Sectoral Innovation Modes and Level of Economic Development: Implications for Innovation Policy in the New Member States

Reinstaller, Andreas; Unterlass, Fabian

doi:10.4337/9780857935212.00012

Cited by 3 publications

(4 citation statements)

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“…The intrinsic differences were recognized as being dominant in the European Union in [93], which asks for policies to increase R&D spending, improve intellectual Property rights, and favoring foreign direct investment (FDI). The findings of this study are in line with findings in [94], where the structural effects have the greatest influence on R&D spending in the top performing countries in this analysis (and the opposite is true for the worst performers). They are also in line with [95], where it was found that Germany is experiencing a structural change towards technology-intense industries, whereas Denmark, Austria, and Sweden have experienced changes in the intrinsic effects.…”

Section: Checking For Robustnesssupporting

confidence: 90%

“…Furthermore, the decomposition of R&D expenditure and employment should be done in a formal analysis. In this regard, [22][23][24] discuss in detail the issues of using total R&D expenditure in research due to business R&D (BERD) being heavily affected by the industrial structure of each country. Furthermore, obtaining information from sector disaggregation is important from a private research (private business sector R&D) perspective.…”

Section: Introductionmentioning

confidence: 99%

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R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

Škrinjarić

2020

Sustainability

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Measuring the efficiency of research and development (R&D) expenditure and innovation policy has gained attention in recent years. This research examines the efficiency of 29 selected European countries for the period ranging from 2007 to 2017 in achieving and obtaining R&D goals. The methodology applied is the data envelopment analysis approach with the inclusion of the missing data approach. The contributions of this research include the following: dynamic analysis is conducted to track changes of (in)efficiencies over time; the decomposition of the efficiency is done by separating the main variables of interest into the private, higher education, and government sectors; and the robustness of the results is evaluated, which is often ignored in the literature. The results of the analysis are discussed with possible directions for inefficient countries. The rankings provided in the empirical part of the study confirm previous findings on disparities between the European countries with respect to innovation and the R&D sector.

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Section: Checking For Robustnesssupporting

confidence: 90%

Section: Introductionmentioning

confidence: 99%

R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

Škrinjarić

2020

Sustainability

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“…In this way, recent studies have shown this vector of influence in different investment contexts, specifically the contributions of Coad (2008;2011), Reinstaller and Unterlass (2012), Hall, Lotti, and Mairesse (2013), and Hölzl and Janger (2014. Coad (2011) presented empirical evidence that firms located on the frontier employ R&D resources more efficiently, generating significantly higher scores than the more distant firms.…”

Section: Quantitative Analysis: Model Estimatesmentioning

confidence: 85%

Innovation and Performance: The Contribution of Investments in R&D to Firm Profitability According to the Technological Frontier

Rocha¹,

Cárdenas²,

Tortato³

et al. 2019

SAE

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This study analyses the influence of innovative efforts, measured by R&D investments, on the financial performance of firms, considering its position in relation to the technological frontier. Recent researches, especially Aghion & Howitt, 2009; Aghion, Akcigit, & Howitt, 2013, have demonstrated that the firm's technological position has a strong impact on the results of the applied investment, since the structure of incentives and potential opportunity costs influence the relation between the variables. For this purpose, the present study uses the frontier analysis with order-α partial frontiers, aiming to capture fluctuations of proximity to the border and its influence on the relation "R & D investment versus performance". Such approach allows different frontiers to be estimated for different quantiles, which provides a more consistent estimate of efficiency scores, which become more robust in relation to traditional problems of outliers and dimensionality. The sample of this article was made up of 2.000 firms and the data needed for the survey was extracted from the European Commission, a database covering 40 sectors in 46 countries. The results of the model suggest that the more efficient firms or the ones situated on the efficiency frontier achieve more profits from the same level of R&D investment compared with less efficient firms. This influence of proximity to the frontier emphasizes that the most efficient firms use the investments in R&D in order to obtain greater returns, what can explain that innovation is not shown uniform among firms.

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“…In this context, the goal of this research is to shed light in understanding the drivers of formal and informal OI by simultaneously analysing the firms’ internal and external drivers. Furthermore, we consider that the adoption of OI can be context-dependent (Ebersberger et al , 2011) because great differences exist owing to cultural heterogeneity (Muroveca and Prodan, 2009) and the different industrial conditions, public funding policies and national innovation systems (Reinstaller and Unterlass, 2011; Kafouros and Forsans, 2012). For this, we conducted the study in two European regions, Navarre (Spain), classified an innovator follower, and Noord Brabant (Netherlands), an innovator leader (Hollanders et al , 2012).…”

Section: Introductionmentioning

confidence: 99%

Public funds and internal innovation goals as drivers of formal and informal open innovation practices

Cruz‐Cázares

Sáez

García‐Marco

et al. 2018

MRJIAM

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Purpose The purpose of this paper is to analyse a firm’s internal and external drivers of formal and informal open innovation (OI) practices. To enrich the analysis and to obtain more robust results, the authors checked the study’s hypotheses using samples from two European regions, Navarre (Spain), classified an innovator follower, and Noord-Brabant (Netherlands), an innovator leader. Design/methodology/approach The sample selected includes manufacturing and service firms that completed the Community Innovation Survey for the year 2008 in both regions. The final sample had 1,288 observations from Navarre and 623 observations from Noord-Brabant. The authors consider two OI dimensions, breadth of information sources for informal OI practices and breadth of cooperation agreement for formal OI practices. Finally, the estimates were performed by means of a negative binomial regression. Findings Results indicate that for the internal drivers, product-related motives to innovate and in-house R&D intensity are strong drivers for both formal and informal OI engagement in general, while the influence of process- and environmental-related motives are context dependence. Originality/value This study distinguishes between formal (i.e. cooperation activities) and informal (i.e. external sources of information used for new ideas) inbound OI practices, while most of the literature has focussed on one single type of OI practice. The use of two samples coming from two different European regions allows observe whether the adoption motives of the OI practices are robust independently from the firms’ location or if they vary across regions owing to context dependence.

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Sectoral Innovation Modes and Level of Economic Development: Implications for Innovation Policy in the New Member States

Cited by 3 publications

References 0 publications

R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

R&D in Europe: Sector Decomposition of Sources of (in)Efficiency

Innovation and Performance: The Contribution of Investments in R&D to Firm Profitability According to the Technological Frontier

Public funds and internal innovation goals as drivers of formal and informal open innovation practices

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