International Science Index
Searching the Efficient Frontier for the Coherent Covering Location Problem
In this article, we will try to find an efficient boundary
approximation for the bi-objective location problem with coherent
coverage for two levels of hierarchy (CCLP). We present the
mathematical formulation of the model used. Supported efficient
solutions and unsupported efficient solutions are obtained by solving
the bi-objective combinatorial problem through the weights method
using a Lagrangean heuristic. Subsequently, the results are validated
through the DEA analysis with the GEM index (Global efficiency
Detection Efficient Enterprises via Data Envelopment Analysis
In this paper, the Turkey’s Top 500 Industrial Enterprises data in 2014 were analyzed by data envelopment analysis. Data envelopment analysis is used to detect efficient decision-making units such as universities, hospitals, schools etc. by using inputs and outputs. The decision-making units in this study are enterprises. To detect efficient enterprises, some financial ratios are determined as inputs and outputs. For this reason, financial indicators related to productivity of enterprises are considered. The efficient foreign weighted owned capital enterprises are detected via super efficiency model. According to the results, it is said that Mercedes-Benz is the most efficient foreign weighted owned capital enterprise in Turkey.
Hybrid Approach for Country’s Performance Evaluation
This paper presents an integrated model, which hybridized data envelopment analysis (DEA) and support vector machine (SVM) together, to class countries according to their efficiency and performance. This model takes into account aspects of multi-dimensional indicators, decision-making hierarchy and relativity of measurement. Starting from a set of indicators of performance as exhaustive as possible, a process of successive aggregations has been developed to attain an overall evaluation of a country’s competitiveness.
Assessing Efficiency Trends in the Indian Sugar Industry
This paper measures technical and scale efficiencies of 40 Indian sugar companies for the period from 2004-05 to 2013-14. The efficiencies are estimated through input-oriented DEA models using one output variable—value of output (VOP) and five input variables—capital cost (CA), employee cost (EMP), raw material (RW), energy & fuel (E&F) and other manufacturing expenses (OME). The sugar companies are classified into integrated and non-integrated categories to know which one achieves higher level of efficiency. Sources of inefficiency in the industry are identified through decomposing the overall technical efficiency (TE) into pure technical efficiency (PTE) and scale efficiency (SE). The paper also estimates input-reduction targets for relatively inefficient companies and suggests measures to improve their efficiency level. The findings reveal that the TE does not evince any trend rather it shows fluctuations across years, largely due to erratic and cyclical pattern of sugar production. Further, technical inefficiency in the industry seems to be driven more by the managerial inefficiency than the scale inefficiency, which implies that TE can be improved through better conversion of inputs into output.
Evaluating Efficiency of Nina Distribution Company Using Window Data Envelopment Analysis and Malmquist Index
Achieving continuous sustained economic growth and following economic development can be the target for all countries which are looking for it. In this regard, distribution industry plays an important role in growth and development of any nation. So, estimating the efficiency and productivity of the so called industry and identifying factors influencing it, is very necessary. The objective of the present study is to measure the efficiency and productivity of seven branches of Nina Distribution Company using window data envelopment analysis and Malmquist productivity index from spring 2013 to summer 2015. In this study, using criteria of fixed assets, payroll personnel, operating costs and duration of collection of receivables were selected as inputs and people and net sales, gross profit and percentage of coverage to customers were selected as outputs. Then, the process of performance window data envelopment analysis was driven and process efficiency has been measured using Malmquist index. The results indicate that the average technical efficiency of window Data Envelopment Analysis (DEA) model and fluctuating trend is sustainable. But the average management efficiency in window DEA model is related with negative growth (decline) of about 13%. The mean scale efficiency in all windows, except in the second one which is faced with 8%, shows growth of 18% compared to the first window. On the other hand, the mean change in total factor productivity in all branches of the industry shows average negative growth (decrease) of 12% which are the result of a negative change in technology.
Non-Parametric, Unconditional Quantile Estimation of Efficiency in Microfinance Institutions
We apply the non-parametric, unconditional,
hyperbolic order-α quantile estimator to appraise the relative
efficiency of Microfinance Institutions in Africa in terms of outreach.
Our purpose is to verify if these institutions, which must constantly
try to strike a compromise between their social role and financial
sustainability are operationally efficient.
Using data on African MFIs extracted from the Microfinance
Information eXchange (MIX) database and covering the 2004 to
2006 periods, we find that more efficient MFIs are also the most
profitable. This result is in line with the view that social performance
is not in contradiction with the pursuit of excellent financial
performance. Our results also show that large MFIs in terms of asset
and those charging the highest fees are not necessarily the most
A Review on the Comparison of EU Countries Based on Research and Development Efficiencies
Nowadays, technological progress is one of the most
important components of economic growth and the efficiency of
R&D activities is particularly essential for countries. This study is an
attempt to analyze the R&D efficiencies of EU countries. The
indicators related to R&D efficiencies should be determined in
advance in order to use DEA. For this reason a list of input and
output indicators are derived from the literature review. Considering
the data availability, a final list is given for the numerical analysis for
Study of the Effect of Inclusion of TiO2 in Active Flux on Submerged Arc Welding of Low Carbon Mild Steel Plate and Parametric Optimization of the Process by Using DEA Based Bat Algorithm
Submerged arc welding is a very complex process. It
is a very efficient and high performance welding process. In this
present study an attempt have been done to reduce the welding
distortion by increased amount of oxide flux through TiO2 in
submerged arc welding process. Care has been taken to avoid the
excessiveness of the adding agent for attainment of significant
results. Data Envelopment Analysis (DEA) based BAT algorithm is
used for the parametric optimization purpose in which DEA is used
to convert multi response parameters into a single response
parameter. The present study also helps to know the effectiveness of
the addition of TiO2 in active flux during submerged arc welding
Efficiency for Sustainable Growth: Evidence from the North African Countries
Improved resource efficiency of production is a key
requirement for sustainable growth, worldwide. In this regards, by
considering the energy and tourism as the extra inputs to the classical
Coub-Douglas production function, this study aims at investigating
the efficiency changes in the North African countries. To this end, the
study uses panel data for the period 1995-2010 and adopts the
Malmquist index based on the data envelopment analysis. Results
show that tourism increases technical and scale efficiencies, while it
decreases technological and total factor productivity changes. On the
other hand, when the production function is augmented by the energy
input; technical efficiency change decreases, while the technological
change, scale efficiency change and total factor productivity change
increase. Thus, in order to satisfy the needs for sustainable growth,
North African governments should take some measures for increasing
the contribution that the tourism makes to economic growth and some
others for efficient use of resources in the energy sector.
Measurement of Operational and Environmental Performance of the Coal-Fired Power Plants in India by Using Data Envelopment Analysis
In this study, the performance analyses of the twenty
five Coal-Fired Power Plants (CFPPs) used for electricity generation
are carried out through various Data Envelopment Analysis (DEA)
models. Three efficiency indices are defined and pursued. During the
calculation of the operational performance, energy and non-energy
variables are used as input, and net electricity produced is used as
desired output (Model-1). CO2 emitted to the environment is used as
the undesired output (Model-2) in the computation of the pure
environmental performance while in Model-3 CO2 emissions is
considered as detrimental input in the calculation of operational and
environmental performance. Empirical results show that most of the
plants are operating in increasing returns to scale region and Mettur
plant is efficient one with regards to energy use and environment.
The result also indicates that the undesirable output effect is
insignificant in the research sample. The present study will provide
clues to plant operators towards raising the operational and
environmental performance of CFPPs.
Fuzzy Multi-Component DEA with Shared and Undesirable Fuzzy Resources
Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using α cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.
Efficiency of the Slovak Commercial Banks Applying the DEA Window Analysis
The aim of this paper is to estimate the efficiency of the Slovak commercial banks employing the Data Envelopment Analysis (DEA) window analysis approach during the period 2003-2012. The research is based on unbalanced panel data of the Slovak commercial banks. Undesirable output was included into analysis of banking efficiency. It was found that most efficient banks were Postovabanka, UniCredit Bank and Istrobanka in CCR model and the most efficient banks were Slovenskasporitelna, Istrobanka and UniCredit Bank in BCC model. On contrary, the lowest efficient banks were found Privatbanka and CitiBank. We found that the largest banks in the Slovak banking market were lower efficient than medium-size and small banks. Results of the paper is that during the period 2003-2008 the average efficiency was increasing and then during the period 2010-2011 the average efficiency decreased as a result of financial crisis.
Comparative Analysis of the Public Funding for Greek Universities: An Ordinal DEA/MCDM Approach
This study performs a comparative analysis of the 21 Greek Universities in terms of their public funding, awarded for covering their operating expenditure. First it introduces a DEA/MCDM model that allocates the fund into four expenditure factors in the most favorable way for each university. Then, it presents a common, consensual assessment model to reallocate the amounts, remaining in the same level of total public budget. From the analysis it derives that a number of universities cannot justify the public funding in terms of their size and operational workload. For them, the sufficient reduction of their public funding amount is estimated as a future target. Due to the lack of precise data for a number of expenditure criteria, the analysis is based on a mixed crisp-ordinal data set.
Data Envelopment Analysis with Partially Perfect Objects
This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.
DEA Method for Evaluation of EU Performance
The paper deals with an application of quantitative analysis – the Data Envelopment Analysis (DEA) method to performance evaluation of the European Union Member States, in the reference years 2000 and 2011. The main aim of the paper is to measure efficiency changes over the reference years and to analyze a level of productivity in individual countries based on DEA method and to classify the EU Member States to homogeneous units (clusters) according to efficiency results. The theoretical part is devoted to the fundamental basis of performance theory and the methodology of DEA. The empirical part is aimed at measuring degree of productivity and level of efficiency changes of evaluated countries by basic DEA model – CCR CRS model, and specialized DEA approach – the Malmquist Index measuring the change of technical efficiency and the movement of production possibility frontier. Here, DEA method becomes a suitable tool for setting a competitive/uncompetitive position of each country because there is not only one factor evaluated, but a set of different factors that determine the degree of economic development.
Performance Evaluation of Faculties of Islamic Azad University of Zahedan Branch Based-On Two-Component DEA
The aim of this paper is to evaluate the performance of the faculties of Islamic Azad University of Zahedan Branch based on two-component (teaching and research) decision making units (DMUs) in data envelopment analysis (DEA). Nowadays it is obvious that most of the systems as DMUs do not act as a simple inputoutput structure. Instead, if they have been studied more delicately, they include network structure. University is such a network in which different sections i.e. teaching, research, students and office work as a parallel structure. They consume some inputs of university commonly and some others individually. Then, they produce both dependent and independent outputs. These DMUs are called two-component DMUs
with network structure. In this paper, performance of the faculties of Zahedan branch is calculated by using relative efficiency model and also, a formula to compute relative efficiencies teaching and research components based on DEA are offered.
Intellectual Capital and Competitive Advantage: An Analysis of the Biotechnology Industry
Intellectual capital measurement is a central aspect of knowledge management. The measurement and the evaluation of intangible assets play a key role in allowing an effective management of these assets as sources of competitiveness. For these reasons, managers and practitioners need conceptual and analytical tools taking into account the unique characteristics and economic significance of Intellectual Capital. Following this lead, we propose an efficiency and productivity analysis of Intellectual Capital, as a determinant factor of the company competitive advantage. The analysis is carried out by means of Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). These techniques identify Bests Practice companies that have accomplished competitive advantage implementing successful strategies of Intellectual Capital management, and offer to inefficient companies development paths by means of benchmarking. The proposed methodology is employed on the Biotechnology industry in the period 2007-2010.
A DEA Model for Performance Evaluation in The Presence of Time Lag Effect
Data Envelopment Analysis (DEA) is a methodology
that computes efficiency values for decision making units (DMU) in a
given period by comparing the outputs with the inputs. In many cases,
there are some time lag between the consumption of inputs and the
production of outputs. For a long-term research project, it is hard to
avoid the production lead time phenomenon. This time lag effect
should be considered in evaluating the performance of organizations.
This paper suggests a model to calculate efficiency values for the
performance evaluation problem with time lag. In the experimental
part, the proposed methods are compared with the CCR and an
existing time lag model using the data set of the 21st century frontier
R&D program which is a long-term national R&D program of Korea.
Ranking Alternatives in Multi-Criteria Decision Analysis using Common Weights Based on Ideal and Anti-ideal Frontiers
One of the most important issues in multi-criteria decision analysis (MCDA) is to determine the weights of criteria so that all alternatives can be compared based on the collective performance of criteria. In this paper, one of popular methods in data envelopment analysis (DEA) known as common weights (CWs) is used to determine the weights in MCDA. Two frontiers named ideal and anti-ideal frontiers, instead of ideal and anti-ideal alternatives, are defined based on two new proposed CWs models. Ideal and antiideal frontiers are more flexible than that of alternatives. According to the optimal solutions of these two models, the distances of an alternative from the ideal and anti-ideal frontiers are derived. Then, a relative distance is introduced to measure the value of each alternative. The suggested models are linear and despite weight restrictions are feasible. An example is presented for explaining the method and for comparing to the existing literature.
Data Envelopment Analysis under Uncertainty and Risk
Data Envelopment Analysis (DEA) is one of the most
widely used technique for evaluating the relative efficiency of a set
of homogeneous decision making units. Traditionally, it assumes that
input and output variables are known in advance, ignoring the critical
issue of data uncertainty. In this paper, we deal with the problem
of efficiency evaluation under uncertain conditions by adopting the
general framework of the stochastic programming. We assume that
output parameters are represented by discretely distributed random
variables and we propose two different models defined according to a
neutral and risk-averse perspective. The models have been validated
by considering a real case study concerning the evaluation of the
technical efficiency of a sample of individual firms operating in
the Italian leather manufacturing industry. Our findings show the
validity of the proposed approach as ex-ante evaluation technique
by providing the decision maker with useful insights depending on
his risk aversion degree.
Scheduling a Flexible Flow Shops Problem using DEA
This paper considers a scheduling problem in flexible
flow shops environment with the aim of minimizing two important
criteria including makespan and cumulative tardiness of jobs. Since
the proposed problem is known as an Np-hard problem in literature,
we have to develop a meta-heuristic to solve it. We considered
general structure of Genetic Algorithm (GA) and developed a new
version of that based on Data Envelopment Analysis (DEA). Two
objective functions assumed as two different inputs for each Decision
Making Unit (DMU). In this paper we focused on efficiency score of
DMUs and efficient frontier concept in DEA technique. After
introducing the method we defined two different scenarios with
considering two types of mutation operator. Also we provided an
experimental design with some computational results to show the
performance of algorithm. The results show that the algorithm
implements in a reasonable time.
Two DEA Based Ant Algorithms for CMS Problems
This paper considers a multi criteria cell formation
problem in Cellular Manufacturing System (CMS). Minimizing the
number of voids and exceptional elements in cells simultaneously are
two proposed objective functions. This problem is an Np-hard
problem according to the literature, and therefore, we can-t find the
optimal solution by an exact method. In this paper we developed two
ant algorithms, Ant Colony Optimization (ACO) and Max-Min Ant
System (MMAS), based on Data Envelopment Analysis (DEA). Both
of them try to find the efficient solutions based on efficiency concept
in DEA. Each artificial ant is considered as a Decision Making Unit
(DMU). For each DMU we considered two inputs, the values of
objective functions, and one output, the value of one for all of them.
In order to evaluate performance of proposed methods we provided
an experimental design with some empirical problem in three
different sizes, small, medium and large. We defined three different
criteria that show which algorithm has the best performance.
A Hybrid DEA Model for the Measurement of the Enviromental Performance
Data envelopment analysis (DEA) has gained great popularity in environmental performance measurement because it can provide a synthetic standardized environmental performance index when pollutants are suitably incorporated into the traditional DEA framework. Since some of the environmental performance indicators cannot be controlled by companies managers, it is necessary to develop the model in a way that it could be applied when discretionary and/or non-discretionary factors were involved. In this paper, we present a semi-radial DEA approach to measuring environmental performance, which consists of non-discretionary factors. The model, then, has been applied on a real case.
Application of Data Envelopment Analysis and Performance Indicators to Irrigation Systems in Thessaloniki Plain (Greece)
In this paper, a benchmarking framework is presented
for the performance assessment of irrigations systems. Firstly, a data
envelopment analysis (DEA) is applied to measure the technical
efficiency of irrigation systems. This method, based on linear
programming, aims to determine a consistent efficiency ranking of
irrigation systems in which known inputs, such as water volume
supplied and total irrigated area, and a given output corresponding to
the total value of irrigation production are taken into account
simultaneously. Secondly, in order to examine the irrigation
efficiency in more detail, a cross – system comparison is elaborated
using a performance indicators set selected by IWMI. The above
methodologies were applied in Thessaloniki plain, located in
Northern Greece while the results of the application are presented and
discussed. The conjunctive use of DEA and performance indicators
seems to be a very useful tool for efficiency assessment and
identification of best practices in irrigation systems management.
Application of Data Envelopment Analysis to Assess Quality Management Efficiency
This paper is aimed to give an illustration on the
application of Data Envelopment Analysis (DEA) as a tool to assess
Quality Management (QM) efficiency. A variant of DEA, slack based
measure (SBM) is used for this purpose. From this study, it is found
that DEA is suitable to measure QM efficiency and give
improvement suggestions to the inefficient QM.
Ranking DMUs by Ideal PPS in Data Envelopment Analysis
An original DEA model is to evaluate each DMU
optimistically, but the interval DEA Model proposed in this paper
has been formulated to obtain an efficiency interval consisting of
Evaluations from both the optimistic and the pessimistic view points.
DMUs are improved so that their lower bounds become so large as to
attain the maximum Value one. The points obtained by this method
are called ideal points. Ideal PPS is calculated by ideal of efficiency
DMUs. The purpose of this paper is to rank DMUs by this ideal PPS.
Finally we extend the efficiency interval of a DMU under variable
Role of Credit on Production Efficiency of Farming Sector in Pakistan(A Data Envelopment Analysis)
The study identified the sources of production
inefficiency of the farming sector in district Faisalabad in the Punjab
province of Pakistan. Data Envelopment Analysis (DEA) technique
was utilized at farm level survey data of 300 farmers for the year
2009. The overall mean efficiency score was 0.78 indicating 22
percent inefficiency of the sample farmers. Computed efficiency
scores were then regressed on farm specific variables using Tobit
regression analysis. Farming experience, education, access to
farming credit, herd size and number of cultivation practices showed
constructive and significant effect on the farmer-s technical
Benchmarking Cleaner Production Performance of Coal-fired Power Plants Using Two-stage Super-efficiency Data Envelopment Analysis
Benchmarking cleaner production performance is an
effective way of pollution control and emission reduction in coal-fired
power industry. A benchmarking method using two-stage
super-efficiency data envelopment analysis for coal-fired power plants
is proposed – firstly, to improve the cleaner production performance of
DEA-inefficient or weakly DEA-efficient plants, then to select the
benchmark from performance-improved power plants. An empirical
study is carried out with the survey data of 24 coal-fired power plants.
The result shows that in the first stage the performance of 16 plants is
DEA-efficient and that of 8 plants is relatively inefficient. The target
values for improving DEA-inefficient plants are acquired by
projection analysis. The efficient performance of 24 power plants and
the benchmarking plant is achieved in the second stage. The two-stage
benchmarking method is practical to select the optimal benchmark in
the cleaner production of coal-fired power industry and will
continuously improve plants- cleaner production performance.
The Effect of Risky Assets to Operating Efficiencies for Listed Securities Firms in Taiwan Using the Data Envelopment Analysis
This paper employs a the variable returns to scale DEA
model to take account of risky assets and estimate the operating
efficiencies for the 21 domestic listed securities firms during the
period 2005-2009. Evidence is found that on average the brokerage
securities firms- operating efficiencies are better than integrated
securities firms. Evidence is also found that the technical inefficiency
from inappropriate management constitutes the main source of the
operating inefficiency for both types of securities firms. Moreover, the
scale economies prevail in brokerage and integrated securities firms,
in other words, which exhibit the characteristic of increasing returns to
Environmental Performance of the United States Energy Sector: A DEA Model with Non-Discretionary Factors and Perfect Object
It is suggested to evaluate environmental performance
of energy sector using Data Envelopment Analysis with nondiscretionary
factors (DEA-ND) with relative indicators as inputs and
outputs. The latter allows for comparison of the objects essentially
different in size. Inclusion of non-discretionary factors serves
separation of the indicators that are beyond the control of the objects.
A virtual perfect object comprised of maximal outputs and minimal
inputs was added to the group of actual ones. In this setting, explicit
solution of the DEA-ND problem was obtained. Energy sector of the
United States was analyzed using suggested approach for the period
of 1980 – 2006 with expected values of economic indicators for 2030
used for forming the perfect object. It was obtained that
environmental performance has been increasing steadily for the
period from 7.7% through 50.0% but still remains well below the