The Efficiency of National Innovation Systems in Post-Soviet Countries: DEA-Based Approach (original) (raw)
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Measuring National Innovation Systems Efficiency – A Review of DEA Approach
http://papers.ssrn.com/sol3/cf\_dev/AbsByAuth.cfm?per\_id=1989392 The paper reviews the application of the data envelopment analysis (DEA) method for measuring the efficiency of national innovation systems (NIS). The paper firstly visualizes the logic of DEA method and briefly summarizes the key advantages and main limitations of the DEA method. Further, this paper provides a comprehensive review of 11 empirical studies on cross-country analysis of NIS efficiency with DEA technique. In its main part the paper analyses the specifications of DEA models used in the reviewed studies, the content of the country samples, sets of input and output variables used and the resulting lists of efficient countries. The review detects general trends and differences in the sets of variables and the content of country samples. Moreover, this paper highlights the problem of “small countries bias” in the reviewed studies: situation when “small” (in terms of national innovation system scope and the level of development) countries (like Venezuela, Kyrgyzstan etc.) are included in the country sample, these “small” countries become the efficient ones. In general, empirical studies on cross-country analysis of national innovation systems efficiency using DEA method pay little attention to profound analysis of previous relevant studies. Therefore, this paper is among the first papers with deep review of such empirical studies. The full version can be downloaded for free here http://papers.ssrn.com/sol3/cf\_dev/AbsByAuth.cfm?per\_id=1989392
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The main aim of this study is to compare Russian regions according to their ability to create new technologies efficiently and to identify factors that determine these differences over a long period of time. We apply data envelopment analysis (DEA) to assess the relationship between the results of patenting and resources of a regional innovation system (RIS). Unlike previous studies, we apply the DEA method over a long period, comparing regions to one another and over time. In general, RIS efficiency in Russia increased during the period, especially in the least developed territories. There was significant regional differentiation. The most efficient RIS were formed in the largest agglomerations with leading universities and research centers: the cities Moscow and Saint Petersburg and the Novo-sibirsk, Voronezh, and Tomsk regions. Econometric calculations show that RIS efficiency was higher in technologically more developed regions with the oldest universities and larger patent stock. Time is a crucial factor for knowledge accumulation and creating links between innovative agents within RIS. Entrepreneurial activity was also a significant factor because it helps to convert ideas and research into inventions and new technologies and it enhances the interaction between innovative agents. It is advantageous to be located near major innovation centres because of more intensive interregional knowledge spillovers. Public support of more efficient regions can lead to a more productive regional innovation policy.
Analysis of the Efficiency of Innovation Management in the Countries of the Eurasian Economic Union
Polish journal of management studies, 2019
The article contains a crosscountry analysis of the effectiveness of innovation management based on information from the Global Innovation Index among the countries of the Eurasian Economic Union (EAEU). From the analysis, it follows that the problem in the EAEU countries is low demand for innovations and its inefficient structure: it is more profitable for enterprises in the EAEU countries to purchase ready-made equipment abroad than to engage in their own innovative activities. A comparative analysis of the Global Innovation Index shows that indicators of the development of institutions and infrastructure ensure the relatively high positions of Kazakhstan, first of all, with a significant lag in all measurements of the efficiency of resource use of innovation
Modeling the relative efficiency of national innovation systems
Research Policy, 2012
Although a large amount of past research has theorized about the character of national innovation systems (NISs), there has been limited process-oriented empirical investigation of this matter, possibly for methodological reasons. In this paper, we first propose a relational network data envelopment analysis (DEA) model for measuring the innovation efficiency of the NIS by decomposing the innovation process into a network with a two-stage innovation production framework, an upstream knowledge production process (KPP) and a downstream knowledge commercialization process (KCP). Although the concept of innovation efficiency is a simplification of the innovation process, it may be a useful tool for guiding policy decisions. We subsequently use a second-step partial least squares regression (PLSR) to examine the effects of policy-based institutional environment on innovation efficiency, considering statistical problems such as multicollinearity, small datasets and a small number of distribution assumptions. The hybrid two-step analytical procedure is used to consider 22 OECD (Organisation for Economic Co-operation and Development) countries. A significant rank difference, which indicates a non-coordinated relationship between upstream R&D (research and development) efficiency and downstream commercialization efficiency, is identified for most countries. The evidence also indicates that the overall innovation efficiency of an NIS is mainly subject to downstream commercial efficiency performance and that improving commercial efficiency should thus be a primary consideration in future innovation policy-making in most OECD countries. Finally, the results obtained using PLSR show that the various factors chosen to represent the embedded policy-based institutional environment have a significant influence on the efficiency performance of the two individual component processes, confirming the impact of public policy interventions undertaken by the government on the innovation performance of NISs. Based on these key findings, some country-specific and process-specific innovation policies have been suggested.
The Efficiency and Productivity Evaluation of National Innovation Systems in Europe
European Research Studies Journal, 2021
Purpose: An efficient innovation system currently plays a crucial role in creating competitive prevalence, contributing to the economic growth of individual states. The innovation system is influenced by many socioeconomic factors, including in international rankings of innovativeness of economies. These classifications have some limitations. Primarily, they do not examine the efficiency, which means they do not analyze the relationship between the involved inputs and the relevant outputs generated in the innovation system. The study aims to measure the efficiency and productivity of the European state's innovation system based on the data from the international ranking of economies' innovation. Design/Methodology/Approach: In this study, the changes in the efficiency and productivity of the innovation system coming from European states were measured using the DEA and Malmquist index methods, based on data from the European Innovation Scoreboard international ranking innovation in economies. The maximizing of economic benefits was assumed in its impact on employment and sales in a given state. The non-radial SBM model, Super SBM, and Malmquist index based on SBM were used for the research. 27 European states were subjected to the analysis in the period from 2012 to 2019. Findings: The research results indicate that the average level of efficiency in the surveyed period fluctuated around 70%. Higher results of efficiency were achieved more frequently by states that joined the EU after 2004. The increase in the productivity of individual states was caused most frequently by an increase in their efficiency (catch-up effect) and less frequently by shifting the efficiency frontier (frontier effect). Practical Implications: The following research hypothesis was decided to be laid down: developing states and those newly admitted to the European Union after 2004 have been gaining relatively more economic benefits from smaller national innovation systems (NIS) resources than developed states and the so-called states of the "old Union." Originality/Value: The added value of the article is, first of all, a comprehensive measurement of the efficiency and productivity of European states NIS in three aspects-efficiency status, efficiency ranking, and productivity changes assessment.
EURINT, 2019
The aim of this paper is to investigate the innovation efficiency in Central and Eastern Europe by performing an input-output approach using Data Envelopment Analysis (DEA). R&D government spending and total R&D personnel stand for inputs and patent applications and high-tech exports stand for innovation outputs. We performed a comparative analysis between Czech Republic, Hungary, Poland and Romania using a 10 year-time span (2007-2016). We demonstrated that over time the innovation efficiency has improved (both regarding technical efficiency and scale efficiency) in all the four countries under scrutiny. Moreover, our research showed that the most efficient country was Hungary which balanced properly between the efforts of supporting innovation and its benefits due to reaping its positive effects in terms of high-tech exports and patent creation.
Are systems of innovation in Eastern Europe efficient?
2009
This paper explores the determinants of the productivity in the countries of Eastern Europe (EE) through the perspective of 'narrow'and 'broad'national systems of innovation (NSI). Based on panel econometrics it examines the extent to which systems in EE could be considered '(in) efficient'. Our results suggest that the EE countries have lower levels of productivity than might be expected given their research and development (R&D), innovation and production capabilities.
Efficiency of the R&D Sector in the EU-27 at the Regional Level: An Application of DEA
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The main aim of the paper is to measure the relative efficiency of the R&D sector in the EU-27 at the regional level. For this purpose, the paper applies a non-parametric approach, i.e. data envelopment analysis (DEA), to assess the relative technical efficiency of R&D activities across selected EU (NUTS-2) regions. The empirical analysis integrates available inputs (R&D expenditures, researchers and employment in high-tech sectors) and outputs (patent and high-tech patent applications) over the 2005– 2010 period. The empirical results show that among regions with a high intensity of R&D activities the most efficient performers are Noord-Brabant (Netherlands), Stuttgart (Germany) and Tirol (Austria). In contrast, a wide range of NUTS-2 regions from the Baltics, Eastern and Southern Europe is characterized by an extremely low rate of knowledge production and its efficiency, particularly in Poland (Mazowieckie), Lithuania (Lietuva), Latvia (Latvija), Romania (Bucuresti-Ilfov), Bulgari...
Efficiency of innovation system in the Czech Republic: Comparison with other European countries
New Trends and Issues Proceedings on Humanities and Social Sciences, 2017
This paper examines the efficiency of the innovation system in the Czech Republic compared to other European Union countries. The analysis is based on a data envelopment method using a model containing innovation drivers, knowledge creation and indicators of innovation and entrepreneurship as inputs, and intellectual property and application assets producing outputs of the national innovation systems of selected European countries. The data envelopment analysis method focuses on non-parametric linear programming, examining the relative performance and efficiency of particular units under a constant return to scale, converting inputs into outputs as variables of modelling. The measured technical efficiency indicates a difference in performance of innovation systems of selected countries of the European Union and compares an obtained score in efficiency evaluated in the model. The Czech Republic belongs to the moderate group in terms of innovation performance; its national innovation system is characterised by weaknesses in intellectual assets and research.
Comparative Economic Research, 2017
The purpose of this paper is to explain how national innovation systems may transform innovation input into innovation output in different counties. Using the Global Innovation Index (GII) we discuss what can be understood by the term ‘innovation’ and how it is translated into the national level. The research question is founded on the assumption that the higher the innovation input, the higher the innovation output attained by a country. We use cluster analysis to verify our assumption, referring to a total of 228 countries. Afterwards we conduct a more in‑depth analysis of two cases (Poland and Bulgaria), where the research question does not find confirmation. Using the cross‑comparison method we aim to verify how and why national innovation systems failed (or succeeded) in creating innovations.