Measuring the relative efficiency of fund management strategies in New Zealand using a spreadsheet-based stochastic data envelopment analysis model

Omega ◽  
1998 ◽  
Vol 26 (2) ◽  
pp. 319-331 ◽  
Author(s):  
IM Premachandra ◽  
John G Powell ◽  
Jing Shi
Keyword(s):  
New Zealand ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Management Strategies ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Fund Management ◽  
Analysis Model ◽  
Stochastic Data

scholarly journals A Two-Phase Data Envelopment Analysis Model for Portfolio Selection

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
David Lengacher ◽  
Craig Cammarata
Keyword(s):  
Data Envelopment Analysis ◽  
Portfolio Selection ◽  
Relative Efficiency ◽  
Relative Effectiveness ◽  
Mixed Integer ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Two Phase ◽  
Mip Model

When organizations do not have well defined goals and constraints, traditional mixed integer programming (MIP) models are ineffective for portfolio selection. In such cases, some organizations revert to building project portfolios based on data envelopment analysis (DEA) relative efficiency scores. However, implementing the k most efficient projects until resources are expended will not always result in the most efficient portfolio. This is because relative efficiency scores are not additive. Instead, the efficiency of each candidate portfolio must be evaluated against all possible portfolios, making for a computationally intensive task. This paper has two main contributions to the literature. First, we introduce a new DEA-MIP model which can identify the most efficient portfolio capable of meeting organizational goals at incremental resource levels. Second, by utilizing a second-stage DEA model to calculate the relative effectiveness of each most efficient portfolio, we provide managers, a tool for justifying budget increases or defending existing budget levels.

scholarly journals REDUCTION OF NON-PERFORMING LOANS IN THE BANKING INDUSTRY: AN APPLICATION OF DATA ENVELOPMENT ANALYSIS

2017 ◽  
Vol 18 (5) ◽  
pp. 833-851 ◽  
Author(s):  
Chih-Ching YANG
Keyword(s):  
Data Envelopment Analysis ◽  
Finite Number ◽  
Relative Efficiency ◽  
Banking Industry ◽  
Negative Impact ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
The World ◽  
Using Data

The increase in non-performing loans around the world has had quite a negative impact on many nations’ banking systems. To address these problems, many creative regulatory solutions and well-designed risk techniques have been utilized in the hope of reducing non-performing loans to an acceptable level. The purpose of this study is to apply a newly developed data envelopment analysis model to suggest the most efficient plan (called Plan 4) to reduce non-performing loans that can maximize the efficiency of the entire banking industry’s control over the bad debts. For comparison purpose, three other reduction plans are also represented. The four plans are presented using data from Taiwan’s banking industry. The empirical results show that among the plans presented, Plan 4 shows the most effective allocation of the industry-wide reduction target. The plan focuses on a finite number of banks, helping identify the key units to improve industry-wide efficiency. The findings implicitly suggest that the regulator should devise more incentive measures to encourage target banks to perform the non-performing loan reduction task. Our results also suggest that for the regulator, forcing banks to cut their non-performing loans by the same ratio will not help improve the relative efficiency of the industry.

scholarly journals A knowledge system proposal with weighted goal programming approach for multi-criteria dea model and an application

2021 ◽  
Vol 12 (2) ◽  
pp. 422-438
Author(s):  
Tugba Polat ◽  
Safak Kiris
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Goal Programming ◽  
Evaluation Process ◽  
Knowledge System ◽  
Programming Approach ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Weighted Goal Programming

In today's competitive environment, enterprises should use their resources correctly; they should continuously improve themselves and work efficiently. It is important to evaluate the performances of the units under the same conditions in enterprises according to each other, to see the current situations and to determine appropriate improvements in necessary points. One of the commonly used approaches to performance evaluation is Data Envelopment Analysis. Many approaches have been developed for the Data Envelopment Analysis model, and Goal programming using in multi-objective decision making solutions approaches is one of them. Goal Programming gives decision-makers the opportunity to evaluate many objectives together in the decision-making process. In this study, classical Data Envelopment Analysis and weighted goal programming approach for multi-criteria data envelopment analysis model was applied in the evaluation process of the projects worked in an automotive supplier industry. A knowledge system has also been proposed in order to evaluate the effectiveness of the projects periodically and to include new projects or conditions into the evaluation.

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