Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data

Jiang, Bao; Chi, Enxin; Li, Jian

doi:10.3390/math10132161

Cited by 2 publications

(4 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is where uncertainty modeling techniques, such as uncertainty theory, play a vital role. Uncertainty theory is a mathematical framework that deals with the modeling and quantification of uncertainty in various domains [ 81 , 82 , 83 , 84 , 85 , 86 ]. It provides concepts, methods, and techniques to represent, analyze, and reason with uncertain information.…”

Section: Uncertainty Theorymentioning

confidence: 99%

Performance Evaluation of Hospitals under Data Uncertainty: An Uncertain Common-Weights Data Envelopment Analysis

Peykani,

Pishvaee

2024

Healthcare

View full text Add to dashboard Cite

In the context of healthcare systems, the performance evaluation of hospitals plays a crucial role in assessing the quality of healthcare systems and facilitating informed decision-making processes. However, the presence of data uncertainty poses significant challenges to accurate performance measurement. This paper presents a novel uncertain common-weights data envelopment analysis (UCWDEA) approach for evaluating the performance of hospitals under uncertain environments. The proposed UCWDEA approach addresses the limitations of traditional data envelopment analysis (DEA) models by incorporating the uncertainty theory (UT) to model the inherent uncertainty in input and output data. Also, by utilizing a common set of weights (CSW) technique, the UCWDEA method provides a more robust and reliable assessment of hospital performance. The main advantages of the proposed UCWDEA approach can be succinctly summarized as follows. Firstly, it allows for the comparison of all hospitals on a consistent basis to calculate a realistic efficiency score, rather than an overly optimistic efficiency score. Secondly, the uncertain common-weights DEA approach exhibits linearity, enhancing its applicability. Thirdly, it possesses the capability to extend its utility under various other prevalent uncertainty distributions. Moreover, it enhances the discriminatory power of results, facilitates the ranking of hospitals in the presence of data uncertainty, and aids in identifying the sensitivity and stability levels of hospitals towards data uncertainty. Notably, in order to showcase the pragmatic application and efficacy of the uncertain common-weights DEA model, a genuine dataset has been utilized to evaluate the efficiency of 20 public hospitals in Tehran, all of which are affiliated with the Iran University of Medical Sciences. The results of the experiment demonstrate the efficacy of the UCWDEA approach in assessing and ranking hospitals amidst uncertain conditions. In summary, the research outcomes can offer policymakers valuable insights regarding hospital performance amidst data uncertainty. Additionally, it can provide practical recommendations on optimizing resource allocation, benchmarking performance, and formulating effective policies to augment the overall efficiency and effectiveness of healthcare services.

show abstract

Section: Uncertainty Theorymentioning

confidence: 99%

Performance Evaluation of Hospitals under Data Uncertainty: An Uncertain Common-Weights Data Envelopment Analysis

Peykani,

Pishvaee

2024

Healthcare

View full text Add to dashboard Cite

show abstract

“…In the calculation results of model (15), multiple DMUs' efficiency values may simultaneously be 1, which is not conducive to sorting the DMU set. In order to further study the ranking of efficient DMUs, the uncertain super-efficiency generalized DEA model is proposed as follows:…”

Section: 2mentioning

confidence: 99%

“…is added in model (15), each DMU has the same α-efficiency assessment result as the uncertain CCR model. Through this example, it is shown that by different α values, the basic uncertain DEA models can be expressed in a uniform way by the uncertain generalized DEA model.…”

Section: 1mentioning

confidence: 99%

See 1 more Smart Citation

A generalized DEA model with imprecise data

Wu,

Xie,

Sheng

2024

JIMO

View full text Add to dashboard Cite

Data envelopment analysis (DEA) has excellent efficiency evaluation performance and is extensively employed in measuring efficiency of decision-making units (DMUs). At present, there exist fundamental models such as the DEA model for assessing DMU's technical efficiency, the DEA model for evaluating DMU's scale efficiency, and the model for measuring DMU's efficiency without assuming convexity. In practical production life, the actual statistical data is usually imprecise, as it is affected by various uncontrollable factors and is difficult to collect. In this paper, the expected value method of uncertainty theory is used to deal with these models in order to extend the traditional DEA models which can only deal with precise data to uncertain DEA models which can deal with imprecise data. To simplify the solution and representation of uncertain DEA models and optimize their performance, the uncertain generalized DEA model is further proposed to unify these three basic uncertain DEA models. Furthermore, to further make a clear ranking of DMUs, the super-efficiency method is introduced. Then, this paper applies the basic uncertain DEA models and uncertain generalized DEA model to two numerical examples. The results are analyzed and compared to illustrate the rationality and superiority of the new proposed model.

show abstract

Uncertain Data Envelopment Analysis for Cross Efficiency Evaluation with Imprecise Data

Cited by 2 publications

References 24 publications

Performance Evaluation of Hospitals under Data Uncertainty: An Uncertain Common-Weights Data Envelopment Analysis

Performance Evaluation of Hospitals under Data Uncertainty: An Uncertain Common-Weights Data Envelopment Analysis

A generalized DEA model with imprecise data

Contact Info

Product

Resources

About