A <b>Data Envelopment Analysis  Toolbox</b> for <i>MATLAB</i>

Álvarez, Inmaculada; Barbero, Javier; Zofío, José L.

doi:10.18637/jss.v095.i03

Cited by 29 publications

(23 citation statements)

References 26 publications

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“…Furthermore, efficient pandemic treatment practice with the number of infections and available resources necessitates minimizing the fatality rate and maximizing the number of patients treated. In this context, the DEA model adequately handles such parameters (desirable and undesirable outputs) and objectively evaluates efficiency by accounting for the asymmetry between both types of outputs [ 32 ] and alleviating the possibility of biased results due to converting undesirable outputs to their inverse (ratio) [ 33 ].…”

Section: Methodsmentioning

confidence: 99%

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Pandemic Response Management Framework Based On Efficiency of COVID-19 Control and Treatment

2020

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Aims: The existing response management system for pandemic disease fell short of controlling COVID-19. This study evaluates the response management relative efficiency of 58 countries in two stages, using two models. Materials & methods: Data envelopment analysis was applied for efficiency analysis. Results: 89.6% of countries were inefficient in pandemic control and 79% were inefficient in treatment measures. Sensitivity analysis underlines resources as a critical factor. Further examination points to absence of a robust and uniform mitigation measure against the pandemic in most countries. Conclusions: Preventing spread is not only the first line of defense; it is the only line of defense. The lack of a global public health database support system and uniform response compounded inefficiency. A robust pandemic response management framework is developed based on practices of key performers. Action plans are proposed, with a recommendation for a global public health pandemic database monitoring and support system as the nucleus.

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Section: Methodsmentioning

confidence: 99%

“…Most efficiency evaluation models do not account for the asymmetry between both types of outputs, which leads to erroneous efficiency estimation. Incorporation of the characteristics of undesirable outputs into DEA efficiency estimation relies on a directional measure that handles desirable and undesirable outputs differently [ 32 ].…”

Section: Methodsmentioning

confidence: 99%

Pandemic Response Management Framework Based On Efficiency of COVID-19 Control and Treatment

2020

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“…And the data exchange method GetFullmatrix among MATLAB servers was used to extract the results such as the evaluation efficiency and dual price and so on[34]. Based on SBM-DEA model, the key influencing factors were analysed by reducing and increasing the value of the indexes with the largest and the second largest dual price[35].…”

mentioning

confidence: 99%

The Evaluation and Its Key Influencing Factors Analysis of “Double First-Class” Universities’ Teaching Efficiency in China Based on SBM-DEA and Its Visual Decision Analysis System Development

Pang

Zuo

et al. 2021

Discrete Dynamics in Nature and Society

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Based on a systematical summary of relevant research on university teaching efficiency, an evaluation index system was built to evaluate teaching efficiency of “Double First-Class” universities in China. The evaluation model to evaluate the teaching efficiency of these universities was built based on Slack-Based Measure model using Superefficiency Data Envelopment Analysis (SBM-DEA). Teaching efficiency of 36 “Double First-Class” universities had been evaluated after their assessment indexes data had been collected. The influencing relations between the teaching efficiency of “Double First-Class” universities and dual prices of each evaluation index had been analysed. It had been proven that teaching efficiency could be greatly improved by increasing the index value with a higher double price. We proceeded to count the frequencies of evaluation indicators with the highest or the second highest dual prices. The indexes with higher total importance were defined as the key factors for the development of teaching efficiency in China’s “Double First-Class” universities. Several countermeasures had been proposed to improve the development of “Double First-Class” universities’ teaching efficiency. Finally, based on the above theoretical research, the evaluation and decision analysis software for teaching efficiency in “Double First-Class” universities in China had been developed by Visual Basic 2015 and MATLAB 2015 with Access database to store the data. It provides a convenient visualization tool to manage the data of the evaluation index system and make the data analysis of the SBM-DEA model.

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“…However, there are some software-related differences in the way the DEA algorithms are developed and run in the respective analytics packages. For example, the Matlab's DEA Toolbox utilizes a two-stage DEA optimization model and dualsimplex method for LP optimization (Alvarez et al, 2020), whereas the other three analytics software Simm, 2020;Zhu, 2014). The R's rDEA package does not specify which form of the DEA model is used -Multiplier or Envelopment Form (Simm, 2020), while for the other three analytics software the traditional Multiplier Form of the DEA model is being applied.…”

Section: Energy Efficiency Analysis and Interpretation Of Resultsmentioning

confidence: 99%

Data Envelopment Analysis and Analytics Software for Optimizing Building Energy Efficiency

Radovilsky

Taneja²,

Sahay³

2021

International Journal of Business Analytics

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This research was motivated by the need to identify the most effective Data Envelopment Analysis (DEA) model and associated data analytics software for measuring, comparing, and optimizing building energy efficiency. By analyzing literature sources, the authors identified several gaps in the existing DEA approaches that were resolved in this research. In particular, the authors introduced energy efficiency indices like energy consumption per square foot and per occupant as a part of DEA models’ outputs. They also utilized inverse and min-max normalized output variables to resolve the issue of undesirable outputs in the DEA models. The evaluation of these models was done by utilizing various data analytics software including Python, R, Matlab, and Excel. The authors identified that the CCR DEA model with inverse output variables provided the most reliable energy efficiency scores, and the Python’s PyDEA package produces the most consistent efficiency scores while running the CCR model.

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A Data Envelopment Analysis Toolbox for MATLAB

Cited by 29 publications

References 26 publications

Pandemic Response Management Framework Based On Efficiency of COVID-19 Control and Treatment

Pandemic Response Management Framework Based On Efficiency of COVID-19 Control and Treatment

The Evaluation and Its Key Influencing Factors Analysis of “Double First-Class” Universities’ Teaching Efficiency in China Based on SBM-DEA and Its Visual Decision Analysis System Development

Data Envelopment Analysis and Analytics Software for Optimizing Building Energy Efficiency

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