Abstract
Recent developments in destination management suggest that administrative divisions may be misleading as a unit of decision making for tourism planning and management, since they may comprise several areas with different tourism functionality. Identifying homogenous areas of tourism activity and delimiting their boundaries can enhance the utility of information for smart management purposes. The objective of this paper is to highlight the relevance of the geographical dimension of smart destinations by showing how functional areas can be delimited and how this smaller unit of analysis can improve destination management in the new context of improved availability of data and smart decisions supported by technology. The paper illustrates its key ideas with an application to the island of Gran Canaria.
Highlights
The current trend of combining information and communication technologies (ICTs) and human capital at destinations is expected to lead to an improvement in both the tourist experience and the tourist product within so-called smart destinations
Taking as a starting point the current concept of smart destinations (Gretzel et al, 2015; Boes et al 2015), and recent literature on destination management (Beritelli, et al, 2014), this paper aims to make a contribution towards the operationalisation of the concept of smart destination, in particular, its geographical dimension
Destination management can be supported by the features associated with smart destinations
Summary
The current trend of combining information and communication technologies (ICTs) and human capital at destinations is expected to lead to an improvement in both the tourist experience and the tourist product within so-called smart destinations. It is this use of technology together with human capital in tourism that has led to the development of the concept of smart destination (Buhalis, Amaranggana, 2013). As Gretzel et al (2015) point out; smart tourism is related to the emerging forms of information and communication technologies that allow value to be obtained from large amounts of data. Using these new forms of data to support decision
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