Knowledge management and diffusion: the network paradigm
Introduction This chapter deals with the issues related with the management and the diffusion of knowledge in a group of tourism companies by discussing the network approach to the phenomenon. As well known, a tourism destination is a complex interconnected system made of a number of diverse entities (firms, associations, consortia, etc.). Today, more than ever, these systems have a necessity to find creative and innovative ways to assemble their products, to communicate and market them. As discussed in other contributions to this volume, an essential prerequisite for acting effectively is the formation of a common knowledge which must be generated, shared and used (Cooper 2006). This, as with other dynamic processes, has been found to depend strongly on the number, the distribution and the type of relationships that bind the different actors in a destination (Barrat et al. 2008). The network formed by them needs thus to be carefully studied and understood in order to find optimal paths for the spread of knowledge. These studies, complemented by the qualitative analysis of the determinants and the environmental conditions for efficient knowledge transfer and acquisition may give a comprehensive picture of the situation and provide important hints for developing governance practices aimed at improving destination stakeholders’ capabilities (Scott et al. 2011). Network analysis methods have not been widely applied to tourism destinations. However, the results obtained so far have shown their effectiveness in a number of different circumstances. They have been used to identify the important members in a destination; those who can make the most important contributions to the growth of tourism activities and to destination governance. A comparison between the perceived importance of organizations in a destination and their network characteristics allows the establishment of a set of metrics able to describe this feature. It has been found also that the key stakeholders are located in the core of the network, and form an elite that are seen as more relevant than the peripheral stakeholders. This implies that the governance of a destination is controlled by a limited number of actors and is a further confirmation of the necessity of creating cohesive inter-organizational networks for the production of integrated tourism experiences (Cooper et al. 2009). As may be
expected, public stakeholders are among the most important elements in destination networks (Presenza and Cipollina 2009) as they ‘possess’ critical resources, have the highest centrality and hold the greatest legitimacy and power over others (Timur and Getz 2008). A number of other network properties reflect real world characteristics as identified by Scott et al. (2008). The density of links (actual number of links compared to total number of possible links) relates to the cohesiveness of a group, an important property in determining cooperative behaviour. The possible local inhomogeneities in the density allow the identification of differences in the measures of inter-organizational cohesion in different settings. The statistical distribution of the relationships that form a value-creation system affects the general dynamic behaviour of the system. Studies have shown that tourism destinations networks have low density of connections and limited clustering (Baggio et al. 2010; da Fontoura Costa and Baggio 2008). This is an important result, because the identification of weaknesses in the cohesiveness of the destination can be addressed by policy and management interventions. In fact, network analysis techniques are not only useful as diagnostic tools, but also allow the modelling of possible changes to a destination system in order to achieve configurations that are optimized with respect to some desired objective. In this contribution the network paradigm is discussed by looking at the main methods that a vast interdisciplinary literature has been assembling in the last few years. The most important and used statistical and mathematical techniques for the study of a system of interconnected entities are described. Next there is a brief introduction to the main concepts and measurements. Finally, the dynamic processes of diffusion are examined.