IRIS - Institutional Research Information System
IRIS è il sistema di gestione integrata dei dati della ricerca adottato dalla Luiss Guido Carli. Il Catalogo dei prodotti della ricerca della Luiss raccoglie e rende disponibile, dove possibile nel rispetto del diritto d'autore, la produzione scientifica dei docenti e ricercatori dell'Ateneo. Il Catalogo alimenta inoltre i siti docenti del MIUR.
EnglishThe paper investigates the impact of clusters, or localized networks involving industrial, academic and institutional players, in the life-science setting and aims to enrich the line of inquiry into cluster-based innovation by applying a social network analysis (SNA) approach. The cluster concept has been defined in ambiguous ways, corresponding to a large variety of spatial and organizational concrete configurations. We try to understand which of these configurations - i.e. what structural and nodal network characteristics of the cluster - are best suited to maximize the likelihood of clusters' innovation, from an intra-cluster and intercluster perspective. Quantitative methods are applied to relational and nodal data, using SNA and a regression model. The work sheds light on the factors that give rise to differential innovative outcomes across different clusters.
| Titolo: | Localized networks and innovation in the life-science sector. Inter-cluster and intra-cluster dynamics |
| Autori: | |
| Data di pubblicazione: | 2013 |
| Abstract: | The paper investigates the impact of clusters, or localized networks involving industrial, academic and institutional players, in the life-science setting and aims to enrich the line of inquiry into cluster-based innovation by applying a social network analysis (SNA) approach. The cluster concept has been defined in ambiguous ways, corresponding to a large variety of spatial and organizational concrete configurations. We try to understand which of these configurations - i.e. what structural and nodal network characteristics of the cluster - are best suited to maximize the likelihood of clusters' innovation, from an intra-cluster and intercluster perspective. Quantitative methods are applied to relational and nodal data, using SNA and a regression model. The work sheds light on the factors that give rise to differential innovative outcomes across different clusters. |
| Handle: | http://hdl.handle.net/11385/67660 |
| Appare nelle tipologie: | 04.1 - Contributo in Atti di convegno (Paper in Proceedings) |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| EGOS Full paper_D'Alise_Giustiniano.pdf | Documento in Pre-print | DRM non definito | Open Access Visualizza/Apri |
Copyright © 2020