摘要：The comparison of company performances, i.e., benchmarking, is becoming more and more
critical. Presently, companies mostly use traditional financial ratios to evaluate their financial performance.
We also use financial ratios to measure and compare company performances, from
which we create complex efficiency coefficients using Data Envelopment Analysis. Using Data
Envelopment Analysis, we analyzed the efficiency of retail food companies in Hungary’s Northern
Great Plain region from 2009 to 2014 using their financial reports. To improve the result of
the performance measurement, we used the bootstrap method, the Hamiltonian Monte Carlo
simulation, and Bayesian statistics. We transformed the primarily deterministic DEA method into
a stochastic DEA model. The primary target of this extension is to enhance statistical inference
in DEA and to integrate it with a stochastic mechanism of Bayesian techniques. To develop the
stochastic DEA model, we use Stan Stochastic Modelling Language within the framework of
the R Statistics. Analyzing the results, we can state that the DEA method can be used for analyzing
efficiency, and the additions shown can make the evaluation much more accurate. We can
conclude that the best results were produced by the combined method, during a simultaneous
application of the input orientation.
关键词：performance measurement; principal components analysis; data envelopment analysis; bayesian
statistics; stan stochastic programming language
