SPECIFYING WEIGHT RESTRICTION LIMITS IN DATA ENVELOPMENT ANALYSIS WITH THE WONG AND BEASLEY AND CONE RATIO METHODS

• Autor(a) principal: Macrini,Leonardo
• Data de Publicação: 2018
• Outros Autores: Gonçalves,Antonio Carlos, Almeida,Renan M.V.R., Samanez,Carlos Patricio
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Pesquisa operacional (Online)
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382018000300523
• topic: Data Envelopment Analysis; Weight Restrictions; Wong-Beasley method; Cone Ratio method

ABSTRACT This study presents a new approach for the definition of weight restrictions in Data Envelopment Analysis (DEA) for the one output, multiple inputs case, using the results of a Linear Regression model (LRM) developed with the same DEA variables. Thus, the limits of Wong-Beasley and Cone Ratio methods are chosen without interference from a decision maker, with DEA weight search intervals defined from the estimated standardized coefficients of a linear regression (which represent the statistical importance of the inputs for the definition of the DEA efficiency scores). As an example, weight restrictions for a DEA model (Constant Returns to Scale (CRS)) were obtained through the unrestricted, Wong-Beasley and Cone Ratio methods applied to a dataset consisting of hospital admissions (output), number of beds and number of health professionals (inputs) in the year 2016; and rankings were compared by a Spearman correlation procedure. The regression model had R 2 = 0.89 with coefficients 0.43 (professionals) and 0.54 (beds); and the Spearman correlation among rankings was at least R S 2 = 0.84. In conclusion, rankings were consistent and interpretable, and the approach circumvents the need for a subjective intervention by a decision maker when defining weight restrictions in DEA.