An Analysis of University Governance Dimensions in Academic Research and S3 Innovation Performance

2019 ◽  
pp. 153-185
Author(s):  
Markus Dettenhofer ◽  
Mathieu Doussineau ◽  
Eskarne Arregui-Pabollet
Keyword(s):  
Academic Research ◽  
Innovation System ◽  
Innovation Systems ◽  
University Governance ◽  
Quadruple Helix ◽  
Regional Research ◽  
Regional Innovation ◽  
Eu Member States ◽  
Research And Innovation ◽  
Smart Specialization

The chapter examines the multi-dimensional university governance topic, looking into five governance dimensions of universities and the differences across EU member states. It analyzes how the differences in university governance dimensions influence in their role in their regional research and innovation systems, and specifically in the smart specialization strategies (S3) implementation. The S3 is a new policy that has introduced novelties in regional development policy, requiring the mobilization of quadruple helix actors in setting the regional priorities for innovative potential. The involvement of universities in the formulation of these strategies is of high importance; however, it poses a number of challenges, particularly in regions with incipient regional innovation systems with low institutional capacity and leadership to coordinate the different actors' capacities. The chapter sheds light for policymakers and university managers on the most relevant university governance dimensions that can influence on how they engage with their regional research and innovation system.

scholarly journals Quadruple Helix Models for Sustainable Regional Innovation: Engaging and Facilitating Civil Society Participation

Economies ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 48 ◽  
Author(s):  
Mona Roman ◽  
Henry Varga ◽  
Vladimir Cvijanovic ◽  
Alasdair Reid
Keyword(s):  
Civil Society ◽  
Innovation Policy ◽  
Quadruple Helix ◽  
Regional Innovation ◽  
Innovation Research ◽  
Entrepreneurial Discovery ◽  
Research And Innovation ◽  
Civil Society Participation ◽  
Smart Specialization ◽  
Research And Policy

Prior research has emphasized the importance of bringing together quadruple helix (QH) actors (academia, industry, government and civil society) to strengthen regional innovation. The QH model forms an integral part of European innovation policy, which aims to create sustainable and inclusive growth in Europe. As part of this policy, European Union (EU) regions are to design and implement research and innovation strategies for smart specialization (RIS3) through the participatory entrepreneurial discovery process (EDP). Despite the strong emphasis on the QH model, the model is still far from a well-established concept in innovation research and policy, and civil society participation in RIS3 has remained low. Our paper aims to support regional governments to engage with and facilitate the participation of civil society in a territorial EDP based on two case studies from Finland and Sweden. It contributes to the literature on regional innovation systems through identifying mechanisms to foster the QH model and suggests lessons learnt for the operationalization of the QH model as part of RIS3.

scholarly journals REGIONAL INNOVATION SYSTEMS AND UNIVERSITY COMPETITIVENESS

2019 ◽  
Vol 7 (2) ◽  
pp. 227-235 ◽  
Author(s):  
Borislava Borisova Stoimenova
Keyword(s):  
Knowledge Transfer ◽  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Research And Innovation ◽  
Knowledge Triangle ◽  
Regional Sources ◽  
Regional Engagement ◽  
Core Idea

This paper is a literature review, presenting the concept of regional innovation systems (RIS) and identifying criteria and indicators for measurement of university competitiveness within these systems. A regional innovation system is defined as an interactive learning engagement among a network of various actors within an institutional framework. It is built around the core idea that innovation stems from interactions within a network of different actors. The development of RIS is fostered by the European Commission in its attempts to make Europe and the EU the world’s most competitive and dynamic economy by embracing the whole innovation chain from education to economic impact, popular as the “knowledge triangle” of education, research and innovation. Universities contribute to the creation and dissemination of new knowledge and the generation of intellectual capital. In such context, the two most frequently cited criteria used to measure the university competitiveness are knowledge transfer and regional engagement. Knowledge transfer is defined by industry income, patents, co-publications with industrial partners, and spin-offs, while regional engagement – by graduates working in the region, student internships in the region, regional joint publications and income from regional sources.

-------------- [[[ ] (Features of Development of Regional Research and Innovation Systems [On the Example of Russia and Kazakhstan])

2016 ◽  
Author(s):  
Lyudmila Petrovna Kleeva ◽  
Ivan Vladimirovich Kleev ◽  
Annn Nikittva ◽  
Alexander Yur'evich Krotov
Keyword(s):  
Innovation Systems ◽  
Regional Research ◽  
Research And Innovation

scholarly journals Regional Innovation Systems in Poland: How to classify them?

2021 ◽  
Vol 17 (3) ◽  
pp. 987-1003
Author(s):  
Dorota Ciołek ◽  
Anna Golejewska ◽  
Adriana Zabłocka-Abi Yaghi
Keyword(s):  
Innovation Policy ◽  
Innovation System ◽  
Weighted Average ◽  
Innovation Systems ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Metropolitan Regions ◽  
Industrial Enterprises ◽  
Innovation Potential ◽  
And Performance

The literature emphasises the role of regional and local innovation environment. Regional Innovation Systems show differences in innovation outputs determined by different inputs. Understanding these relationships can have important implications for regional and innovation policy. The research aims to classify Regional Innovation Systems in Poland according to their innovation capacity and performance. The analysis covers 72 subregions (classified as NUTS 3 in the Nomenclature of Territorial Units for Statistics) in 2004–2016. Classes of Regional Innovation Systems in Poland were identified based on a combination of linear and functional approaches and data from published and unpublished sources. It was assumed that innovation systems in Poland differ due to their location in metropolitan and non-metropolitan regions, thus, the Eurostat NUTS 3 metro/non-metro typology was applied for this purpose. Panel data regressions as models with individual random effects were estimated separately for metropolitan and non-metropolitan groups of subregions. The study identified common determinants of innovation outputs in both NUTS 3 types: share of innovative industrial enterprises, industry share, unemployment rate, and employment in research and development. Next, NUTS 3 were classified within each of two analysed types in line with output- and input-indices, the latter being calculated as non-weighted average of significant inputs. Last, the subregions were clustered based on individual inputs to enable a more detailed assessment of their innovation potential. The cluster analysis using k-means method with maximum cluster distance was applied. The results showed that the composition of the classes identified within metropolitan and non-metropolitan systems in 2004– 2016 remains unstable, similarly to the composition of clusters identified by inputs. The latter confirms the changes in components of the capacity within both Regional Innovation System types. The observed situation allows us to assume that Regional Innovation Systems in Poland are evolving. In further research, the efficiency of Regional Innovation Systems should be assessed, taking into account the differences between metropolitan and non-metropolitan regions as well as other environmental factors that may determine the efficiency of innovative processes.

scholarly journals Cross-border approach to regions’ smart specialization: experience of the EU member states

2020 ◽  
Vol 7 (3) ◽  
pp. 36-48
Author(s):  
Olha Demedyuk ◽  
Khrystyna Prytula
Keyword(s):  
Regional Development ◽  
Recent Decade ◽  
Innovation Systems ◽  
Member States ◽  
Innovative Strategies ◽  
Eu Member States ◽  
Border Regions ◽  
Cross Border ◽  
Smart Specialization ◽  
The Eu

In the recent decade, the EU Member States have been actively implementing the regional development policy based on innovative strategies of smart specialization. However, lately, European researchers have been paying increasing attention to the issues of regions’ capacity to overcome the boundaries of administrative units inside the country and abroad and to the need to consider regions in the context of their functioning among others, especially from the viewpoint of the growing role of their innovative networks in global value chains. That is why currently the EU is addressing the development of cross-border smart specialization strategies. The paper aims to study the European experience on the functioning of cross-border innovation systems and joint strategic planning of cross-border regions’ development based on smart specialization and to outline the opportunities to implement the EU experience of cross-border approach to smart specialization in cross-border regions of Ukraine with EU Member States. The paper analyzes the views of foreign researchers on the links between innovation systems in cross-border space that constitute the theoretical basis of the study of cross-border smart specialization strategies, namely regarding the dimensions and level of their development. The research of European scientists on cross-border innovation systems in specific cross-border regions is examined, in particular on Spanish-French and German-French borders. Directions of implementation of smart specialization projects in cross-border context under the EU programs and other EU instruments that support regions in cooperation for the elaboration of joint view of development with neighbouring economically, socially, culturally, and historically close regions are outlined. The experience and methodology of the first cross-border smart specialization strategy for Spanish and Portuguese regions are studied in detail. The opportunities to use the EU experience by several Western Ukrainian regions based on the joint smart specialization priorities with the neighboring EU states are outlined. For this purpose, 1) the RIS3 strategies of the regions of Poland and Romania adjoining Ukraine and Regional Development Strategies of respective Ukrainian regions were analyzed to detect similar smart specialization priorities; 2) the clusters in the mentioned regions were analyzed as main drivers of achievement of smart specialization goals to detect similar or complementary functioning areas.

scholarly journals Propuesta de un Método para la Aplicación de un Modelo de Simulación Basada en Agentes del Sistema Regional de Innovación

2015 ◽  
Vol 3 (2) ◽  
Author(s):  
E Embuz ◽  
J D Fernández-Ledesma
Keyword(s):  
Simulation Model ◽  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation System ◽  
Regional Innovation Systems ◽  
Research Groups ◽  
Regional Innovation ◽  
Regional Systems ◽  
Project Analysis ◽  
Los Grupos

Este artículo propone un método que permite aplicar de forma práctica, precisa y efectiva un Modelo de Simulación Basado en Agentes del Sistema Regional de Innovación (SRI), el cual ha sido desarrollado dentro del Proyecto “Análisis de la Estructura, relaciones y dinámicas de agentes de los Sistemas Regionales de Innovación” liderado por los Grupos de Investigación GISAI y GTI pertenecientes a la Universidad Pontificia Bolivariana sede Medellín. Esta propuesta de método está centrada en una revisión de las necesidades más relevantes de los Sistemas Regionales de Innovación y cómo éstas deben ser suplidas paso a paso a través de la estructura del Modelo de Simulación en su aplicación. AbstractThis paper describes a method of applying a simulation model based on Agents of Regional Innovation System (SRI), which has beendeveloped within the project "Analysis of the structure, relationships and dynamics of agents of the Regional Systems described innovation"led by GISAI Research Groups and belonging to the Universidad Pontificia Bolivariana in Medellín GTI. This proposed method is focusedon a review of the most important needs of the Regional Innovation Systems and how they should be met step by step through the structure of the simulation model in its application.  

Regional Innovation Systems: Finland’s Experience

2012 ◽  
pp. 51-63
Author(s):  
V. Pchelintsev
Keyword(s):  
Systems Approach ◽  
Innovation Policy ◽  
Regional Scale ◽  
Innovation System ◽  
Policy Instruments ◽  
Innovation Systems ◽  
Regional Innovation Systems ◽  
Regional Innovation ◽  
Non Local ◽  
Innovation Policies

The paper examines governmental strategies, main actors and instruments of innovation policies shaping innovation-driven economy in Finland, with particular attention to the regional scale. The analysis focuses on how the regional innovation systems approach became a framework for the design of innovation policies. An innovation system involves cooperation between firms and knowledge creating and diffusing organizations, – such as universities, colleges, training organizations, R&D-institutes, technology transfer agencies. Innovations are considered as interactive learning process. Cooperation and interaction between regional/local and national/international actors is necessary to combine both local and non-local knowledge, skills and competences. The key elements of the policy environment, as well as implementation of the main regional innovation policy instruments – the Centers of Expertise Programme and Regional Centre Programme – are described.

Israel

2010 ◽  
pp. 272-280
Author(s):  
Edna Pasher ◽  
Sigal Shachar
Keyword(s):  
Intellectual Capital ◽  
Best Practice ◽  
Success Factors ◽  
Innovation System ◽  
Innovation Systems ◽  
Regional Innovation Systems ◽  
Information Communication ◽  
Regional Innovation ◽  
Knowledge Based ◽  
Critical Success

This chapter focuses on knowledge based development in regions, based on Israel’s experience. Israel, a small country in the Middle East, is a very unique case of a knowledge based region. The authors have extensively studied Israel as an innovative region in different contexts. Since 1998 they published three Israel Intellectual Capital Reports for the Israeli Government. During 2007 the authors led a study for the European Commission focused on regional innovation systems. This study has aimed to measure the effectiveness of participation in ICT (Information Communication Technology) EU projects on the EU innovation system at the regional level. Israel was selected as a regional best practice though it is a nation state and not a region since it is as small as a region, and since the authors had good relevant data from the previous IC reports and since Israel is consistently recognized as one of the most innovative countries in the world. The authors discovered that an Intellectual Capital audit is a powerful and useful framework to understand the effectiveness of regional innovation systems, offering the possibility for evidence-based future policies rather than retrospective performance analyses. This chapter demonstrates the case of Israel as a knowledge-based region, as well as critical success factors for regional innovation systems.

scholarly journals Unused potential for Smart Specialization development through collaboration: Lithuanian case

2019 ◽  
Vol 65 (No. 10) ◽  
pp. 463-469
Author(s):  
Živilė Gedminaitė-Raudonė ◽  
Dalia Vidickienė ◽  
Rita Vilkė
Keyword(s):  
Quadruple Helix ◽  
Structured Interviews ◽  
Policy Makers ◽  
Research And Innovation ◽  
Research Findings ◽  
The Will ◽  
Smart Specialization ◽  
Post Industrial ◽  
Quadruple Helix Model ◽  
Industrial Economic

Smart Specialization in this research is addressed to the use of collaboration as a tool for increasing efficiency of investment in entrepreneurship, research and innovation in a service-driven post-industrial economic system. This study provides evidence that collaboration potential is used only partly during the implementation of Smart Specialization strategy. The research illustrates given thesis by the evaluation of collaboration in Lithuanian biogas sector, which is listed among the priorities of Lithuania’s Smart Specialization strategy till 2020, using structured interviews. The main aim of this empirical research is to assess the will to collaborate in order to enhance the development of Smart Specialization and identify unused collaboration potential among all Quadruple Helix model counterparts in the biogas sector. Empirical findings show that collaboration in the Smart Specialization development has a big potential. However, this potential is used only partly because of lack of knowledge and available business infrastructure for this task and the passive role in collaboration processes of government institutions. Research findings suggest that current situation should be changed by supporting measures for business and NGOs with the aim to encourage collaborative initiatives for Smart Specialization. Research findings might serve as guidelines for policy makers, entrepreneurs, university and NGO managers.<br />

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