Mapping out the Triple Helix: how institutional coordination for competitiveness is achieved in the global wine industry
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Notice bibliographique
Résumé
As of 2010, the OECD countries spent over $968 billion annually on research and development (R&D), with China spending another $179 billion, Russia $32 billion and Taiwan $24 billion. Evidently, the world’s policymakers have concluded that investment in R&D is a key to their future economic growth. As globalisation takes place, and developing countries increasingly show their ability to compete in labour-intensive manufactures, the race is on to develop new innovations that will create high skill, high productivity employment. President Obama’s championing of electric cars, alternative energy research and other high technology ventures is mirrored in efforts around the global to win the innovation race. But how such efforts should be organised is very much open to debate. This paper reviews in depth perhaps the fastest growing perspective, namely the Triple Helix. In June 2013, a Google search for ‘Triple Helix innovation’ revealed 281,000 hits. A library search gave over 1300 citations in books and papers using the same terms. An international association, TripleHelix.org, organises an annual conference featuring thousands of participants from academia, government and business. All of this indicates that the Triple Helix has become one of, if not the, most widely used perspectives on innovation. However, there are some major shortcomings with the approach, in particular its applicability to policy situations. Over the course of 2009–12, we developed case studies of the wine industry in Latin America, the Middle East, Central Asia, Australia, New Zealand, Canada and several US states by mapping out Triple Helix institutions and examining their interactions through secondary analysis of the literature; primary searches for industry and policy documents and websites; a global online survey of key actors; and, in most cases, in-depth interviews with the principals of key research, policy and industry bodies. Our exercise allows us to move towards more specific policy recommendations for improving innovation and competitiveness than Triple Helix theory has allowed up to this point. In creating a more precise and analytical mapping tool for Triple Helix interaction, we can develop the present heuristic approach of the Triple Helix into an approach that can examine what is actually happening in terms of inter-institutional coordination for innovation. With more precise maps of institutional interaction as it exists, we can understand more about what types of interactions are most effective in which situations. We are able to show the utility of this approach by revealing patterns across the wine case studies which suggest how the Triple Helix can be better understood, measured and applied to concrete situations. Above all, attention to strategy developed through consensus and policy leadership, and the development of specialised and locally-adapted hybrid organisations with both formal and informal overlapping personnel and funding, appear to be the keys to ensuring a successful Triple Helix innovation system.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| 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 découle