Best practice as actual and relative benchmark to inefficient units: multiset DEA analysis - Vuković, Dubravka R. (Vojnotehnički glasnik / Military Technical Courier, 2018)
The direction in research of the efficiency of decision-making units    in this paper is an efficient→multi-inefficient→multi-efficient unit. So, the general purpose of this paper is twofold: (1) identification of «hidden» inefficient units within a multi-set, among efficient units of the basic set, and (2) achieving the efficiency in such identified inefficient units. This indicates (warns of!) a negative efficient→inefficient process, so as to provide a timely response and thereby prevent multi-inefficiency. The specific goal is to assess the efficiency of the Serbian railway passenger stations, first within the basic set of the Passenger Transport Section Belgrade, then in the multi-set of the Passenger Transport Sections, and finally in the superset, the Passenger Transport Sector. This is achieved by means of the multi-set DEA (Data Envelopment Analysis) method, which is a system for: (i) relative efficiency assessment, in the first iteration, through the basic set analysis, and (ii) decrease in efficiency of potentially inefficient units, in subsequent iterations, through the multi-set analysis. The result is that the efficient stations Požarevac and Pančevo Bridge are at the initial level, and the (newly) efficient Požarevac, Novi Sad and Inđija at the final level. The best practice station remains the Požarevac Station, which is multi-efficient, and therefore the role model to inefficient stations. The conclusion is drawn that the solution resulting from the multi-set DEA analysis is more realistic, and less relative, because it applies to a wider analysed set of decision-making units, i.e., a larger coverage when considering the issue. This is important for fitting into the new era of growing globalization, and therefore our recommendation is the integral multi-set, as opposed to the individual single set approach.
Keywords: Efficiency; Data Envelopment Analysis; Multi-Set Analysis; Railway Stations