Par la promotion de l’innovation en réseau, les instruments de dynamiques territoriales sont devenus aujourd’hui des outils de support indispensables à la compétitivité des entreprises et à la croissance des nations. C’est dans cet esprit que sont conçus les pôles de compétitivité dans le dispositif français de 2005. L’innovation collaborative à l’échelle des pôles de compétitivité vise en premier lieu à créer des débouchés nouveaux, c’est-à-dire à générer des innovations prêtes à être diffusées sur les marchés. Or, si les réseaux d’innovation ont été largement étudiés à travers des outils de pilotage, de gouvernance et de coordination, par la finance, la propriété intellectuelle ou les pratiques de RH, par la formation, par la confiance entre les partenaires, par les externalités, ou encore par la dynamique des PME, une carence persiste dans les recherches actuelles à propos de l’orientation stratégique composite des réseaux d’innovation, en particulier l’orientation marché ou client dans la dynamique des projets/acteurs. Les premiers rapports d’évaluation des Pôles dénotent au demeurant, des écueils relatifs à une collaboration propice à des innovations prêtes pour l’accès aux marché et la stabilisation de problèmes liés au fonctionnement, à la gouvernance et à la performance des pôles. Tout en nous inscrivant dans le courant des travaux de recherche qui mettent en exergue les spécificités du dispositif français des pôles de compétitivité composé d’acteurs complémentaires (Recherche, Formation et Entreprises), notre travail met l’accent sur le fait que l’innovation collaborative est mise en tension par des intentions stratégiques différenciées, liées précisément aux profils hétérogènes, et parfois divergents, des partenaires animés par un projet commun. Par une analyse empirique portant sur le pôle SCS que nous avons choisi en raison de son profil, de la nature de ses projets et de son historique collaboratif avec notre laboratoire de recherche (abondance de données préexistantes), nous tentons de comprendre la façon dont s’intègre l’orientation « marché » dans les projets d’innovation en réseau, et le rôle que la dimension marketing joue dans la dynamique d’innovation collaborative au sein des pôles de compétitivité. L’étude « qualimétrique » conduite a permis de mettre en évidence une relation de dépendance réciproque très forte entre les particularités des déterminants de l’innovation collaborative, notamment les profils d’acteurs et les intentions stratégiques, et les modalités d’intégration de l’orientation client/marché dans les dans les projets d’innovation collaboratifs (PIC). L’attribut « réseaux de connaissances » qui distingue les PdC octroie au marketing une place limitée dans les PIC. Aujourd’hui, une révision du modèle assimilable à un « réseau connaissances » s’impose, car les résultats montrent aussi une limite des marges de manœuvre des Pôles qui peut constituer une entrave à l’accès aux marchés des innovations issues des PIC. En effet, le processus d’innovation collaborative à l’échelle des PdC ne permet qu’au plus de parvenir à dresser des prototypes (β Product) et n’octroie pas de possibilité d’aller au-delà (test, production, mise sur le marché, etc.). Nos contributions théoriques et managériales permettent aujourd’hui d’ouvrir des grilles d’analyses nouvelles et d’améliorer le fonctionnement, la gouvernance et la performance des pôles à travers le succès des projets d’innovations collaboratifs. La thèse nous a aussi amené à développer des hypothèses nouvelles qui pourraient être échafaudées dans le cadre de recherches ultérieures, notamment au regard de la pertinence des réseaux de connaissances dans le processus complet d'innovation collaborative. / By promoting networked innovation, instruments of territorial dynamics have now turn out to be essential tools supporting firms' competitiveness and growth of nations. Clusters of competitiveness (CC) designed by French government in 2005 follows that state of mind. The first goal of collaborative innovation within CC is to create new opportunities and generate innovations ready to be diffused on new markets. However, if innovation networks have been widely studied through many questions (such as monitoring tools, governance and coordination, with finance, intellectual property or HR practices, training, trust between partners, externalities, or by the dynamics of SMEs), a deficiency persists in current researches about the strategic orientation of the composite innovation networks, more particularly with the customer or market orientation in the dynamics of projects / actors. Moreover, the first evaluation reports of the system had put a focus on pitfalls considering its capacity to generate innovations ready for market access and the stabilization of operation difficulties, as well as some governance and performance problems. While placing our analysis within current researches which highlight the specificities of the French clusters of competitiveness composed of complementary protagonists (Research, Academic and Enterprise), we intend to focus on the fact that collaborative innovation is tensioned by differentiated strategic intentions and profiles specifically related to heterogeneous, and sometimes conflicting, partners driven by a common project. By an empirical analysis carried out on the SCS French cluster chosen owing to its profile, the nature of its projects and the background history of collaboration with our laboratory (a wealth of existing data); we try to understand how the customer orientation fits into the clusters, and the role that marketing plays in the dynamic collaborative innovation within clusters of competitiveness. Our “qualimetric” study has allowed us to bring out a very strong mutual relationship of dependency between the particularity of collaborative innovation determinants, notably profiles of actors and strategic intentions, and how to integrate the customer / market orientation within the collaborative innovation projects. As "knowledge networks", CC grant to marketing and customer orientation a limited role in the collaborative innovation projects. Today, a revision of the model similar to a "knowledge network" is needed because our results seem also to reveal a limited room for maneuver of clusters of competitiveness, which can be for the collaborative innovation projects an obstacle for generating innovations ready for market access. Indeed, in its current state the process of collaborative innovation on a clusters of competitiveness scale enable only to obtain prototypes (β Product), and does not permit to go beyond (ie. test, production, market, etc.). Our theoretical and managerial contributions allow to open up new analytical tools as well as to improve the operation, the governance and the performance of cluster competitiveness through the success of collaborative innovation projects. The thesis has also led us to develop new hypotheses, which could be built up through further researches, in particular with regard to the relevance of knowledge networks in the whole process of collaborative innovation.

This research investigates the impact of organizations' collaboration strategies and network positional variables on invention performance. Organizations, particularly those pursuing a differentiation strategy, are motivated to introduce novel products and services in order to remain competitive. Thus, two questions of interest to such organizations regarding the network dynamics of the invention process are: 1) What kind of strategies allow them to attain superior invention results? 2) What is the most advantageous structural positioning in a collaborative network of innovators? Three independent studies attempt to find answers to these questions by using three complementary study approaches. In the first study, in order to examine invention performance of organizations with different collaboration strategies, a simulation model is constructed and run at various levels of technological dynamism and with various types of invention tasks. The cognitive cooperation strategy, which pursues technological knowledge integration as a priority, is found to be the most effective strategy in most experiments. Success-driven cooperators, whose priority is to collaborate with the most effective performers in the network, provided the most consistent invention performance. Moreover, different strategies are shown to perform best at certain points of the industry environment space spanned by technological dynamism and invention type. The second study investigates the impact of positional metrics in a collaboration network on the inventive performance of organizations (as measured by the number of patents issued) by using survey data. Twenty-eight high-tech companies and universities located in Florida are surveyed to reveal their collaborative networking map. Network structural measures are obtained in order to test the hypotheses that high values in centrality metrics correspond with higher inventive performance. The regression analyses imply that degree and closeness centralities are predictive indicators of high inventive performance but the data does not support the significance of impact of local clustering. The third study analyzes the impact of positional metrics on inventive performance by using a national database for the announced research and production joint ventures. From the most inventive organizations (in terms of patent counts) 63 of them are selected for analysis. 371 research and production joint ventures are analyzed to identify their relationship network every year from 1994 to 2012. The results indicate that the number of joint venture partners, being close to other members of the network through network connections and strong local connectivity (except for their interaction effect) is associated with higher invention performance. All three studies bring new methodological contributions to the area of invention network research. The simulation study offers a new model in the area of collaborative invention networks. Furthermore, the ideas and practices developed during the construction of the agent based simulation model for the invention network can be adapted to similar areas of application. The survey study offers a holistic approach for the definition of connections in the development of invention network map and empirically tests it. The database study longitudinally analyzes the evolution of a highly accurate joint venture network over 19-year period while testing the impact of positional metrics with un-weighted and weighted calculation methods. Solutions to our health problems, communication or transportation needs etc. are not usually found due to some series of fortunate events. They are the product of an effective recombination process of technological knowledge. Moreover, effective invention performance is not only important for organizations individually, it is crucial for governments that are concerned with the problems of its citizens. Effective ways of facilitating the recombination of technological knowledge are addressed and presented to inform both companies and policy makers. Better understanding of the dynamics of the invention process will bring more solutions to existing problems.

This thesis addresses the challenges that firms are faced with when collaborating with suppliers in new product development (NPD) projects under technological uncertainty. A critical observation that is made in this context is that technologies are evolving faster, making products more complex. At the same time, firms become more specialized. Due to increased complexity and specialization, firms do not possess all the necessary technologies in-house and therefore need to collaborate with external organisations to incorporate new technology into their products. Common collaborators are suppliers who become integrated into the buying firm’s NPD project. However, finding suppliers and collaborating with suppliers in NPD can be problematic. In addition, external collaborations also impact the buying firm internally, since it often needs to coordinate its departments. The purpose of this thesis is to explore supplier involvement in NPD under technological uncertainty. Challenges in supplier selection are concerned with the issues of involving new suppliers or relying on old acquaintances, managing uncertainties, the dilemma of whether to commit to long-term relationships or to maintain flexibility, and deciding on which department that is responsible for evaluating and selecting the supplier. The present study of buyers and suppliers in NPD, shows the challenges that are involved in balancing control, reaching goal alignment, and managing transactional and relational governance. Internal challenges investigate the coordination between the R&D department and purchasing in NPD projects where suppliers are involved. The present findings may be of value for firms who engage in collaborative NPD, or for firms who aim to involve suppliers in their development of new products.