Effectiveness of Knowledge Economy Determinants: Case of Selected EU Members

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F17%3A39910845" target="_blank" >RIV/00216275:25410/17:39910845 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Effectiveness of Knowledge Economy Determinants: Case of Selected EU Members

Popis výsledku v původním jazyce

Nowadays, economic actors more frequently force to seek new sources of competitive advantage – usually knowledge, to help to build the competitive advantage and sufficiently set them apart from the competition. Therefore, we can see a shift from traditional resources, such as work, land, and capital towards knowledge and its use, especially from hard factors (e.g., infrastructure) towards soft (intangible) factors such as local atmosphere, synergetic effects, human capital, and knowledge assets. However, most countries fail in their attempt to become knowledge or knowledge-based economies and they are not effective during the processes of knowledge creation, use, dissemination and commercialization. We can see a lack of studies analysing and comparing countries´ efficiency during this processes at EU 28 level. We fill this gap and evaluate the efficiency of these processes by using determinants of knowledge economy within EU 28 countries. These determinants are divided into four drivers (pillars) such as: (i) economic incentive and institutional regime, (ii) educated and qualified workers, (iii) an effective innovation system, and (iv) information infrastructure. For our analyses, we used Data Envelopment Analysis which is commonly used for evaluating the effectiveness and productivity of comparable production units based on the size of inputs and outputs. Results show that most of European countries are not effective in the processes of using determinants of knowledge economy (mainly financing of research and development). The main advantage of our research is that, the Data Envelopment Analysis provides practical implications (for each country) on how to improve and how to change inputs and outputs to become efficient. As a data source, we use data from Eurostat databases.

Název v anglickém jazyce

Effectiveness of Knowledge Economy Determinants: Case of Selected EU Members

Popis výsledku anglicky

Nowadays, economic actors more frequently force to seek new sources of competitive advantage – usually knowledge, to help to build the competitive advantage and sufficiently set them apart from the competition. Therefore, we can see a shift from traditional resources, such as work, land, and capital towards knowledge and its use, especially from hard factors (e.g., infrastructure) towards soft (intangible) factors such as local atmosphere, synergetic effects, human capital, and knowledge assets. However, most countries fail in their attempt to become knowledge or knowledge-based economies and they are not effective during the processes of knowledge creation, use, dissemination and commercialization. We can see a lack of studies analysing and comparing countries´ efficiency during this processes at EU 28 level. We fill this gap and evaluate the efficiency of these processes by using determinants of knowledge economy within EU 28 countries. These determinants are divided into four drivers (pillars) such as: (i) economic incentive and institutional regime, (ii) educated and qualified workers, (iii) an effective innovation system, and (iv) information infrastructure. For our analyses, we used Data Envelopment Analysis which is commonly used for evaluating the effectiveness and productivity of comparable production units based on the size of inputs and outputs. Results show that most of European countries are not effective in the processes of using determinants of knowledge economy (mainly financing of research and development). The main advantage of our research is that, the Data Envelopment Analysis provides practical implications (for each country) on how to improve and how to change inputs and outputs to become efficient. As a data source, we use data from Eurostat databases.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

50601 - Political science

Projekt

<a href="/cs/project/GA17-11795S" target="_blank" >GA17-11795S: Modelování dynamiky determinantů národní a regionální produktivity založené na znalostních a kooperačních efektech</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 18th European Conference on Knowledge Management (ECKM 2017)

ISBN

978-1-911218-49-4

ISSN

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e-ISSN

neuvedeno

Počet stran výsledku

8

Strana od-do

825-832

Název nakladatele

Academic Conferences and Publishing International

Místo vydání

Reading

Místo konání akce

Barcelona

Datum konání akce

7. 9. 2017

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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