Measuring the efficiency of European education systems by combining Data Envelopment Analysis and Multiple-Criteria Evaluation

Agasisti, Tommaso; Munda, Giuseppe; Hippe, Ralph

doi:10.1007/s11123-019-00549-6

Cited by 33 publications

(18 citation statements)

References 56 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The literature related to the measurement of efficiency in educational processes has shown increasing dynamics in recent years (Witte and López-Torres, 2017). Therefore, it is possible to find different approaches to evaluate efficiency in this sector (Agasisti, Munda and Hippe, 2019;Gralka, Wohlrabe and Bornmann, 2019;Khan, Khan and Hameed, 2019;Tran and Villano, 2019), in addition to studies applied to the Colombian context (Visbal-Cadavid, Mendoza and Hoyos, 2019 and Guijarro (2017) developed a model to predict the efficiency of public universities. In a similar approach, Aparicio, Cordero, and Ortiz (2019) make comparisons between efficiency analysis models using PISA tests as input data.…”

Section: Efficiency and Educationmentioning

confidence: 99%

“…By comparison, our research measures the relative impact colleges have on students when evaluating high school and college exam results. Like Agasisti, Munda and Hippe (2019), our study evaluates the university's contribution to students' professional achievement. Therefore, the proposed methodology produces good results and is relevant for the educational context when comparing our research results with similar approaches.…”

Section: -1617mentioning

confidence: 99%

See 1 more Smart Citation

Assessing and Classification of Academic Efficiency in Engineering Teaching Programs

2021

View full text Add to dashboard Cite

This research uses a three-phase method to evaluate and forecast the academic efficiency of engineering programs. In the first phase, university profiles are created through cluster analysis. In the second phase, the academic efficiency of these profiles is evaluated through Data Envelopment Analysis. Finally, a machine learning model is trained and validated to forecast the categories of academic efficiency. The study population corresponds to 256 university engineering programs in Colombia and the data correspond to the national examination of the quality of education in Colombia in 2018. In the results, two university profiles were identified with efficiency levels of 92.3% and 97.3%, respectively. The Random Forest model presents an Area under ROC value of 95.8% in the prediction of the efficiency profiles. The proposed structure evaluates and predicts university programs’ academic efficiency, evaluating the efficiency between institutions with similar characteristics, avoiding a negative bias toward those institutions that host students with low educational levels.

show abstract

Section: Efficiency and Educationmentioning

confidence: 99%

Section: -1617mentioning

confidence: 99%

Assessing and Classification of Academic Efficiency in Engineering Teaching Programs

2021

View full text Add to dashboard Cite

show abstract

“…The DEA method has been widely used to evaluate the performance of various fields, such as health (Kohl et al, 2019), education (Agasisti et al, 2019), the automotive industry (Jiang et al, 2018), and banking (Othman et al, 2016). Likewise, with the tourism industry, DEA is widely used mainly in hotels (Assaf, 2012), travel agents (Fuentes, 2011), and restaurants (Mhlanga, 2018).…”

Section: Journal Of Sustainability Science Andmentioning

confidence: 99%

Measuring the Efficiency of Tourist Attraction Management in North Toraja Regency, Indonesia

Nurfaida¹,

Arifin²,

Sitorus³

et al. 2021

JSSM

View full text Add to dashboard Cite

“…The objects used to evaluate the research efficiency of universities can be divided into three levels (according to the hierarchy of decision-making units): macro, medium, and micro. Macro research concerns the scientific research efficiency of entire regions, and the regions where schools are located are the corresponding DMUs [7], [8]. The medium research level assumes that universities represent DMUs and mainly compares the efficiency of scientific research at the university level, while micro research evaluates the research efficiency of departments or disciplines [9], [11].…”

Section: A Selection Of Decision-making Units (Dmus)mentioning

confidence: 99%

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

Ding-xin

et al. 2020

IEEE Access

View full text Add to dashboard Cite

Evaluating the efficiency of scientific research plays an important role in accelerating technological innovation and optimizing the allocation of research resources. Most studies have focused on measuring research efficiency from a macro perspective, ignoring differences within disciplines. Furthermore, existing methods have failed to discriminate between evaluation results and the fact that research has variable returns to scale. To address this, in this paper we propose a multiple-criteria decision-making (MCDM) nonradial super efficiency data envelopment analysis (NRSDEA) model, which uses an outputoriented nonradial SDEA method to manage nonsolution problems and integer decision variable constraints. In addition, we used a Malmquist index to decompose the productivity changes of statistics discipline's research efficiency at different universities in China. Finally, we verified the rationality and effectiveness of the proposed method. INDEX TERMS Discipline research efficiency, multiple-criteria decision-making, nonradial SDEA, Malmquist index.

show abstract

Measuring the efficiency of European education systems by combining Data Envelopment Analysis and Multiple-Criteria Evaluation

Cited by 33 publications

References 56 publications

Assessing and Classification of Academic Efficiency in Engineering Teaching Programs

Assessing and Classification of Academic Efficiency in Engineering Teaching Programs

Measuring the Efficiency of Tourist Attraction Management in North Toraja Regency, Indonesia

A Nonradial Super Efficiency DEA Framework Using a MCDM to Measure the Research Efficiency of Disciplines at Chinese Universities

Contact Info

Product

Resources

About