Efficiency of National Innovation Systems – Poland and Bulgaria in The Context of the Global Innovation Index

Jankowska, Barbara; Matysek-Jędrych, Anna; Mroczek-Dąbrowska, Katarzyna

doi:10.1515/cer-2017-0021

Cited by 37 publications

(27 citation statements)

References 38 publications

(23 reference statements)

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“…Heterogeneous results were produced in terms of the full integration of these economies into the framework of competitiveness stated in the Europe 2020 strategy. Using the GII, Jankowska et al (2017) described what can be understood by the term 'innovation', and they also explained how national innovation systems may transform innovation inputs into innovation outputs. Analysis of comparative innovative advantages was performed by Vlasova et al (2017).…”

Section: Literature Reviewmentioning

confidence: 99%

The evaluation of competitive position of EU-28 economies with using global multi-criteria indices

Kiseľáková

Šofranková

Onuferová

et al. 2019

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Research background: Under the current conditions of increasing competitiveness and interdependence, national economies are more influenced by the global business environment and its development. Constantly changing economic, social, political aspects, and many other factors, cause the differences in the global competitiveness of economies, so the economies are forced to analyze their competitive level more complexly. Despite that, there is a lack of research studies analyzing the international competitiveness of EU-28 economies from the point of view various multi-criteria indices. Purpose of the article: The paper investigates the relations between the Global Competitiveness Index (GCI) and other selected multi-criteria indices, namely the Global Innovation Index (GII), the Doing Business Index (DBI), the Economic Freedom Index (EFI) and the Corruption Perceptions Index (CPI) in the case of EU–28 economies. Methods: In order to investigate the relations between the global competitiveness and selected multi-criteria indices affecting the EU–28 economies, the multiple linear regression analyses were applied. The multiple regression model was quantified for every single year, as well as, the regression model using the average score of all analyzed indices. The secondary data concerning the scores of individual indices were collected based on annually published online reports over the period of 2014–2018. Findings & Value added: The research confirmed that there is a statistically significant dependence between the global competitiveness, corruption and the level of innovation potential within the EU–28 economies. Besides, we identified the worst results in the context of competitiveness evaluation especially in the area of corruption and innovation activities. In this regard, the issue of insufficient innovation development and inappropriate corruption perception is considered to be key determinants influencing the assessment of the global competitiveness of the EU–28 member states. In our opinion, to improve the competitiveness of these countries, targeted activities should be implemented in the frame of national competitive strategies, programs, and policies.

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Section: Literature Reviewmentioning

confidence: 99%

The evaluation of competitive position of EU-28 economies with using global multi-criteria indices

Kiseľáková

Šofranková

Onuferová

et al. 2019

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show abstract

“…Using the GII data, authors discovered that business sophistication and infrastructure have the strongest direct effects on improving the innovation capabilities of countries. Jankowska, Matysek-Jedrych, and Mroczek-Dabrowska (2017) presented the paper related to the national innovation systems also using the GII as the important economy efficiency metric. The research question was founded on the assumption that higher innovation input leads to the higher innovation output attained by a country.…”

Section: Literature Reviewmentioning

confidence: 99%

Categorization of the EU Member States in the Context of Selected Multicriteria International Indices Using Cluster Analysis

Onuferová

Čabinová

Matijová

2020

Review of Economic Perspectives

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The main aim of the paper was to analyse the economic and social development of the European Union (EU) member states (28 countries) on the basis of selected five multicriteria indices (the Global Competitiveness Index, the Economic Freedom Index, the Global Innovation Index, the Corruption Perceptions Index, the Human Development Index). To perform settled aim, a multidimensional classification of EU countries for years 2011 and 2018 using cluster analysis was realized. The purpose of the analysis was to categorize the individual EU countries into clusters and to find out to what extent the position of EU member states has changed in terms of selected international indices over the analysed period. Based on the findings, it is arguable that a major part of the EU member states cluster into the same groups based on the selected indices assessment, regardless of the time period. However, six countries (Czech Republic, Estonia, Germany, Latvia, Lithuania, and United Kingdom) improved their position during the period under review and ranked into the cluster of more prosperous countries in 2018. The rate of change (improvement) was quantified at the level of 21.43%. Based on the results, Latvia and Lithuania were the most similar countries in terms of economic prosperity (Euclidean distance reached the level of 3.08), while the least similar countries were Greece and Sweden (Euclidean distance reached the level of 70.8). Declining Euclidean distances indicate that economic disparities of the individual EU countries have decreased in the period under review. This paper aims at developing the research to find out how, besides hierarchy, we can analyse the EU member states from the perspective of various multicriteria indices. The four proposed clusters could be used as a starting point for future policy reforms, pointing to the weaknesses of various countries.

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“…Research that points to GII as a rich data set for comparative innovation analysis between organizations and nations, characterizing the conditions of the development of innovative investments from different perspectives, helped supporting the adoption of the Index in this study. Jankowska et al (2017) use the GII to prove that the greater the innovation input, the greater the country's innovative output. Couto e Silva et al (2017) use the GII pillars related to human factors, to identify gaps and to assist the analysis of decision on investments in the area, by the National Innovation Systems; Prim et al (2017) analyze a correlation between the intrinsic values of a national culture and the its favoring in the development of innovationfor nations and organizations; Crespo and Crespo (2016) through the comparative analysis of GII indicators, postulate that a country can achieve better innovative performance through various facilitator combinations -innovation input; Sohn et al (2016) use the GII in the observation of the innovative capacity and the level of efficiency of the countries analyzed by the index; Shayan et al (2015) are based on the GII to demonstrate that the media can be a strong lever of innovation and economic development; Solozhentsev (2015) is based on the GII to explore the impact of corruption and its relation to economic development; Alfantookh and Bakry (2015) are concerned with " [...] investigating the state of innovation in the Persian Gulf countries in order to allow the development of future plans that promote innovation [...]"; Nair et al (2014) analyzes the production of innovation in the United Arab Emirates with the support of a neural regression network and the GII; Rullan et al (2012), using the GII, show that an economy based on innovation is fundamental to boost competitiveness in Latin America.…”

Section: The Global Human Capital and Innovation Indicesmentioning

confidence: 99%

Similarity modeling with ideal solution for comparative analysis of projects in the context of the additional brics proposal

Saisse

Lima

2019

BJO&PM

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Goal: Based on the project called "Additional BRICS", this study aims to present an analysis on the topics Human Capital and Innovation, discussed at the X BRICS Summit, involving four countries – Argentina, Indonesia, Jamaica and Turkey – invited to participate in the Project which is intended for cooperation between emerging countries. Design/ Methodology / Approach: In this context, from the modeling of the indicators provided by the Global Human Capital and Innovation Reports, published annually by the World Economic Forum (WEF) and the World Intellectual Property Organization (WIPO), during the period from 2015 to 2017 an analysis of the performance of the invited countries was carried out with the methodological support of the TOPSIS (Technique for Ordering Performance by Similarity to the Ideal Solution). Results: The analysis of the results by the method, among the dimensions considered, highlighted Turkey in the Human Capital and Innovation issues, considering the global market. Practical implications: This study provides parameters for decision-making by executives and legislators in planning actions to fill gaps in these areas within these countries.

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Efficiency of National Innovation Systems – Poland and Bulgaria in The Context of the Global Innovation Index

Cited by 37 publications

References 38 publications

The evaluation of competitive position of EU-28 economies with using global multi-criteria indices

The evaluation of competitive position of EU-28 economies with using global multi-criteria indices

Categorization of the EU Member States in the Context of Selected Multicriteria International Indices Using Cluster Analysis

Similarity modeling with ideal solution for comparative analysis of projects in the context of the additional brics proposal

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