Advanced Manufacturing Activities of Top R&D investors: Geographical and Technological Patterns
Notice bibliographique
Résumé
Advanced manufacturing technologies (AMTs) and other key enabling technologies (KETs) are expected to have a major impact on productivity, efficiency, profitability and employment in major industrial sectors worldwide. Thus, development of AMTs and KETs\nis considered essential if the European Union is to achieve the strategic goals set out in the European Commission’s Employment, Growth and Investment priorities. Indeed, AMTs and KETs are among the top priorities identified as necessary to support the competitiveness of European industries in the context of the European flagship on industrial modernisation.\n\nThis study builds upon and extends results that were obtained in the context of the Advanced Manufacturing Technologies for Competitiveness AMTEC project, in which the technological profiles of the patent portfolios of the EU Industrial R&D Investment\nScoreboard companies were constructed using patent-based analysis. In particular, their technological competences were investigated and it was found that European companies invest in KETs, and in particular in AMTs, as these technologies are considered to be vital\nfor maintaining current competitiveness. However, other countries also invest heavily in AMTs and KETs.\n\nIt is therefore very important for the EU to define a strategy that aims to find a suitable position in the global value and innovation chains and that selectively augments existing capabilities. To this end, a methodology based on patent analysis was applied to assess the capacity of the world’s top R&D investors in developing AMTs. Particular emphasis was placed on complex AMT patents that also pertain to at least one of the five KETs. These patents are considered important because they represent AMT applications used for the development of KETs in general or, conversely, they represent other KET applications that can be incorporated into AMT systems. \n\nThe main questions addressed by this study were (1) In which countries are the most important inventors of AMTs and applicants for AMT-related patents located? (2) Is it possible to analyse internationalisation patterns and knowledge flows between world regions and countries? and (3) Are there any special patterns and clusters between AMT related technological fields and the five core KETs and, if so, which companies are responsible for the development of these technological applications?\n\nDeveloping and patenting AMT-related technologies is particularly important for firms in the Aerospace & defence, Industrials, Automobiles & parts and Electronics & electrical equipment sectors. Moreover, the more specialised a sector is in developing AMT-related technologies, the less internationalised the AMT-related activities of the firms in the sector appear to be.\n\nIn general AMT-related R&D activities of European- and US-based firms are more internationalised than the activities of Japanese- and Asian-based companies. It was found that many Scoreboard firms based in the USA, Japan, Germany, France and the UK own and develop a large number of AMT-related patents. However, there are also many inventors of AMT-related technologies based in other countries, such as China, India, Canada, Italy, Belgium and Spain.\n\nFinally, the ratio of complex AMT patents to the total number of AMT-related patents is close to 8%, the vast majority being patents that relate to micro- and nano-electronics, advanced materials or photonics. Companies that own these complex patents are often relatively small firms that are highly specialised in the development of AMT-related applications.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,007 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».