Measuring Efficiency in Korean Banking Industry by Window Data Envelopment Analysis

2012 ◽  
Vol 26 (3) ◽  
pp. 139-156
Author(s):  
현정원
Keyword(s):  
Data Envelopment Analysis ◽  
Banking Industry ◽  
Data Envelopment ◽  
Measuring Efficiency

scholarly journals Measuring Efficiency of Knowledge Production in Health Research Centers Using Data Envelopment Analysis (DEA): A Case Study in Iran

10.19082/3266 ◽  
2016 ◽  
Vol 8 (11) ◽  
pp. 3266-3271
Author(s):  
Mohammad Meskarpour Amiri ◽  
Taha Nasiri ◽  
Seyed Hassan Saadat ◽  
Hosein Amini Anabad ◽  
Payman Mahboobi Ardakan
Keyword(s):  
Data Envelopment Analysis ◽  
Knowledge Production ◽  
Health Research ◽  
Data Envelopment ◽  
Research Centers ◽  
Measuring Efficiency ◽  
Using Data

scholarly journals Cost efficiency of the Czech and Slovak banking sectors: an application of the data envelopment analysis

2016 ◽  
Author(s):  
Iveta Palecková
Keyword(s):  
Data Envelopment Analysis ◽  
Cost Efficiency ◽  
Commercial Banks ◽  
Banking Sector ◽  
Banking Industry ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Cost Efficient ◽  
The Cost ◽  
Variable Returns To Scale

The aim of the paper is to estimate the cost efficiency of the Czech and Slovak commercial banks within the period 2010-2014. For empirical analysis the Data Envelopment Analysis input-oriented model with variable returns to scale is applied on the data of the commercial banks. The intermediation approach is adopted to define the inputs and outputs. The Czech commercial banks are more cost efficient than Slovak commercial banks. The development of average cost efficiency is similar in the Czech and Slovak banking industry. The most efficient Czech banks are Ceská sporitelna and Sberbank in the Czech banking sector, the most efficient Slovak bank is Privatbanka with 100% efficiency.

Measuring and Evaluating Efficiency on IT Outsourcing operations through Data Envelopment Analysis

2016 ◽  
Vol 12 (1) ◽  
pp. 1-20 ◽  
Author(s):  
João Correia dos Santos ◽  
Miguel Mira da Silva
Keyword(s):  
Data Envelopment Analysis ◽  
Design Science ◽  
Science Research ◽  
Business Environment ◽  
It Outsourcing ◽  
Data Envelopment ◽  
It Services ◽  
Programming Technique ◽  
Efficient Operation ◽  
Measuring Efficiency

Information Technology (IT) outsourcing is a set of IT services that require providers to manage a long relationship with multiple services that have a high degree of variance between clients. IT outsourcing operational contexts display multi-input and multi-output variables, so managers need guidance on developing suitable approaches in order to identify the set of variables to analyse. This work proposes a model based on Data Envelopment Analysis (DEA), which is a linear programming technique able to manipulate multiple inputs and outputs. DEA allows the identification of the most efficient operation, which in turn enables providers to set the best operational strategy to follow. The results demonstrate the importance of quantitative measures in a dynamic business environment like IT outsourcing. To develop the authors' research, design science research was applied, and eighteen IT outsourcing contracts were used to demonstrate their model's utility. This work is a major contribution for measuring efficiency in IT outsourcing operations.

A common-weights approach for efficiency evaluation in fuzzy data envelopment analysis with undesirable outputs: Application in banking industry

2020 ◽  
Vol 39 (5) ◽  
pp. 7705-7722
Author(s):  
Mohammad Kachouei ◽  
Ali Ebrahimnejad ◽  
Hadi Bagherzadeh-Valami
Keyword(s):  
Data Envelopment Analysis ◽  
Performance Management ◽  
Banking Industry ◽  
Evaluation Process ◽  
Fuzzy Arithmetic ◽  
Data Envelopment ◽  
Fuzzy Data ◽  
Undesirable Outputs ◽  
Dea Model ◽  
The Impact

Data Envelopment Analysis (DEA) is a non-parametric approach based on linear programming for evaluating the performance of decision making units (DMUs) with multiple inputs and multiple outputs. The lack of the ability to generate the actual weights, not considering the impact of undesirable outputs in the evaluation process and the measuring of efficiencies of DMUs based upon precise observations are three main drawbacks of the conventional DEA models. This paper proposes a novel approach for finding the common set of weights (CSW) to compute efficiencies in DEA model with undesirable outputs when the data are represented by fuzzy numbers. The proposed approach is based on fuzzy arithmetic which formulates the fuzzy additive DEA model as a linear programing problem and gives fuzzy efficiencies of all DMUs based on resulting CSW. We demonstrate the applicability of the proposed model with a simple numerical example. Finally, in the context of performance management, an application of banking industry in Iran is presented for analyzing the influence of fuzzy data and depicting the impact of undesirable outputs over the efficiency results.

scholarly journals Data envelopment analysis in measuring the efficiency of volleyball teams in Primorsko-Goranska County

2020 ◽  
Vol 8 (1) ◽  
pp. 121-134
Author(s):  
Jelena Jardas Antonić ◽  
Kristina Kregar ◽  
Nenad Vretenar
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Analysis ◽  
Efficiency Score ◽  
Financial Resources ◽  
Data Envelopment ◽  
Financial Factors ◽  
Measuring Efficiency ◽  
Dea Models ◽  
Sport Organisation ◽  
Ccr Model

Every sport organisation strives to evaluate its performance: its weaknesses and strengths. Measuring efficiency and sports are two interrelated concepts and it is not surprising that most of the research on sports is focused on analysing the efficiency of teams according to player techniques, attack and defence efficiency. However, there are very few studies based on the analysis of financial factors such as teams’ revenue and costs. In this paper two Data Envelopment Analysis (DEA) models were used to evaluate 16 young cadet volleyball teams in Primorsko-Goranska County based on two economic inputs. The paper aims to explain the importance of teams’ financial resources in achieving sports efficiency. To analyse the relative efficiency of teams, two frequently used models are employed, the Banker Charnes Cooper (BCC) and the Charnes Cooper Rhodes (CCR) model. In the end, a super efficiency analysis was conducted to make a distinction in efficiency scores between efficient units. Analyses showed that financial factors are not crucial factors for efficiency score and gave possibility to use obtained results and improve the performance of inefficient volleyball teams. The study was conducted on a sample of 16 teams through 4 inputs and 1 output collected during 2017/2018 season.

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