scholarly journals Efficiency of the Slovak forestry in comparison to other European countries: An application of Data Envelopment Analysis

2018 ◽  
Vol 64 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Miroslav Kovalčík
Keyword(s):  
Data Envelopment Analysis ◽  
European Countries ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Efficiency Improvement ◽  
Parametric Approach ◽  
Output Data ◽  
Average Efficiency ◽  
Input And Output ◽  
Forestry Sector

AbstractEfficiency improvement is important for increasing the competitiveness of any sector and the same is essential for the forestry sector. A non-parametric approach – Data Envelopment Analysis (DEA) was used for the assessment of forestry efficiency. The paper presents the results of the efficiency evaluation of forestry in European countries using DEA. One basic and two modified models (labourandwood sale) were proposed, based on available input and output data from Integrated Environmental and Economic Accounts for Forests and specific conditions of forestry also. The sample size was 22 countries and the data for 2005–2008 was processed. Obtained results show average efficiency in the range of 69 – 90% (depending on the model). Based on the results of the analysis following can be concluded: Slovak forestry achieved under average efficiency in comparison to other European countries, there were great differences in efficiency among individual countries; state of economy (advanced countries and countries with economy in transition) and region did not influence the efficiency statistically significant.

scholarly journals The efficiency analysis of organic and conventional olive farms: Case of Turkey

2010 ◽  
Vol 56 (No. 2) ◽  
pp. 89-96 ◽  
Author(s):  
M.M. Artukoglu ◽  
A. Olgun ◽  
H. Adanacioglu
Keyword(s):  
Data Envelopment Analysis ◽  
Technical Efficiency ◽  
Efficiency Analysis ◽  
Data Envelopment ◽  
Average Efficiency ◽  
Total Potential ◽  
Input And Output ◽  
Study Results ◽  
Crs Model ◽  
Potential Improvement

This paper investigates technical and economically efficiency of 62 organic and 62 conventional olive producing farms in Turkey. According to the study results; by using the CRS model which is input and output-oriented, the average technical efficiency of organic olive farms is 67.68%, the average technical efficiency of conventional olive farms is 47.93%. The technical efficiency of the output-oriented VRS model is 74.78%, and the technical efficiency of the input-oriented VRS model is 93.46%. Also, considering the same model, the average efficiency of the conventional olive farms in the input and output are 59.58% and 94.97%, respectively. Therefore, according to the Data Envelopment Analysis, the technical efficiency in conventional olive farms is less than in the organic ones. When the farms have been evaluated one by one in the light of the total potential improvement values, inputs and outputs, improvement is needed in all values.

scholarly journals On the evalution of Brazilian landline telephone services companies

2002 ◽  
Vol 22 (2) ◽  
pp. 231-246 ◽  
Author(s):  
José Virgílio Guedes de Avellar ◽  
Alexandre Olympio Dower Polezzi ◽  
Armando Zeferino Milioni
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Data Envelopment ◽  
Efficiency Improvement ◽  
Telephone Service ◽  
National Agency ◽  
Service Companies ◽  
Input And Output ◽  
Using Data ◽  
Landline Telephone

In this work we investigate the relative efficiency of 34 Brazilian Landline Telephone Service companies using Data Envelopment Analysis with weight constraints in the input and output variables. We formulate two different models that take into account the performance of the companies with respect to the criteria defined by Brazilian National Agency of Telecommunications (ANATEL). We also illustrate the potential of efficiency improvement through the simulation of corporate Merger.

Chance-constrained data envelopment analysis modeling with random-rough data

2018 ◽  
Vol 52 (1) ◽  
pp. 259-284 ◽  
Author(s):  
Rashed Khanjani Shiraz ◽  
Madjid Tavana ◽  
Debora Di Caprio
Keyword(s):  
Data Envelopment Analysis ◽  
Deterministic Model ◽  
Equivalent Model ◽  
Management Tool ◽  
Data Envelopment ◽  
Output Data ◽  
Quadratic Constraints ◽  
Dea Model ◽  
Deterministic Equivalent ◽  
Input And Output

Data envelopment analysis (DEA) is a useful management tool for measuring the relative efficiency of decision making units (DMUs) which consumes multiple inputs to produce multiple outputs. Although precise input and output data are fundamentally indispensable in classical DEA models, real-world problems often involve random and/or rough input and output data. We present a chance-constrained DEA model with random and rough (random-rough) input and output data and propose a deterministic equivalent model with quadratic constraints to solve the model. The main contributions of this paper are fourfold: (3.1) we propose a DEA model for problems characterized by random-rough variables; (3.2) we transform the proposed chance-constrained model with random-rough variables into a deterministic equivalent non-linear form that could be simplified as a deterministic model with quadratic constraints; (3.3) we perform sensitivity analysis to investigate the stability and robustness of the proposed model; and (3.4) we use a numerical example to demonstrate the feasibility and richness of the obtained solutions.

scholarly journals A FUZZY DATA ENVELOPMENT ANALYSIS FOR CLUSTERING OPERATING UNITS WITH IMPRECISE DATA

2013 ◽  
Vol 21 (01) ◽  
pp. 29-54 ◽  
Author(s):  
SABER SAATI ◽  
ADEL HATAMI-MARBINI ◽  
MADJID TAVANA ◽  
PER J. AGRELL
Keyword(s):  
Data Envelopment Analysis ◽  
Parametric Method ◽  
Data Envelopment ◽  
Output Data ◽  
Fuzzy Environment ◽  
Input And Output ◽  
Fuzzy Data Envelopment Analysis ◽  
Human Decision ◽  
Fuzzy Dea ◽  
Operating Units

Data envelopment analysis (DEA) is a non-parametric method for measuring the efficiency of peer operating units that employ multiple inputs to produce multiple outputs. Several DEA methods have been proposed for clustering operating units. However, to the best of our knowledge, the existing methods in the literature do not simultaneously consider the priority between the clusters (classes) and the priority between the operating units in each cluster. Moreover, while crisp input and output data are indispensable in traditional DEA, real-world production processes may involve imprecise or ambiguous input and output data. Fuzzy set theory has been widely used to formalize and represent the impreciseness and ambiguity inherent in human decision-making. In this paper, we propose a new fuzzy DEA method for clustering operating units in a fuzzy environment by considering the priority between the clusters and the priority between the operating units in each cluster simultaneously. A numerical example and a case study for the Jet Ski purchasing decision by the Florida Border Patrol are presented to illustrate the efficacy and the applicability of the proposed method.

The Assessment of Outsourcing IT Services using DEA Technique

2016 ◽  
Vol 7 (1) ◽  
pp. 45-57
Author(s):  
Mohammad Amin Zare ◽  
Mohammad Taghi Taghavi Fard ◽  
Payam Hanafizadeh
Keyword(s):  
Decision Making ◽  
Information Technology ◽  
Data Envelopment Analysis ◽  
It Outsourcing ◽  
Data Envelopment ◽  
Efficiency Improvement ◽  
Research Centers ◽  
It Services ◽  
Input And Output ◽  
Decision Making Units

This article proposes a model to make an assessment of efficiency in Information Technology (IT) outsourcing in research centers through data envelopment analysis (DEA). In this research input and output variables of DEA model for assessment of IT outsourcing efficiency distinguished. The decision-making units (DMUs) include 36 research centers in Iran. Expenses and capabilities of contractors represent the inputs and the satisfaction of users, risks, and quality constitute the outputs. In order to calculate the input and output values, a questionnaire has been conducted to DMUs. Afterwards, BCC model has facilitated the calculation of the efficiency of the DMUs and classifies efficient and inefficient units. In addition, Anderson Peterson's model is used for ranking efficient DMUs. This research has brought us to the conclusion that the variables of risk and quality account for the biggest shares in efficiency improvement of non-efficient DMUs.

scholarly journals The basic solution ellipsoid method approach for the efficiency measurement problems

2016 ◽  
Vol 57 ◽  
Author(s):  
Eligijus Laurinavičius ◽  
Daiva Rimkuvienė ◽  
Aurelija Sakalauskaitė
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Data Envelopment Analysis ◽  
Basic Solution ◽  
Data Envelopment ◽  
Efficiency Evaluation ◽  
Parametric Approach ◽  
Ellipsoid Method ◽  
Method Approach ◽  
Decision Making Units

The efficiency is a measure of a performance of a decision making units (DMUs can be a firm, a person, an organization). The data envelopment analysis (DEA) is a datadriven non-parametric approach for measuring the efficiency of a set of DMUs. The DEA is a linear programming (LP) based technique which deals with the basic models (CCR, BCC, SBM, additive) of the efficiency evaluation. This paper presents basic solution ellipsoid method approach associated with some problems of initial basic solution and the steps of it.

scholarly journals Efficiency Distribution Analysis with Data Envelopment Analysis (DEA) Approach Fertilizer

Tibuana ◽  
2021 ◽  
Vol 4 (02) ◽  
pp. 91-98
Author(s):  
Titiek Koesdijati ◽  
Andarmadi Jati Abdhi Wasesa
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Environmental Changes ◽  
Distribution Channels ◽  
Data Envelopment ◽  
Distribution Analysis ◽  
Output Data ◽  
Input And Output ◽  
Level Of Use ◽  
Output Efficiency

Distribution channels have an important meaning for achieving company success in the field of marketing so that company management is required to always be responsive and able to adapt to environmental changes. Input and output data processing is done by giving weights to the input and output using the DEA CCR primal model by maximizing the input-oriented-based objective function. The results of processing the efficiency scale show the relative efficiency level of the scale of each DMU in the company. The efficiency scale is obtained through the formulation of the DEA CCR primal model between each DMU input and output. If the DMU gets an input and output efficiency value of less than 100%, then the DMU is said to be relatively inefficient. Meanwhile, if the efficient value is equal to 100%, then the DMU is said to be relatively efficient. Of the 5 distribution cities, Sidoarjo, PaluKendari, Bandung and Lamongan which were analyzed, there were 2 cities that were inefficient or experiencing waste in their input and output variables, so the company needed to reorganize the level of use of inputs and outputs it achieved and utilize them optimally to get output that is optimal. targeted.

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