Publication
Essays in regional innovation systems, knowledge economy and policy-making: an applied perspective to European context.
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.author | Soeiro, Filipe Castro | |
| dc.date.accessioned | 2016-02-03T14:35:28Z | |
| dc.date.available | 2016-02-03T14:35:28Z | |
| dc.date.issued | 2013-07 | |
| dc.description.abstract | EU Policy-making, Knowledge Economy and Regional Innovation Systems (RIS) are being researched with the aim of improving R&D and Innovation Investments and translate them into economic and employment growth in a sustainable and convergent way. However, in one hand, the EU1 context is far from convergence at country-based innovation level and on the other hand is experiencing a transitional macro referential change from an economy based on natural resources and physical inputs to one based on knowledge, intellectual assets, technology market transfer processes and commercialization of innovation. Moreover, international overview based on EU and A.P.E.C.2 countries had been risen the priority of studying, and optimizing Regional Innovation Systems, and also the need to overcome, on the one hand, the “European Paradox” and the role of Regional Innovation Systems (RIS), translating R&D investments into economic and employment growth, and the necessary changes on EU policies, on the other hand. Thus, the aim of this doctoral research is to provide a full comprehension of the RIS structure and respective mapping of inputs, outputs and hidden variables, in order to foster optimization and provide an empirical model on Regional Innovation System, as well as discussing implications regarding knowledge Economy processes and Policy-Making recommendations in the EU context. This PhD thesis follows the three Essays structure. The first chapter is focusing on identifying, analyzing and discussing the dimensions that shape Regional Innovation Systems’ structure and evaluate if and how the underlying RIS subsystems exert any statistically significant effect on employment and economic growth, leading to the analysis and discussion of best common practices and policy-making applied to European regions. There is empirical evidence showing that Innovation could effectively be managed in a regional scope, due to localized nature of sources of competitive advantages, technological transference knowledge, new business formation and local innovation capabilities and processes. Considering empirical research models and operational datasets available concerning NEG (New Economic Geography), Knowledge Production Function, Knowledge Spillover Theory of Entrepreneurship and other “Endogenous Growth” theories, and RIS (Regional Innovation Systems) theoretical models, there is still room for improvement regarding empirical models research. In this first chapter, based in theoretical findings in the literature review and progress beyond the knowledge state-of-art concerning Knowledge Economy and Regional Innovation Systems, is discussed the idea on how the European Commission’s Research and EU Innovation policies can be more effective and improved, even if that implies a paradigm change from a transnational approach to a localized-regional, operational and measurable framework, in order to effectively translate R&D investments into innovation, employment and economic growth. The purposes of chapter two is to analyze and discuss an innovative model approach to Regional Innovation System (RIS), by applying Artificial Neural Networks (ANNs), in order to generate pattern recognition algorithms capable of capturing salient features from a set of inputs and mapping them to outputs without making a priori assumptions about the specific nature and impact of the relationships. Hence, the main goal is to cast some light inside the “innovation’s black-box”, describing Regional Innovation Systems (RIS) architecture and reducing the uncertainty surrounding R&D investments’ effectiveness in order to promote innovation, economic growth and employment. The ANNs modelling was applied to the study of RIS architecture, aiming to identify the “hidden” mediatory variables, which could influence the overall impact on employment and economic growth. Empirical evidences demonstrate that the underlying RIS subsystems are not homogenous and can generate negative side-effects, leading to decreasing of net job formation. Results suggest that the economical agents’ “quality” cannot be merely replaced with success by the implementation of “Keynesian policies” focused on enhancing “Market Potential”, “Demand Sophistication” and “Governmental R&D Investments”. In this sense, improving regional “Absorptive Capacity” is the most balanced and short-term development strategy for the regions characterized by a lower industrialization and income. However, the most stalwart and long-run impact on employment and economic growth potential is provided through regional “Innovative Potential” reinforcement. The importance of applying ANN model leads to higher “goodness-of-fit” to explicative variables, when compared with other methods, namely Linear Regression, and also supports guidance on Policy-Making, in a more accurate and integrative way. The findings reinforce the idea that European Commission’s Research and Innovation policies can be restructured and improved, changing from an expenditure increase paradigm, focused on a transnational approach, to a localized regional framework in order to effectively translate R&D investments into Employment and Economic Growth. The main findings were analyzed at the light of the research knowledge that applies ANNs to study RIS and policy-making implications are discussed. Finally, in chapter three, general and specific arguments that support the use of State policies towards the promotion of innovation and entrepreneurial activities are discussed in the EU context, and by considering the insights of the previous two chapters, is discussed the justification of current innovation entrepreneurial policies in EU and in Portugal and assessed what could be as forward recommendations to RIS model and Policy-Making. The development of the three “Essays” focusing on Regional Innovation Systems, “Innovation Black-box” and Policy-Making in the EU context, is aiming to contribute to European Commission’s Research, namely in what regards to Regional Innovation Systems’ planning and management, and to Innovation and Growth Policies. (Keywords: Artificial Neural networks, Knowledge Economy, Regional Innovation Systems, European Paradox, Knowledge Triangle, Innovation, 8th Framework Program for Research and Innovation, Europe 2020 Growth Strategy, Agglomeration Economics, Knowledge Spillover Theory of Entrepreneurship and Spatial Clusters, Sources of Sustained Competitive Advantages, Competitive Industry Structure, knowledge-Based Clusters, Cluster Mapping and Policy-Making). | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.6/3986 | |
| dc.language.iso | eng | pt_PT |
| dc.subject | Economia do conhecimento | pt_PT |
| dc.subject | Economia regional - Sistemas de inovação | pt_PT |
| dc.subject | Desenvolvimento económico - Estratégias políticas | pt_PT |
| dc.subject | Europa - Sistemas regionais de inovação | pt_PT |
| dc.title | Essays in regional innovation systems, knowledge economy and policy-making: an applied perspective to European context. | pt_PT |
| dc.type | doctoral thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | doctoralThesis | pt_PT |
| thesis.degree.name | Doutoramento em Economia | pt_PT |
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