022 ◽  
Vol 6 (2) ◽  
Author(s):  
Pantri Widyastuti ◽  
Atik Nurwahyuni
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Mixed Method ◽  
Data Envelopment ◽  
Cross Sectional ◽  
Decision Making Unit

Tantangan pengawasan obat dan makanan mengharuskan Unit Pelaksana Teknis (UPT) BPOM bekerja optimal di tengah keterbatasan sumber daya. Analisis efisiensi relatif pada Unit Pelaksana Teknis BPOM tahun 2019 dilakukan bertujuan untuk perbaikan dalam perencanaan, penganggaran, dan kebijakan strategis BPOM dalam upaya peningkatan capaian kinerja pada masing-masing UPT. Perhitungan efisiensi relatif menggunakan metode DEA (Data envelopment Analysis). Penelitian ini menggunakan mixed method dengan desain penelitian cross sectional. Sampel penelitian adalah 31 UPT BPOM yang memenuhi syarat sebagai DMU (Decision Making Unit) dan menggunakan 3 input dan 4 output yang diuji dengan metode DEA. Terdapat 10 informan dalam analisis kualitatif untuk mengetahui strategi dalam pencapaian efisiensi UPT. Hasil dari analisis terdapat 15 UPT yang efisien dan 16 UPT yang tidak efisien. Hasil wawancara diketahui bahwa UPT yang efisien dan yang tidak efisien telah melaksanakan strategi efisiensi internal dengan baik. DEA merupakan analisis efisiensi relatif dengan konsep memaksimalkan rasio output dan input. Penggunaan model VRS (Variabel return to Scale) yang mempertimbangkan proses, diharapkan mengeliminasi kekurangan yang terdapat dalam perhitungan dengan DEA. Perhitungan DEA dilakukan secara mekanik, maka diperlukan pendalaman proses untuk menggali faktor efisiensi yang tidak didapatkan dari perhitungan DEA, terlebih untuk organisasi yang dalam prosesnya melibatkan faktor eksternal yang cukup besar.

scholarly journals A COMPARATIVE STUDY OF CONVENTIONAL AND SHARIAH LIFE INSURANCE EFFICIENCY USING DATA ENVELOPMENT ANALYSIS

2020 ◽  
Vol 9 ◽  
Author(s):  
Mulia Saputra ◽  
Muhammad Arfan ◽  
Neni Zahara
Keyword(s):  
Data Envelopment Analysis ◽  
Life Insurance ◽  
Value Added ◽  
Sampling Technique ◽  
Insurance Companies ◽  
Data Envelopment ◽  
Insurance Company ◽  
Life Insurance Company ◽  
Purposive Sampling ◽  
Test Input

This study aims to analyze and compare the efficiency between conventional life insurance companies and Islamic life insurance companies in Indonesia over the period of 2014-2018. The sample of this study was taken from 10 conventional life insurance companies and 10 shariah life insurance companies that were selected based on the purposive sampling technique. Measurement of efficiency in this study was conducted using the method of data envelopment analysis (DEA) based on Bankers-Charnes-Cooper (BCC) and Charnes-Cooper-Rhodes (CCR) models of the value-added approach. This was followed by testing the hypothesis using a different Mann-Whitney U-test. Input variables used are assets, capital, general and administrative costs, and commission expenses. Meanwhile, the output variables are premiums and investment income. The results showed that conventional life insurance companies are more efficient than Islamic life insurance companies based on the BCC and CCR models. Furthermore, the results of different tests using the Mann-Whitney U-test showed an insignificant difference in efficiency between conventional life insurance companies and Islamic life insurance companies during the study period. The results of the comparison of the average efficiency value with the DEA method indicated that the efficiency level of a conventional life insurance company was better than a shariah life insurance company.========================================================================================================Studi Perbandingan Efisiensi antara Asuransi Jiwa Konvensional dengan Syariah Menggunakan Data Envelopment Analysis. Penelitian ini bertujuan untuk menganalisis perbandingan efisiensi perusahaan asuransi jiwa konvensional dengan perusahaan asuransi jiwa syariah di indonesia pada periode 2014-2018. Sampel penelitian ini adalah 10 perusahaan asuransi jiwa konvensional dan 10 perusahaan asuransi jiwa syariah yang dipilih berdasarkan teknik purposive sampling. Pengukuran efisiensi dalam penelitian ini menggunakan metode data envelopment analysis (DEA) dengan model BCC dan CCR berdasarkan pendekatan nilai tambah. dilanjutkan dengan melakukan uji hipotesis menggunakan uji beda mann-whitney u-test. Variabel input yang digunakan adalah aset. modal. biaya administrasi dan umum. dan beban komisi. Sedangkan variabel outputnya adalah premi dan pendapatan investasi. Hasil penelitian menunjukkan bahwa perusahaan asuransi jiwa konvensional lebih efisien dibandingkan perusahaan asuransi jiwa syariah berdasarkan pengukuran dengan model BCC maupun model CCR. Selanjutnya hasil uji beda menggunakan uji mann-whitney u- test menunjukkan bahwa tidak terdapat perbedaan efisiensi yang signifikan antara perusahaan asuransi jiwa konvensional dan perusahaan asuransi jiwa syariah selama periode penelitian ini. Hasil perbandingan nilai efisiensi rata-rata dengan metode DEA menunjukkan bahwa tingkat efisiensi perusahaan asuransi jiwa konvensional lebih baik daripada perusahaan asuransi jiwa syariah.

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