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The chapter describes the emergence of the profession in Czechia. The major driver for universities and research and technology organisations (RTOs) was the country’s accession to the European Union (EU) in 2004. The country has a rich system of national research, development, and innovation (R&D&I) funding and EU Framework Programmes are witnessing a slowly growing interest and success of Czech researchers.¹ Yet, the major force in changing the research management and administration (RMA) culture and addressing the need of professionalising the environment of research administration, management, intellectual property rights, and technology transfer (TT) was European Structural and Investment Funds (ESIF). The Czech government repeatedly, through four EU programming periods, stressed the need for investments to reshape the research infrastructure, environment, and conditions on a scale not experienced by the universities or the RTOs ever before. The availability of EU funds and increasing emphasis on international cooperation enabled Czechia to witness slow, yet steady growth of demand to deliver better service in the field of RMA. This is illustrated through several EU-funded projects focussed on RMA skills development and the recent establishment of the Czech Association of Research Managers and Administrators (CZARMA) in 2022 (Masaryk University, 2022a).

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.

This study aims to examine the hysteresis hypothesis in unemployment using monthly data from 13 countries in transition.

Stationarity in the unemployment rate of selected transition economies was analyzed using four different group unit root tests, namely, linear, structural breaks, non-linear and structural breaks and non-linear.

The empirical results show that the unemployment hysteresis hypothesis is valid for the majority of transition economies, including Bulgaria, Croatia, the Czech Republic, Estonia, Hungary, the Kyrgyz Republic, Latvia, Lithuania, Poland, Romania and Slovenia. However, the results strongly reject the null hypothesis of unemployment hysteresis for the Kazakhstan and the Slovak Republics.

This study revealed that, for countries in transition, advanced unit root tests exhibit greater validity when compared to standard tests

This paper aims to identify the changes in the share of large public interest entities (PIEs) in European Union (EU) Member States providing Sustainable Development Goal (SDG) reporting prior to (2017) and after (2019) the implementation of Directive 2014/95/EU and the factors that influence their decisions to provide SDG reporting in 2019.

The authors use the multilevel theory of social change in organizations as the theoretical background. The sample consists of 341 PIEs based in the EU Member States, for which reports published in 2017 and 2019 are available in the global reporting initiative sustainability disclosure database. The authors analyzed the data using the statistical significance test of equal proportions and the logistic regression model.

The study findings allow to identify a significant positive change in the share of companies providing a reference to SDGs in 2019 compared with 2017. The research confirms that companies’ engagement in United Nations Global Compact and previous experience in sustainability reporting positively influences the decision to report on SDGs in 2019. Contrary to the expectations, industry, size, SDG implementation score, future orientation of government and corporate governance score do not seem to be relevant factors influencing PIEs’ disclosures.

The paper adds to the understanding of the differences in SDG reporting within the EU, which is seen as a frontrunner in implementing the 2030 Agenda and the SDGs.

This study examines the role of behavioural factors, such as confidence, optimism, pessimism and rational expectation, in affecting investment decisions in the Pakistani stock market.

Using daily trading data of Karachi Stock Exchange-100 index from January 2012 to December 2015, different regression models, including descriptive statistics and stationarity tests, are performed.

Results indicate that stock market trading has suffered from pessimistic behaviour of investors. In the first model, the authors find a positive sign of confidence and negative sign of optimism with the trading volume. The second model shows a positive role of confidence and rational expectations in affecting the trading volume in daily, Monday and Friday samples. The results of the third model show a negative sign of both optimism and rational expectation with the trading volume. Furthermore, the next model shows a negative sign of confidence combined with pessimism while testing their relationship with the trading volume. Finally, results of the final model suggest that optimism negatively affects the trading volume, and on the other hand, pessimism has a positive impact on the trading volume.

The method and empirical testing of behavioural biases and their relationship with economic variable used in this study seem to be a promising way to better understand the role of psychology in deriving financial decisions for academics and policymakers.

This study uses secondary data for measuring behavioural biases and decomposes the effect between rational expectation and behavioural biases.

This study examines Covid-19-related policies as a showcase for priorities in migration governance, the role of the state and employers’ associations, as well as gaps in social security and social protection.

This paper looks at how immigration interacts with the labour market in the Czech Republic through the prism of the varieties of capitalism framework and its relation to the concepts of labour market segmentation and flexibility.

The findings show that pandemic-related measures focused on continuously adjusting a legislative framework granting access to third-country workers. However, protective measures that would guarantee migrant workers and their families access to social rights, such as healthcare, were lacking. In this context, several lines of segmentation are observed: between migrant workers in standard employment and those in non-standard employment, when looking at their access to healthcare; between migrants hired directly by employers and those working through temporary agencies in terms of their wages, stability and protection; and, at a sectoral level, between the skilled workforce and migrants that are pushed to low-qualified poorly paid, and routinised jobs.

This paper expands the existing literature on the preferences and influence of governments, employers and trade unions regarding the demand for foreign labour in varieties of capitalism by adding the perspective of a Central European economic model. At the same time, its findings contribute to the understanding that labour market inequalities are not fostered on the supply side of migrant labour, through exogenous societal or cultural characteristics specific to countries of origin, but rather through institutionalised measures, practices and policies in countries of destination.

The study aims to analyse library user preferences in the willingness to read and pay for e-books, using a sample of both active readers (users of public library services) and non-users (the general population).

Two empirical surveys were conducted from August to November of 2019; the research sample consisted of 1,334 users from the Municipal Library of Prague and 1,101 non-users from the general Czech population. The research was focussed on e-book user preferences. The willingness to pay (WTP) for e-book services and the determinants that affect this willingness were also examined.

The results show the specific approach of Czech readers, whose main determinant of WTP is not the content, but the price and method of its payment (allocation). Some people prefer a cheaper annual lump sum, whereas others may prefer a charge of small regular fees. The decision to pay depends on their reading or payment habits.

This study also aims to clarify the demand for various types of digital media in Czech libraries and the preferred distribution models. Furthermore, the study determines the dependence of the preferences of library users in their WTP for e-books using different evaluation models. The originality of this study is in the evaluation of the determinants of WTP for e-books, which makes this study unique, and the findings should contribute to the expansion of existing knowledge in the field of information science.

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.

This study aims to provide a framework for assessing the technical condition of a house to determine its market value, including the identification of other price-setting factors and their statistical significance. Time on market (TOM) in relation to the technical condition of a house is also addressed.

The primary database contains 631 houses, and the initial asking price and selling price are examined. All the houses are located in the Brno–venkov district in the Czech Republic. Regression analysis was used to test the influence of price-setting factors. The standard ordinary least squares estimator and the maximum likelihood estimator were used in the frame of generalized linear models.

Using envelope components of houses separately, such as the façade condition, windows, roof, condition of interior and year of construction, brings better results than using a single factor for the technical condition. TOM was found to be 67 days lower for houses intended for demolition – as compared to new houses – and 18 days lower for houses to refurbishment.

To the best of the authors’ knowledge, this paper is original in the substitution of specific price-setting factors for factors relating to the technical condition of houses as well as in proposing the framework for professionals in the Czech Republic.