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The issue of prediction of financial state, or especially the threat of the financial distress of companies, is very topical not only for the management of the companies to take the appropriate actions but also for all the stakeholders to know the financial health of the company and its possible future development. Therefore, the main aim of the paper is ensemble model creation for financial distress prediction. This model is created using the real data on more than 550,000 companies from Central Europe, which were collected from the Amadeus database. The model was trained and validated using 27 selected financial variables from 2016 to predict the financial distress statement in 2017. Five variables were selected as significant predictors in the model: current ratio, return on equity, return on assets, debt ratio, and net working capital. Then, the proposed model performance was evaluated using the values of the variables and the state of the companies in 2017 to predict financial status in 2018. The results demonstrate that the proposed hybrid model created by combining methods, namely RobustBoost, CART, and k-NN with optimised structure, achieves better prediction results than using one of the methods alone. Moreover, the ensemble model is a new technique in the Visegrad Group (V4) compared with other prediction models. The proposed model serves as a one-year-ahead prediction model and can be directly used in the practice of the companies as the universal tool for estimation of the threat of financial distress not only in Central Europe but also in other countries. The value-added of the prediction model is its interpretability and high-performance accuracy.
Michal Pavlicko; Marek Durica; Jaroslav Mazanec. Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries. Mathematics 2021, 9, 1886 .
AMA StyleMichal Pavlicko, Marek Durica, Jaroslav Mazanec. Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries. Mathematics. 2021; 9 (16):1886.
Chicago/Turabian StyleMichal Pavlicko; Marek Durica; Jaroslav Mazanec. 2021. "Ensemble Model of the Financial Distress Prediction in Visegrad Group Countries." Mathematics 9, no. 16: 1886.
Before the COVID-19 pandemic there had already been an increase in individual shipment transportation including inner-city areas. During the pandemic and implementation of adopted preventive measures, it has increased by more than 100% in some cities. This presents an unsustainable development, particularly in terms of urban environment. The above-mentioned development has accelerated the research related to optimal allocation of logistics centres considering the last-mile distribution. Unfortunately, the theoretical mathematical model that finds an optimal urban logistics centre location based on the matrix of distance, number, and weight of shipments is not applicable in most cities. Therefore, the following research methodology was chosen in accordance with the approved territorial plan. The authors considered those locations in Bratislava—the capital of Slovak Republic—which are designated, or suitable for building up of an urban logistics centre. These localities were afterwards evaluated in a real-world case study employing methods of mathematical programming (linear programming), the nearest neighbour method, and the Clarke-Wright method. The presented methodology can be applied not only when deciding on the appropriate location of the city logistics centre, but also at optimizing the vehicle routing problem. Taking into account the urban logistics sustainability and the e-commerce growth, it was analysed whether the suggested location of urban logistics centre is feasible to provision examined facilities using electric vehicles. The range of considered electric vehicles of N2 category present in the market tends to be at the limits of distribution routes length for the given case study. Therefore, the article also deals with the fast-charging possibilities of vehicles during handling operations and the use of hybrid freight vehicles in city logistics.
Tomáš Settey; Jozef Gnap; Dominika Beňová; Michal Pavličko; Oľga Blažeková. The Growth of E-Commerce Due to COVID-19 and the Need for Urban Logistics Centers Using Electric Vehicles: Bratislava Case Study. Sustainability 2021, 13, 5357 .
AMA StyleTomáš Settey, Jozef Gnap, Dominika Beňová, Michal Pavličko, Oľga Blažeková. The Growth of E-Commerce Due to COVID-19 and the Need for Urban Logistics Centers Using Electric Vehicles: Bratislava Case Study. Sustainability. 2021; 13 (10):5357.
Chicago/Turabian StyleTomáš Settey; Jozef Gnap; Dominika Beňová; Michal Pavličko; Oľga Blažeková. 2021. "The Growth of E-Commerce Due to COVID-19 and the Need for Urban Logistics Centers Using Electric Vehicles: Bratislava Case Study." Sustainability 13, no. 10: 5357.
Jaroslav Frnda; Michal Pavlicko; Marek Durica; Lukas Sevcik; Miroslav Voznak; Philippe Fournier-Viger; Jerry Chun-Wei Lin. A new perceptual evaluation method of video quality based on neural network. Intelligent Data Analysis 2021, 25, 571 -587.
AMA StyleJaroslav Frnda, Michal Pavlicko, Marek Durica, Lukas Sevcik, Miroslav Voznak, Philippe Fournier-Viger, Jerry Chun-Wei Lin. A new perceptual evaluation method of video quality based on neural network. Intelligent Data Analysis. 2021; 25 (3):571-587.
Chicago/Turabian StyleJaroslav Frnda; Michal Pavlicko; Marek Durica; Lukas Sevcik; Miroslav Voznak; Philippe Fournier-Viger; Jerry Chun-Wei Lin. 2021. "A new perceptual evaluation method of video quality based on neural network." Intelligent Data Analysis 25, no. 3: 571-587.
Alena Kostalova; Michal Pavlicko. Utilization of Regression and Correlation Analysis for Optimal Composition of Factors Affecting Premium Rates of Compulsory Contractual Insurance. Proceedings of the 2016 International Conference on Engineering Science and Management 2016, 1 .
AMA StyleAlena Kostalova, Michal Pavlicko. Utilization of Regression and Correlation Analysis for Optimal Composition of Factors Affecting Premium Rates of Compulsory Contractual Insurance. Proceedings of the 2016 International Conference on Engineering Science and Management. 2016; ():1.
Chicago/Turabian StyleAlena Kostalova; Michal Pavlicko. 2016. "Utilization of Regression and Correlation Analysis for Optimal Composition of Factors Affecting Premium Rates of Compulsory Contractual Insurance." Proceedings of the 2016 International Conference on Engineering Science and Management , no. : 1.