EFFICIENCY ANALYSIS OF PROVINCIAL DEPARTMENTS OF PHYSICAL EDUCATION IN IRAN

2012 ◽  
Vol 11 (05) ◽  
pp. 983-1008 ◽  
Author(s):  
JAHANGIR SOLEIMANI-DAMANEH ◽  
MAJID SOLEIMANI-DAMANEH ◽  
MEHRZAD HAMIDI
Keyword(s):  
Physical Education ◽  
Efficiency Score ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Scale Size ◽  
Dea Models ◽  
The Government ◽  
Student’S T ◽  
Most Productive Scale Size ◽  
Hierarchy Process

In many countries, including Iran, Provincial Departments of Physical Education try to develop the athletic sports and sports for all in their related areas (state), using the government resources. Their success rate has always been an important subject for the top sports managers of country. In this paper we use data envelopment analysis (DEA) and analytic hierarchy process (AHP) techniques for analyzing the performance of physical education organizations in Iran. Some convex and nonconvex DEA models have been used. Afterwards, we have used the Shannon's entropy for aggregating the results obtained from different models and providing a final efficiency score (FES) and a unified ranking. It can be seen that, in the ranking approach provided in this paper the most productive scale size (MPSS) units have the best rank (see Proposition 1). Our findings reveal that the average of FESs of the states is 0.472635 and 50% of the states have an FES more than this average. Classifying the sates to five efficiency classes, "Excellent, Good, Middle, Weak and Very Weak", the percentage of the states belonging to these classes are 6.7, 30, 16.6, 36.7 and 10, respectively. Also, some correlation and difference studies have been carried out using the Pearson's correlation and student's t-tests. Finally, comparisons between the results of some relevant existing publications and those given in the present paper are addressed.

A hybrid AHP/DEA-AR model for measuring and comparing the efficiency of airports

2019 ◽  
Vol 68 (3) ◽  
pp. 524-541 ◽  
Author(s):  
Burak Keskin ◽  
Can Deniz Köksal
Keyword(s):  
Practical Implication ◽  
Evaluation Study ◽  
Ar Model ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Assurance Region ◽  
The Government ◽  
First Time ◽  
Hierarchy Process

PurposeThe purpose of this paper is to employ an efficiency analysis and compare the efficiency scores of publicly or privately operated airports in Turkey.Design/methodology/approachThis study uses analytic hierarchy process, which is one of the widely known multi-criteria decision-making methods to calculate the relative weights of input and outputs. This study also uses data envelopment analysis and assurance region (AR) method to calculate the efficiency scores of airports at the empirical analysis stage.FindingsThe empirical results reveal that DEA-BCC and DEA-CCR methods produced almost the same efficiency scores, and 14 airports were found as efficient. Also, AR method was employed and under this method, it was only two airports operated by the private sector that were found as efficient. None of the publicly operated airports was found as efficient.Practical implicationsThe main practical implication of this study is that publicly operated airports must improve their efficiency levels in Turkey. This situation indicates that the government policy for the aviation sector must be changed. It is not a coincidence that all publicly operated airports are inefficient. To cope with this situation, it may be a useful policy that establishes a regional airport system or applies the privatization process to all airports.Originality/valueThe most significant contribution of this study to literature is that the AR method, which was never used before in a single country’s airport performance evaluation study, was applied for the first time. Also, this technique was applied first time to Turkish airports for measuring their efficiency levels.

scholarly journals An integrated approach to grey relational analysis, analytic hierarchy process and data envelopment analysis

2016 ◽  
Vol 9 (1) ◽  
pp. 71-86 ◽  
Author(s):  
Mohammad Sadegh Pakkar
Keyword(s):  
Data Envelopment Analysis ◽  
Grey Relational Analysis ◽  
Data Envelopment ◽  
Analytic Hierarchy ◽  
Content Type ◽  
Attribute Weights ◽  
Relational Analysis ◽  
Dea Models ◽  
Grey Relational ◽  
Hierarchy Process

Purpose This paper aims to propose an integration of the analytic hierarchy process (AHP) and data envelopment analysis (DEA) methods in a multiattribute grey relational analysis (GRA) methodology in which the attribute weights are completely unknown and the attribute values take the form of fuzzy numbers. Design/methodology/approach This research has been organized to proceed along the following steps: computing the grey relational coefficients for alternatives with respect to each attribute using a fuzzy GRA methodology. Grey relational coefficients provide the required (output) data for additive DEA models; computing the priority weights of attributes using the AHP method to impose weight bounds on attribute weights in additive DEA models; computing grey relational grades using a pair of additive DEA models to assess the performance of each alternative from the optimistic and pessimistic perspectives; and combining the optimistic and pessimistic grey relational grades using a compromise grade to assess the overall performance of each alternative. Findings The proposed approach provides a more reasonable and encompassing measure of performance, based on which the overall ranking position of alternatives is obtained. An illustrated example of a nuclear waste dump site selection is used to highlight the usefulness of the proposed approach. Originality/value This research is a step forward to overcome the current shortcomings in the weighting schemes of attributes in a fuzzy multiattribute GRA methodology.

Environmental Efficiency Measurement Based on Cross-Efficiency DEA Models in Power Industry

2011 ◽  
Vol 63-64 ◽  
pp. 659-663 ◽  
Author(s):  
Dan Niu ◽  
Shu Yu Guo
Keyword(s):  
Air Pollution ◽  
Power Industry ◽  
Environmental Efficiency ◽  
Data Envelopment ◽  
Practical Application ◽  
Analytic Hierarchy ◽  
The Sustainable Development ◽  
Dea Models ◽  
Components Analysis ◽  
Hierarchy Process

Air pollution becomes more serious with the development of industry. Taking the “sustainable development” into account, more and more corporations consider environment as an important feature in their products. Because coal is the main consumption of power industry and coal combustion can produce air pollution seriously, how to measure the environmental efficiency in power industry becomes more significant. Although there are many of synthetic evaluation methods were proposed for measuring the green degree of production, such as AHP (Analytic Hierarchy Process), PCA (Principal Components Analysis), DEA (Data Envelopment Analysis) etc., the shortcomings of each method for measure green performance are appeared in practical application. A peer appraisal methodology, denoted as cross-efficiency DEA, was applied in this paper to measure the environmental efficiency of power industry in US.

scholarly journals An Approach for Generating Weights Using the Pairwise Comparison Matrix

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Zaher Sepehrian ◽  
Sahar Khoshfetrat ◽  
Said Ebadi
Keyword(s):  
Pairwise Comparison ◽  
Decision Criterion ◽  
Data Envelopment ◽  
Decision Criteria ◽  
Analytic Hierarchy ◽  
Pairwise Comparison Matrix ◽  
Proposed Model ◽  
Assurance Region ◽  
Potential Applications ◽  
Hierarchy Process

Data envelopment analysis (DEA) has been used for obtaining weights for the analytic hierarchy process (AHP), an approach known as DEAHP. This method sometimes identifies more than one decision criterion or alternative as DEAHP-efficient. To overcome this problem, this paper proposes a new approach that not only generates appropriate weights for the decision criteria or alternatives, but also differentiates between DEAHP-efficient decision criteria or alternatives. To this end, we propose a DEA model with an assurance region and a cross-weight model that prioritizes decision criteria or alternatives by considering their most unfavorable weights. Two numerical examples are also provided to illustrate the advantages and potential applications of the proposed model.

scholarly journals Strategies for Improvement of Government Budget Absorption of Bogor City

2020 ◽  
Vol 8 (2) ◽  
pp. 207
Author(s):  
Gustawan Rachman ◽  
Ma’mun Sarma ◽  
Dwi Rachmina
Keyword(s):  
Government Regulation ◽  
Work Conditions ◽  
Government Budget ◽  
Analytic Hierarchy ◽  
Budget Planning ◽  
The Government ◽  
Hierarchy Process ◽  
External Intervention ◽  
Budget Expenditure

This study aims to analyze for factors that cause delays in the absorption of the Bogor City Government's expenditure budget so that a strategy can be formulated to improve the performance of this budget absorption. Searching for variables forming the causal factors is done by direct observation and library data search. Exploratory Factor Analysis (EFA) is used to look for underlying factors extracted from the factors forming variables. The search for alternative strategies to improve performance of budget absorption was carried out using the Analytic Hierarchy Process (AHP). The EFA analysis found five main factors causing delays in the absorption of budget expenditure, namely factor in budget planning activities, factor in government regulation and bureaucracy, factor of work conditions, factor influencing financial activities and disbursement of the Government budget, and human resources of the state civil apparatus (ASN). AHP analysis shows that of the five leading sectors of the Regional Apparatus that play a role as key leaders in improving the performance of budget absorption is Sekretariat Daerah. The main obstacle in improving budget absorption is internal and external intervention. The main strategy to correct delays in spending is to improve quality of budget planning and procurement of service goods.

Students’ Tendencies in Choosing Technical and Vocational Education and Training (TVET): Analysis of the Influential Factors using Analytic Hierarchy Process

2021 ◽  
Vol 12 (3) ◽  
pp. 2608-2615
Author(s):  
Chia Ming Hong Et.al
Keyword(s):  
Analytic Hierarchy Process ◽  
Vocational Education ◽  
Social Perception ◽  
Influential Factor ◽  
Skilled Workers ◽  
Analytic Hierarchy ◽  
Technical And Vocational Education ◽  
The Government ◽  
Trained Manpower ◽  
Hierarchy Process

In the era of Industry Revolution (IR) 4.0, business and industry are being transformed by a new wave of digital technology. In order to boost the economy’s prosperity in Malaysia, skilled workforce or well-trained manpower is vital in accomplishing the goal.However, it requires mainstreaming Technical and Vocational Education Training (TVET)in education system by providingcomprehensive training, effective research consultancy, holistic courses, collaboration, student placement and program attachment opportunity. Coherent from this issue, the government can produce more skill workers that can handle the rapid changing world of work. In Malaysia, there are more than 1000 TVET institutions, where 506 are considered as public institutions. However, itstill receives less attention by the students after secondary education. The identified potential factors are TVET instructors, current policy in Malaysia, social perception, employers’ perception, parents, facility, education cost and student themselves. Therefore, this study aims to rank these factors according to the levels of importance using Analytic Hierarchy Process (AHP) method. AHP is a method used to rank criteria by assigning the weight for each criterion. In this study, primary data is collected using questionnaires from 32 TVET instructors of Institut Kemahiran Belia Negara (IKBN) in northern region of Malaysia. The result of AHP shows that the variable of parents is the most influential factor with the weight of 18.81%, followed by the variable of facilities (18.56%). Conversely, the least influential factor is the variable of social perception with the weight of 7.21%. Hence, the government should implement appropriate strategies to attract more secondary school students to enroll in TVET programs. Due to the growth of skilled workers, our country is expected to transform the landscape of the manufacturing industry over the next decade. Hence, developingthe country’s productivity and curbing youth unemployment.

Assessing most productive scale size with fuzzy stochastic data envelopment analysis

2022 ◽  
pp. 1-11
Author(s):  
Hooshang Kheirollahi ◽  
Mahfouz Rostamzadeh ◽  
Soran Marzang
Keyword(s):  
Relative Efficiency ◽  
Data Envelopment ◽  
Random Inputs ◽  
Dea Model ◽  
Scale Size ◽  
Stochastic Dea ◽  
Probability Constraints ◽  
Most Productive Scale Size ◽  
Decision Making Units ◽  
Fuzzy Random

Classic data envelopment analysis (DEA) is a linear programming method for evaluating the relative efficiency of decision making units (DMUs) that uses multiple inputs to produce multiple outputs. In the classic DEA model inputs and outputs of DMUs are deterministic, while in the real world, are often fuzzy, random, or fuzzy-random. Many researchers have proposed different approaches to evaluate the relative efficiency with fuzzy and random data in DEA. In many studies, the most productive scale size (mpss) of decision making units has been estimated with fuzzy and random inputs and outputs. Also, the concept of fuzzy random variable is used in the DEA literature to describe events or occurrences in which fuzzy and random changes occur simultaneously. This paper has proposed the fuzzy stochastic DEA model to assess the most productive scale size of DMUs that produce multiple fuzzy random outputs using multiple fuzzy random inputs with respect to the possibility-probability constraints. For solving the fuzzy stochastic DEA model, we obtained a nonlinear deterministic equivalent for the probability constraints using chance constrained programming approaches (CCP). Then, using the possibility theory the possibilities of fuzzy events transformed to the deterministic equivalents with definite data. In the final section, the fuzzy stochastic DEA model, proposed model, has been used to evaluate the most productive scale size of sixteen Iranian hospitals with four fuzzy random inputs and two fuzzy random outputs with symmetrical triangular membership functions.

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