Current Trends in Regional Innovation System Thinking and Policy Making
Notice bibliographique
Résumé
The literature on the spatial organisation of innovation has been exemplified by concepts such as ‘innovative environments’ (Aydalot, 1985), ‘innovative milieux’ (Camagni, 1991), and ‘regional innovation systems’ (Cooke, 1992). Over the past two decades, the concept of regional innovation systems has evolved into an accepted way of understanding the uneven spatial development of the knowledge-based economy. Innovation systems emphasize both the importance and uniqueness of context, path-dependency and lock-ins, and complementary action by a broad range of stakeholders in affecting change. The focus on a broad set of actors (private, public, and more recently society in a broader sense) and formal and informal interactions for knowledge dissemination, adaptation, and production to explain regionally produced competitive advantage made regional innovation system thinking a popular tool for policy makers to support the creation of new pathways for exchange by means of implementing a vast array of newly developed innovation instruments (Guy, 2014; Teirlinck et al., 2013), not in the least in the field of technology intermediaries. Our understanding of regional innovation systems is not static and has evolved in line with major trends in innovation (such as open innovation - Chesbrough, 2003) but also in terms of our understanding of how to account for the specific regional context (Asheim et al., 2013). System components, linkages, and boundaries, along with path-dependency (Boschma and Frenken, 2006) and endogenous potential (following the views provided by Friedmann, 1972; and Aydalot, 1985) reflected in critical mass, absorptive capacity, smart specialisation, network capabilities, and the institutional framework within the region, are increasingly being considered keystones in regional innovation system thinking (Guy, 2014). This innovation system way of thinking is opposed to a neoclassical economic approach assuming that economic agents can easily change production technology or its underlying broader knowledge base (Guy, 2014). Building on some of the core themes presented and debated at the 8th European Conference on Innovation and Entrepreneurship (ECIE 2013, Brussels, Belgium), this special issue of the International Journal of Innovation and Regional Development is devoted to actual trends in innovation systems and policy making. The issue offers a balanced geographical mixture of regions in emerging and more developed economies (Mexico, Poland, Canada, Belgium, and Indonesia) as well as a triangulation of qualitative and quantitative approaches. The issue starts with two papers providing original overall system level insights in further strengthening our understanding of the regional innovation system approach. They capture the permanent changes - territorial, sectoral, technological - innovation system thinking is undergoing. Starting points are that each system has its own features and characteristics, and the necessity to give a dynamic description of the configuration of each system in order to forecast its possible future evolution.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».