Non-discretionary and discretionary factors and scale in data envelopment analysis

Alternative approaches to include exogenous variables in DEA measures: A comparison using Monte Carlo

“…Ruggiero [13], Syrjänen [14] and Muñiz et al [15] use a simulation analysis to compare alternative approaches to deal with non-discretionary inputs as well. Actually, they do compare different alternatives based on the use of DEA like one-stage, basic two-stage and three-stage models studied in previous section, as well as original methodological options proposed by Ruggiero [13,44] and Yang and Paradi [45].…”

“…Thus, Yu [12] focuses on comparing parametric and non-parametric approaches using a Monte Carlo experiment rather than analyzing alternative nonparametric models. In contrast, Ruggiero [13], Syrjänen [14] and Muñiz et al [15] compare different approaches developed in the context of DEA using simulated data. However, they are limited because they use a single replication instead of the large number is usual in Monte Carlo experiments.…”

Effects of Ownership on Hospital Efficiency in Germany.

“…Finally, in our third DEA model we used 1 minus the average hospital mortality rate per year, which represents an index variable. Syrjänen (2004) dies which, however, as mentioned earlier, have certain methodological limitations. Among the control variables, market concentration (HHI) and hospital size (BEDS) were important exogenous market effects, and the regression results revealed a significant positive association with efficiency in all three models (P0.001).…”

Benchmarking Distance Learning Centers with a Multiobjective Data Envelopment Analysis Model

“…As pointed out by the authors, the constant returns to scale version of this model can be easily formulated with the exclusion of the convexity constraint (Cooper et al, 2006, Syrjänen, 2004 …”