Sensitivity analysis of inefficient units in data envelopment analysis

Jahanshahloo, G. R.; Lotfı, Farhad Hosseinzadeh; Shoja, N.; Abri, A. Gholam; Jelodar, M. Fallah; Firouzabadi, Kamran Jamali

doi:10.1016/j.mcm.2010.09.008

Cited by 21 publications

(4 citation statements)

References 18 publications

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“…According to [32], sensitivity analysis under DEA is carried out by determining the precise change region where the e ciency value of a certain ine cient DMU changes to a predetermined e ciency score. [33] uses the stability radius to demonstrate the sensitivity of returns to scale.…”

Section: Input -Output Targets For Ine Cient Handrmentioning

confidence: 99%

Super efficiency and sensitivity analysis of the Indian hotels and restaurants

Sharma,

Mogha

2024

OPSEARCH

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Over the course of COVID-19, the global growth of the hospitality and restaurant (H&Rs) sector has declined. During this di cult period, this sector's overall performance declined. As a result, this industry must adopt fresh approaches to seize the potential and overcome the obstacles at this pivotal moment. One of these di culties is guring out how to evaluate H&Rs' effectiveness using a variety of factors. This study evaluates the performance of 45 signi cant H&R businesses operating in India using the Data Envelopment Analysis (DEA) method.The Basic DEA models usually do not disclose the improvement in the capability of different DMUs as these models calculate only radial e ciency. In this paper, the New Slack Model (NSM) of DEA has been employed to examine the e ciency of the different 45 large-scale Indian Hotels and Restaurants (H&Rs). The NSM model cognate the input and output slacks straight away. In this study, four inputs: Capital employed, Gross xed assets, Current assets, and Operating costs, and two outputs: Operating income and Pro t before depreciation, interest, and tax (PBDIT) are considered. The data for the study has been collected from the Prowess database of the Centre for Monitoring Indian Economy (CMIE). The study indicates that only 65.58% of H&R are technically e cient which shows that some resources are unutilized and therefore there is a huge scope for an upswing. To validate the stability of results sensitivity analysis is also carried out. brought on by scale or size (scale ine ciency) and/or management techniques (pure technical ine ciency). In 1978, Charnes et al. created the fundamental DEA model, which was further expanded by [1]. Numerous theoretical extensions have been created based on these fundamental DEA models, including the Cone Ratio Model (Cooper et al. 1997), the Slack Adjusted Model [2], the Slack Based Model [3], and the New Slack Model [4], etc.Slacks are not taken into account by the fundamental CCR and BCC models, whereas the radial features of DEA are not present in the additive model or the SBM model. The NSM model, which meets the monotone decreasing property with regard to slacks, is applied in this study while keeping these constraints in mind. Additionally, it satis es all of the other radial DEA model features. All multipliers have become positive, according to the dual of the NSM model, meaning that all input and output factors have been properly accounted for in the performance evaluation of the DMUs. Additionally, it satis es all of the other features of radial DEA model.Rest of the paper is organized as follows: Section 2 elaborates the literature revie, section 3 explains about methodology applied, a description of data and variable used is provide in section 4 which is followed by the section 5 which contains result and discussion, Sensitivity analysis and super e ciency are described in section 6, which is followed by the conclusion.

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Section: Input -Output Targets For Ine Cient Handrmentioning

confidence: 99%

Super efficiency and sensitivity analysis of the Indian hotels and restaurants

Sharma,

Mogha

2024

OPSEARCH

View full text Add to dashboard Cite

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“…Definition 3. DMU o , the DMU under test, is efficient if and only if an optimum is attained with all slacks zero in Model (7).…”

Section: The Dea Additive Modelmentioning

confidence: 99%

“…Hladik [ 32 ] proposed stability analysis in linear programming and addressed the expansion of the maximum tolerance area. Jahanshahloo et al [ 7 ] obtained a stability region for inefficient DMUs. Their method was considered a new frontier with a performance score of α < 1 for a specific inefficient DMU that α defined as constant by the manager.…”

Section: Introductionmentioning

confidence: 99%

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Stability analysis with general fuzzy measure: An application to social security organizations

Arabjazi

Rostamy-Malkhalifeh²,

Lotfı³

et al. 2022

PLoS ONE

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An effective method for evaluating the efficiency of peer decision-making units (DMUs) is data envelope analysis (DEA). In engineering sciences and real-world management problems, uncertainty in input and output data always exists. To achieve reliable results, uncertainties must be taken into account. In this research, a General Fuzzy (GF) approach is designed to cope with uncertainty in the presence of fuzzy observations for categorizing and specifying stability radius and alterations ranges of efficient and inefficient DMUs, which is applicable to real-world decision-making problems. For this purpose, a DEA sensitivity analysis model is presented, which will be modeled by fuzzy sets. Then, by applying the General Fuzzy (GF) approach, the fuzzy DEA sensitivity analysis model is transformed into the equivalent crisp form of fuzzy chance constraints according to specific confidence levels. Finally, a numerical example and a case study of branches of the social security organization are presented to illustrate sensitivity and stability analysis in the presence of fuzzy data. The obtained results provide the input and output changes of the evaluated units according to the attitude and preference of the decision maker with different confidence levels so that the data changes in the fuzzy environment do not change the units’ classification from efficient to inefficient and vice versa.

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Are economically advanced countries more efficient in basic and applied research?

Holý

Šafr

2018

Cent Eur J Oper Res

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Sensitivity analysis of inefficient units in data envelopment analysis

Cited by 21 publications

References 18 publications

Super efficiency and sensitivity analysis of the Indian hotels and restaurants

Super efficiency and sensitivity analysis of the Indian hotels and restaurants

Stability analysis with general fuzzy measure: An application to social security organizations

Are economically advanced countries more efficient in basic and applied research?

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