On some methods for performance ranking and correspondence analysis in the DEA context

Tsou, Chi-Ming; Huang, Deng-Yuan

doi:10.1016/j.ejor.2009.09.010

Cited by 21 publications

(5 citation statements)

References 33 publications

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“…Other units that are located in a convex space (production capability set) are inefficient units (Banker et al , 1984). Inefficient units are rated by using basic DEA models with efficiency scores (between zero and one), however, units with efficiency scores of one are not rated (Tsou and Huang, 2010).…”

Section: Methodsmentioning

confidence: 99%

A new approach for ranking efficient DMUs with data envelopment analysis

Banihashemi

Khalilzadeh

2020

WJE

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Purpose Classical models of data envelopment analysis (DEA) calculate the efficiency of decision-making units do not differentiate between efficient units. The purpose of this paper is to present a new method for ranking efficient units and compare it with the other methods presented in this field. Design/methodology/approach In this paper, a new method is presented for ranking efficient units. To validate the proposed method, a real case, which was studied by Li et al. (2016) is examined and the rankings of the efficient units are compared with four other methods including the Andersen and Petersen’s super-efficiency, game theory and the concept of Shapley value and the technique for order of preference by similarity to ideal solution methods. Findings The results show that there is a high correlation between the rankings of efficient units obtained by the new proposed method and the other methods such as Andersen and Petersen’s super-efficiency, game theory and Shapley value methods. Originality/value The problem of ranking efficient units with the DEA method is an important issue for researchers. Extensive studies have been proposed to provide methods for ranking efficient units. This paper proposes a simple and fast method for ranking efficient units that achieves better results.

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Section: Methodsmentioning

confidence: 99%

A new approach for ranking efficient DMUs with data envelopment analysis

Banihashemi

Khalilzadeh

2020

WJE

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“…"DEA as a non-parametric approach is able to provide relative efficiency for a series of DMUs based on multiple inputs/outputs with no assumptions of production function" (Tsou & Huang, 2010). The DEA methodology calculates a measure of the relative efficiency of each DMU.…”

Section: Data Envelopment Analysismentioning

confidence: 99%

Measuring the Efficiency of Indian Real Estate Firms During the Pre- and Post-Demonetization Period by Adopting Data Envelopment Analysis

Prasad

2019

Baltic Journal of Real Estate Economics and Construction Management

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Indian real estate segment has been one of the utmost affected segments of economy contemplating the changes in economic policies. The Indian economy experienced a radical change as an outcome of demonetization and the consequences are perceived on the real estate segment. The current study has been proposed to evaluate the efficiency of Indian real estate firms by adopting the technique of data envelopment analysis during the pre- and post-period of demonetization. The aim of the research is to understand the effect of demonetization on the performance of the Indian real estate firms during the post-demonetization period compared to pre-demonetization period. Eight real estate firms have been considered for the analysis. The firms have been ranked on the basis of the efficiency score. It is evident from the results of the study that there is a significant difference between the ranks of the firms during the period of pre and post demonetization; and it can be elucidated that the demonetization has an impact on the performance of the firms.

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“…For an input matrix A∈R m×n , with rank r, r ≤ min(m, n), the SVD of A can be written in the form of [21]:…”

Section: Single Variable Integrationmentioning

confidence: 99%

Access for Performance of Transportation Planning and Operations: Case Study in Beijing Metropolitan Region

Wang

Zhang

Cao

et al. 2012

JART

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Considering the importance of maintaining effective performance at desired levels, the Transportation Adaptability Performance Index, as a weighted multi-criteria combination approach, is proposed to continuously identifying the performance of degradable transportation networks and making effective supplement, contrapuntal revision and intime adjustment of the program implementation process, in response to new requirements of the urban system. For the design of strategic and quantitative methodology, 50 variables belonging to 8 domains in 2 components are chosen as the original input inherently reflecting the various interests of involved stakeholders. Specifically, the paired comparison matrix of the domain is constructed by the analytic hierarchy process to weight the importance of each single variable. If the consistency of the matrix is acceptable, the domain weight in two components is determined directly through the singular value decomposition approach and while the consistency level is unacceptable, the significant element in the matrix is identified and revised until the consistency satisfies the constraint. The methodology is then applied to evaluate the performance of transportation networks in Beijing metropolitan region using the derived 2000~2010 data and the findings indicate that the hidden and potential problems could be quantitatively identified by this approach that can be used as a user-friendly tool for metropolitan planning organizations in assessing the effectiveness and efficiency of in-service infrastructures, updating plans, setting priorities and optimizing resource allocation for next step.

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On some methods for performance ranking and correspondence analysis in the DEA context

Cited by 21 publications

References 33 publications

A new approach for ranking efficient DMUs with data envelopment analysis

A new approach for ranking efficient DMUs with data envelopment analysis

Measuring the Efficiency of Indian Real Estate Firms During the Pre- and Post-Demonetization Period by Adopting Data Envelopment Analysis

Access for Performance of Transportation Planning and Operations: Case Study in Beijing Metropolitan Region

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