Applications of Data Envelopment Analysis in Education

Thanassoulis, Emmanuel; Witte, Kristof De; Johnes, Jill; Johnes, Geraint; Karagiannis, Giannis; Portela, Conceição

doi:10.1007/978-1-4899-7684-0_12

Cited by 47 publications

(28 citation statements)

References 127 publications

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“…The sequence of raw data (11,779,12,619,13,399,14,197) simulates this sequence X (0) by respectively using the following three GM (1,1) and comparing the accuracy of the simulation:…”

Section: Results and Analysis Of The Grey Forecasting Of The Input Anmentioning

confidence: 99%

“…Instead, these techniques establish a set of segments linking efficient firms, which combine environmental efficiency comparing the rest of the units. The main interest here is for choosing the DEA is that the technique does not predefine any functional form for the production function and then, efficiency evaluation were designed to analyse industries comprising multi-input multi-output producers in order to measure its contribution to productivity [13,14]. In addition, it is not financially oriented in principle; instead, the objective is to perform an analysis of the process of the transformation of inputs into outputs that generates a measurement or set of measurements, which reflects the efficiency of a firm with regard to the transformation process.…”

Section: Related Research About Deamentioning

confidence: 99%

“…Emmanuel [14] used DEA to evaluate efficiency in the education sector, which comprises multi-input, multi-output producers and lacking data. The DEA method is also widely applied to analyze sustainability in the energy field; the DEA approach was proposed by Ren to analyze sustainability efficiencies of biodiesel production systems, including soybean, rapeseed, sunflower, jatropha and palm-based diesel production [11].…”

Section: Related Research About Deamentioning

confidence: 99%

“…Average MAPE (%) DMUs Average MAPE (%) DMU 1 0.9462 DMU 11 1.4125 DMU 2 0.7709 DMU 12 1.227 DMU 3 0.27 DMU 13 0.6516 DMU 4 1.2972 DMU 14 2.742 DMU 5 1.983 DMU 15 0.384 DMU 6 0.505 DMU 16 0.469 DMU 7 1.263 DMU 17 1.083 DMU 8 1.4853 DMU 18 1.65 DMU 9 2.662 DMU 19 0.588 DMU 10 3.0697…”

Section: Dmusmentioning

confidence: 99%

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A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies

Wang

2016

Sustainability

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Abstract:Logistics plays an important role in globalized companies and contributes to the development of foreign trade. A large number of external conditions, such as recession and inflation, affect logistics. Therefore, managers should find ways to improve operational performance, enabling them to increase efficiency while considering environmental sustainability due to the industry's large scale of energy consumption. Based on data collected from the financial reports of top global logistics companies, this study uses a DEA model to calculate corporate efficiency by implementing a Grey forecasting approach to forecast future sustainability values. Consequently, the study addresses the problem of how to enhance operational performance while accounting for the impact of external conditions. This research can help logistics companies develop operation strategies in the future that will enhance their competitiveness vis-à-vis rivals in a time of global economic volatility.

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“…The sequence of raw data (11,779,12,619,13,399,14,197) simulates this sequence X (0) by respectively using the following three GM (1,1) and comparing the accuracy of the simulation:…”

Section: Results and Analysis Of The Grey Forecasting Of The Input Anmentioning

confidence: 99%

Section: Related Research About Deamentioning

confidence: 99%

Section: Related Research About Deamentioning

confidence: 99%

Section: Dmusmentioning

confidence: 99%

See 2 more Smart Citations

A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies

Wang

2016

Sustainability

View full text Add to dashboard Cite

show abstract

“…Instead, these techniques establish a set of segments linking efficient firms, which combine environmental efficiency comparing the rest of the units. The main interest here is for choosing the DEA is that the technique does not predefine any functional form for the production function and then, efficiency evaluation were designed to analyse industries comprising multi-input multi-output producers in order to measure its contribution to productivity [23]. In addition, it is not financially oriented in principle; instead, the objective is to perform an analysis of the process of the transformation of inputs into outputs that generates a measurement or set of measurements, which reflects the efficiency of a firm with regard to the transformation process.…”

Section: Related Research About Deamentioning

confidence: 99%

A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies

Wang

2016

Preprint

View full text Add to dashboard Cite

Logistics plays an important role in globalized companies and contributes to the development of foreign trade. A large number of external conditions, such as recession and inflation, affect logistics. Therefore, managers should find ways to improve operational performance, enabling them to increase efficiency while considering environmental sustainability due to the industry’s large scale of energy consumption. Based on data collected from the financial reports of top global logistics companies, this study uses a DEA model to calculate corporate efficiency by implementing a Grey forecasting approach to forecast future sustainability values. Consequently, the study addresses the problem of how to enhance operational performance while accounting for the impact of external conditions. This research can help logistics companies develop operation strategies in the future that will enhance their competitiveness vis-à-vis rivals in a time of global economic volatility.

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Beyond the Z‐score: A novel measure of bank stability for effective policymaking

Gulati

2023

Journal of Public Affairs

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This article looks beyond Z‐score and proposes a novel methodological framework to build an all‐encompassing indicator of bank stability for individual banks using the optimisation‐based ‘benefit‐of‐the‐doubt (BoD)’ approach. Unlike other available approaches, this approach is totally data‐driven and generates endogenous weights to aggregate sub‐indicators of bank stability and dimensions. Further, the final outcomes are not limited to a scalar measure of bank stability. The unique optimal weights offer valuable policy‐relevant insights and highlight the most precarious areas of stability, which demand the immediate attention of the bank's management and the industry regulators for both micro‐and macro‐level policymaking. Using the data of Indian public sector banks operating in the year 2018, the study illustrates the proposed framework to obtain a holistic indicator of bank stability, defined on 14 ratio sub‐indicators and 5 broad dimensions (soundness, asset quality, profitability, management efficiency, and liquidity) of bank stability.

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Applications of Data Envelopment Analysis in Education

Cited by 47 publications

References 127 publications

A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies

A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies

A Grey Forecasting Approach for the Sustainability Performance of Logistics Companies

Beyond the Z‐score: A novel measure of bank stability for effective policymaking

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