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.

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.

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 Implementasi Model CCR Data Envelopment Analysis (DEA) Pada Pengukuran Efisiensi Keuangan Daerah

2016 ◽  
Vol 6 (1) ◽  
pp. 76 ◽  
Author(s):  
LM Fajar Israwan ◽  
Bayu Surarso ◽  
Farikhin Frikhin
Keyword(s):  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Programming Approach ◽  
Data Envelopment ◽  
Work Unit ◽  
Input And Output ◽  
Regional Budget ◽  
Budget Control ◽  
Regional Work ◽  
Decision Making Units

Regional budget control system is implemented through an audit and evaluation to ensure that its implementation is in accordance with the plan that it can be efficiently and effectively used. Regional budget efficiency measurement then aims to measure the efficienty of budget use of each Regional Work Unit (SKPD) and to optimalize its use. The efficiency of Regional Work Unit is measured using CCR Data Envelopment Analysis (DEA) model with one input variable and eight output variables, in which this CCR DEA applies Linear Programming approach and evaluates relative efficiency of Decision Making Units (DMUs). The sample was in a total of sixteen DMUs. The result revealed that seven DMUs were efficient, in which their reference set was then used to optimalize the input and output variables of other inefficient DMUs. This result was validated through paired sample t-test, proving to meet the hypothesis of Ho -2,042 ≤ tcount ≤ 2,042 showing that CCR DEA can be used as a method to measure regional budget efficiency with accurate results.

scholarly journals Increasing Sustainability of Logistic Networks by Reducing Product Losses: A Network DEA Approach

2018 ◽  
Vol 2018 ◽  
pp. 1-21
Author(s):  
S. Lozano ◽  
B. Adenso-Díaz
Keyword(s):  
Data Envelopment Analysis ◽  
Experimental Design ◽  
Relative Efficiency ◽  
Loss Factor ◽  
Network Data ◽  
Perishable Products ◽  
Data Envelopment ◽  
Network Dea ◽  
Input And Output ◽  
Operating Points

This paper considers a multiproduct supply network, in which losses (e.g., spoilage of perishable products) can occur at either the nodes or the arcs. Using observed data, a Network Data Envelopment Analysis (NDEA) approach is proposed to assess the efficiency of the product flows in varying periods. Losses occur in each process as the observed output flows are lower than the observed input flows. The proposed NDEA model computes, within the NDEA technology, input and output targets for each process. The target operating points correspond to the minimum losses attainable using the best observed practice. The efficiency scores are computed comparing the observed losses with the minimum feasible losses. In addition to computing relative efficiency scores, an overall loss factor for each product and each node and link can be determined, both for the observed data and for the computed targets. A detailed illustration and an experimental design are used to study and validate the proposed approach. The results indicate that the proposed approach can identify and remove the inefficiencies in the observed data and that the potential spoilage reduction increases with the variability in the losses observed in the different periods.

scholarly journals Study of the Impact of Environmental Pollution on Efficiency and Sustainable Development using Data Envelopment Analysis

MATEMATIKA ◽  
2020 ◽  
Vol 36 (2) ◽  
pp. 157-179
Author(s):  
Hamid Hosseini ◽  
Sara Fanati Rashidi ◽  
Ali Hamzehee
Keyword(s):  
Economic Growth ◽  
Data Envelopment Analysis ◽  
Environmental Changes ◽  
Critical Role ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Input And Output ◽  
Decision Making Unit ◽  
Using Data ◽  
The Impact

Environmental changes resulting from industrial activity have been occurring for many years, and with the increasing production of greenhouse gases and other pollutants, these changes have played a critical role in global warming. Nowadays, all countries have become aware of the great importance of attention to the environment alongside economic growth. Therefore, they are all after solutions that would allow maximum economic growth with minimum harm to the environment. In the present study, the environmental efficiency of a given system is evaluated using data envelopment analysis (DEA). For this purpose, the economic and environmental dimensions are taken into consideration for each decision-making unit (DMU), with the condition of having undesirable outputs in the environmental dimension. Then, using the concept of “order of efficiency”, an enhanced DEA method is proposed based on weak and strong disposability axioms, which can be used to compare and rank units with undesirable outputs. Next, the capabilities of the proposed approach are demonstrated through an example involving various industries in Iran. Enhanced DEA not only takes more comprehensive input and output sets into account but also monitors the units based on the principles of sustainability.

Relative Efficiency of Decision Making Units Producing Both Desirable and Undesirable Outputs: A Case of Textile Processing Units in Pakistan.

2011 ◽  
Vol 50 (4II) ◽  
pp. 685-698
Author(s):  
Samina Khalil
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Relative Efficiency ◽  
Value Added ◽  
Data Envelopment ◽  
Undesirable Outputs ◽  
Textile Processing ◽  
Decision Making Unit ◽  
Desirable And Undesirable Outputs ◽  
Decision Making Units

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

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