Genetic-Fuzzy Data Envelopment Analysis Model for Evaluating Financial Institutions Relative Productivity in a Fluctuating Economic Market

Authors

  • Francis Imouokhome Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City. NIGERIA
  • Joy Okoh Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City. NIGERIA
  • Veronica Osubor Department of Computer Science, Faculty of Physical Sciences, University of Benin, Benin City. NIGERIA
Abstract:

This paper presents a Genetic Algorithm Fuzzy Data Envelopment Analysis (GA-FDEA) model that caters for optimal selecting of economic indicators for the measurement of relative productivity and performance of financial institutions. Imprecise or uncertain data of financial institutions due to varying monetary policies and market risk were retrieved from Nigeria Stock Exchange Commission and evaluated. It was observed that GA-FDEA provides better results than the conventional DEA. The findings provide economic barometers for ascertaining the viability of these institutions toward bringing the expected growth of these institutions and the nation at large.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

A model for productivity evaluation of hospital units based on data envelopment analysis and fuzzy best-worst

Introduction:   Today, there isgap between the potential of the health system and its current performance, which justifies the need to a performance appraisal model for the health sector. The purpose of this study is to provide a comprehensive performance evaluation model for assessing the performance of hospitals. Methods:   For this purpose, 12 hospitals under the supervision of Tehran Unive...

full text

A Data Envelopment Analysis Model with Triangular Intuitionistic Fuzzy Numbers

DEA (Data Envelopment Analysis) is a technique for evaluating the relative effectiveness of decision-making units (DMU) with multiple inputs and outputs data based on non-parametric modeling using mathematical programming (including linear programming, multi-parameter programming, stochastic programming, etc.). The classical DEA methods are developed to handle the information in the form of cri...

full text

Presenting a Hybrid Approach based on Two-stage Data Envelopment Analysis to Evaluating Organization Productivity

   Measuring the performance of a production system has been an important task in management for purposes of control, planning, etc. Lord Kelvin said :“When you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meager and unsatisfactory kind.” Hence, manag...

full text

Fuzzy Data Envelopment Analysis for Classification of Streaming Data

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

full text

Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis

A DEA-based stochastic estimation framework is presented to evaluate contextual variables affecting productivity. Conditions are identified under which a two-stage procedure consisting of DEA followed by regression analysis yields consistent estimators of the impact of contextual variables. Conditions are also identified under which DEA in the first stage followed by maximum likelihood estimati...

full text

Fuzzy Data Envelopment Analysis for Classification of Streaming Data

The classification of fuzzy uncertain data is considered one of the most challenging issues in data analysis. In spite of the significance of fuzzy data in mathematical programming, the development of the analytical methods of fuzzy data is slow. Therefore, the current study proposes a new fuzzy data classification method based on fuzzy data envelopment analysis (DEA) which can handle strea...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 30  issue 1

pages  77- 86

publication date 2019-01-26

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023