Suchergebnisse

This report is an account of the relationship between the ERA development and German research and innovation policy (R&I policy). The report introduces what ERA is and how the activities and instruments at European level have fundamentally changed and broadened. It provides a discussion of key initiatives at European level and their interrelation with German R&I policy. In the last decade, and accelerated in the recent years, the European research policy and subsequently the innovation policy have undergone dramatic changes. A range of long-term ambitious initiatives have been developed, most notably within the path-breaking ERA process (research) and the Lisbon strategy (growth). This report addresses these developments by differentiating between traditional (Framework Programme, EUREKA and COST) and new instruments. The new instruments deviate from the classical cooperation funding by addressing either excellence (ERC, EIT) or coordination issues (ETP, ERA-Net). Moreover, also at European level research is no longer a stand-alone approach. Instead, innovation has gained rapidly in importance as a key driver for economic growth. In this report, we present evidence from document analysis and expert interviews for the merit and challenges of the instruments in general and in particular with respect to Germany.

This study empirically investigates the two options which were considered by the German presidency for finding a solution to the crisis of the EU's reform process. Our findings reveal that making concessions to the remaining eight ratification countries and renegotiating the text with all Member States were feasible solutions for reform. Adapted from the source document.

Missing or incomplete data on actors' positions can cause significant problems in political analysis. Research on missing values suggests the use of multiple imputation methods rather than case deletion, but few studies have yet considered the non-ignorable problem - positions that are hidden for strategic purposes. We examine this problem and discuss the advantages and drawbacks of (i) multiple imputation as implemented in AMELIA; (ii) a computationally easy but, in the context of spatial modelling, straightforward measure of indifference and (iii) a conditional averaging algorithm, LDM, which seeks to reasonably fix actors' positions in the policy space pre- and post-imputation. The analysis suggests that actors biased by the status quo strategically hide their more supportive positions. Although none of the existing methods - which produce quite different results - is perfectly suited for imputing hidden positions, LDM has the highest hit rate for the conjectured more supportive position.

International audience ; Missing or incomplete data on actors' positions can cause significant problems in political analysis. Research on missing values suggests the use of multiple imputation methods rather than case deletion, but few studies have yet considered the non-ignorable problem - positions that are hidden for strategic purposes. We examine this problem and discuss the advantages and drawbacks of (i) multiple imputation as implemented in AMELIA; (ii) a computationally easy but, in the context of spatial modelling, straightforward measure of indifference and (iii) a conditional averaging algorithm, LDM, which seeks to reasonably fix actors' positions in the policy space pre- and post-imputation. The analysis suggests that actors biased by the status quo strategically hide their more supportive positions. Although none of the existing methods - which produce quite different results - is perfectly suited for imputing hidden positions, LDM has the highest hit rate for the conjectured more supportive position.

Missing or incomplete data on actors' positions can cause significant problems in political analysis. Research on missing values suggests the use of multiple imputation methods rather than case deletion, but few studies have yet considered the non-ignorable problem -- positions that are hidden for strategic purposes. We examine this problem & discuss the advantages & drawbacks of (i) multiple imputation as implemented in AMELIA; (ii) a computationally easy but, in the context of spatial modelling, straightforward measure of indifference & (iii) a conditional averaging algorithm, LDM, which seeks to reasonably fix actors' positions in the policy space pre- & post-imputation. The analysis suggests that actors biased by the status quo strategically hide their more supportive positions. Although none of the existing methods -- which produce quite different results -- is perfectly suited for imputing hidden positions, LDM has the highest hit rate for the conjectured more supportive position. 4 Tables, 46 References. [Reprinted by permission of Sage Publications Ltd., copyright 2005.]

Missing or incomplete data on actors' positions can cause significant problems in political analysis. Research on missing values suggests the use of multiple imputation methods rather than case deletion, but few studies have yet considered the non-ignorable problem - positions that are hidden for strategic purposes. We examine this problem and discuss the advantages and drawbacks of (i) multiple imputation as implemented in AMELIA; (ii) a computationally easy but, in the context of spatial modelling, straightforward measure of indifference and (iii) a conditional averaging algorithm, LDM, which seeks to reasonably fix actors' positions in the policy space pre- and post-imputation. The analysis suggests that actors biased by the status quo strategically hide their more supportive positions. Although none of the existing methods - which produce quite different results - is perfectly suited for imputing hidden positions, LDM has the highest hit rate for the conjectured more supportive position.

We contribute to the Responsible Research and Innovation (RRI) literature in two ways: (i) we consider how societal aspects are taken into account in research and innovation activities in four fundamentally different futures, as opposed to analysing current practices; and (ii) put the emphasis on the framework conditions, as opposed to focussing on RRI principles and instruments. In the Kingdom of RRI citizens participate directly in decision-making processes; Fortress Europe depicts a libertarian system; Failed Democracy is a populist regime; while Benevolent Green Eurocrats describes a technocratically coordinated strong state. The RRI concept is ignored, manipulated, or rather selectively applied in the latter three scenarios. The scenarios offer novel insights into the nature and repercussions of possible policy problems. We discuss issues related to efficacy and efficiency of policy-making; legitimacy of research and innovation activities; societal involvement; equity; and freedom of research in each scenario. We also posit that there is room for safeguarding meaningful interactions between the societal and professional actors in an innovation system even in the harshest framework conditions.

We contribute to the Responsible Research and Innovation (RRI) literature in two ways: (i) we consider how societal aspects are taken into account in research and innovation (R&I) activities in four fundamentally different scenarios, as opposed to analysing current practices; and (ii) put the emphasis on the political conditions of the interactions among the actors, as opposed to focussing on RRI principles and instruments. In the Kingdom of RRI citizens participate directly in decision-making processes; Fortress Europe depicts a libertarian system; Failed Democracy is a populist regime; while Benevolent Green Eurocrats describes a technocratically coordinated strong state. The scenarios offer novel insights into the nature and repercussions of possible policy problems, that is, efficacy; efficiency; legitimacy of R&I activities; societal involvement; equity; and freedom of research. Meaningful interactions between lay people and professional actors in an innovation system can be safeguarded even in the harshest ideological and political framework.

Die gegenständliche Studie untersucht, ob sich neue 'Politikstile' - insbesondere das Konzept der 'neuen Missionsorientierung' - in der Forschungs- und Innovations- (F&I) Politik beobachten lassen, wie diese charakterisiert werden können, und welche Schlussfolgerungen für die deutsche F&I-Politik zu ziehen wären. Diese neuen Ansätze sind theoretisch schon gut beschrieben und in einigen Ländern schon in verschiedenen Formen ("Akzelerator/Transformator Missionen") zu beobachten. Diese Missions-Typen weisen jeweils unterschiedliche Anforderungen an Governance auf den Ebenen der Strategiefindung, der Koordination und der Implementierung auf. In Deutschland finden sich diese Ansätze explizit erst in jüngerer Zeit in Strategien und Programmen wieder. Eine Reihe von Politikinitiativen konnten als tendenziell diesem Politikstil zurechenbar identifiziert werden, obgleich sie bislang nicht explizit als missionsorientierte Politik betrieben werden (z.B. Mikroelektronik, Industrie 4.0, Nanotechnologie aus der HTS III, Rohstoffstrategie 2020 u.a.). Diese Befunde könnten dazu dienen, die identifizierten Politiken zu missionsorientierten Politiken weiterzuentwickeln oder zumindest die vermuteten Potentiale zu überprüfen. Auf diesen Befunden aufbauend werden Bedingungen für die erfolgreiche Umsetzung dieser neuen Ansätze in Deutschland beschrieben.

[Einleitung] Während der Phase seit der ersten Hightech-Strategie sind die Aufwendungen für Forschung und Entwicklung im öffentlichen wie auch im privaten Bereich angestiegen. Dieser Mittelaufwuchs kann ursächlich mit der Hightech-Strategie in Zusammenhang gebracht werden. Im Jahr 2012 wurde eine FuE-Intensität (FuE-Aufwendungen in Relation zum Bruttoinlandsprodukt) von knapp 3% erreicht, nachdem zwischen 2000 und 2006 die Quote bei etwa 2,4-2,5% lag. Ein Wert, der von der Bundesrepublik Deutschland zuletzt vor der Wiedervereinigung erreicht wurde. Die nominalen FuE-Aufwendungen sind zwischen 1985 und 2006 jahresdurchschnittlich um 3,5% gewachsen. In der Zeit zwischen 2000 und 2006 waren es durchschnittlich lediglich 2,5%. Betrachtet man die realen Steigerungen, dann wurden Werte von 2,8% zwischen 1985 und 2006 bzw. 1,5% zwischen 2000 und 2006 erreicht. Zu Beginn des neuen Jahrtausends hatte sich das Wachstum also deutlich verlangsamt. Mit der Hightech-Strategie und der unter anderem durch sie initiierten Effekte in der Wirtschaft, wurden zwischen den Jahren 2006 und 2013 Mittelzuwächse von nominal 4,5% und real von etwa 3% realisiert. In dieser Periode sind die öffentlichen FuE-Aufwendungen zudem stärker gestiegen als die privaten, während es in der Zeit vorher nahezu ausschließlich einen Mittelaufwuchs der privaten Aufwendungen gab. Hier waren die öffentlichen Aufwendungen real sogar rückläufig. Dieser Mittelzuwachs im Rahmen bzw. mit initiiert durch die Hightech-Strategie ermöglichte eine Zunahme des Forschungspersonals in Deutschland um über 90.000 Personen zwischen 2006 und 2009. In Deutschland wird somit insgesamt mehr Forschung und Entwicklung von mehr forschenden Einrichtungen und Personen betrieben. Die Inputseite des Innovationsprozesses ist zur Zeit der Hightech-Strategie demnach gewachsen. Um die Wirkung der Hightech-Strategie zu bewerten, müssen die Effekte auf der Outputseite dazu allerdings in Relation gesetzt werden. Während der generelle Aufwuchs der Mittel leicht nachweisbar ist, lässt sich die Outputseite von FuE-Prozessen schwieriger belegen. Eine Evaluation der Hightech-Strategie war in den vergangenen zehn Jahren zu keinem Zeitpunkt vorgesehen, da dies aufgrund der Komplexität und der thematischen Breite auch nicht im Detail möglich ist. Daher wurden zwar einzelne Programme innerhalb der Hightech-Strategie evaluiert, nicht jedoch die Hightech-Strategie als Ganze. [.]