Bridging a cultural divide: strengthening similarities and managing differences in university-industry relationships
Notice bibliographique
Résumé
Many policy makers view universities as economic agents that drive the innovations responsible for increased productivity and economic growth. Initiatives to harness this potential currently focus on commercializing academic research by protecting, managing, and licensing intellectual property. However, many recognize that traditional academic norms and practices can impede these activities. Consequently, some view the cultural boundaries between universities and firms as obstacles to effective knowledge transfer and argue that universities should alter these boundaries by creating commercial incentives to support "entrepreneurial academics." To create the appropriate incentives, policy makers need to understand how academic culture influences the creation of useful knowledge and how the differences between universities and firms influence collaboration. This dissertation addresses this need by investigating how the cultural and physical boundaries between researchers at the University of Toronto and their industry partners influence knowledge sharing within three collaborative programs: the IBM Centre for Advanced Studies, the Nortel Institute for Telecommunications, and the Bell University Labs. This includes an investigation into the benefits that motivate collaboration and the mechanisms through which the partners create, sustain, and conclude partnerships. This study finds that firms and universities share a number of interests and practices. These similarities foster greater understanding and trust between the partners, which facilitates collaboration. Resource sharing strengthens these similarities and firms that invest personnel, knowledge, materials, and data in a partnership increase effective communication and knowledge exchange. This study also finds that academic and firm partners exhibit distinct interests and practices that strongly influence knowledge transfer. These differences are an incentive as well as an impediment to collaboration. Conflicting norms and practices can create tensions but they also promote the development of complementary resources. Universities and firms collaborate because each brings distinct, though complementary, resources into the partnership. Since the norms and practices of each partner shape these distinctions, attempts to diminish cultural differences may partially erode the incentives to collaborate. Overemphasizing commercialization within universities may also impede the valuable informal knowledge exchanges that take place between partners. Managing tensions through third-party mediation and more effective communication channels promotes knowledge transfer more effectively than minimizing cultural differences.
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 | 0,001 | 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 | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| 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 ».