Configuration Paths to Efficient National Innovation Ecosystems
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F21%3A39917957" target="_blank" >RIV/00216275:25410/21:39917957 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.sciencedirect.com/science/article/pii/S0040162521002195?dgcid=rss_sd_all" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0040162521002195?dgcid=rss_sd_all</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.techfore.2021.120787" target="_blank" >10.1016/j.techfore.2021.120787</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Configuration Paths to Efficient National Innovation Ecosystems
Popis výsledku v původním jazyce
Efficient National Innovation Ecosystems (NIEs) create appropriate conditions for the generation of new knowledge, collaboration, and innovation, which are key determinants of countries' economic growth and competitiveness in the era of a globalized, knowledge-based economy. Prior studies have therefore focused on measuring both the efficiency of NIEs and key attributes occurring within them. This has led to the assessment of countries in terms of their ability to effectively convert inputs into outputs and has provided a benchmark for less successful economies and their NIEs by using Data Envelopment Analysis (DEA) and its modifications. However, while these methods have measured the efficiency of individual economic entities, they do not show how to achieve this efficiency. Therefore, we propose a novel, hybrid two-step model combining DEA and fuzzy-set Qualitative Comparative Analysis. This enables us to examine the relationships between all possible combinations of inputs and outputs within the NIEs of OECD countries and to identify configuration paths showing how to achieve effective outputs in terms of cooperation, knowledge creation, and innovation. We also show that countries could benefit from multiplication and crowding-in effects emerging from combinations of different R&D expenditures rather than from one financial source.
Název v anglickém jazyce
Configuration Paths to Efficient National Innovation Ecosystems
Popis výsledku anglicky
Efficient National Innovation Ecosystems (NIEs) create appropriate conditions for the generation of new knowledge, collaboration, and innovation, which are key determinants of countries' economic growth and competitiveness in the era of a globalized, knowledge-based economy. Prior studies have therefore focused on measuring both the efficiency of NIEs and key attributes occurring within them. This has led to the assessment of countries in terms of their ability to effectively convert inputs into outputs and has provided a benchmark for less successful economies and their NIEs by using Data Envelopment Analysis (DEA) and its modifications. However, while these methods have measured the efficiency of individual economic entities, they do not show how to achieve this efficiency. Therefore, we propose a novel, hybrid two-step model combining DEA and fuzzy-set Qualitative Comparative Analysis. This enables us to examine the relationships between all possible combinations of inputs and outputs within the NIEs of OECD countries and to identify configuration paths showing how to achieve effective outputs in terms of cooperation, knowledge creation, and innovation. We also show that countries could benefit from multiplication and crowding-in effects emerging from combinations of different R&D expenditures rather than from one financial source.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
50204 - Business and management
Návaznosti výsledku
Projekt
<a href="/cs/project/GA20-03037S" target="_blank" >GA20-03037S: Návrh dynamického znalostního business modelu založeného na principech otevřených inovací</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2021
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
Technological Forecasting and Social Change
ISSN
0040-1625
e-ISSN
—
Svazek periodika
168
Číslo periodika v rámci svazku
July 2021
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
14
Strana od-do
120787
Kód UT WoS článku
000651337500015
EID výsledku v databázi Scopus
2-s2.0-85103948119