Avaliação de empresas aéreas com modelo de análise envoltória de dados clusterizado pela escala de operação

In this article, we carried out a comparative analysis of the efficiency results obtained using two existing approaches of DEA in relation to the methodology proposed here, which is an alternative to deal with differences of scale. For this, a study on the operational performance of the Brazilian air passenger transportation business is conducted. The proposal combines static clustering to the constant returns-to-scale model, and compensation scale differences among the clusters. The innovation relies on the adaption of a technique, originally designed to handle non-homogeneity to treat differences of scale. The results show that the proposed methodology increases the discrimination among companies, that is, some units that resulted 100% efficient in the existing approaches, had their efficiency reduced, resulting in less draws. Another relevant aspect is that the proposed methodology has comparative advantages over existing alternatives in the literature.

[1]  A. Charnes,et al.  Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis , 1984 .

[2]  João Carlos Correia Baptista Soares de Mello,et al.  Eficiência técnica das companhias aéreas brasileiras: um estudo com análise envoltória de dados e conjuntos nebulosos , 2011 .

[3]  João Carlos Correia Baptista Soares de Mello,et al.  Eficiência de empresas aéreas: uma análise baseada no modelo de Li & Reeves , 2012 .

[4]  Gilson Brito Alves Lima,et al.  Evaluation of bidding processes for hiring offshore support vessels using data envelopment analysis models , 2014 .

[5]  Boaz Golany,et al.  Restricted best practice selection in DEA: An overview with a case study evaluating the socio-economic performance of nations , 1997, Ann. Oper. Res..

[6]  Eliane Gonçalves Gomes,et al.  EFFICIENCY MEASURES FOR A NON-HOMOGENEOUS GROUP OF FAMILY FARMERS , 2012 .

[7]  Anil K. Jain Data clustering: 50 years beyond K-means , 2010, Pattern Recognit. Lett..

[8]  Eliane Gonçalves Gomes,et al.  Análise de envoltória de dados no estudo da eficiência e dos benchmarks para companhias aéreas brasileiras , 2003 .

[9]  João Carlos Correia Baptista Soares de Mello,et al.  RETORNOS DE ESCALA EM DEA: CRÍTICAS AO BCC E NOVO MODELO , 2014 .

[10]  Agha Iqbal Ali,et al.  Streamlined computation for data envelopment analysis , 1993 .

[11]  Abraham Charnes,et al.  Measuring the efficiency of decision making units , 1978 .

[12]  J. MacQueen Some methods for classification and analysis of multivariate observations , 1967 .

[13]  João Carlos Correia Baptista Soares de Mello,et al.  Eficiência de portos e terminais privativos brasileiros com características distintas , 2011 .

[14]  E. Thanassoulis,et al.  Improving discrimination in data envelopment analysis: some practical suggestions , 2007 .

[15]  Lidia Angulo Meza,et al.  Identificação de benchmarks e anti-benchmarks para companhias aéreas usando modelos DEA e fronteira invertida , 2011 .

[16]  Eliane Gonçalves Gomes,et al.  About negative efficiencies in Cross Evaluation BCC input oriented models , 2013, Eur. J. Oper. Res..

[17]  Lidia Angulo Meza,et al.  Evaluation of Brazilian airlines nonradial efficiencies and targets using an alternative DEA approach , 2016, Int. Trans. Oper. Res..

[18]  Ramu Ramanathan,et al.  An Introduction to Data Envelopment Analysis , 2003 .

[19]  Luiz Biondi Neto,et al.  Ex-Post Clustering of Brazilian Beef Cattle Farms Using Soms and Cross-Evaluation Dea Models , 2012 .

[20]  Joe Zhu,et al.  Data envelopment analysis: Prior to choosing a model , 2014 .

[21]  Juliana da Silveira,et al.  Evaluación de la eficiencia de las compañías aéreas brasileñas a través de un modelo híbrido de análisis envolvente de datos (DEA) y programación lineal multiobjetivo , 2012 .