Ranking Intervals and Dominance Relations for Ratio-Based Efficiency Analysis

Salo, Ahti; Punkka, Antti

doi:10.1287/mnsc.1100.1265

Cited by 57 publications

(62 citation statements)

References 49 publications

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“…The best performers (or worst performers) based on our approach may not be the same as that of Salo and Punkka [3]'s approach. The red bar char in Figure 2 reports the DMUs' efficiency bounds when the two-stage structure is considered.…”

Section: Empirical Illustrationmentioning

confidence: 93%

“…. , ), Salo and Punkka [3] defined efficiency dominance between DMUs based on the efficiency scores of model (2).…”

Section: Efficiency Bounds By Salo and Punkka [3]mentioning

confidence: 99%

“…Salo and Punkka [3] proposed the following model to maximize and minimize the ratio through linear programming.…”

Section: Definitionmentioning

confidence: 99%

“…To overcome this problem, Salo and Punkka [3] have proposed a procedure to obtain the efficiency bounds by taking into account all possible weights (see also [4]). That is to say, the efficiency bounds show how the DMUs' efficiency ratios relate to each other for all feasible weights, rather than for those weights only for which the data envelopment analysis (DEA) efficiency score of some DMU is maximized.…”

Section: Introductionmentioning

confidence: 99%

“…In the next section, the procedure of efficiency bounds by Salo and Punkka [3] has been reviewed briefly. Then, in Section 3, a method is developed to obtain the efficiency bounds considering the two-stage production systems.…”

Section: Introductionmentioning

confidence: 99%

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Efficiency Bounds for Two-Stage Production Systems

Shi

2018

Mathematical Problems in Engineering

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Traditional data envelopment analysis (DEA) models find the most desirable weights for each decision-making unit (DMU) in order to estimate the highest efficiency score as possible. These efficiency scores are then used for ranking the DMUs. The main drawback is that the efficiency scores based on weights obtained from the standard DEA models ignore other feasible weights; this is due to the fact that DEA may have multiple solutions for each DMU. To overcome this problem, Salo and Punkka (2011) deemed each DMU as a "Black Box" and developed models to obtain the efficiency bounds for each DMU over sets of all its feasible weights. In many real world applications, there are DMUs that have a two-stage production system. In this paper, we extend the Salo and Punkka's (2011) model to a more common and practical case considering the two-stage production structure. The proposed approach calculates each DMU's efficiency bounds for the overall system as well as efficiency bounds for each subsystem/substage. An application for nonlife insurance companies has been discussed to illustrate the applicability of the proposed approach and show the usefulness of this method.

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Section: Empirical Illustrationmentioning

confidence: 93%

“…. , ), Salo and Punkka [3] defined efficiency dominance between DMUs based on the efficiency scores of model (2).…”

Section: Efficiency Bounds By Salo and Punkka [3]mentioning

confidence: 99%

“…Salo and Punkka [3] proposed the following model to maximize and minimize the ratio through linear programming.…”

Section: Definitionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Efficiency Bounds for Two-Stage Production Systems

Shi

2018

Mathematical Problems in Engineering

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Data Envelopment Analysis Based on Choquet Integral

Mao

Chen

2017

Int. J. Intell. Syst.

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Data envelopment analysis (DEA) is a widely used technique in decision making. The existing DEA models always assume that the inputs (or outputs) of decision-making units (DMUs) are independent with each other. However, there exist positive or negative interactions between inputs (or outputs) of DMUs. To reflect such interactions, Choquet integral is applied to DEA. Selfefficiency models based on Choquet integral are first established, which can obtain more efficiency values than the existing ones. Then, the idea is extended to the cross-efficiency models, including the game cross-efficiency models. The optimal analysis of DEA is further investigated based on regret theory. To estimate the ranking intervals of DMUs, several models are also established. It is founded that the models considering the interactions between inputs (or outputs) can obtain wider ranking intervals. C 2017 Wiley Periodicals, Inc.

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