Inverse data envelopment analysis model to preserve relative efficiency values: The case of variable returns to scale

2011 ◽  
Vol 61 (4) ◽  
pp. 1017-1023 ◽  
Author(s):  
Saowanee Lertworasirikul ◽  
Peerayuth Charnsethikul ◽  
Shu-Cherng Fang
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Variable Returns To Scale

scholarly journals Influence of Constant Returns to Scale and Variable Returns to Scale Data Envelopment Analysis Models in ICT Infrastructure Efficiency Utilization

2021 ◽  
pp. 158-181
Author(s):  
Yinka Oyerinde ◽  
Felix Bankole
Keyword(s):  
Data Envelopment Analysis ◽  
Human Development ◽  
Relative Efficiency ◽  
Returns To Scale ◽  
Data Envelopment ◽  
Information And Communication ◽  
Ict Infrastructure ◽  
Policy Direction ◽  
Constant Returns To Scale ◽  
Variable Returns To Scale

A lot of research has been done using Data Envelopment Analysis (DEA) to measure efficiency in Education. DEA has also been used in the field of Information and Communication Technology for Development (ICT4D) to investigate and measure the efficiency of Information and Communication Technology (ICT) investments on Human Development. Education is one of the major components of the Human Development Index (HDI) which affects the core of Human Development. This research investigates the relative efficiency of ICT Infrastructure Utilization on the educational component of the HDI in order to determine the viability of Learning Analytics using DEA for policy direction and decision making. A conceptual model taking the form of a Linear Equation was used and the Constant Returns to Scale (CRS) and Variable Returns to Scale (VRS) models of the Data Envelopment Analysis were employed to measure the relative efficiency of the components of ICT Infrastructure (Inputs) and the components of Education (Outputs). Results show a generally high relative efficiency of ICT Infrastructure utilization on Educational Attainment and Adult Literacy rates, a strong correlation between this Infrastructure and Literacy rates as well, provide an empirical support for the argument of increasing ICT infrastructure to provide an increase in Human Development, especially within the educational context. The research concludes that DEA as a methodology can be used for macroeconomic decision making and policy direction within developmental research.

Technical Efficiency of State Road Transport Undertakings in India - Data Envelopment Analysis

2012 ◽  
Vol 1 (2) ◽  
pp. 31-42 ◽  
Author(s):  
V. Prakash ◽  
J. Rajesh ◽  
M. Thilagam
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Relative Efficiency ◽  
Fuel Efficiency ◽  
Returns To Scale ◽  
Road Transport ◽  
Data Envelopment ◽  
Variable Returns To Scale ◽  
Decision Making Units

Data envelopment analysis (DEA) is a method of analyzing the relative efficiency of similar types of organizations known as decision making units (DMU’s). In this paper, DEA model is applied to evaluate the relative technical efficiency of state road transport undertakings (SRTU’s) in India during the period 2011-2012. The authors have considered thirty-four SRTU’s functioning in India. The variables chosen to characteristic production units are the number of fleet held, staff strength and fuel efficiency as inputs and Passengers carried as output. The BCC model is input- oriented allowing for variable returns to scale (VRS), units are ranked and the projection analyses are given.

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 Assessment of cooperative sugar factories in tamilnadu - a dea approach

2017 ◽  
Vol 7 (1) ◽  
pp. 16-26
Author(s):  
RAJESH J ◽  
PRAKASH V
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Tamil Nadu ◽  
Returns To Scale ◽  
Similar Type ◽  
Data Envelopment ◽  
Sugar Production ◽  
Variable Returns To Scale ◽  
Decision Making Units

Data Envelopment Analysis (DEA) is a method of analyzing the relative efficiency of similar type of organizations known as Decision Making Units (DMUs). In this paper, DEA model is applied to evaluate the relative technical efficiency of Cooperative Sugar Factories in Tamil nadu during the period 2012-2013. We have considered 15 sugar factories functioning in the state. The variables chosen here to characterize production units are,Sugar cane crushed, Share capital as inputs and Sugar production as output. The BCC model is Output- oriented allowing for variable returns to scale (VRS), units are ranked based on peer count summary.

Sign in / Sign up

Export Citation Format

Share Document