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The purpose of this study was to emphasize that the Data Envelopment Analysis (DEA) method is an important benchmarking tool which provides necessary information for improving business performance. To fulfil the abovementioned goal, we used a sample of 48 Slovak companies involved in the field of heat supply. As their position in the economic and social environment of the country is essential, considerable attention should be paid to improving their performance. In addition to the DEA method, we applied the Best Value Method (BVM). We found that DEA is a highly important benchmarking tool, as it provides benchmarks for units that have problems with performance and helps us to reveal risk performance factors. The DEA method also allows us to determine target values of indicators. The originality of this paper is in its comparison of the results of the BVM and the DEA methods.
Jarmila Horváthová; Martina Mokrišová; Mária Vrábliková. Benchmarking—A Way of Finding Risk Factors in Business Performance. Journal of Risk and Financial Management 2021, 14, 221 .
AMA StyleJarmila Horváthová, Martina Mokrišová, Mária Vrábliková. Benchmarking—A Way of Finding Risk Factors in Business Performance. Journal of Risk and Financial Management. 2021; 14 (5):221.
Chicago/Turabian StyleJarmila Horváthová; Martina Mokrišová; Mária Vrábliková. 2021. "Benchmarking—A Way of Finding Risk Factors in Business Performance." Journal of Risk and Financial Management 14, no. 5: 221.
The paper deals with the issue of analyzing the financial failure of businesses. The aim was to select key performance indicators entering the DEA model. The research was carried out on a sample of 343 Slovak heat management companies. When addressing the research problem, we made use of multidimensional scaling (MDS) and principal component analysis (PCA), which pointed out the areas of financial health of companies that may predict their financial failure. The core of our interest and research was the data envelopment analysis (DEA) method, which represents a more exact approach to the assessment of financial health. The important finding is that the statistical graphical methods—PCA and MDS—are very helpful in identifying outliers and selecting key performance indicators entering the DEA model. The benefit of the paper is the identification of companies that are at risk of bankruptcy using the DEA method. The originality is the selection of key inputs and outputs to the DEA model by the PCA method.
Róbert Štefko; Jarmila Horváthová; Martina Mokrišová. The Application of Graphic Methods and the DEA in Predicting the Risk of Bankruptcy. Journal of Risk and Financial Management 2021, 14, 220 .
AMA StyleRóbert Štefko, Jarmila Horváthová, Martina Mokrišová. The Application of Graphic Methods and the DEA in Predicting the Risk of Bankruptcy. Journal of Risk and Financial Management. 2021; 14 (5):220.
Chicago/Turabian StyleRóbert Štefko; Jarmila Horváthová; Martina Mokrišová. 2021. "The Application of Graphic Methods and the DEA in Predicting the Risk of Bankruptcy." Journal of Risk and Financial Management 14, no. 5: 220.
The paper deals with methods of predicting bankruptcy of a business with the aim of choosing a prediction method which will have exact results. Existing bankruptcy prediction models are a suitable tool for predicting the financial difficulties of businesses. However, such tools are based on strictly defined financial indicators. Therefore, the Data Envelopment Analysis (DEA) method has been applied, as it allows for the free choice of financial indicators. The research sample consisted of 343 businesses active in the heating industry in Slovakia. Analysed businesses have a significant relatively stable position in the given industry. The research was based on several studies which also used the DEA method to predict future financial difficulties and bankruptcies of studied businesses. The estimation accuracy of the Additive DEA model (ADD model) was compared with the Logit model to determine the reliability of the DEA method. Also, an optimal cut-off point for the ADD model and Logit model was determined. The main conclusion is that the DEA method is a suitable alternative for predicting the failure of the analysed sample of businesses. In contrast to the Logit model, its results are independent of any assumptions. The paper identified the key indicators of the future success of businesses in the analysed sample. These results can help businesses to improve their financial health and competitiveness.
Jarmila Horváthová; Martina Mokrišová; Róbert Štefko. Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses. Journal of Risk and Financial Management 2020, 13, 212 .
AMA StyleJarmila Horváthová, Martina Mokrišová, Róbert Štefko. Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses. Journal of Risk and Financial Management. 2020; 13 (9):212.
Chicago/Turabian StyleJarmila Horváthová; Martina Mokrišová; Róbert Štefko. 2020. "Bankruptcy Prediction with the Use of Data Envelopment Analysis: An Empirical Study of Slovak Businesses." Journal of Risk and Financial Management 13, no. 9: 212.
This paper focuses on business financial health evaluation with the use of selected mathematical and statistical methods. The issue of financial health assessment and prediction of business failure is a widely discussed topic across various industries in Slovakia and abroad. The aim of this paper was to formulate a data envelopment analysis (DEA) model and to verify the estimation accuracy of this model in comparison with the logit model. The research was carried out on a sample of companies operating in the field of heat supply in Slovakia. For this sample of businesses, we selected appropriate financial indicators as determinants of bankruptcy. The indicators were selected using related empirical studies, a univariate logit model, and a correlation matrix. In this paper, we applied two main models: the BCC DEA model, processed in DEAFrontier software; and the logit model, processed in Statistica software. We compared the estimation accuracy of the constructed models using error type I and error type II. The main conclusion of the paper is that the DEA method is a suitable alternative in assessing the financial health of businesses from the analyzed sample. In contrast to the logit model, the results of this method are independent of any assumptions.
Jarmila Horváthová; Martina Mokrišová. Comparison of the Results of a Data Envelopment Analysis Model and Logit Model in Assessing Business Financial Health. Information 2020, 11, 160 .
AMA StyleJarmila Horváthová, Martina Mokrišová. Comparison of the Results of a Data Envelopment Analysis Model and Logit Model in Assessing Business Financial Health. Information. 2020; 11 (3):160.
Chicago/Turabian StyleJarmila Horváthová; Martina Mokrišová. 2020. "Comparison of the Results of a Data Envelopment Analysis Model and Logit Model in Assessing Business Financial Health." Information 11, no. 3: 160.
In this paper, the following research problem was addressed: Is DEA (Data Envelopment Analysis) method a suitable alternative to Altman model in predicting the risk of bankruptcy? Based on the above-mentioned research problem, we formulated the aim of the paper: To apply DEA method for predicting the risk of bankruptcy and to compare its results with the results of Altman model. The research problem and the aim of the paper follow the research of authors aimed at the application of methods which are appropriate for measuring business financial health, performance and competitiveness as well as for predicting the risk of bankruptcy. To address the problem, the following methods were applied: financial ratios, Altman model for private non-manufacturing firms and DEA method. When applying DEA method, we formulated input-oriented DEA CCR model. We found that DEA method is an appropriate alternative to Altman model in predicting the risk of possible business bankruptcy. The important conclusion is that DEA allows us to apply not only outputs but also inputs. Since prediction models do not include these indicators, DEA method appears to be the right choice. We recommend, especially for Slovak companies, to apply cost ratio when calculating risk of bankruptcy.
Jarmila Horváthová; Martina Mokrišová. Risk of Bankruptcy, Its Determinants and Models. Risks 2018, 6, 117 .
AMA StyleJarmila Horváthová, Martina Mokrišová. Risk of Bankruptcy, Its Determinants and Models. Risks. 2018; 6 (4):117.
Chicago/Turabian StyleJarmila Horváthová; Martina Mokrišová. 2018. "Risk of Bankruptcy, Its Determinants and Models." Risks 6, no. 4: 117.
A molecular graph is a graph in which vertices are atoms of a given molecule and edges are its chemical bonds. A numerical quantity which characterizes the whole structure of a graph is called a topological index. Three degree based topological indices, the Randić (Rα), the atombond connectivity (ABC) and the geometric-arithmetic (GA) indices of multi-walled carbon nanotube networks are studied. Expressions for Rα, ABC and GA indices for these important classes of networks are obtained.
Martin Bača; Jarmila Horvathova; Martina Mokrišová; Andrea Semaničová-Feňovčíková; Alžbeta Suhányiová. On Topological Indices of Multi-Walled Carbon Nanotubes. Journal of Computational and Theoretical Nanoscience 2015, 12, 5705 -5710.
AMA StyleMartin Bača, Jarmila Horvathova, Martina Mokrišová, Andrea Semaničová-Feňovčíková, Alžbeta Suhányiová. On Topological Indices of Multi-Walled Carbon Nanotubes. Journal of Computational and Theoretical Nanoscience. 2015; 12 (12):5705-5710.
Chicago/Turabian StyleMartin Bača; Jarmila Horvathova; Martina Mokrišová; Andrea Semaničová-Feňovčíková; Alžbeta Suhányiová. 2015. "On Topological Indices of Multi-Walled Carbon Nanotubes." Journal of Computational and Theoretical Nanoscience 12, no. 12: 5705-5710.
A numerical quantity that characterizes the whole structure of a graph is called a topological index. The concept of Randić (Rα), atom−bond connectivity (ABC), and geometric−arithmetic (GA) topological indices was established in chemical graph theory based on vertex degrees. In this paper, we study a carbon nanotube network that is motivated by the molecular structure of a regular hexagonal lattice and determine Rα, ABC, and GA indices for this important class of networks.
Martin Bača; Jarmila Horváthová; Martina Mokrišová; Andrea Semaničová-Feňovčíková; Alžbeta Suhányiová. On topological indices of a carbon nanotube network. Canadian Journal of Chemistry 2015, 93, 1157 -1160.
AMA StyleMartin Bača, Jarmila Horváthová, Martina Mokrišová, Andrea Semaničová-Feňovčíková, Alžbeta Suhányiová. On topological indices of a carbon nanotube network. Canadian Journal of Chemistry. 2015; 93 (10):1157-1160.
Chicago/Turabian StyleMartin Bača; Jarmila Horváthová; Martina Mokrišová; Andrea Semaničová-Feňovčíková; Alžbeta Suhányiová. 2015. "On topological indices of a carbon nanotube network." Canadian Journal of Chemistry 93, no. 10: 1157-1160.
Jarmila Horváthová; Martina Mokrišová; Alžbeta Suhányiová; Ladislav Suhányi. THE IMPLEMENTATION OF BSC INTO THE MANAGEMENT OF SLOVAK COMPANIES. US-China Law Review 2015, 12, 1 .
AMA StyleJarmila Horváthová, Martina Mokrišová, Alžbeta Suhányiová, Ladislav Suhányi. THE IMPLEMENTATION OF BSC INTO THE MANAGEMENT OF SLOVAK COMPANIES. US-China Law Review. 2015; 12 (7):1.
Chicago/Turabian StyleJarmila Horváthová; Martina Mokrišová; Alžbeta Suhányiová; Ladislav Suhányi. 2015. "THE IMPLEMENTATION OF BSC INTO THE MANAGEMENT OF SLOVAK COMPANIES." US-China Law Review 12, no. 7: 1.
This paper is devoted to the issue of business performance. It is dedicated to more detailed elaboration of performance, key performance indicators, measurement and evaluation of the performance of selected industry applying Creditworthy model as well as risk factors influencing performance of businesses from given industry. Nowadays modern performance indicators are adopted as well as mathematical and statistical methods are applied in assessing business performance. In this paper this problem is solved by the application of correlation matrix constructed for a chosen indicators‘group in order to select key performance indicators. Subject for objective fulfilment was a group of businesses operating in the same Slovak industry. The most difficult point of solution was the selection of appropriate inputs for the construction of correlation matrix as well as the collecting of sufficient amount of relevant data to ensure analytically-based outputs. Benefit of this paper is formation of Creditworthy model with the application of key performance indicators and risk factors of businesses from selected industry. Creditworthy model designed in such a way allows to influence and measure the performance of given industry in terms of key performance indicators and to eliminate specific risks of businesses from given industry.
Jarmila Horváthová; Martina Mokrišová; Alžbeta Suhányiová; Ladislav Suhányi. Selection of Key Performance Indicators of Chosen Industry and their Application in Formation of Creditworthy Model. Procedia Economics and Finance 2015, 34, 360 -367.
AMA StyleJarmila Horváthová, Martina Mokrišová, Alžbeta Suhányiová, Ladislav Suhányi. Selection of Key Performance Indicators of Chosen Industry and their Application in Formation of Creditworthy Model. Procedia Economics and Finance. 2015; 34 ():360-367.
Chicago/Turabian StyleJarmila Horváthová; Martina Mokrišová; Alžbeta Suhányiová; Ladislav Suhányi. 2015. "Selection of Key Performance Indicators of Chosen Industry and their Application in Formation of Creditworthy Model." Procedia Economics and Finance 34, no. : 360-367.
Martin Baca; Jarmila Horváthová; Martina Mokrišová; Alžbeta Suhányiová. On topological indices of fullerenes. Applied Mathematics and Computation 2015, 251, 154 -161.
AMA StyleMartin Baca, Jarmila Horváthová, Martina Mokrišová, Alžbeta Suhányiová. On topological indices of fullerenes. Applied Mathematics and Computation. 2015; 251 ():154-161.
Chicago/Turabian StyleMartin Baca; Jarmila Horváthová; Martina Mokrišová; Alžbeta Suhányiová. 2015. "On topological indices of fullerenes." Applied Mathematics and Computation 251, no. : 154-161.