Машински факултет [Научни радови] / Faculty of Mechanical Engineering [Scientific papers]

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https://repozitorijum.ues.rs.ba/handle/123456789/48

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Прегледај Машински факултет [Научни радови] / Faculty of Mechanical Engineering [Scientific papers] по Аутор "Arsovski, Slavko"

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    Fuzzy Approach in Ranking of Banks according to Financial Performances
    (Hindawi, 2016) Jakšić, Milena; Moljević, Slaviša; Aleksić, Aleksandar; Misita, Mirjana; Arsovski, Slavko; Tadić, Danijela; Mimović, Predrag
    Evaluating bank performance on a yearly basis and making comparison among banks in certain time intervals provide an insight into general financial state of banks and their relative position with respect to the environment (creditors, investors, and stakeholders).The aim of this study is to propose a new fuzzy multicriteria model to evaluate banks respecting relative importance of financial performances and their values. The relative importance of each pair of financial performance groups is assessed linguistic expressions which are modeled by triangular fuzzy numbers. Fuzzy Analytic Hierarchical Process (FAHP) is applied to determine relative weights of the financial performances. In order to rank the treated banks, new model based on Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS) is deployed. The proposed model is illustrated by an example giving real life data from 12 banks having 80% share of the Serbian market. In order to verify the proposed FTOPSIS different measures of separation are used. The presented solution enables the ranking of banks, gives an insight of bank’s state to stakeholders, and provides base for successful improvement in a field of strategy quality in bank business.
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    Modelling and Enhancement of Organizational Resilience Potential in Process Industry SMEs
    (MDPI, 2015) Arsovski, Slavko; Putnik, Goran; Arsovski, Zora; Tadić, Danijela; Aleksić, Aleksandar; Đorđević, Aleksandar; Moljević, Slaviša
    The business environment is rapidly changing and puts pressure on enterprises to find effective ways to survive and develop. Since it is almost impossible to identify the multitude of complex conditions and business risks, an organization has to build its resilience in order to be able to overcome issues and achieve long term sustainability. This paper contributes by establishing a two-step model for assessment and enhancement of organizational resilience potential oriented towards Small and Medium Enterprises (SMEs) in the process industry. Using a dynamic modelling technique and statistical tools, a sample of 120 SMEs in Serbia has been developed as a testing base, and one randomly selected enterprise was used for model testing and verification. Uncertainties regarding the relative importance of organizational resilience potential factors (ORPFs) and their value at each level of business are described by pre-defined linguistic expressions. The calculation of the relative importance of ORPFs for each business level is stated as a fuzzy group decision making problem. First, the weighted ORPFs’ values and resilience potential at each business level are determined. In the second step, near optimal enhancement of ORPFs’ values is achieved by applying a genetic algorithm (GA).