Dynamic super-efficiency interval data envelopment analysis

Li, Ling; Lv, Xuliang; Xu, Weidong; Zhang, Zhixin; Rong, Xianhui

doi:10.1109/iccse.2015.7250245

Cited by 2 publications

(16 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model is static and devoid of interval data, in contrast to the proposed model in our research. The empirical comparison of our integrated dynamic InDEA model with the subsisting models in [17] and [26] strengthen our conviction in the execution of the recommended model. To the degree of our understanding, this research constitutes a critical contribution to the contemporary writings of InDEA.…”

Section: 2supporting

confidence: 61%

“…-Li et al [26] introduced a dynamic super-efficiency InDEA model, though without considering carryover variables. In other words, the unit is regarded as a static system in each period by ignoring operations and interrelations between the periods.…”

Section: 2mentioning

confidence: 99%

“…In other words, the unit is regarded as a static system in each period by ignoring operations and interrelations between the periods. The model in [26] requires first identifying efficient and inefficient DMUs, and then determining the super-efficiency of DMUs among the efficient ones through a two-step procedure. Our proposed integrated In-DEA model classifies the efficient and super-efficient units in a single-step.…”

Section: 2mentioning

confidence: 99%

“…We apply the PD method to rank the units within their respective classes further. We illustrate it for the DMUs in the class S. [26] has no carryovers connecting the two consecutive periods. The intervals of efficiency score are computed in each period t.…”

Section: Comparison Analysismentioning

confidence: 99%

“…In Section 4, we sketch out a scheme to classify DMUs into three distinct classes and the designated class ranking. In Section 5, we compare our model with the one in [17] and [26]. This section also includes an example to demonstrate the proposed method's working on a synthetically generated dataset.…”

mentioning

confidence: 99%

See 4 more Smart Citations

Integrated dynamic interval data envelopment analysis in the presence of integer and negative data

Bansal¹,

Mehra²

2022

JIMO

View full text Add to dashboard Cite

The conventional data envelopment analysis (DEA) models presume that the values of input-output variables of the decision-making units (DMUs) are precisely known. However, some real-life situations can authoritatively mandate the data to vary in concrete fine-tuned ranges, which can include negative values and measures that are allowed to take integer values only. Our study proposes an integrated dynamic DEA model to accommodate interval-valued and integer-valued features that can take negative values. The proposed one-step model follows the directional distance function approach to determine the efficiency of DMUs over time in the presence of carryovers connecting the consecutive periods. We use the pessimistic and optimistic standpoints to evaluate the respective lower and upper bounds of the interval efficiency scores of the DMUs. We compare our proposed approach with a few relevant studies in the literature. We also validate our model on a synthetically generated dataset. Furthermore, we showcase the proposed procedure's applicability on a real dataset from 2014 to 2018 of airlines operating in India.

show abstract

Section: 2supporting

confidence: 61%

Section: 2mentioning

confidence: 99%

Section: 2mentioning

confidence: 99%

Section: Comparison Analysismentioning

confidence: 99%

mentioning

confidence: 99%

See 3 more Smart Citations