Stochastic ranking and dominance in DEA

Davtalab-Olyaie, Mostafa; Asgharian, Masoud; Nia, Vahid Partovi

doi:10.1016/j.ijpe.2019.04.004

Cited by 13 publications

(6 citation statements)

References 40 publications

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“…After that, modeling was enhanced by some researchers such as K C , Olesen and Petersen (1995), Cooper et al (2002). Recently, many researchers have tried to extend the DEA models with stochastic data in various aspects, like Birandom data (Tavana et al (2014)); Cost-efficiency (Khanjani Shiraz et al (2016)); Ranking DMUs (Davtalab-Olyaie et al (2019), Khodadadipour et al (2021)); Fuzzy and stochastic data (Tavana et al (2013), Tavassoli et al (2020), Peykani et al (2021)); Undesirable data (Zha et al (2016), Chen et al (2017)); Network structure (Z Zhou et al (2017), Farzipoor Saen (2018), Zhongbao Zhou et al (2021)).…”

Section: Stochastic Dea Modelsmentioning

confidence: 99%

Maintenance groups evaluation under uncertainties: a novel stochastic free disposal hull in the presence of lognormally distributed data

Izadikhah¹,

Dibachi²

2023

RAIRO-Oper. Res.

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Maintenance groups play an essential role in the successful operation of large companies and factories. Additionally, data envelopment analysis (DEA) is known as a valuable tool for monitoring the performance of maintenance groups. Especially, in contrast to the conventional DEA models that impose the convexity assumption into the technology, the free disposal hull (FDH) model provides a method for assessing the efficiency without the assumption of convexity and can be considered a valuable tool for determining one of the observed groups as the benchmark for each maintenance group. Meanwhile, because of the stochastic structure of data with lognormal distribution in the maintenance groups, this paper extends the FDH model in stochastic data with the lognormal distribution. Moreover, the method’s capabilities are confirmed based on some theorems, and a simulation study that illustrated the properties of the developed procedure is also performed. The developed methodology is applied to assess the performance of 21 maintenance groups of AZCO under uncertainty conditions.

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Section: Stochastic Dea Modelsmentioning

confidence: 99%

Maintenance groups evaluation under uncertainties: a novel stochastic free disposal hull in the presence of lognormally distributed data

Izadikhah¹,

Dibachi²

2023

RAIRO-Oper. Res.

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“…Tavassoli et al (2020) evaluated 25 Iran Khodro companies in Iran; they used fuzzy models with random data. The presentation of two ranking methods for SDEA can be seen in Davtalab-Olyaie et al (2019). Ghofran et al (2021) used bi-objective multiple criteria DEA models with random data to rank DMUs and then examined 17 power distribution units in Iran.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Sengupta (1982, 1987); Cooper et al (1996, 2002); Bruni et al (2009), Udhayakumar et al (2011); Branda and Kopa (2016); Kao and Liu (2009), Kao and Liu (2019); Tavassoli et al (2020), Davtalab-Olyaie et al (2019); Ghofran et al (2021); and Khodadadipour et al (2021).…”

Section: Introductionmentioning

confidence: 99%

“…In the third case, the economic system that DMUs are operating is also a cause of uncertainty; for example, there can be fluctuations in costs and profits arising from changes in the relationship between supply and demand in the market. Some studies in this field are as follows: Sengupta (1982Sengupta ( , 1987; Cooper et al (1996Cooper et al ( , 2002; Bruni et al (2009), Udhayakumar et al (2011); Branda and Kopa (2016); Kao and Liu (2009), Kao and Liu (2019); Tavassoli et al (2020), Davtalab-Olyaie et al (2019); Ghofran et al (2021); and Khodadadipour et al (2021).…”

Section: Introductionmentioning

confidence: 99%

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Stochastic network DEA-R models for two-stage systems

Ostovan

Mozaffari

Gerami

et al. 2022

JM2

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Purpose This paper aims to present two-stage network models in the presence of stochastic ratio data. Design/methodology/approach Black-box, free-link and fix-link techniques are used to apply the internal relations of the two-stage network. A deterministic linear programming model is derived from a stochastic two-stage network data envelopment analysis (DEA) model by assuming that some basic stochastic elements are related to the inputs, outputs and intermediate products. The linkages between the overall process and the two subprocesses are proposed. The authors obtain the relation between the efficiency scores obtained from the stochastic two stage network DEA-ratio considering three different strategies involving black box, free-link and fix-link. The authors applied their proposed approach to 11 airlines in Iran. Findings In most of the scenarios, when alpha in particular takes any value between 0.1 and 0.4, three models from Charnes, Cooper, and Rhodes (1978), free-link and fix-link generate similar efficiency scores for the decision-making units (DMUs), While a relatively higher degree of variations in efficiency scores among the DMUs is generated when the alpha takes the value of 0.5. Comparing the results when the alpha takes the value of 0.1–0.4, the DMUs have the same ranking in terms of their efficiency scores. Originality/value The authors innovatively propose a deterministic linear programming model, and to the best of the authors’ knowledge, for the first time, the internal relationships of a two-stage network are analyzed by different techniques. The comparison of the results would be able to provide insights from both the policy perspective as well as the methodological perspective.

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“…There are a couple of researches in the area of stochastic DEA (SDEA) (e.g. Wu and Lee, 2010; Tavana et al , 2015; El-Demerdash Basma et al , 2016; Zhou et al , 2017; Davtalab-Olyaie et al , 2019; Tavassoli et al , 2020). On the other hand, some researchers have developed DEA models in the presence of zero data (e.g.…”

Section: Introductionmentioning

confidence: 99%

Developing a new super-efficiency DEA model in the presence of both zero data and stochastic data: a case study in the Iranian airline industry

Tavassoli

Fathi

Saen

2020

BIJ

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PurposeThe purpose of this study is to propose a novel super-efficiency DEA model to appraise the relative efficiency of DMUs with zero data and stochastic data. Our model can work with both variable returns to scale (VRS) and constant returns to scale (CRS).Design/methodology/approachThis study proposes a new stochastic super-efficiency DEA (SSDEA) model to assess the performance of airlines with stochastic and zero inputs and outputs.FindingsThis paper proposes a new analysis and contribution to the knowledge of efficiency assessment with stochastic super-efficiency DEA model by (1) using input saving and output surplus index for efficient DMUs to get the optimal solution; (2) obtaining efficiency scores from the proposed model that are equivalent to original stochastic super-efficiency model when feasible solutions exist. A case study is given to illustrate the applicability of our proposed model. Also, poor performance reasons are identified to improve the performance of inefficient airlines.Originality/valueFor the first time, a new SSDEA model for ranking DMUs is proposed. The introduced model produces a feasible solution when dealing with zero input or output. This paper applies the input saving and output surplus concept to rectify the infeasibility problem in the stochastic DEA model.

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Stochastic ranking and dominance in DEA

Cited by 13 publications

References 40 publications

Maintenance groups evaluation under uncertainties: a novel stochastic free disposal hull in the presence of lognormally distributed data

Maintenance groups evaluation under uncertainties: a novel stochastic free disposal hull in the presence of lognormally distributed data

Stochastic network DEA-R models for two-stage systems

Developing a new super-efficiency DEA model in the presence of both zero data and stochastic data: a case study in the Iranian airline industry

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