Using Augmented DEA to Calculate Efficiency Scores of Organizational Resources

Rezaie, Kamran; Haeri, Abdorrahman; Amalnick, Mohsen-Sadegh; Ansarinejad, Ayyub

doi:10.1109/uksim.2011.76

Cited by 3 publications

(5 citation statements)

References 12 publications

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“…Some of the previous research used augmented DEA as a performance evaluation tool for different DMUs. For instance, Rezaie et al [2] used augmented DEA to improve discriminatory power of DEA to can rank organizational resources properly. They introduced a virtual DMU high outputs and low inputs.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The DEA method has several applications consists of ranking efficiency scores (Rezaie et al [2]; Haeri et al [3]) and providing improvement plan (Haeri and Rezaie [4]; Haeri and Ghousi [5]; Rezaee et al [6]). Over the recent years, DEA as a powerful technique for performance evaluation has drawn great attention, while beside its popularity, the basic type of DEA model has some drawbacks.…”

Section: Introductionmentioning

confidence: 99%

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A heuristic method for choosing 'virtual best' DMUs to enhance discrimination power of augmented DEA model

Rezaei

Haeri

2019

Scientia Iranica

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Despite its intrinsic advantageous features as a tool for increasing discrimination power of the basic DEA (data envelopment analysis) model, augmented DEA has two main drawbacks including the presence of unrealistic efficiency scores and the presence of great distance between its efficiency scores and scores obtained by primary model. In this regard, this paper extends a heuristic method for dealing with both issues and improving the power of augmented DEA model in performance evaluation. Since different virtual DMUs lead to different results for ranking, the hierarchical clustering algorithm is applied in this study to select the best virtual DMUs in order to reduce the possibility of having inappropriate efficiency scores. Finally, to demonstrate the superiority of the proposed approach over previous approaches in literature, two numerical examples are provided.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A heuristic method for choosing 'virtual best' DMUs to enhance discrimination power of augmented DEA model

Rezaei

Haeri

2019

Scientia Iranica

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“…The method for improving efficiency of DMU4 is as follows: That means the investment of DMU4 can be adjust to (38, 59, 11, 3), the output can be raised to (7,93).…”

Section: Dmu1mentioning

confidence: 99%

“…The basic idea of DEA is to each unit to be assessed as a DMU, again by many DMU constitute the group evaluation, through the comprehensive analysis of input and output ratio, DMU each input and output index weights for variable operations, determine the efficient production surface, and according to each DMU and efficient surface distance state to determine the DMU is DEA efficient, and gives various meanings of evaluation index. DEA is widely used in production [2] [3], finance [4] [5], business [6] [7], research & development [8] and other fields [9] [10]. The better results have been obtained by providing a scientific basis for decision makers.…”

Section: Introductionmentioning

confidence: 99%

An IDEA-BCC Model for Performance Management of Scientific Research

Shang¹

2016

Proceedings of the 2016 6th International Conference on Machinery, Materials, Environment, Biotechnology and Computer

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Abstract. Aiming at the practical problems in the performance management of scientific research, an IDEA-BCC model based on the combination of kernel function mapping and the BCC model in the traditional DEA method is proposed in this paper. Taking the annual research input and output data of the scientific research institution as an example, the IDEA-BCC application model is established and the validity of the method is illustrated by the experimental data.

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“…The analyzed items must have homogeneity, hence we need to add Zweights so that the parameters can be pulled together to look at the same level. And this method use DMU curve to determine the smaller gap to closer the optimal solution [11] [12].…”

Section: B Data Envelopment Analysismentioning

confidence: 99%

A fair cloud resource allocation using data envelopment analysis

Cho

Chao

et al. 2014

10th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness

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Internet technology is advancing with each passing day, the user's demand is also increasing. Of course the users will more concern to quality of service. The vendors must find out a win win method of resource allocation to meet users and itself. Therefore, the resource allocation of cloud computing has become one of hottest topics. In literatures, some researchers have proposed resource allocation methods which include allocation of virtual machines and service classification, etc. However, these methods are based on subjective observations that lead to the overall cloud architecture becomes imbalance. In order to prevent such situation happened, we use the Data Envelopment Analysis (DEA) to solve the imbalance problem. In this paper, our analysis is start from the user's requests, and use the DEA to evaluate the whole cloud parameters. Then we can find out the resource allocation policy which is the most suitable between the users and vendors.

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Using Augmented DEA to Calculate Efficiency Scores of Organizational Resources

Cited by 3 publications

References 12 publications

A heuristic method for choosing 'virtual best' DMUs to enhance discrimination power of augmented DEA model

A heuristic method for choosing 'virtual best' DMUs to enhance discrimination power of augmented DEA model

An IDEA-BCC Model for Performance Management of Scientific Research

A fair cloud resource allocation using data envelopment analysis

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