Efficiency improvement of decision making units: a new data envelopment analysis model

2015 ◽  
Vol 7 (6) ◽  
pp. 720 ◽  
Author(s):  
Sahar Khoshfetrat ◽  
Masoud Rahiminezhad Galankashi
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Efficiency Improvement ◽  
Analysis Model ◽  
Decision Making Units

scholarly journals Designing an Intuitionistic Fuzzy Network Data Envelopment Analysis Model for Efficiency Evaluation of Decision-Making Units with Two-Stage Structures

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Nafiseh Javaherian ◽  
Ali Hamzehee ◽  
Hossein Sayyadi Tooranloo
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Two Stage ◽  
Intuitionistic Fuzzy Numbers ◽  
Intuitionistic Fuzzy ◽  
Dea Models ◽  
Decision Making Units

Data envelopment analysis (DEA) is a powerful tool for evaluating the efficiency of decision-making units for ranking and comparison purposes and to differentiate efficient and inefficient units. Classic DEA models are ill-suited for the problems where decision-making units consist of multiple stages with intermediate products and those where inputs and outputs are imprecise or nondeterministic, which is not uncommon in the real world. This paper presents a new DEA model for evaluating the efficiency of decision-making units with two-stage structures and triangular intuitionistic fuzzy data. The paper first introduces two-stage DEA models, then explains how these models can be modified with intuitionistic fuzzy coefficients, and finally describes how arithmetic operators for intuitionistic fuzzy numbers can be used for a conversion into crisp two-stage structures. In the end, the proposed method is used to solve an illustrative numerical example.

Use Shapley value for increasing power distinguish of data envelopment analysis model: An application for estimating environmental efficiency of industrial producers in Iran

2019 ◽  
Vol 31 (4) ◽  
pp. 656-675
Author(s):  
Hashem Omrani ◽  
Mohaddeseh Amini ◽  
Mahdieh Babaei ◽  
Khatereh Shafaat
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Shapley Value ◽  
Environmental Efficiency ◽  
Data Envelopment Analysis Model ◽  
Game Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Proposed Model ◽  
Decision Making Units

Data envelopment analysis is a linear programming model for estimating the efficiency of decision making units (DMUs). Data envelopment analysis model has two major advantages: it does not need the explicit form of production function for estimating the efficiency scores of decision making units and also, it allows decision making units to choose the weights of inputs and outputs to reach the estimated efficient frontier. In several cases, the distinguish power of data envelopment analysis model is weak and it is unable to rank decision making units, entirely. The goal of this study is to provide a better methodology to fully rank all the decision making units. First, the efficiency scores of all decision making units are generated using the cross-efficiency data envelopment analysis model and then, the cooperative game theory approach is applied to produce a fully fair ranking of decision making units. The DEA-Game model calculates the Shapley value for each coalition of decision making units and the final ranking is relied on common weights. These fair common weights are found using the Shapley value to rank decision making units, completely. To illustrate the capability of the proposed model, the industrial producers in the provinces of Iran are evaluated. First, the suitable indicators are defined and then, the actual environmental data for year 2013 is gathered. Finally, the proposed model is applied to fully rank the industrial producers in provinces of Iran from environmental perspective. The results show that the DEA-Game model can rank provinces, entirely. Based on the results, the industrial producers in big provinces such as Tehran, Fars and Yazd have undesirable performance in environmental efficiency.

scholarly journals A knowledge system proposal with weighted goal programming approach for multi-criteria dea model and an application

2021 ◽  
Vol 12 (2) ◽  
pp. 422-438
Author(s):  
Tugba Polat ◽  
Safak Kiris
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Goal Programming ◽  
Evaluation Process ◽  
Knowledge System ◽  
Programming Approach ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Weighted Goal Programming

In today's competitive environment, enterprises should use their resources correctly; they should continuously improve themselves and work efficiently. It is important to evaluate the performances of the units under the same conditions in enterprises according to each other, to see the current situations and to determine appropriate improvements in necessary points. One of the commonly used approaches to performance evaluation is Data Envelopment Analysis. Many approaches have been developed for the Data Envelopment Analysis model, and Goal programming using in multi-objective decision making solutions approaches is one of them. Goal Programming gives decision-makers the opportunity to evaluate many objectives together in the decision-making process. In this study, classical Data Envelopment Analysis and weighted goal programming approach for multi-criteria data envelopment analysis model was applied in the evaluation process of the projects worked in an automotive supplier industry. A knowledge system has also been proposed in order to evaluate the effectiveness of the projects periodically and to include new projects or conditions into the evaluation.

scholarly journals A Revised Inverse Data Envelopment Analysis Model Based on Radial Models

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 803
Author(s):  
Xiaoyin Hu ◽  
Jianshu Li ◽  
Xiaoya Li ◽  
Jinchuan Cui
Keyword(s):  
Data Envelopment Analysis ◽  
Efficiency Index ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Numerical Examples ◽  
Wide Range ◽  
Dea Models ◽  
Overall Efficiency ◽  
Decision Making Units

In recent years, there has been an increasing interest in applying inverse data envelopment analysis (DEA) to a wide range of disciplines, and most applications have adopted radial-based inverse DEA models. However, results given by existing radial based inverse DEA models can be unreliable as they neglect slacks while evaluating decision-making units’ (DMUs) overall efficiency level, whereas classic radial DEA models measure the efficiency level through not only radial efficiency index but also slacks. This paper points out these disadvantages with a counterexample, where current inverse DEA models give results that outputs shall increase when inputs decrease. We show that these unreasonable results are the consequence of existing inverse DEA models’ failure in preserving DMU’s efficiency level. To rectify this problem, we propose a revised model for the situation where the investigated DMU has no slacks. Compared to existing radial inverse DEA models, our revised model can preserve radial efficiency index as well as eliminating all slacks, thus fulfilling the requirement of efficiency level invariant. Numerical examples are provided to illustrate the validity and limitations of the revised model.

Evaluation of Ground Thermal Infrared Camouflage Based on Dynamic DEA Model

2014 ◽  
Vol 886 ◽  
pp. 598-602
Author(s):  
Ming Xu Sui ◽  
Xu Liang Lü ◽  
Ling Li ◽  
Xiao Di Weng ◽  
Xiao Peng Li
Keyword(s):  
Decision Making ◽  
Thermal Infrared ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Effect Factors ◽  
The Index System ◽  
Camouflage Patterns ◽  
Decision Making Units ◽  
Infrared Camouflage

Thermal infrared camouflage refers to a series of camouflage patterns for coping with modern thermal infrared reconnaissance. In order to solve the problems that the subjectivity of traditional evaluation methods on ground thermal infrared camouflage and correlation constraint is not easy to test and so on. The effect factors of thermal infrared camouflage were analyzed, the index system of model of ground thermal infrared camouflage was established, and based on it, the dynamic DEA (data envelopment analysis) model was applied to evaluate the ground thermal infrared camouflage. The example shows that the method in this paper can be applied to compare the DMUs (decision making units) efficiently and it can select the best DMU.

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.

Efficiency decomposition in parallel production systems with shared sources on interval data: An illustration of Iranian Banks

2014 ◽  
Vol 07 (05) ◽  
pp. 1450059
Author(s):  
Sohrab Kordrostami
Keyword(s):  
Decision Making ◽  
Production Systems ◽  
Interval Data ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Bounded Interval ◽  
Real World Applications ◽  
Efficiency Decomposition ◽  
Decision Making Units

In real-world applications, some systems are composed of independent production units that use different inputs to produce outputs. The conventional data envelopment analysis model measures the relative efficiencies of a set of decision-making units with exact values of both inputs and outputs. In this paper, we propose an approach to assess parallel production systems with shared sources and bounded interval data, and also we provide a model that focuses on calculating the efficiency of the whole of a system along with the efficiencies of its components.

scholarly journals Centralized Resource Allocation and Target Setting Based on Data Envelopment Analysis Model

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Tiantan Yang ◽  
Pingchun Wang ◽  
Feng Li
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
Efficient Frontier ◽  
Total Output ◽  
Data Envelopment Analysis Model ◽  
Data Envelopment ◽  
Analysis Model ◽  
Planning Period ◽  
Target Setting

This paper aims to develop a data envelopment analysis (DEA) based model for allocating input resources and deciding output targets in organizations with a centralized decision-making environment, for example, banks, police stations, and supermarket chains. The central decision-maker has an interest in maximizing the total output production and at the same time minimizing the total input consumption. Traditionally, all decision-making units (DMUs) can be easily projected to the efficient frontier, which is a mathematical feasibility; however, it does not guarantee the managerial feasibility during the planning period. In this paper, we will take potential limitations of input-output changes into account by building a difficulty coefficient matrix of modifying their production in the current production possibility set so that the solution guarantees managerial feasibilities. Three objectives, namely, maximizing aggregated outputs, minimizing the consumption of input resources, and minimizing the total difficulty coefficient, are proposed and incorporated into the formation of resource allocation and target setting scheme. Building on this, we combine DEA and multiobjective programming to solve the resource allocation and target setting problem. In the end, we apply our proposed approach to a real-world problem of sixteen chain hotels to illustrate the efficacy and usefulness of the proposed approach.

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