An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies

Authors

  • Snezana Pavle Knežević Faculty of Organizational Sciences, University of Belgrade
  • Ksenija Mandić Faculty of Organizational Sciences, University of Belgrade
  • Aleksandra Mitrović University of Kragujevac, Faculty of Hotel Management and Tourism
  • Veljko Dmitrović Faculty of Organizational Sciences, University of Belgrade
  • Boris Delibašić Faculty of Organizational Sciences, University of Belgrade

DOI:

https://doi.org/10.7595/management.fon.2017.0011

Keywords:

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

Abstract

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.

Author Biographies

Snezana Pavle Knežević, Faculty of Organizational Sciences, University of Belgrade

Snežana Knežević was born in Pančevo (Jabuka), where she finished school of economics. She graduated from the Faculty of Economics at the University of Belgrade, where she also got her MSc degree. She got her PhD degree at the Faculty of Organizational Sciences at the University of Belgrade. Her fileds of interest include accounting, financial analysis, and valuation. She is bilingual fluency in both English and French. She has published several monographs and she has produced over 50 papers of scientific and professional orientation in the country and abroad. She is currently working at the Faculty of Organizational Sciences in Belgrade, Department of Financial Management and Accounting as an Associate professor. She is the owner of the Agency for accounting and consulting services.

Ksenija Mandić, Faculty of Organizational Sciences, University of Belgrade

Ksenija Mandić received her BSc, MSc and the PhD degrees in Faculty of Organizational Science from the University of Belgrade, Serbia, in 2006, 2008 and 2015 respectively. She works in telecommunication company Crony since 2007. Her research interests are decision making theory, supply chain management, multi-criteria decision making methods, fuzzy logic and Interpolative Boolean Algebra.

Aleksandra Mitrović, University of Kragujevac, Faculty of Hotel Management and Tourism

Aleksandra Mitrović, Ph.D., works as a Assistant Professor at the Faculty of Hotel Management and Tourism in Vrnjačka Banja, University of Kragujevac. She completed her Bachelor Studies in Accounting and Corporate Finance as well as her Master studies at the Faculty of Economics in Kragujevac. She got her PhD degree in 2016. The fields of her scientific and professional interests are related to Accounting and Finance.

Veljko Dmitrović, Faculty of Organizational Sciences, University of Belgrade

Veljko Dmitrović works at the Faculty of Organizational Sciences, University of Belgrade, at the Department of Financial Management and Accounting as assistant professor. He achieved PhD degree at the Faculty of Organizational Sciences. He achieved his MSc degree in Financial Management at the Faculty of Organizational Sciences, University of Belgrade, and his BSc and MA degrees in Marketing Management at the Faculty of Economics in Subotica, University of Novi Sad. So far he has authored and coauthored more than 50 papers published in international and national journals and conferences. He has been involved in several research projects. Before the academic career he gained practical experience working for five years in “Fidelinka” a.d., Subotica.

Boris Delibašić, Faculty of Organizational Sciences, University of Belgrade

Boris Delibašić is professor at the University of Belgrade - Faculty of Organizational Sciences, Serbia. His research interests lie in business intelligence, data mining, machine learning, multicriteria decision analysis, and decision support systems. He serves in editorial boards of several international journals. He is a coordinator of the EURO working group on Decision Support Systems. He obtained his PhD in 2007 from the University of Belgrade. He was awarded with the Fulbright Visiting Scholar Grant in 2011. He speaks fluently English, and German, and speaks also Russian, French, and Italian. His research profile is available at https://www.researchgate.net/profile/Boris_Delibasic

Downloads

Published

2017-09-21

How to Cite

Knežević, S. P., Mandić, K., Mitrović, A., Dmitrović, V., & Delibašić, B. (2017). An FAHP-TOPSIS framework for analysis of the employee productivity in the Serbian electrical power companies. Management:Journal of Sustainable Business and Management Solutions in Emerging Economies, 22(2), 47–60. https://doi.org/10.7595/management.fon.2017.0011

Issue

Vol. 22 No. 2 (2017)

Section

Articles

Most read articles by the same author(s)

Similar Articles

1 2 3 4 5 6 7 8 9 10 > >> 

You may also start an advanced similarity search for this article.