Search results

This study aims to supplement the international knowledge on factors determining retention in the teaching profession with findings from the Czech Republic. The study aims to answer the question of what factors on the part of schools and teachers are related to teachers’ decision to leave the teaching profession, either temporarily or permanently. It also examines the differences between teachers at the beginning and end of their professional careers.

This study presents a secondary analysis of the data collected in a survey of 1,230 Czech secondary school teachers implemented in 2021 in the same schools as the TALIS survey in 2018. The longitudinal design makes it possible to observe the impact of school variables on teachers’ willingness to remain in the profession. Data are analysed through logistic regression.

The analysis shows the importance of sufficient financial evaluation, the composition of the student body, instructional leadership, and school innovativeness for the retention of teachers in the profession. The analysis further shows that the factors causing teachers to leave the profession differ for those at the beginning and at the end of their teaching careers.

The limitations of the study lie in the fact that this is a secondary analysis. The questionnaires were not designed in accordance with the aim of our study, and so the variables were constructed from existing data to best fit our chosen framework.

The results of our analysis indicate that the Czech education policy should focus not only on general increases in teachers’ salaries, but also on the adjustment of increases over the course of a teacher’s career. The starting salary may be important for retaining young teachers in the profession, while at later stages in their careers their decision to stay may be more influenced by other factors. Our research also showed the importance of leadership. In schools where the principal supports his or her teachers and takes care of their professional development, teachers have a greater tendency to stay in the profession than in schools where the management does not perform this function.

The study enriched international knowledge about factors affecting teachers' retention in the profession with findings from the Czech educational system characterized by high school autonomy and low teacher salaries.

The aim of this chapter is to examine the nominal and real convergence of Czechia. The importance of the convergence of Czechia with the euro area is linked to the future intention of joining the Economic and Monetary Union after the Maastricht criteria are met. This chapter covers the period from 2004 to 2021. We argue that nominal convergence is relative to the Maastricht criteria, when real convergence focuses on different areas: the Maastricht criteria, gross domestic product (GDP) per capita in purchasing power standards and real GDP growth rate, labour market (minimum labour costs and unemployment rates. Findings suggest that Czechia has reported the strongest real convergence in the area of relative economic level, moderate convergence of labour costs and divergence of unemployment. The nominal convergence analysis suggests that Czechia will not meet the Maastricht benchmarks in the near future and is not ready to join the euro area given its high inflation rate and the state of public finances.

In this article, the authors draw-upon an extended unified theory of acceptance and use of technology (UTAUT) and propose a research model involving performance expectancy (PE), effort expectancy (EE), facilitating conditions (FC) and competitive pressure (CP) as potential salient factors explaining the adoption of digitalization in European SMEs. The authors also postulate that there may be cross-cultural differences, thereby leading us to include the country as a moderator in the model.

The authors validate this model with a cross-cultural sample involving 188 owner-managers from the Czech Republic and Slovakia and through the partial least square structural equation modeling (PLS-SEM) techniques as well as multi-group analysis.

The results using the study’s global dataset indicate that PE, FC and CP significantly affect owner-managers intentions toward digitalization in SMEs. The authors’ application of the multi-group analysis also suggests that although the two countries differ in digitalization adoption intention, the differences are statistically insignificant. In the conclusion, the authors highlight several implications these findings have for theory and practice.

The authors recommend that the providers of emerging digital technologies should improve on the performance features of those technologies and ensure they are relevant to the SMEs. By doing so, the adoption of digitalization will grow, because owner-managers of SMEs will have the confidence that adopting such technologies will improve their operations. Second, SMEs are required to provide adequate organizational and technical infrastructure to support digitalization adoption.

Aside from being among the few attempts to extend the explanatory power of UTAUT with PE, EE, FC and CP in investigating digitalization adoption in SMEs context, this study also validates its model with rigorous methodological approach as well as three datasets (global, Czech Republic and Slovakia) thereby strengthening the validity of the results.

The purpose of this paper is to define the impact of training and development (T&D) in the Visegrad countries (V4) as impacted by the Covid-19 pandemic, namely, Hungary, Poland, Slovakia and the Czech Republic. These countries have some political, cultural, social and economic similarities and share some common ground in the human resource development (HRD) sectors.

The authors used the HRD theory and the human capital theory to analyse the context, operations and impact of T&D in the V4 countries due to the Covid-19 pandemic. The research was conducted in 400 companies, 100 from each of the four countries using the computer assisted web interviewing technique. The questionnaire was in a six-point Likert scale format and addressed 12 topics related to T&D: policy, expectations, procedures of diagnosis, preparation, implementation, monitoring, trainees, trainers, investment and expenditures, evaluation, results and controlling.

The authors concluded that in the Visegrad countries, Covid-19 raised expectations on T&D. This was followed by increased levels of action in diagnosis, preparation, monitoring and implementation, following pre-existing and adjusted policies. Evaluation and control were complicated. Investment and results and the human side of the T&D (trainees and trainers) were the ones for which there were more uncertainties and perplexities.

The study has the limitation of using only a small sample in four countries. For further research, the authors suggest a larger study extended to all the European Union countries, an in-depth analysis of the current data and the kurtosis on Policy of T&D.

The results of the research can be used to improve T&D programs after the Covid-19 pandemic. They could also provide information to external trainers to improve and adjust their services according to the opinions of the respondents of the study. The research findings can also serve institutions responsible for policy provision of HRD at a national level by providing possibilities to apply for funding either within national or regional funds like the National Training Fund in Poland or within European Union money at a national level.

The study is original because even if the T&D in V4 countries during the Covid-19 pandemic had already been studied separately (e.g. Mikołajczyk, 2021; Vrabcová, Urbancová 2021; Vinichenko et al., 2021), no empirical, cross-national research analysing specifically the T&D in those countries has been carried out so far. The authors use an innovative methodology, addressing 12 topics and the people involved together with the stages in which a T&D policy is divided. That makes it innovative and very relevant.

This research contributes to a better understanding of the effects of public demographic and population policy. The study investigates whether a considerable increase in birth grants in 2006 in the Czech Republic resulted in a higher number of births.

To quantify the effects, we work with the administrative, statistical daily data (1993–2016) on the number of births and use time series analysis tools. In particular, we estimate a time series regression model via the ordinary least squares (OLS) technique with robust standard errors, testing placebo effects and the differences between the trend-forecasted values in the absence of the grant change.

Our results, spread over several time windows covering up to a ten-year period after the intervention, show that the intervention significantly and positively affected the number of births in the post-intervention periods. The evidence obtained from the econometric analysis of the time series clearly shows that after the demographic and population policy change, there was an average increase of 17–19 births daily when the data was analysed up to 2016. Therefore, the conclusion is that the policy intervention led to expected and desired policy outcomes.

The study provides the stakeholders and policymakers with an experience of the public policy aiming to support fertility, which has reached its expectations.

In this chapter, we aim to analyze the housing market development in Czechia, in particular the development of housing prices over the last 25 years. We quantify and discuss three distinct periods of excessive growth of regional Czech housing prices, identified through the formation of large positive GAPs – (1) before the entrance of Czechia to the European Union (EU), (2) at the onset of the Global Financial Crisis GFC, (3) in 2021. In all these periods, we identify significant differences among regions. We find that GAPs above 15% may be considered an indication of unsustainable long-term housing price growth that will be followed by a correction.

We then employ fixed effect panel data model to determine the drivers of flat and house prices in 14 Czech regions. Our results show that wage growth, migration and crime rate are significant factors affecting the prices of both flats and houses. Nevertheless, the impact of GDP per capita and job market indicators differs between flats and houses. Moreover, we find that higher migration into the region increases the difference between the prices of houses and flats, while increasing GDP per capita growth and crime rate mitigate this difference significantly.

The aim of this paper is to determine the thermal conductivity of a protective layer of alkali-activated cement and the possibility of performing fire protection with fireclay sand and Lightweight mortar. Unprotected steel structures have generally low fire resistance and require surface protection. The design of passive protection of a steel element must consider the service life of the structure and the possible need to replace the fire protection layer. Currently, conventional passive protection options include intumescent coatings, which are subject to frequent inspection and renewal, gypsum and cement-based fire coatings and gypsum and cement board fire protection.

Alkali-activated cements provide an alternative to traditional Portland clinker-based materials for specific areas. This paper presents the properties of hybrid cement, its manufacturability for conventional mortars and the development of passive fire protection. Fire experiments were conducted with mortar with alkali-activated and fireclay sand and lightweight mortar with alkali-activated cement and expanded perlite. Fire experiment FE modelling.

The temperatures of the protected steel and the formation of cracks in the protective layer were investigated. Based on the experiments, the thermal conductivities of the two protective layers were determined. Conclusions are presented on the applicability of alkaline-activated cement mortars and the possibilities of applicability for the protection of steel structures. The functionality of the passive fire layer was confirmed and the strengths of the mortar used were determined. The use of alkali-activated cements was shown to be a suitable option for sustainable passive fire protection of steel structures.

Eco-friendly fire protection based on hybrid alkali-activated cement of steel members.

Government communication is an essential part of the democratic process – it interconnects various stakeholder groups with the public, while also enabling the functioning of democratic systems based on values such as human rights, freedom of speech and public participation in governance. Besides promoting government successes or measures, government communication should foster mutual two-way communications between government organisations and different stakeholder groups. Specifically, communication about potential risks and hazards can suddenly appear and are subject to a different communication modus operandi. The accessibility and comprehensiveness of government information play an important role in how citizens make decisions and behave. In critical times, governments are required to meaningful crisis communication strategies to address the needs of different stakeholders. However, the Czech Republic as a post-communist country has not yet fully developed an integrated system of government communication with various stakeholder groups. The ministerial PR departments serve merely as technical support and media relations assistants for the ministers. This chapter presents research results regarding how the Czech Ministry of Education communicated during the pandemic crisis, how its communications were received by key stakeholders, and what pitfalls in communication it faced. The chapter presents empirical evidence of government communication challenges in times of crisis in a post-communist country and thus addresses the gap in government communication knowledge concerning the role of democracy and stakeholder participation in transforming societies. The chapter concludes with practical implications to prevent failures in future crises.

The primary purpose of this paper is to identify the so-called core authors and their publications according to pre-defined criteria and thereby direct the users to the fastest and easiest way to get a picture of the otherwise pervasive field of bankruptcy prediction models. The authors aim to present state-of-the-art bankruptcy prediction models assembled by the field's core authors and critically examine the approaches and methods adopted.

The authors conducted a literature search in November 2022 through scientific databases Scopus, ScienceDirect and the Web of Science, focussing on a publication period from 2010 to 2022. The database search query was formulated as “Bankruptcy Prediction” and “Model or Tool”. However, the authors intentionally did not specify any model or tool to make the search non-discriminatory. The authors reviewed over 7,300 articles.

This paper has addressed the research questions: (1) What are the most important publications of the core authors in terms of the target country, size of the sample, sector of the economy and specialization in SME? (2) What are the most used methods for deriving or adjusting models appearing in the articles of the core authors? (3) To what extent do the core authors include accounting-based variables, non-financial or macroeconomic indicators, in their prediction models? Despite the advantages of new-age methods, based on the information in the articles analyzed, it can be deduced that conventional methods will continue to be beneficial, mainly due to the higher degree of ease of use and the transferability of the derived model.

The authors identify several gaps in the literature which this research does not address but could be the focus of future research.

The authors provide practitioners and academics with an extract from a wide range of studies, available in scientific databases, on bankruptcy prediction models or tools, resulting in a large number of records being reviewed. This research will interest shareholders, corporations, and financial institutions interested in models of financial distress prediction or bankruptcy prediction to help identify troubled firms in the early stages of distress.

Bankruptcy is a major concern for society in general, especially in today's economic environment. Therefore, being able to predict possible business failure at an early stage will give an organization time to address the issue and maybe avoid bankruptcy.

To the authors' knowledge, this is the first paper to identify the core authors in the bankruptcy prediction model and methods field. The primary value of the study is the current overview and analysis of the theoretical and practical development of knowledge in this field in the form of the construction of new models using classical or new-age methods. Also, the paper adds value by critically examining existing models and their modifications, including a discussion of the benefits of non-accounting variables usage.