Export and its financing in the SME segment. Case study from Slovakia

The export orientation of small and medium enterprises represents an important attribute of the enterprises' competitive ability. In this context, the area of export financing becomes a very important field of company management. The aim of this study is to define and quantify relevant approaches of entrepreneurs to the export activities and export financing, with regard to the impact of the selected socio-economic factors (gender, level of education and age). The study is based on the research of Slovak business environment carried out in 2016, which was evaluated by the tools of descriptive statistics, including percentages and averages, pivot tables, the methods of comparison and deduction, Pearson's chi-square statistics at 5% significance level. Our results suggest that Slovak entrepreneurs primarily supply their products and services on the domestic market, while their export potential is limited. The assessment of the state support of export activities is rather negative. An alarming finding is that Slovak entrepreneurs in the SME segment do not use even basic tools of financial risk reduction to a higher extent, and that the usage of services of the state export bank Eximbank is negligible

Approaches of Czech entrepreneurs to debt financing and management of credit risk

The aim of this article was to define, quantify and compare significant factors of the debt financing in the segment of SMEs. The research focused on the significant differences between groups of entrepreneurs, defined in relation to gender, education, size and age of the company, was carried out in the Czech Republic in 2015 on a sample of 1,141 respondents. We found that while the importance of the credit risk increased during the crisis, the level of knowledge of conditions under which commercial banks provide loans is relatively low between entrepreneurs. Entrepreneurs presume that the credit conditions in commercial banks are not transparent, but agree that the better knowledge of credit criteria allows for easier access to funding. Substantial differences in the assessment of the factors of credit risk by defined groups of entrepreneurs were identified

Comparative Study of the Perception of Financial and Credit Risks among Slovak and Czech Entrepreneurs: Impact of Gender, Level of Education and Business Experience on SMEs

Financial and credit risk has become a widely discussed topic in relation to the recent financial and economic crisis. The aim of this chapter is to bring statistical evidence about the impact of the selected factors (gender, level of education and business experience) on the perception of financial and credit risks by the entrepreneurs in Slovakia and the Czech Republic and to identify whether the entrepreneurship in these regions is influenced by identical or different factors. The research data were obtained through the surveys carried out in 1579 small- and medium-sized enterprises (SMEs) in these countries in 2016. Pearson´s chi-square analysis was applied to confirm statistically significant dependencies. Our results show that while the gender and the level of business experience of the entrepreneur could be considered as factors with the substantial impact on the perception of financial risk in both countries, the level of education (university degree) does not have a significant impact in the researched data sample

Economics of the international ridesharing services - A trap for amateurs

An explosively growing international business model of peer-to-peer ridesharing brings benefits to the customers and provides part-time and full-time jobs for the drivers. While the services are provided mostly by the drivers with low knowledge of economics and finance, provision of the services might be a trap for them in case that they do not take into consideration all costs related to the service provision. The aim of the study was to investigate the economics of the ridesharing providers in case of UBER in Prague, and to create a simulation model estimating the annual performance of the ridesharing transport service operators and classic taxi service from the point of view of individual drivers, considering certain deviations and random effects defined by the stochastic methods using Monte Carlo approach. The results of the modelling show that the net income of Uber drivers is compatible with the taxi drivers only in case of the most expensive Uber Black category, but the net income of ridesharing providers in the category of Uber Pop and Uber Select hardly covers the costs of service provision. The alarming fact is that most of the drivers, who took part in our research, were not capable to acknowledge the hidden costs of ridesharing and were blinded by the vision of a short-term cash incomes without any awareness of the existence of the postponed or implicit costs. While our results confirm that Uber drivers in general are significantly underpaid, Uber Pop and Uber Select services generate a loss for the driver when we take into account the implicit costs of the driver's salary at the level of an average salary in the Czech Republic

The payment discipline of Small and Medium-sized Enterprises

The issue of payment discipline is strongly interconnected with the competitiveness of companies. The aim of this article is to examine the opinions of entrepreneurs from SMEs in Slovakia on the payment discipline issue and its consequences, including the risk of insolvency and lowered competitiveness, and to compare the results in terms of the defined social groups. The entrepreneurs were divided into monitored groups according to the following criteria: gender, age ( groups: younger than 35, 36 to 45 years old, and older than 45) and level of education (groups: university educated, other level of education). This article is based on the research conducted in the Slovak business environment in 2016. The results showed that payment discipline represents a major problem in SMEs in Slovakia, a fact confirmed by affirmative replies from more than 67% of the entrepreneurs. While 83% of them noted the existence of problems with overdue receivables, 30% of the respondents acknowledged problems with their own payment discipline and identified secondary insolvency as the most important reason for it

Business risks and their impact on business future concerning the entrepreneur's experience with business bankruptcy: Case of Czech Republic

The article aims to determine the difference in the perception of selected business risks and their impact on the future of business concerning the entrepreneur's experience with business bankruptcy. The case study involved 73 small and medium-sized enterprises (SMEs) with experience of business bankruptcy and 381 SMEs without the experience of business bankruptcy from the Czech Republic (CR). Linear regression models were used to verify statistically significant causal relationships between selected indicators of the most significant business risks and respondents' perceptions of the future of business. The results brought interesting findings. The attitudes of entrepreneurs show that personnel, market, and financial risk are among the three most significant business risks. Experience with business failure is not a significant factor in determining the impact of market indicators on the business's perceived future. The adequacy of sales of services and products has the greatest impact. The experience of the bankruptcy of SMEs is important in financial risk attitudes. According to entrepreneurs who have no experience with bankruptcy, the perception of financial performance has the greatest direct impact on the future of business. Conversely, for entrepreneurs who have experienced bankruptcy, the ability to properly manage financial risk on the company's future has the greatest direct impact. © 2020 LLC CPC Business Perspectives. All rights reserved

Selected aspects of financial risks of SMEs in Czech Republic and Slovakia

The article examines the selected aspects of financial risk of SMEs in the Czech Republic and Slovakia. Significant attributes of financial risks are defined and attitudes of entrepreneurs to risk are compared. Czech entrepreneurs were less critical in the opinion that SMEs have difficulties in gaining access to external sources of financing. It was found that only a small part of entrepreneurs in both countries can properly manage financial risks. The biggest differences are observed between these countries during the comparison of the impacts on financial risks’ growth and SMEs’ approach to external financing sources. Czech entrepreneurs have more positive attitude than the Slovak ones. Some differences were also found among the attitudes of companies in terms of their age, older companies in both countries more intensively perceive the importance of financial risks during crisis. © Ludmila Kozubikova, Aleksandr Kljucnikov, Lubos Smrcka, 2016

Bank size, relationship lending and SME financing: Evidence from Bangladesh

This paper examines the effect of bank size on relationship lending and how relationship lending can affect credit availability, interest rates and collateral to SMEs in the context of Bangladesh. Our empirical results suggest that SMEs with a long-term relationship with small banks have more access to finance than from large banks. However, we did not find any evidence that long-term relationship with small banks can reduce interest rates or collateral requirements for SMEs. We find evidence though that a stronger and much more exclusive relationship with a small bank can reduce the interest rates for SMEs. This mixed evidence suggests that small banks do not have full comparative advantage in processing soft information, but large banks in Bangladesh may have different lending techniques to extend loans to SMEs with similar interest rates and collateral requirements as like as small banks. Furthermore, we find evidence that small banks are giving priority to both long-term relationship and collateral requirement for SME credit risk than large banks. © Ashiqur Rahman, M. Twyeafur Rahman, Aleksandr Kljucnikov, 2016

Demand forecasting: An alternative approach based on technical indicator Pbands

Research background: Demand forecasting helps companies to anticipate purchases and plan the delivery or production. In order to face this complex problem, many statistical methods, artificial intelligence-based methods, and hybrid methods are currently being developed. However, all these methods have similar problematic issues, including the complexity, long computing time, and the need for high computing performance of the IT infrastructure. Purpose of the article: This study aims to verify and evaluate the possibility of using Google Trends data for poetry book demand forecasting and compare the results of the application of the statistical methods, neural networks, and a hybrid model versus the alternative possibility of using technical analysis methods to achieve immediate and accessible forecasting. Specifically, it aims to verify the possibility of immediate demand forecasting based on an alternative approach using Pbands technical indicator for poetry books in the European Quartet countries. Methods: The study performs the demand forecasting based on the technical analysis of the Google Trends data search in case of the keyword poetry in the European Quartet countries by several statistical methods, including the commonly used ETS statistical methods, ARIMA method, ARFIMA method, BATS method based on the combination of the Cox-Box transformation model and ARMA, artificial neural networks, the Theta model, a hybrid model, and an alternative approach of forecasting using Pbands indicator. The study uses MAPE and RMSE approaches to measure the accuracy. Findings & value added: Although most currently available demand prediction models are either slow or complex, the entrepreneurial practice requires fast, simple, and accurate ones. The study results show that the alternative Pbands approach is easily applicable and can predict short-term demand changes. Due to its simplicity, the Pbands method is suitable and convenient to monitor short-term data describing the demand. Demand prediction methods based on technical indicators represent a new approach for demand forecasting. The application of these technical indicators could be a further forecasting models research direction. The future of theoretical research in forecasting should be devoted mainly to simplifying and speeding up. Creating an automated model based on primary data parameters and easily interpretable results is a challenge for further research.Web of Science1241094106

Demand forecasting: AI-based, statistical and hybrid models vs practice-based models - the case of SMEs and large enterprises

Demand forecasting is one of the biggest challenges of post-pandemic logistics. It appears that logistics management based on demand prediction can be a suitable alternative to the just-in-time concept. This study aims to identify the effectiveness of AI-based and statistical forecasting models versus practice-based models for SMEs and large enterprises in practice. The study compares the effectiveness of the practice-based Prophet model with the statistical forecasting models, models based on artificial intelligence, and hybrid models developed in the academic environment. Since most of the hybrid models, and the ones based on artificial intelligence, were developed within the last ten years, the study also answers the question of whether the new models have better accuracy than the older ones. The models are evaluated using a multicriteria approach with different weight settings for SMEs and large enterprises. The results show that the Prophet model has higher accuracy than the other models on most time series. At the same time, the Prophet model is slightly less computationally demanding than hybrid models and models based on artificial neural networks. On the other hand, the results of the multicriteria evaluation show that while statistical methods are more suitable for SMEs, the prophet forecasting method is very effective in the case of large enterprises with sufficient computing power and trained predictive analysts.Web of Science154623