Analysis of knowledge-based economy impact on economic development in the European Union countries

Directions of changes in the world economy occurring in recent years show the transition from industrial era economy to knowledge-based economy. Increasing investments in fixed assets is no longer a sufficient way of ensuring permanent economic growth. Research-development activity, innovation and human capital become decisive factors of development. As an essential determinant of the innovativeness level of individual economies are considered expenditures on research and development designed to conduct basic, applied research and development activities as well as effects of these research appearing in the form of innovations. The objective of the article is to analyze correlative connections between the two main variables describing knowledge-based economy, that is between the share of R&D expenditures in GDP and R&D expenditures per capita, and the remaining characteristics of knowledge - based economy. Another aim of the article is to assess the impact of these two variables on the basic macroeconomic indicators in the European Union countries, and, connected with them, to analyze the impact of knowledge-based economy on economic development of these countries.Celem artykułu jest analiza związków korelacyjnych między dwiema głównymi zmiennymi opisującymi gospodarkę opartą na wiedzy, tj. między udziałem nakładów na B+R w PKB i nakładami na B+R per capita, a pozostałymi charakterystykami GOW, jak również ocena wpływu tych dwu zmiennych na podstawowe wielkości makroekonomiczne w krajach Unii Europejskiej, a co za tym idzie analiza wpływu gospodarki opartej na wiedzy na rozwój gospodarczy tych krajów

Knowledge creation, knowledge impact and knowledge diffusion: how do they connect with higher education?

Knowledge-based economy causes changes in the higher education system: university graduates must have the ability to constantly learn and improve their skills, generate and disseminate new knowledge, form and multiply the knowledge capital of business. This paper aims to investigate a pairwise interconnection between higher education indicators and sets of parameters characterizing knowledge creation, impact, and diffusion. The following higher education indicators are used: expenditure on education, tertiary enrollment, graduates in science and engineering, tertiary inbound mobility, researcher, gross expenditure on R&D, top 3 global corporate R&D investors, top 3QS university ranking. Knowledge creation indicators are patents by origin, PCT patents by origin, utility models by origin, scientific and technical articles, citable documents, H-index. Knowledge impact is characterized through labor productivity growth, new businesses, software spending, ISO 9001 quality certificates, high-tech manufacturing. Knowledge diffusion parameters include intellectual property receipts, production and export complexity, high-tech exports, ICT services exports. The information base of the study is the data of the Global Innovation Index Report from the World Intellectual Property Organization for 40 European countries (selected depending on the availability of statistics) for 2022, research method – Canonical Correlation Analysis. The strongest positive correlation was found between higher education indicators and knowledge creation parameters. The second position takes connection between higher education indicators and knowledge diffusion parameters, the third – between higher education indicators and knowledge impact indicators. Among the higher education indicators, the most significant were gross expenditure on R&D, top 3 global corporate R&D investors, top 3 QS university ranking

The knowledge economy and Dutch cities

How can cities and metropolitan regions remain prosperous and competitive in a rapidly changing economy? In our paper we argue that ‘the knowledge economy’ offers perspectives for growth and added value creation. The paper clarifies what elements the knowledge economy actually consists of, how it can be measured in statistical indicators, in which regions and cities in the Netherlands the knowledge economy has its most significant imprints and what statistical association there is between these regions and cities and relatively good economic performance of firms. We test two contrasting hypotheses often heard in the international literature. The current embedding of knowledge externalities in endogenous economic growth theory have led to important contributions that stress the urban character knowledge transmission in particular. The reasoning is that if knowledge spillovers and –externalities are important to growth and innovation, they should be more easily identified in cities where many people are concentrated into a relatively small geographic space so that knowledge can be transmitted between them more easily. Much recent research indeed finds a limited extent of spatial spillovers and a large degree of local clustering. Alternatively, a large body of literature on Western spatial configurations of innovation and high-technology firms predominantly stresses the supposed ‘urban field’ character of firm performance: location and agglomeration aspects do not seem to have a systematic impact on the distribution of innovative and growth inducing activities over space. We test the urban hypothesis using spatial econometric modeling techniques. On the one hand, the fact that a distance squared distance weight matrix in spatial lag estimations fits the performance data best in relation to knowledge economy factors indicates that spatial relations are limited and urban fixed. On the other hand, the significance of several spatial regimes though (especially those of the Randstad core region, the so-called intermediate zone and medium-sized cities) indicates that the urban structure related to the knowledge economy and economic performance is not straightforward hierarchical (largest cities are not the relatively most attached to the knowledge economy). Both hypotheses (urban and non-urban) are too extreme to fit the Dutch situation. We also conclude that the locational attributes of the factor ‘knowledge workers’ are much more significantly related to economic growth and added value (in practically all specifications over regimes and spatial lag estimations) than the R&D-based innovation input factor. This questions Dutch policy initiatives that mainly focus on R&D as stimulator of the ‘knowledge economy’.

Impact Of Fiscal Policy On Economic Development In Ukraine

The paper aims on assessing the impact and efficiency of fiscal policy instruments for gaining macroeconomic goals in transition economies. For this reason the macroeconomic model of the Ukrainian budgetary sector is developed. The model represents interrelations between the budgetary sector and real economy reflecting the way financial resources are redistributed through the budgetary system. The model serves as a basis for scenario analysis of different types of fiscal policy and their effect on economic indicators. It also allows for forecasting budgetary revenues in order to compose an efficient budget estimates. The results of the research prove that in transition economy such as Ukrainian the channel of tax rate on personal income tax is more efficient from fiscal point of view than the one on enterprise profit tax, while reallocation of resources between budgetary transfers to population and R&D is more efficient than increasing budget expenditures. Since increase in expenditures influences higher increase in GDP, the model proves Keynesian effects in the economy of Ukraine

The role of small and medium enterprises in innovation activities in Kazakhstan = Kis és középvállalkozások szerepe az innovációs tevékenységekben Kazahsztánban

This article is about the fact that there are certain factors that have a huge impact on the activities of small and medium-sized enterprises in innovation on the example of the Republic of Kazakhstan. Indicators of SMEs are reflected in the economy of the people and their country. The author used statistical analysis of indicators of innovation-based growth in the Republic of Kazakhstan. Moreover, these figures were compared to those of developed countries, which were involved in such indicators as the share of innovation of active enterprises, domestic expenditure on R&D (as a percentage of gross domestic product). According to the survey the key factors that have a major impact on innovation by SMEs were identified

The role of small and medium enterprises in innovation activities in Kazakhstan = Kis és középvállalkozások szerepe az innovációs tevékenységekben Kazahsztánban

This article is about the fact that there are certain factors that have a huge impact on the activities of small and medium-sized enterprises in innovation on the example of the Republic of Kazakhstan. Indicators of SMEs are reflected in the economy of the people and their country. The author used statistical analysis of indicators of innovation-based growth in the Republic of Kazakhstan. Moreover, these figures were compared to those of developed countries, which were involved in such indicators as the share of innovation of active enterprises, domestic expenditure on R&D (as a percentage of gross domestic product). According to the survey the key factors that have a major impact on innovation by SMEs were identified

R&D Expenditures: comparative analysis between Serbia and selected countries

R&D expenditures are one of the key indicators of the success in innovation process. Successful transformation of R&D expenditures into some form of technological innovation creates a stable basis for sustainable profitability and competitive advantages of the company, which have a positive impact on the growth of the entire economy. Due to the role of R&D expenditures in achieving success at the country and firm level, the subject of research in this paper is a comparative analysis of R&D expenditures between Serbia and selected countries. The aim is to examine the situation in Serbian R&D area in the context of R&D expenditures, in comparison with, first of all, the countries from the environments of the Serbia, which are the EU members. The survey coveres the period 2008 – 2016. Results show that Serbia has a significantly higher GERD (%GDP) than all countries, except Slovenia and Hungary, while Croatia has insignificantly higher GERD then Serbia. All countries from the Serbian environment that are members of the EU have significantly higher BERD (%GDP) than Serbia, except Romania, which has insignificantly higher BERD than Serbia

Human Rights in the Least Developed Countries of Asia: An Index for Quantifying Sustainable Development Goal 3 (Good Health and Wellbeing)

This paper aims to measure disparities among the variables associated with Sustainable Development Goal (SDG) 3 defined by the United Nations (UN) in the least developed countries (LDCs) of Asia. In the terms of the UN Conference on Trade and Development, LDCs are countries with profound economic and social inequalities. The indicator was constructed using a set of variables associated with SDG3: Good Health and Wellbeing. Applying Pena’s DP2 distance method to the most recent data available (2018) enables regional ordering of Asia’s LDCs based on the values of these variables. The index integrates socioeconomic variables that permit examination of the impact of each individual indicator to determine territorial disparities in terms of the partial indicators of SDG3. “Maternal education,” “Proportion of women who make their own informed decisions regarding sexual relations, contraceptive use, and reproductive health care,” and “Gender parity index in primary education” are the most important variables in explaining spatial disparities in good health and wellbeing in the LDCs of Asia.R&D&I Research Project REINAC- “Reintegration and support processes for women on temporary release”, Reference EDU2016-79322-R (2016–2020)Spanish National Plan for Research, R&D&I Research Projects, the Spanish Ministry of Economy and Competitiveness (MINECO)State Research Agency (AEI)FEDER, SpainMinistry of Economy, Industry and Competitiveness of SpainState Research Agency (SRA)European Regional Development Fund (ERDF), grant number ECO2017-86822-RRegional Government of Andalusia and the European Regional Development Fund (projects P18-RT-576 and B-SEJ-018- UGR18);University of Granada (Plan Propio. Unidad Científica de Excelencia: Desigualdad, Derechos Humanos y Sostenibilidad (DEHUSO)

The Impact of Entrepreneurs\u27 Characteristics on the Performance of Venture Businesses

In South Korea, venture businesses play a key role in commercializing new technology and revitalizing the economy. The Korean government implements various policies and supporting programs directly. Evaluating the possibility of future growth and selecting good venture business is very important for the effectiveness and efficiency of government programs supporting venture businesses. There have been many studies aimed at finding the factors affecting the success of venture businesses, and entrepreneurs‟ characteristics are known as the major factor. In this study, the impact of entrepreneurs‟ characteristics on the performance of venture businesses is analyzed by using the survey data of 2,049 Korean venture businesses. Human capital and demographics, skill, and motivation of entrepreneurs are used as independent variables to measure the general and financial performance of venture businesses. The results of regression analysis show that education of entrepreneurs positively affects the size, innovativeness, and net sales of venture businesses. In contrast, entrepreneur‟s skills, such as entrepreneurial experience and working experience show a negative impact in general. Networking activity, however, shows a positive impact on the size and innovativeness of venture businesses. R&D activity shows positive impact only on the innovativeness, but significantly negative impact on the size and net sales of venture businesses, and external funding has a positive impact on all of indicators of the performance of venture businesses. These results suggest that we need to consider the several factors, such as education, networking, and external funding in the evaluation process, and promote networking and cooperation with others in order to increase the effectiveness and efficiency of programs