Exploration of efficiency underestimation of CCR model: Based on medical sectors with DEA-R model

Data Envelopment Analysis (DEA) is one of the best-known efficiency evaluation methods due to its advantages in selection of weights. Many research papers have extensively discussed the issue of weight restrictions, rather than those implied in the model itself. However, this often leads to a failure to represent the relations of certain weights, as well as underestimation of the efficiency of Decision Making Units (DMUs). When analyzing the medical sectors of Taiwan with the developed models and CCR, it is found that efficiency underestimation by efficient DMUs is more serious than that of inefficient DMUs. In addition, underestimation occurs when weights are concentrated in the same output, however, every output of referenced DMU is the same times of corresponding output of targeted DMU.

Research highlights
► This study suggested that the CCR-based model has occasional underestimations when evaluating high efficiency DMUs.
► This study proposed to use Super-DEA to discuss the underestimation problems of DMUs.
► This study developed a new DEA model based on Super-high and ratio concepts.