The purpose of this research is to explore how proximity dimensions can favour the diffusion of knowledge between economic actors, focusing on the knowledge relationships established by a knowledge gatekeeper. In particular, the authors formulate several hypotheses regarding the role of proximity dimensions (i.e. geographical, organizational, and technological) in affecting the establishment of gatekeepers’ knowledge relationships, taking into account their collaborative-non collaborative type and exploitative-explorative nature. Adopting a patent-based analysis, the authors test their hypotheses on a research sample constituted by 527 knowledge relationships established by two distinct types of knowledge gatekeeper, i.e. an university and a firm.
Top1. Introduction
Nowadays, it is generally recognized that the creation of knowledge and its efficient and effective use are fundamental for the development of innovations and high value-added activities, then representing the core of firms and nations’ strategies for growth (see also Hamel and Prahalad, 1994; Tallman et al., 2004). The creation of new knowledge and its implementation into innovations can be conceived as an open system which combines pieces of knowledge and information both internal and external to the organizations (Katz and Kahn, 1996). This depends on the fact that organizations are more and more specialized and hence, seldom have all the required resources internally.
Shifting the focus from single organizations to regions or districts, scholars have underlined the importance of knowledge sources external to the geographical areas. In fact, they can “open” these areas through the establishment of global relationships, so avoiding cognitive locking situations at the local level (see also Camagni, 1991; Breschi, 2000; Pouder and John, 1996).
The process of inter-organizations knowledge transfer is often performed by networks, which can be seen as hybrid organizational structures, alternative to both market and hierarchy (Lambooy and Boschma, 2001; Powell et al., 1996; Williamson, 1999). Networks consist of three components: i) nodes, as individuals or organizations, ii) connections, as communication channels, and iii) the intensity of the transfer of knowledge, in terms of strong or weak ties (Granovetter, 1973; Krackhardt, 1992). In general, it can be contended that these structures perform two main functions. First, they support the co-ordination of decisions made by separate nodes of the network and second the transmission of data, information, and knowledge (Lambooy, 2004). With this regard, nodes can establish relationships aimed at exchanging knowledge (knowledge relationships) based on different types of learning processes, such as interaction and imitation ones (e.g. Malerba, 1992). In particular, processes of learning by interaction are related both to the interaction with upstream/downstream sources of knowledge (such as suppliers, and customers) and to the collaboration with other firms and scientific organizations (such as universities and research centres). On the contrary, processes of learning by imitation are based on the observation of what competitors and other organizations are doing and on the absorption of their developments in science and technology. On the basis of this distinction, it is possible to recognize two main types of knowledge relationships between nodes, such as collaborative and non collaborative ones, created through interaction and imitation learning processes, respectively. In particular, I identify collaborative (non collaborative) knowledge relationships according to the direct (indirect) participation and involvement of two or more actors in designing and/or producing a product or process (see also Polenske, 2004).