Abstract
Regional innovation performance is an important indicator for decision-making regarding the implementation of policies intended to support innovation. However, patterns in regional innovation structures are becoming increasingly diverse, complex and nonlinear. To address these issues, this study aims to develop a model based on a multi-output neural network. Both intra- and inter-regional determinants of innovation performance are empirically investigated using data from the 4th and 5th Community Innovation Surveys of NUTS 2 (Nomenclature of Territorial Units for Statistics) regions. The results suggest that specific innovation strategies must be developed based on the current state of input attributes in the region. Thus, it is possible to develop appropriate strategies and targeted interventions to improve regional innovation performance. We demonstrate that support of entrepreneurship is an effective instrument of innovation policy. We also provide empirical support that both business and government R&D activity have a sigmoidal effect, implying that the most effective R&D support should be directed to regions with below-average and average R&D activity. We further show that the multi-output neural network outperforms traditional statistical and machine learning regression models. In general, therefore, it seems that the proposed model can effectively reflect both the multiple-output nature of innovation performance and the interdependency of the output attributes.
Highlights
Innovation has been recognized as a central issue in EU development and one of the crucial drivers of economic welfare, especially since the introduction of the Lisbon strategy
We argue that multi-output artificial neural networks (ANNs) model is more appropriate to model intrinsic multi-output and nonlinear character of innovation performance than traditional statistical and machine learning regression models
Several Multilayer Perceptron (MLP) architectures were tested, using the same set of 50 runs for each, avoiding problems associated with local minima
Summary
Innovation has been recognized as a central issue in EU development and one of the crucial drivers of economic welfare, especially since the introduction of the Lisbon strategy. Regions in the EU are important since they profit from spatial proximity and knowledge spillovers. Effective formal and informal cooperation among regional actors (both within companies as well as between firms and other organizations such as universities, innovation centers, educational institutions, etc.) can be established. Interactions in the FDI attractiveness of regions. Data from European Private Equity and Venture Capital Association (EVCA) are accessible at: www.investeurope.eu, file: Country-tables-Public-version-FINAL.xlsx
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