Financial Performance Measurement of Hungarian Retail Food Companies

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.