Models of data envelopment analysis and stochastic frontier analysis in the efficiency assessment of universities

2017 ◽  
Vol 78 (5) ◽  
pp. 902-923 ◽  
Author(s):  
F. T. Aleskerov ◽  
V. Yu. Belousova ◽  
V. V. Petrushchenko
2017 ◽  
Vol 23 (6) ◽  
pp. 787-795 ◽  
Author(s):  
Joanicjusz NAZARKO ◽  
Ewa CHODAKOWSKA

The primary problems pertaining to productivity or – more precisely – efficiency are: how to define it and how to measure it. This article studies technical efficiency in Stochastic Frontier Analysis (SFA) – the input-oriented frontier model – in the construction industry and compares it with Data Envelopment Analysis (DEA) results. The models ex­plored in this paper were constructed on the basis of two outputs and personnel cost as an input. The research sample consisted of European countries. The aim was to determine whether there are substantial differences in estimation of ef­ficiency derived from those two alternative frontier approaches. The comparison of results according to the models may translate into higher reliability of the undertaken labour efficiency analysis in construction and its conclusions. Although the results are not characterized by high compatibility, the conducted analysis indicated the most attractive countries taking into account labour cost to profit and turnover ratios of enterprises. One of the determinants which should not be ignored when analysing the labour efficiency is the level of development of a country; however, it is not the sole factor affecting the efficiency of the sector.


2020 ◽  
Vol 47 (7) ◽  
pp. 1787-1810
Author(s):  
Kekoura Sakouvogui

PurposeThe consistency of stochastic frontier analysis (SFA) and data envelopment analysis (DEA) cost efficiency measures using a sample of 650 commercial and domestic banks in the United States is investigated based on cluster analysis while accounting for the yearly variation in banks.Design/methodology/approachDue to the importance of efficiency measures for policy and managerial decision-making, the cost efficiency measures of SFA and DEA estimators are examined according to four criteria: levels, rankings, stability over time and stability over clustering groups. In this paper, we present two clustering methods, Gap Statistic and Dindex, that involve SFA and DEA cost efficiency measures. The clustering approach creates homogeneous groups of banks offering a similar mix of efficiency levels. Hence, each evaluated bank knows the cluster to which it belongs. Furthermore, this paper provides nonparametric statistical tests of SFA and DEA cost efficiency measures estimated with and without a clustering approach.FindingsThe results suggest that the clustering approach plays a considerable role in the rankings of US banks. Furthermore, the average SFA and DEA cost efficiency measures over time of the homogeneous US banks are substantially higher than those of the heterogeneous US banks.Originality/valueThis research is the first to provide comparative efficiency measures needed for desirable policy conclusions of heterogeneous and homogeneous US banks.


Author(s):  
Lina Fatayati Syarifa

Penelitian ini bertujuan untuk mengetahui estimasi efisiensi teknis yang menggunakan teknik parametrik dan non-parametrik dikarenakan kedua metode tersebut masing-masing memiliki kekurangan dan kelebihan. Oleh karena itu, penelitian ini melakukan analisis komparasi di antara tiga metode analisis yaitu Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), dan Bootstrap DEA terhadap data dari 380 petani karet di Sumatera Selatan. Hasil analisis stochastic frontier menunjukkan bahwa rata-rata skor efisiensi teknis dari kebun sampel adalah 0,72, yang menunjukkan bahwa rata-rata kebun karet sampel dalam penelitian ini tidak sepenuhnya efisien. Sedangkan hasil dari data envelopment analysis (DEA) yang tidak memperhitungkan randomness menunjukkan bahwa estimasi efisiensi teknis rata-rata sebesar 0,80, yang menunjukkan bahwa estimasi efisiensi teknis yang dihasilkan dari analisis DEA ​​terlalu tinggi. Kelemahan model DEA tersebut dapat diatasi dengan menerapkan model Bootstrap DEA. Pada analisis Bootstrap DEA, efisiensi teknis rata-rata berkurang menjadi 0,76, yang lebih mendekati nilai efisiensi teknis rata-rata SFA. Hal ini dikarenakan bootstrap DEA dapat menghasilkan interval kepercayaan dan estimasi efisiensi DEA dengan bias yang terkoreksi. Perbedaan kinerja di antara ketiga model-model ini dapat dikaitkan dengan asumsi bahwa perkiraan efisiensi teknis dengan pendekatan non-parametrik DEA hanya bergantung pada efek inefisiensi petani, sedangkan perkiraan efisiensi teknis dengan pendekatan parametrik (SFA) bergantung pada inefisiensi petani dan faktor lain di luar kontrol petani.


2020 ◽  
Vol 9 (3) ◽  
pp. 454-478
Author(s):  
Eduardo Lima Leite Nascimento ◽  
Maria Cristina Mario Calvo ◽  
Sandra Rolim Ensslin ◽  
Sandra Mara Iesbik Valmorbida

O objetivo deste estudo é analisar as características das publicações internacionais na temática avaliação do desempenho hospitalar (ADH), por meio de um fragmento da literatura, na busca de geração de conhecimento, identificação de lacunas e possibilidade de contribuições. Esta pesquisa utiliza uma abordagem qualitativa e o instrumento selecionado para identificar e selecionar o fragmento de literatura para análise e reflexão foi o Knowledge Development Process – Constructivist (ProKnow-C). O portfólio bibliográfico com 43 artigos identificou os autores e os núcleos de pesquisas de destaque e os periódicos com maior número de publicações. Quanto aos métodos mais utilizados na ADH, destacam-se os que se baseiam na teoria das fronteiras Eficientes, classificados como: Data Envelopment Analysis (DEA - 53,85%), Stochastic Frontier Analysis (SFA - 12,82%), comparação entre DEA e SFA (7,69%) e Partinal Frontier Analysis (2,56%). Quanto ao emprego ou dimensões analisadas, 38,46% dos artigos destinam-se aos gestores. A partir das análises geradas foi possível identificar lacunas, referentes a mecanismos de avaliação do desempenho voltados para as dimensões que extrapolem as métricas. Para geração e aplicação de conhecimento nesta área, sugere-se a adequação da ADH as especificidades destas organizações, considerando o ambiente e a finalidade do sistema ao qual se insere.


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