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Abstract This paper examines whether and how non-state-owned enterprise (non-SOE) business groups affect a firm’s green innovation. On the basis of a sample of A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2007 to 2021 and hand-collected business group data, we document a negative association between non-SOE business groups and corporate green innovation. Furthermore, we identify two different mechanisms that may explain this relationship from various perspectives: firms’ motivation for benefit maximization and the ability to lighten government environmental regulations. We also find that this negative correlation is more pronounced in competitive industries and is related to reduced executives' environmental awareness, reduced intensity of environmental regulation, and greater official pressure to promote. Our findings not only help improve the existing literature on business groups and corporate green innovation but also provide empirical evidence that non-SOE business groups can negatively affect corporate green innovation.

In the present study, the issues of teacher resilience and the persistent gender stereotypes in the field are discussed. The main objective of the conducted research study was to examine the presence of gender-stereotype-confirming behavior in coping with adversity in vocational school teachers. The Connor-Davidson Resilience Scale CDRISC-25SLOVAKwas selected as the most suitable research instrument, by means of which gender differences in the participants’ (N=474) responses in its subscales were studied. The results obtained confirmed the hypothesis presuming the existence of gender differences in the achieved scores in five of the seven dimensions of the scale, and also stereotype-confirming behaviors—according to which men are rational problem solvers while women tend to apply emotion-focused coping strategies—were reported. This knowledge can be the first step towards introducing measures with the aim to provide individuals of all genders with opportunities to broaden their scale of coping strategies and promote resilience in them. Since vocational school teachers are on the periphery of researchers’ interest and no available extensive study has been focused on gender differences in teacher resilience, the research findings aim to fill the gap in the existing knowledge, provide unique data for policymakers, and create a basis for further resilience research. Doi: 10.28991/ESJ-2024-SIED1-011 Full Text: PDF

This study aimed to investigate the extent to which an agile and flat organizational design based on Holacracy can bring a company a competitive advantage in the market. Holacracy design is considered to be a Dynamic Capability. The research was conducted as a case study of a flatly organized company operating in the field of designing and supplying technologies for industrial automation in the Czech Republic. Interviews with company executives and questionnaires were used to gather their opinions on the company's ability to have a competitive advantage. The questionnaire included a guiding question and four statements about their truthfulness on a 5-point Likert scale. The first group of statements assessed the extent of the company's ability to exploit market opportunities. This ability was rated as average to slightly above average. The second group of statements assessed the extent of the company's ability to neutralize competitive threats. Here, a rather average to slightly below-average level was found. This research found that the innovative Holacracy design may not be able to create a competitive advantage if a company operates in a highly competitive and price-sensitive industry. Companies' efforts to achieve above-average performance thus remain primarily a matter of appropriate pricing, well-managed costs, and the ability to differentiate more than dynamic or agile organizational capabilities. The limitations of this research were mainly the small number of similarly organized companies operating in the same industry and the small base of companies of similar size and structure.

The objective of the paper was to assess the impact of the invasion of Ukraine by the Russian Federation on real household income in the Czech Republic. The research methods used in the study include content analysis, seasonal modification of SARIMA, and discounting method, specifically NPV. Data were collected from publicly available sources of the Czech Statistical Office. Based on a content analysis of the macroeconomic indicators under study, inflation and gross monthly household income were selected to examine further development of real household income in the Czech Republic. Based on historical data, the SARIMA model made statistically relevant forecasts of the selected variables for the "pre-war" year 2022. Comparing real and forecast data, it was confirmed that the Russian invasion of Ukraine (from 24th February 2022 onwards) has shown how vulnerable the European financial system is to external shocks, which can be observed in significant inflationary changes. The ability of the SARIMA model to handle a larger range of data and accurately determined seasonality was demonstrated in forecasting the development of real household income. The identified economic consequences of deviations of the real and forecast figures in the "pre-war" period showed new realities in turbulent economic conditions. In order to further expand the research, combining the applied method with other analytical tools can be recommended. Moreover, it is advisable to include new relevant variables in the model. This would allow understanding better and forecasting the development of real household income in the context of current economic events.

Phosphate fertilisers rank among limited conventional production aids, requiring eco-unfriendly mining methods. On the other hand, wheat is an indispensable agricultural commodity essential in the food industry. For this reason, it is appropriate to monitor the potential bivariate relationship between these commodities and to follow their future development closely. The article aims to identify a correlation (Kendall's tau) and causal (Granger causality test) between the price of Moroccan phosphate and wheat, applying vector autoregression (VAR). The results show a medium-to-strong correlation between phosphate and wheat, while causal analysis suggests a reciprocal relationship. The final prediction indicates the price stability of Moroccan phosphate and a fall in wheat prices, showing steady trends of the Moroccan phosphate and wheat market affected by the alarming situation in Ukraine. The article's drawbacks are a narrow market specialisation, which ignores other agricultural commodities. Our findings contribute to national officeholders and professional public, private and non-profit agrarian organisations. Investors may benefit from exploring turbulent exogenous variables like a critical geopolitical deadlock in Ukraine. The main contribution highlights the fact that the conventional fertiliser and wheat market situation appears to be stable and free from elements of uncertainty.

The inclusion of sustainability criteria in the investment decision processes requires application of tools that consider the vague nature of sustainable characteristics. Fuzzy approach can process the vagueness of sustainability measures. The aim of the paper is to develop a suitable model of the fuzzy assessment of investment alternatives measured by Sustainability Utility Index. Its scheme is described methodologically as a three-stage system of multi-criteria ex-ante evaluation. An algorithmic conception of the system is performed at its third stage by a "fuzzy processor". The fuzzy model is applied to the task of the optimal type of building machinery selection in view of the cost and sustainable criteria. The results enable the manager to optimize his/her decision, who aims to minimize the investment and operation costs of the building machinery. Compared to the fuzzy approach based on Mandani's system, our model avoids several complications associated with the semantics of fuzzy implications in various fuzzy logics, it is more user friendly and easily algorithmized. This model is thus suitable to apply not only in corporate sphere but also in areas of ecology, sociology, economics. The limits of the fuzzy system are twofold - on the general level the fuzzy systems lack the ability to learn and memorize; determining or tuning a suitable membership function and fuzzy rules is not always clear. The challenge is first to test the model in the corporate sphere and second to acquaint potential users with this computationally undemanding fuzzy procedure.

The research goal presented in this paper was to determine the strength of the relationship between the price of coffee traded on ICE Futures US and Consumer Price Indices in the major urban agglomerations of the United States—New York, Chicago, and Los Angeles—and to predict the future development. The results obtained using the Pearson correlation coefficient confirmed a very close direct correlation (r = 0.61 for New York and Chicago; r = 0.57 for Los Angeles) between the price of coffee and inflation. The prediction made using the SARIMA model disrupted the mutual correlation. The price of coffee is likely to anchor at a new level where it will fluctuate; on the other hand, the CPIs showed strong unilateral pro-growth trends. The results could be beneficial for the analysis and creation of policies and further analyses of market structures at the technical level.

The objective was to evaluate the financial development of the service sector affected by anti-pandemic measures against COVID-19, and to propose a strategy for the sector´s further development. To fulfil the objective, the following indicators were used: return on assets (or total capital), return on equity, return on sales, share of sales per employee, cash liquidity, current liquidity and total liquidity. Overall, the service sector in Central Europe can be assessed as being in good economic shape. In terms of profitability indicators, companies in the service sector in Central Europe are above the EU average. All can be summarized quite briefly. In the near future, the Czech Republic must address stabilization of return on sales (which is extremely volatile). Close attention must also be drawn to labour productivity, which is half the European Union average. Finally yet importantly, it is evident that companies use too many fixed assets. Slovakia, Hungary and Poland can be considered stable countries that were not harmed by the COVID-19 pandemic, or were able to quickly eliminate the consequences. They can thus focus on the overall improvement of financial health indicators and sustainable development. Germany, and particularly Austria, can be found at the top of the group. Companies in the service sector are very stable, well above average compared to the EU. However, a certain degree of caution can be observed in relation to them. They can be advised to reduce liquidity of companies, which nowadays works against profitability indicators.

The aim of work was to evaluate the alternative costs of equity of mining companies in the Czech Republic from 2011 to 2021 and to predict the development of costs structure of equity in the following five years. The calculation of Capital Asset Pricing Model (CAMP) model was selected to deal with the issue of alternative costs of equity in the monitored period and multi-layer perceptron networks were selected for the prediction of development. The achieved results clearly demonstrate the ratio of capital structure and its prediction in the future. The research is useful for energy enterprises and a possibility to use it in another sector is obvious.

Inflation in Czech Republic in 2021 significantly deviated from the tolerance band. Although the economic results are lagging behind expectations, inflationary pressures, mainly from abroad, are still intensifying. At the same time, the rapid rise in consumer prices affects not only households and consumers, but also business and companies. As is known, a very important tool for understanding inflation is the Phillips curve, which shows the relationship between two variables, the first one is inflation and the second one is unemployment. The aim of this paper is to research the relationship between the short-term Philips curves and long-term Phillips curves for the Czech Republic. For this purpose, data on the inflation rate and unemployment rate between 1993 and 2018 were contrasted based on data published by the Czech Statistical Office. The short-term Phillips curve was assumed under adaptive expectation conditions, whereby a regression analysis was undertaken using SPSS statistical software to determine suitable values for the corresponding parameters. In addition, and in accordance with the trend figure and data description figure for both the unemployment rate variable and inflation rate variable, the basis for the development of the long-term Phillips curve is described. Subsequently, it is concluded that a mutually substitutive relationship exists with regards to the short-term and that the long-term is an irregular circular curve that moves in a clockwise direction.

The dividend policy presents an important tool to decide whether to pay or with hold the earning. The resolute information about purchasing shares and subsequent dividends show the future prosperity of the company and its position on the market. The article aims at analysing the development of the payout ratio estimated from the current dividend policy of ČEZ Company. CEZ is one of the most important suppliers and producers of electricity in the Czech Republic. The majority owner of the company is the Czech state. It can be stated that the area of operation does not only cover the Czech market, because ČEZ company also operates in other countries, mainly in Central Europe. For this reason, it is very interesting to watch the development of this power giant in terms his dominant role in a small and open economy such as the Czech Republic. The data extraction from company annual reports of 2008-2018 allows the correlation analysis to collect and interpret data on the payout ratio adequacy, examining the actual state of the company, earning distribution and corporate expectations from the market. The earning has a visibly positive impact on the payout ratio. The article offers advice for the organization changes to generalize achieved results, subsequently passing on advice for the whole segment.

A great number of researchers argue that the development of large swathes of the global economy and competitiveness are influenced by fluctuations in international oil prices. The aim of this article is to determine to what extent those fluctuations in oil prices influence the value of the Euro relative to the value of USD. Data on the EUR/USD exchange rate were used for the analysis, with the time series that follow based on the price of Brent Crude. Statistica software (version 13) was used for the data processing. The research was based on a unified procedure with gradual changes in one parameter, namely in the time series (1, 5, 10 and 30 days), following which a regression analysis using neural networks was performed based on 10,000 networks that were generated for each experimental combination. As a result, eight calculations and eight different outcomes were obtained. From each experiment, the 5 artificial neural networks that showed the best results were retained. The outcomes suggest that the EUR/USD exchange rate is strongly dependent on the international price of oil. The impact of fluctuations in the price of oil on the EUR/USD exchange rate can therefore be accurately predicted. These results imply that it is also possible to predict the impact of such fluctuations on the performance of national economies. These predictions can be used to enhance competitiveness, including that of companies actively operating in international markets.

Research background: The article deals with implementing VMI between the supplier and customer. To assess whether the system will be implemented, the evolution game theory is used. The contribution is based on the limitations of the study of the evolutionary game theory approach to modelling VMI policies (Torres et al., 2014) and its later extension, The evolutionary game theory approach to modelling VMI policies (Torres & García-Díaz, 2018). It aims is to complement the studies and provide a comprehensive picture of the issue. Purpose of the article: The main objective of the contribution is to respond to the question whether the VMI system will be introduced between the supplier and customer. Methods: In the first phase, the matrix is analysed from the point of view of the game meaning and its limit parameters. The limit parameters are set taking into account the economic reality. The only examined states of the matrix are those where the result is not obvious. For the purposes of the contribution, we work with a 5-year period. A new software capable of calculating evolutionary focus and their stability is created. Sensitivity analysis is carried out for the individual parameters that affect the system behaviour. Findings & Value added: Value added is a complex description of the system and complementation of previous studies in this field. VMI is confirmed. The results obtained can be used for practical management, so that the managers are able to identify what the actual costs are and what the probability of introducing the sys-tem is. At the same time, they can identify the parameters that can be influenced by them and observe their impact on the shift of the system introduction probability.

The research goal is to determine whether platinum can be seen as a good investment. For this purpose, content analysis of documents and deep learning neural networks with recurrent neural network were used. The results show that it pays for a koruna investor (a person holding their wealth in Czech koruna) to preserve their wealth physically in the form of a precious metal—specifically, platinum. The research confirms that platinum is a store of value but also a koruna investor’s wealth multiplier. This can be due to its rare occurrence in nature, but also to its unique use in manufacturing. A research limitation is the period for which the data were used. The finding that platinum is a store of value, as well as a wealth multiplier, can thus be concretized when using the data for a five-year period. It shall also be added that no turbulent changes are anticipated (such as interruption of platinum supply, unexpected government regulation of trade, etc.).

Transport is one of the key sectors of the European economy. Effectiveness of transport companies depends mainly on the changes in the given environment. Transport companies differ from other types of companies especially in higher focus on ecology, not storing the services offered or high cost investments. The aim of each business is generally the increase of the value of the company. The objective of this contribution is thus to identify the value drivers of a transport company in the Czech Republic, provided that the value of the company is measured by means of the EVA equity indicator. The data set contains complete financial statements of 1500 transport companies in the Czech Republic for the year 2016. For each company, the EVA equity value is calculated. For the analysis, the Statistica software and the method of artificial neural networks are used. 1000 neural networks are generated, out of which 5 showing the best results are retained. In total, 12 variables are chosen that enter/play a part in the process of the company value creation. Based on the sensitivity analysis, the most important components of the variable are the financial result, consumption of material and energy and the profit on ordinary operations.

It is logical that in an uncertain economic environment it is necessary for companies to be able to plan better, to report more precisely and to be able to better evaluate their future financial development. For their analysis, the authors of this article focus on a particular segment of the national economy, namely transport and freight forwarding companies. The aim of this article is to utilize artificial neural networks to predict potential financial problems in transport companies in the Czech Republic. Data on all companies involved in transport and freight forwarding in the Czech Republic for the period 2003 - 2013 were used for modelling the particular neural network. The data file contained nearly 15,000 records on companies for the individual years. These records included both financial statement data and non-accounting data (e.g. data on company employees). The following networks were used for modelling the neural network: a linear network, a probabilistic neural network (PNN), a generalised regression neural network (GRNN), a radial basis function network (RBF), a three-layer perceptron network (TLP) and a four-layer perceptron network (FLP). The analysis resulted in a concrete model of an artificial neural network. The neural network is able to determine with more than ninety per cent accuracy whether a company is able to overcome potential financial problems, within how many years a company might go bankrupt, or whether a company might go bankrupt within one calendar year. The text also includes the basic statistical characteristics of the examined sample and the achieved results (sensitivity analysis, confusion matrix, etc.). The model can be utilized in practice by transport company managers, investors looking for a suitable company for capital investment, competitors, etc.

There are many discussions and arguments about accuracy of the results of statistic regression analysis and neural network regression analysis among experts. Of course all of them look for the best method usable in practice. The objective of the contribution is to use a case study to answer the question which of the methods provides better results. As a case study will be used time series of US Gross Domestic Product. It starts in 1966 and ends in 2014. The future development of the variable for the following 20 years will be calculated. Software Statistica 12 developed by Dell corporation will be used for both analyses. The first one will use multiple regression of the software. The second one will use data mining section with its neural networks. Generalized Regression Neural Networks, Multi-layer Perceptron Network, Radial Basis Function Neural Networks, Linear Neural Networks will by calculated. The results are two curves, the first based on statistic regression analysis. The second curve is provided by the best model of neural networks. Both the curves will describe development of the US GDP in 20 next years.

Financial planning within a company represents one of the basic activities of a company as well as a very demanding activity of the financial manager. Based on the main principles of economy and data from the previous periods (especially main financial statements – balance sheet, profit and loss, cash-flow statement) the future development of the given company is predicted. Different mathematical and statistical models and methods including statistical, causal and intuitive methods are used to carry this out. Some models, such as artificial neural networks, represent a very efficient method for prediction. The article identifies company revenues as the initial indicator in setting a compan´s financial plan. Multilayer perceptron neural networks are very often used for their prediction. Information on Hornbach Company´s Profit and Loss Statement from the period of 1999 to 2015 is used as input data. A total of 1000 artificial neural networks is generated, out of which 5 most appropriate are maintained. Sensitivity analysis is also carried out. The contribution finally states that in practice, the suggested neural structures are useful for compiling a company financial plan which is always derived from the amount of sales.

This article differentiates the euro-economies in terms of the degree of synchronization with the cyclical position of Germany perceived herein as a hegemon economy. The purpose of this study is the identification of the euro-economies that can be identified as an effective monetary area in terms of similarity in economic structure with German economy. The cyclical position is expressed as an average of absolute values of differences of the output gaps between euro-countries and Germany. This procedure is supplemented by correlation and comparative analysis and with the assessment of empirical findings. Two groups are identified according to similarities in cyclical positions. Similar economic performance was ascertained in Austria, Belgium, France, Luxembourg, the Netherlands, and Finland, the economies of which are thus labeled as an effective currency region in the sense of optimum currency area. The assessment of the future development in Eurozone is made taking into account the current political and economic circumstances and the outputs of empirical analyses.

This paper provides a comprehensive method for the evaluation of a company. Specifically, it concerns the prediction of the viability of Czech construction companies. The construction industry is a very specific industry. This is primarily due to the nature of the product. The use of many production factors to convert to a farm (a house, a factory building, etc.) is assumed. Each contract of a construction company (apart from the exceptions) is usually unique. In addition, the field produces long-term assets. As the generic name suggests, the product is used by a consumer (a household or firm) over a long period of time. Such a product is seen to some extent as a consumer one in the consumer market. However, it enters the market of production factors in the form of fixed assets. Due to this fact, construction is usually a field which first inhibits its activity and suffers a loss in times of crisis. On the other hand, it also becomes the first field which enters a phase of growth after a crisis period. The offered method is not only a suitable tool for managers of individual companies, but it may indicate the stage of the economic cycle in the particular country or in a particular market at ta correct selection of those monitored companies. The methodology of the formation in an offered model is applicable not only in the Czech Republic but it is also transferable to other countries in Europe and the world, where it will also be able to take into account the specifics of local markets, too, after its application.

The study deals with the development of the civil engineering industry in the Czech Republic from 1998 to 2011. It should be mentioned that civil engineering is usually the first industry that is affected when it comes to an economic crises. The improvement of outcomes of the civil engineering industry on the contrary indicates the improvement of the entire economy of the country. The study doesn’t asses only civil engineering in the Czech Republic in its entirety but rather reveals the regional disparities at the level of individual regions. In this issue a bankruptcy model was selected as an indicator – Taffler’s index. Taffler’s index has an advantage when it is compared to e.g. Altman’s index, because it doesn’t gauge only the inclination of the company to come to extinction or to preservation but it is able to appreciate any appropriate level of credibility of the company.

The paper deals with bankruptcy models generated by multiple discriminant analysis. It evaluates their design. It addresses the shortcomings by which such bankruptcy models (especially Altman’s indexes) feature. The conclusion is then focused on the possibility of application Altman’s indexes in the Czech Republic. It respectively, offers two options for correction of existing indices, which could increase their explanatory value. It’s just necessary to assess the depth of the correction to the applicable bankruptcy model and its relevant information value.

Experts as well as uninitiated public often call for more simple methods of company evaluation, respectively the assessment of the financial health of the company. Currently, there are many methods that enable to identify the financial situation of the company. It is primarily the assembling of the financial ratios of Schmalenbach’s society (Synek, 2009, 2010), the assembling of so called new indicators that attempt to evaluate the company financial health within the one simple value (added economic value, added market value and others), and assembling of methods of the complex evaluation of an enterprise based on ratio indicators. Financial Analysis by Schmalenbach’s society is built on exact inputs (unfortunately features of the past), but interpretation of the results is very complicated and based on the recommendations and experiences of the evaluator. In relation to the interpretation of results, this financial analysis of financial ratios can be assessed as a benchmarking model. The second group of indicators has a very simple informative value – the result is given as one number, which can be apprised totally objectively by evaluator. The input data are derived from the degree of the risk in most such methods, and therefore distorted by the subjective perspective of the evaluator or of expert view of agencies. The last group (Altman’s index, IN indexes, and others) are built on the mutual relation of ratios indicators and of development of business environment at the time of creation of each method. There is currently no method or system of methods that would give a totally reliable and easily interpretable result. The paper will focus the third group of indicators and will analyse the deficiencies that predispose the selected methods to fail in today’s business environment.

The contribution concentrates on a special form of food sale. It solves several attributes of connection of food sale and electronic commerce. Firstly it describes experiences got by foreign companies like Tesco or Ahold – leaders of food commerce. Strategies and achievements in the field of electronic commerce of theirs were introduced.Following part of the work is devoted to leading Czech e-shops. Vltava e-shop and e-shops of its group (Cybex.cz and others) were assessed. Several market researches were introduced (about number of internet accesses in the Czech Republic, about time dedicated to PC and internet, knowing e-commerce or its use in practice). In the last part of the first section are mentioned foreign e-shop targeting Czech e-commerce market.In the third part are advantages of e-shopping summarized. Time saving, opening time, goods comparisons are briefly mentioned.The application part was aimed to Jednota’s future e-shop. That means that existing retail chain was chosen. So the foundation of e-shop is rather easier. Than the assortment of Czech e-shops was described, especially in connection with customers’ preferences. Customers’ shopping behavior was exa­mi­ned. So possible ways out could be founded.Following part takes care of implementation of food e-shop. Supply, logistic solution, payment solution, strategy of gaining and maintenance customers, contracting, information technologies, solutions and investment return were mentioned or solved.Results of the contribution are summarized in the conclusion. Relationship between theory of e-commerce and its application was highlighted as a necessary condition of its functioning in real world.