Performance Of National Innovation Systems Research Articles

Assessing the Performance of National Innovation Systems with a Helix-Based Composite Indicator: Evidence from 24 European Countries

ABSTRACT We employ the conceptual framework of “N-tuple helices” and devise a composite indicator, namely SFIGA (Society-Finance-Industry-Government-Academia), that aims at measuring the innovation performance of 24 OECD European countries from 2008 to 2017. We also investigate the effects of actors-helices on GDP per capita. The preliminary results from panel data regressions (OLS, quantile, and GMM) indicate their decisive economic importance as key actors of national innovation systems. However, the negative impact of academia on economic growth may explain a highly required resource allocation for basic research in the “knowledge economy” era. Its potential positive economic effects probably require time and patience.

Enterprises’ national innovation system performance in Egypt, Côte d’Ivoire and Cameroon

ABSTRACT This study aims to analyse enterprises’ performance in terms of the National Innovation System – NIS in three Africans countries: Egypt, Côte d’Ivoire and Cameroon. Drawing inspiration from the Schumpeterian approach of innovation and using the World Bank Enterprises Survey (WBES-2016) data, we estimated a multinomial logit model. The results show that innovation system’s different spheres (academic, governmental, enterprise, societal and environmental) of the quintuple helix contribute more to improving the performance of technological innovation in Egypt than in other countries. In addition, the analyses enabled us to highlight the embryonic state of the NIS in Africa. Thus, underlying innovation policies have been proposed to improve enterprises’ performance in terms of the NIS in the different countries studied.

National innovation efficiency: a DEA-based measurement of OECD countries

PurposeThe purpose of this study is to measure and analyze the national innovation efficiency of organisation for economic co-operation and development (OECD) countries. This is to determine to what extent OECD countries efficiently use the elements that enable innovation activities possible in generating innovation outputs.Design/methodology/approachAn input–output model was constructed to measure efficiency. The inputs and outputs in the research model are the input and output sub-indices of the Global Innovation Index. Data envelopment analysis was used to measure the national innovation efficiency levels of OECD countries.FindingsThe results show that national innovation efficiency is generally high in OECD countries. However, some countries lag behind in innovation efficiency. OECD countries’ ability to create and provide the elements that enable innovation activities is higher than their ability to create innovation outputs. OECD countries have a good innovation environment and a high level of resources, but they should focus on how to create more innovation outputs.Originality/valueThis study presents a measurement of national innovation efficiency of OECD countries which contributes “Innovation Strategy” agenda. The results empirically show that overall innovation indices cannot be the only indicator of the performance of national innovation systems. In this study, an innovation efficiency/performance matrix is constructed to present the relative positions of the countries to help in examining countries’ strengths, weaknesses and potentials based on innovation efficiency and innovation performance simultaneously. This study contributes to the literature by presenting a broader perspective and measurement of national innovation efficiency by taking an extensive number of indicators into account.

Огляд ландшафту інструментів інноваційної політики ЄС: висновки для України

The need to modernize and critically rethink the state of Ukraine`s national innovation policy and the tools for its implementation is justified. This is due to the slowdown of innovation processes in the country over the past five years and the chronic problems that have accompanied the national research and innovation sphere for almost the entire period of independence. To that end, it is necessary to rely on the theoretical argumentation of the grounds for state intervention in innovation from the standpoint of various economic schools, and European experience in the development and implementation of innovation policy, which is relevant in the context of Ukraine's European integration, as well as taking into account modern challenges and the specifics of the social and institutional arrangements of Ukraine as a developing country. This article identifies and summarizes the most common instruments used at the level of the EU and its member states to support research, development, and innovation. These include research, collaboration, doctoral and seed grants, public procurement, start-up funds, venture funds, science and technology parks, clusters, technology transfer offices, technology centers, innovation loans and innovation vouchers, tax incentives, "living labs", digital innovation hubs, etc. Some of them have been analyzed to illustrate the similarities and differences in the innovation policy of the EU member states. It has been determined EU member states still tend to use supply tools, supporting knowledge generation to a greater extent, and tools to stimulate demand for innovation are much less common in them, which does not allow the EU to catch up with world leaders, in particular the United States, Japan and South Korea, for the performance of national innovation systems. Based on the analysis of the European experience in supporting and stimulating innovation, proposals are formulated for the development of a national innovation policy for an effective post-war recovery.

Performance of national innovation systems during the global crisis:

The Global Financial Crisis of 2007-2009, followed by the Euro Crisis, changed the world economic and social balances. By turning upside down the letter-perfect and internalized global economic and social judgments and expectations, the Global Financial Crisis gave birth to a new world order and to a ‘new normal’. Since the internal dynamics of the firms, sectors, countries and regions differ highly, the effect of the global crisis to firms, sectors, countries and regions in terms of intensity of the shock and the recovery process was also uneven. This new normal, together with the technological development, increased the importance of the innovation and efficient use of scarce resources to avoid deadlock in the inclusive and sustainable growth. Thus, the aim of this study is to focus on the innovation efficiency of the countries to see the effect of the global crisis on the capabilities of the countries. In this study, two alternative models with two different approaches of Data Envelopment Analysis (DEA) under two different specifications (input-oriented and output-oriented) are utilized to trace innovation performance across 56 countries during the global crisis from 2007 to 2012. The empirical evidence reveals that the negative effects of 2008 crisis are reflected on innovation efficiencies of countries in 2008 in the base model and 2009 in the lag model. In addition, grouping countries according to their GDP and GDP per capita and implementing two different models show that there could be difference in the innovation efficiency results since the DEA model shows the innovation efficiency in comparison with the other countries’ efficiency. Lastly, with the data it is observed that higher GDP or higher GDP per capita do not lead to high innovation efficiency

MODELING NATIONAL INNOVATION SYSTEM ENABLED BY KNOWLEDGE MANAGEMENT

The main objective of this paper is to explore the model of how knowledge management functions enables national innovation system. To achieve the objectives of the study, a conceptual framework is proposed and described, then the systemic analysis is undertaken. Path coefficient and t-value are also used to measure the relationships among chosen variables. A great number of sources are used to collect data, including questionnaires, interviews, observations, and literature review. The achievements of the study demonstrate 10 distinctive national innovation system performance dimensions and the relationship with knowledge management functions. The first layer includes explicit knowledge, while the second layer deals with tacit knowledge. Both of two layers link to a complete knowledge management functions and processes: explicit knowledge building, explicit knowledge gathering, explicit knowledge distributing, explicit knowledge reusing, tacit knowledge capturing, tacit knowledge sharing tacit knowledge disseminating, tacit knowledge innovating; whereas the third layer includes NIS enablers items or performance dimension of national innovation system: quality, effectiveness, quantity, codification, structure, efficiency, internalization, expertise, effectiveness.

Results and impact of national Foresight-studies

Conducting national Foresight studies has become common in many countries. However the impact of such studies on the performance of the national innovation system remains unclear. The paper therefore assesses the impact of national Foresight studies conducted in member countries of the Organization for Economic Cooperation and Development (OECD) and the European Research Area (ERA).The study provides a first indication of the impact of national Foresight studies on the performance of national innovation systems. However the findings so far are preliminary since input data reflect long term developments of national innovation systems. Thus a long term study of the impacts of national Foresight studies is essential. In the short term, it can be concluded that national Foresight studies contribute significantly to the design and in some countries reshape of the innovation system structure and framework conditions. A direct quantitative measurement of the impact and thus the value of Foresight studies cannot yet be done in a statistically reliable fashion. However the changes these studies have caused within the national innovation systems may have an indirect impact on the future national innovation performance. Most recently national Foresight studies have switched from a rather exclusive focus on technology trend assessments towards more integrated holistic approaches identifying future challenges for society and economy as a whole thus deriving strengths and weaknesses of the national scientific, research and technology base to meet these challenges long term in the most appropriate way.

The impact of innovation policies on the performance of national innovation systems: A system dynamics analysis

There has been a growing significance for the National Innovation System (NIS) and its use as a tool for the competitive advantage of a country to date. In this paper, an NIS model has been developed with the use of system dynamics (SD) methodological approach. The objective of this model is to integrate the systemic approach, the computer modelling and the simulation discipline into a holistic dynamic consideration of the NIS. From this central structure, the paper analyzes the impact of innovation policies on the NIS performance. In particular the SD model is used as an “experimental tool” to conduct extensive what-if analysis scenarios with regard to alternative innovation policies. The effectiveness of policies is investigated through the dynamic behaviour of product innovation and process innovation which are obtained by simulation results. By using data from a European Union country with innovation performance below that of the EU27 average, the analysis of results reveals insights over a strategic time horizon.

An Indicator for National Systems of Innovation: Methodology and Application to 17 Industrialized Countries

We develop a composite indicator measuring the performance of national innovation systems. The indicator takes into account both hard factors that are quantifiable (such as R&D spending, number of patents) and soft factors like the assessment of preconditions for innovation by managers. We apply the methodology to a set of 17 industrialized countries on a yearly basis between 2007 and 2009. The indicator combines results from public opinion surveys on the process of change, social capital, trust and science and technology to achieve an assessment of a country's social climate for innovation. After calculating and ranking the innovation indicator scores for the 17 countries, we group them into three classes: innovation leader, middle group and end section. Using multiple sensitivity analysis approaches, we show that the indicator reacts robustly to different weights within these country groups. While leading countries like Switzerland, the USA and the Nordic countries have an innovation system with high scores and ranks in every sub indicator, the middle group consisting among others of Germany Japan, the UK and France, can be characterized by higher variation within ranks. In the end section, countries like Italy and Spain have bad scores for almost all indicators.

Scientific capabilities and technological performance of national innovation systems: An exploration of emerging industrial relevant research domains

Today's theories and models on innovation stress the importance of scientific capabilities and science-technology proximity, especially in new emerging fields of economic activity. Inthis contribution we examine the relationship between national scientific capabilities, the science intensity of technology and technological performance within six emergent industrial fields. Our findings reveal that national technological performance is positively associated with scientific capabilities. Countries performing better on a technological level are characterized both by larger numbers of publications and by numbers of involved institutions that exceed average expected values. The latter observation holds for both companies and knowledge generating institutes actively involved in scientific activities. As such, our findings seem to suggest beneficial effects of scientific capabilities shouldered by a multitude of organizations. In addition, higher numbers of patent activity coincide with higher levels of science intensity pointing out the relevance of science 'proximity' when developing technology in newer, emerging fields. Limitations and directions for further research are discussed.