To this aim, the case of Smart Marca - a mobile tourism app aimed at promoting cultural tourism in Fermo area (Marche Region, Italy)- is presented. This paper investigates the connections among tourism, cultural heritage, and ICT, by providing an assessment of how these applications can influence customers’ intentions to visit a destination. Purpose – In last decades, digital technologies have progressively transformed tourism becoming an opportunity to satisfy the demand for cultural tourism, increasingly asking for immersive and interactive experiences. Finally, the application of clustering algorithms to achieve the purpose of this study and the findings are very new in the literature on tourism, to understand the tourist behaviour towards destination selection based on social media reviews. Firstly, the study empirically revealed tourists' experience and behavioural intention to select tourism destinations and secondly, it finds quantifiable insights into the tourism phenomenon in East Asia, which helps tourism organizations to understand the buying behaviours of tourists' segments.
Finally, it can be identified to which segments, new respondents or potential clients belong consequently, the tourism organizations can design the tour packages. By segmenting travellers of East Asia into homogeneous groups, it is feasible to choose a similar area to test different marketing techniques. Tourism organizations focus on marketing efforts to promote the most attractive benefits to the clusters of travellers. DR technique ensures the reduction in dimensionality with seven directions, of which the first two directions explained 95% of total variability. For selecting the optimal number of clusters as well as the behaviour of the interested travellers groups, both these proposed methods have shown remarkable similarities. The dimension reduction (DR) technique was introduced for better visualizing clustering structure obtained from a finite mixture of Gaussian densities.Ī total of 980 travellers have been clustered into 8 different interest groups according to their tourism destinations selection across East Asia based on individual social media feedback. The study also aims to understand the behaviour of clusters of the travellers towards destination selection and accordingly make the tour packages in order to improve tourists' satisfaction and gain viable benefits.Īgglomerative hierarchical clustering with Ward's minimum variance linkage algorithm and model-based clustering with parameterized finite Gaussian mixture models has been implemented to achieve the respective goals. The study aims to cluster the travellers based on their social media interactions as well as to find the different segments with similar and dissimilar categories according to traveller's choice.
0 kommentar(er)
