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The importance of human and social capital in the processes of growth and economic development has been broadly discussed in the literature. There are many theoretical models of economic growth considering human or social capital. However, there is still a shortage of empirical studies concerning the dependencies between these phenomena. The purpose of this study is to examine the role which human and social capital play in the processes of economic development in the European Union countries. Empirical analysis concerns the year 2015. Owing to the fact that neither of these categories is measurable, the research uses the soft modelling method. It allows users to examine links between variables which are not directly observable (latent variables). The conducted research has demonstrated that human capital as well as social capital had statistically significant, positive impact on the economic development of the EU countries. The obtained results also made it possible to create the rankings of the examined countries according to their stocks of human and social capital and the level of economic development. ; O značaju ljudskog i društvenog kapitala u procesima rasta i ekonomskog razvoja se široko raspravljalo u literaturi. Postoji mnogo teoretskih modela ekonomskog rasta koji uključuju ljudski ili društveni kapital. Međutim, i dalje postoji nedostatak empirijskih studija koje proučavaju zavisnosti između ovih pojava. Svrha ove studije je da ispita ulogu koju ljudski i društveni kapital igra u procesima ekonomskog razvoja u zemljama Evropske unije. Empirijska analiza se odnosi na 2015. godinu. Zbog činjenice da nijedna od ovih kategorija nije merljiva, istraživanje koristi metod mekog modeliranja, koji omogućava korisnicima da ispitaju veze između varijabli koje se ne mogu direktno posmatrati (latentne varijable). Sprovedeno istraživanje je pokazalo da ljudski kapital kao i društveni kapital imaju statistički značajan, pozitivan uticaj na ekonomski razvoj zemalja EU. Dobijeni rezultati su takođe omogućili ...

Social capital according to OECD definition is networks together with shared norms, values and understandings that facilitate co-operation within or among groups. Currently, social capital is identified as a one of the key factors of economic development. Most of the existing literature focuses on the role of social capital for economic growth, meanwhile the purpose of this study is to examine the role which social capital plays in the processes of smart growth in the EU countries. Smart growth is based on knowledge and innovation. The notion of smart growth, its factors and measuring methods are new categories which emerge from the concept of EU's strategic development objectives. The study uses a soft modelling method which allows for measuring and analysis of the relationships among unobserved variables (latent variables).

The knowledge-based economy is an economy where knowledge is created, acquired, transmitted and used effectively by businesses, organizations, individuals and communities. It is not narrowly focused on the industries of advanced technology or ICT, but provides a framework for analysing the range of policy options in education, information infrastructure and systems of innovation, which could help contribute to the knowledge economy. The aim of the paper is to analyse spatial differences in the level of development of the knowledge-based economy in the European Union countries. The study uses a soft modelling method, which enables the estimation of a synthetic measure of KBE as well as the arrangement and classification of the UE-27 countries into typological groups. The research covers the years 2000 and 2013.

Purpose – The article aims to present the possibility of using PLS-SEM method in research on the innovativeness of EU economies. Research method – Structural equation modeling is a method that allows the study of relationships between variables that are unobservable. The SEM model consists of two sub-models: structural and measurement. Covariance-based (CB) or partial least squares (PLS) methods are used to estimate the model. The choice depends on the empirical context, research objectives, sample size and statistical properties of the data. Due to the small size of the population, the PLS method was used in the study. The models were estimated on the basis of cross-sectional data for 2018 and 2021. Results – The article presents the stages of construction of the PLS-SEM model, from model specification, through estimation, statistical verification, to interpretation of the results. Particular attention is paid to the possibility of formulating conclusions based on various elements of the estimated model. Originality / value / implications / recommendations – PLS-SEM is a relatively new econometric method belonging to the group of second generation multivariate analysis methods. Its dynamic development can be observed especially in management sciences. In the discipline of economics, the method is not widely known and used, but it has great potential and can be useful in the study of relationships between unobservable categories. The empirical research presented in the article fills the cognitive gap in the use of advanced econometric methods in economic research.

Purpose: The article aims to assess the extent to which International Technology Transfer (ITT) can influence the innovation level of European Union (EU) countries and, as a result, accelerate their economic development. This is vital from the point of view of the developing countries which are striving to narrow the development gap as rapidly as possible. Design/Methodology/Approach: The study uses a soft modelling method which makes it possible to measure and analyse the dependencies between variables than cannot be directly observed, i.e. latent variables. The soft model consists of two sub-models: an internal one, describing the relationships between the latent variables, and an external one, characterising the latent variables by means of observable variables. The statistical data used for estimating the model come from Eurostat, the World Bank, and the European Innovation Scoreboard database and span the years 2008-2017. Findings: The results of the modelling indicated a positive impact of ITT on innovation levels in EU countries and a positive impact on both ITT and innovation levels on the economic development of the studied countries in the period 2008-2017. The influence of innovation levels on economic development proved to be stronger than the influence of ITT. Practical Implications: The results of the conducted study can have a practical application and serve as an instrument of innovation policies, industrial policies, or as a tool helpful in creating conditions for innovation systems. Originality/Value: The article points to the methods and extent of gaining knowledge and technologies as prerequisites of higher innovativeness of EU countries, which constitutes an original approach to technological processes as a component of economic development. ; peer-reviewed

Purpose: The broadening of the concept of intellectual capital from the micro level to the macro level presents a challenge for contemporary researchers. No universal definition of national intellectual capital (NIC) or its taxonomy have been developed as yet. This hampers empirical research on measuring NIC resources, thus rendering it difficult to make cross-sectional and temporal comparisons. Therefore, methods are being sought to allow for estimating the volumes of intellectual capital on a macroeconomic level. The purpose of the article is to present an original concept of measuring NIC in the European Union (EU) countries, construct a synthetic measure of NIC on the basis of TOPSIS method, and create a ranking and classification of the EU countries in terms of their NIC resources. Design/Methodology/Approach: The study uses TOPSIS, which is a multi-criteria decision-making method. Findings: The obtained results reveal strong disparities between the EU countries as regards NIC resources. They confirm, moreover, the existence of high intellectual capital resources in the countries of Northern Europe. Practical Implications: The outcomes of the conducted study and its conclusions can be used by decision-makers, both at the EU level and in particular countries. They can also serve as an instrument for bolstering the policies and practices promoting a holistic approach to socio-economic development. Originality/Value: The article contains an original author's concept of measuring NIC resources, which can be applied to cross-sectional and temporal comparisons across EU countries. ; peer-reviewed