Analysing inter- business knowledge sharing in the tourism sector

Abstract

Introduction The purpose of this chapter is to consider the structural characteristics of network cohesion as an explanatory measure through which to understand the spread of knowledge resources within a tourism destination network. The dynamics of knowledge sharing can be explained through utilizing social network analysis (SNA). The mechanisms by which business individuals obtain knowledge are varied, but there is support for knowledge sharing being seen as a social practice as discussed in several chapters of this volume. Knowledge is needed to operate a business and as the business environment changes the sources and content of knowledge resources may vary to meet the changing needs of the business. Understanding those knowledge flows in an inter-business context involves utilizing analytical techniques to identify and examine the knowledge sharing practices of business individuals. Consequently, social network analysis is a viable analytical technique and theory that can be utilized to better understand inter-and intra-business knowledge sharing in the tourism sector. Networks can be viewed as relationships that link nodes and these links are often referred to as ties. As individuals relate and inter-relate a structure is formed which is defined as a network and this network can be mapped to understand the resource flows between the nodes. This is useful as knowledge is a resource which can be obtained through network connections (Skyrme 1999). By such a mapping exercise, the network’s cohesion can be examined and the possibilities that network resources can reach certain network members can be explained and therefore the outcomes of cohesive network structures can be determined. Social network methodology can provide a new way of understanding knowledge sharing which is an essential activity for the spread of knowledge resources and therefore these interactions can assist with improving the knowledge resources available to those individuals in an industry. Knowledge stocks, as noted by Chris Cooper in Chapter 5, can therefore be built up by individuals as single entities and an industry as a collective group of business individuals to improve the performance of those businesses in the tourism sector. This chapter begins with this introduction which outlines the importance of applying socialnetwork theory and analysis to the understanding of inter-business knowledge sharing in the tourism sector and, in doing so, social network theory and its application to knowledge sharing have been explored in subsequent sections. Thereafter, social network analysis is applied to a network of knowledge relationships in the tourism sector and analysing this network involves breaking down theories and applying measures to understand the social dynamics of knowledge networks. The chapter concludes with a reflection on the usefulness of social network analysis, its limitations and future opportunities for application to understanding networks of knowledge sharing in the tourism sector.