Efficient decisions using DEA

• Autor(a) principal: Mendes, Armando B.
• Data de Publicação: 2011
• Outros Autores: Silva, Emiliana, Noncheva, Veska
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10400.3/2639
• topic: Efficiency Decisions; Feature Selection and Extraction; DEA; CCA

Data Envelopment Analysis (DEA) is becoming an increasingly popular management tool for decision support related to efficiency comparisons. The task of the DEA is to evaluate the relative performance of units of a system. Is not a problem solution technique but an important problem analysis method based in mathematical programming with some similarities with Multiple Criteria Decision Analysis (MCDA). DEA makes it possible to identify efficient and inefficient units in a framework where results are considered in their particular context. The units to be assessed should be relatively homogeneous and were originally called Decision Making Units (DMUs). It is an extreme point method that compares each DMU with the "best" DMUs. The “Productivity Analysis with R” (PAR) framework establishes a user - friendly data envelopment analysis environment with special emphasis on variable selection and aggregation, and summarization and interpretation of the results. PAR framework has been developed to distinguish between efficient and inefficient observations of performances and to advise explicitly for producers’ possibilities to optimize their production. In this work we will apply PAR to farms in Terceira Island, with a small data set of 30 farms. This data set includes 14 input variables and 4 output variables. With PAR was possible to conclude that 4 farms are scale – efficient and the others are scale inefficiency due to decreasing returns to scale or increasing returns to scale. This implies that either the dairy farm is too big (the number of cows is too large) or to small and that the farmer can improve the productivity of inputs and hence reduce unit costs by reducing or increasing the dimension of the farm.