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.

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 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.

scholarly journals New Approach in Fixed Resource Allocation and Target Setting Using Data Envelopment Analysis with Common Set of Weights

Complexity ◽  
2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Marzieh Ghasemi ◽  
Mohammad Reza Mozaffari ◽  
Farhad Hosseinzadeh Lotfi ◽  
Mohsen Rostamy malkhalifeh ◽  
Mohammad Hasan Behzadi
Keyword(s):  
Decision Making ◽  
Resource Allocation ◽  
Data Envelopment Analysis ◽  
Data Envelopment ◽  
Target Setting ◽  
New Approach ◽  
Common Set Of Weights ◽  
Programming Techniques ◽  
Using Data ◽  
Decision Making Units

One of the mathematical programming techniques is data envelopment analysis (DEA), which is used for evaluating the efficiency of a set of similar decision-making units (DMUs). Fixed resource allocation and target setting with the help of DEA is a subject that has gained much attention from researchers. A new model was proposed by determining a common set of weights (CSW). All DMUs were involved with the aim of achieving higher efficiency in every DMU after the procedure. The minimum resources and targets allocated to each DMU were commensurate to the efficiency of that DMU and the share of DMU in the input resources and the output productions. To examine the proposed method, other methods in the DEA literature were examined as well, and then, the efficiency of the method was demonstrated through a 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.

Evaluating after-sales service units by developing inverse network data envelopment analysis model

2019 ◽  
Vol 27 (2) ◽  
pp. 695-707 ◽  
Author(s):  
Reza Farzipoor Saen ◽  
Seyed Shahrooz Seyedi Hosseini Nia
Keyword(s):  
Decision Making ◽  
Data Envelopment Analysis ◽  
Efficiency Score ◽  
Data Envelopment Analysis Model ◽  
Network Data ◽  
Data Envelopment ◽  
Analysis Model ◽  
Content Type ◽  
Network Data Envelopment Analysis ◽  
Decision Making Unit

Purpose The purpose of this paper is to develop an inverse network data envelopment analysis (INDEA) model to solve resource allocation problems. Design/methodology/approach The authors estimate inputs’ variations based on outputs so that the efficiencies of decision-making unit under evaluation (DMUo) and other decision-making units (DMUs) are constant. Findings The new INDEA model is developed to allocate resources such that inputs are not increased while efficiency scores of all DMUs remain constant. Furthermore, the authors obtain new combinations of inputs and outputs, together with a growth in efficiency score of DMUo such that efficiency scores of other DMUs are not changed. A case study is provided. Originality/value This paper proposes INDEA model to estimate inputs (outputs) without changing efficiency scores of DMUs.

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