Evaluation the Branches of Iran Insurance Corporation based on Data Envelopment Analysis-Free Disposal Hull in the Presence of Weight Restrictions

2019 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Mohammad Reza Fathi ◽  
Hossein Safari ◽  
Abdol Hossein Jafarzadeh
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Weight Restrictions ◽  
Free Disposal Hull ◽  
Free Disposal

scholarly journals A Novel Improved Data Envelopment Analysis Model Based on SBM and FDH Models

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Mirpouya Mirmozaffari ◽  
Gohar Azeem ◽  
Azam Boskabadi ◽  
Ali Aranizadeh ◽  
Aditya Vaishnav ◽  
...  
Keyword(s):  
Data Envelopment Analysis ◽  
High Performance ◽  
Malmquist Productivity Index ◽  
Productivity Index ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Free Disposal Hull ◽  
Free Disposal ◽  
Proposed Model

During the past decade, applying nonparametric operation research problems such as Data Envelopment Analysis(DEA) has received significant consideration among researchers. In this paper, a new DEA-based SBM-FDH model is introduced. Finally, productivity evaluation for banking systems in Malmquist Productivity Index (MPI) based on the proposed model has been compared with Slack Based Measurement (SBM) and Free Disposal Hull (FDH). The obtained results confirm the high performance of the proposed model in comparison to the other models used in this paper.                                                                                                                                                                                                                                                                                                                           

scholarly journals EFFICIENCY PERFORMANCE ANALYSIS OF PANIN DUBAI SYARIAH BANK IN COLLECTING AND DISTRIBUTING THIRD PARTY FUNDS BEFORE AND AFTER MERGER

2019 ◽  
Vol 5 (1) ◽  
pp. 46-56
Author(s):  
Supriyono Supriyono ◽  
Ahmad Rodoni ◽  
Yacop Suparno ◽  
Hermadi Hermadi ◽  
Hilyatun Nafisah
Keyword(s):  
Data Envelopment Analysis ◽  
Parametric Method ◽  
Third Party ◽  
Programming Approach ◽  
Data Envelopment ◽  
Linear Programs ◽  
Parametric Approach ◽  
Free Disposal Hull ◽  
Free Disposal ◽  
Non Parametric

In this study, the researcher would make Panin Dubai Syariah Bank was the object of research on Islamic banks that carry out mergers and acquisitions. This research by using quarterly financial reports to determine the level of efficiency of the Panin Dubai Syariah Bank to be analyzed using the Data Envelopment Analysis (DEA) method. The researcher was used the annual report to find out the extent the Panin Dubai Syariah Bank carries out its Shariah values and objectives to be analyzed based on the Maqashid Index Sharia. The frontier approach can be divided into parametric approaches and non-parametric approaches. The parametric  approach  takes  measurements  using  stochastic  econometrics  and  seeks  to  eliminate interference from the effects of inefficiency. While the non-parametric approach with linear programs ( non-parametric linear programming approach ) performs non-parametric measurements using an approach is not stochastic and tends to combine the interference into inefficiency. This is based on the discovery and observation of the population and evaluates efficiency relative to the units observed. In the non- parametric method, the approaches that can be used are Data Envelopment Analysis (DEA) and Free Disposal Hull (FDH). The results of the measurement of Bank Panin Dubai Syariah using DEA indicate that the decision to merge carried out by Panin Syariah Bank with Dubai Islamic Bank was the right decision because, with the merger, Panin Dubai Syariah Bank could produce almost perfect efficiency value of 99% in the year 2015. With doing the merger, Bank Panin Dubai Syariah can minimize the inefficiencies that occur in the input variable so that it can maximize the efficiency that occurs in the output variable

scholarly journals Estimation of Congestion in Free Disposal Hull Models Using Data Envelopment Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
M. Abbasi ◽  
G. R. Jahanshahloo ◽  
M. Rostamy-Malkhlifeh ◽  
F. Hosseinzadeh Lotfi
Keyword(s):  
Data Envelopment Analysis ◽  
Pairwise Comparisons ◽  
Data Envelopment ◽  
Free Disposal Hull ◽  
Free Disposal ◽  
Proposed Model ◽  
Using Data ◽  
Almost All ◽  
Do So

This paper deals with evaluating congestion in free disposal hull (FDH) models. There are several approaches in data envelopment analysis (DEA) literatures which discuss the theory and application of congestion. However, almost all of these approaches considered convex DEA technologies. So, in the case of nonconvex technologies, including FDH technology, this field is almost nil. This paper makes an attempt to fill in this void. To do so, this study provides a pairwise comparisons-based algorithm to evaluate congestion in FDH model. This algorithm identifies the sources of congestion and estimates its amounts. It is also capable of detecting the losses amounts of output due to congestion. The validity of the proposed model is demonstrated using some numerical and empirical examples.

Weight Restrictions and Free Production in Data Envelopment Analysis

2013 ◽  
Vol 61 (2) ◽  
pp. 426-437 ◽  
Author(s):  
Victor V. Podinovski ◽  
Tatiana Bouzdine-Chameeva
Keyword(s):  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Weight Restrictions

scholarly journals WHEN BIAS KILLS THE VARIANCE: CENTRAL LIMIT THEOREMS FOR DEA AND FDH EFFICIENCY SCORES

2014 ◽  
Vol 31 (2) ◽  
pp. 394-422 ◽  
Author(s):  
Alois Kneip ◽  
Léopold Simar ◽  
Paul W. Wilson
Keyword(s):  
Central Limit ◽  
Limit Theorems ◽  
Central Limit Theorems ◽  
Data Envelopment ◽  
Free Disposal Hull ◽  
Average Efficiency ◽  
Free Disposal ◽  
Monte Carlo Experiments ◽  
The Individual ◽  
Individual Scores

Data envelopment analysis (DEA) and free disposal hull (FDH) estimators are widely used to estimate efficiencies of production units. In applications, both efficiency scores for individual units as well as average efficiency scores are typically reported. While several bootstrap methods have been developed for making inference about the efficiencies of individual units, until now no methods have existed for making inference about mean efficiency levels. This paper shows that standard central limit theorems do not apply in the case of means of DEA or FDH efficiency scores due to the bias of the individual scores, which is of larger order than either the variance or covariances among individual scores. The main difficulty comes from the fact that such statistics depend on efficiency estimators evaluated at random points. Here, new central limit theorems are developed for means of DEA and FDH scores, and their efficacy for inference about mean efficiency levels is examined via Monte Carlo experiments.

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