Knowledge transfer in a tourism destination: the effects of a network structure

TLDR

Tourism destinations must innovate to stay competitive, which requires understanding how they source, share, and use knowledge, with network theory framing stakeholders as interconnected nodes. The paper investigates how network analysis can illuminate knowledge sharing and guide policy to optimize tourism destinations, illustrated with a case study of Elba. Destinations are modeled as networks of public and private stakeholders, and epidemic diffusion models are used as analogies for knowledge transfer, which can be integrated with other network analyses. Numerical simulations of Elba demonstrate that the network can be optimized, confirming the practical value of network analysis for enhancing destination competitiveness. An earlier version of this paper was presented at the IASK Advances in Tourism Research 2008 Conference, Aveiro, Portugal, 26–28 May 2008.

Abstract

Tourism destinations have a necessity to innovate in order to remain competitive in an increasingly global environment. A pre-requisite for innovation is the understanding of how destinations source, share and use knowledge. This conceptual paper examines the nature of networks and how their analysis can shed light upon the processes of knowledge sharing in destinations as they strive to innovate. The paper conceptualizes destinations as networks of connected organizations, both public and private, each of which can be considered as a destination stakeholder. In network theory, they represent the nodes within the system. The paper shows how epidemic diffusion models can act as analogies for knowledge communication and transfer within a destination network. These models can be combined with other approaches to network analysis to shed light on how destination networks operate, and how they can be optimized with policy intervention to deliver innovative and competitive destinations. The paper closes with a practical tourism example taken from the Italian destination of Elba. Using numerical simulations, the case demonstrates how the Elba network can be optimized. Overall, this paper demonstrates the considerable utility of network analysis for tourism in delivering destination competitiveness.† †An earlier version of this paper has been presented at the IASK Advances in Tourism Research 2008 Conference, Aveiro, Portugal, 26–28 May 2008.