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Management: Journal of Sustainable Business and Management Solutions in Emerging Economies
2017, vol. 22, br. 2, str. 47-60
jezik rada: engleski
vrsta rada: neklasifikovan
objavljeno: 02/11/2017
doi: 10.7595/management.fon.2017.0011
An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies
(naslov ne postoji na srpskom)
aUniverzitet u Beogradu, Fakultet organizacionih nauka
bUniverzitet u Kragujevcu, Fakultet za hotelijerstvo i turizam, Vrnjačka Banja



(ne postoji na srpskom)
The aim of this paper is to apply an integrated model, which combines methods of classical and fuzzy Multi-criteria decision making (MCDM) in selected six large equity companies from the Serbian energy sector. The data considered are retrieved from the official financial statements. Four main criteria were analyzed, identified by the previous researchers and pointing to the employees’ productivity: Operating income/ Number of employees, Equity/Number of employees, Net income/Number of employees and Total assets/Number of employees. The contribution of this paper lies in the application of a hybrid model that integrates two MCDM methods: Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) to analyse the employee productivity in selected D-Electrical power supply companies operating in Serbia. The FAHP is an effective method for mathematical representation of uncertain and imprecise evaluations made by humans, while the TOPSIS method is an efficient way to rank the alternatives. Results show that operating income is of highest importance for estimating employee productivity and decision making, while equity is of the weakest. Furthermore, the most productive operations in large enterprises from selected companies of the sector D-Electrical power supply are found in the company PC EPS Beograd, and the lowest are in the ED Center llc Kragujevac.

Ključne reči

employee productivity; Serbian companies; electricity sector; fuzzy logic; MCDM methods; FAHP; TOPSIS