Abstract
This study is intended to examine the relationship between tourist attractions (natural, cultural and historical) and tourist flows. In the study, secondary data for six provinces and 110 sub-provinces in the Southwestern Anatolia region of Turkey, visited by local and foreign tourists, are used. Four of these provinces have a coastline to the Aegean Sea and the Mediterranean. In this context, overnight data of tourists for 110 sub-provinces and the printed and online materials and overnight data of tourists are used to identify attractions. In this study, mapping analysis, local and global Moran’s I, the classical regression and spatial regression models are benefited. Primarily, the spillover of attractions through maps and the distribution of tourist flows are presented in the study. When the relationship between tourist attractions and tourist flows are examined, the results of our analyses show that the Global Moran’s I value is 0.25 and that those 110 sub-provinces could be similar in terms of tourist flow. It was determined whether there is a global clustering based on Global Moran’s I value, and then the similar clusters, that is, similar sub-provinces in terms of tourist flow, were determined using the spectral clustering method. In addition, the neighborhood relationship and neighborhood interactions in terms of tourist flow are determined using local indicators of spatial analysis (LISA) alongside the Spectral Clustering Method. Finally, in the study field, the relationship between cultural, historical, and natural tourist attractions and tourist flow is explained using the classical regression model and the spatial regression model. The spatial-based models, especially the SEM, improve the model performance compared to the corresponding OLS model. In conclusion, it is found that there is a positive correlation between tourist flows and natural and historical attractions of the region, but a negative relationship between tourist flows and cultural attractions. Destination management implications are discussed.
Highlights
The tourism sector is regarded as a source of economic growth, employment creation and export factor, for developing countries, which hold 10.4% of the world's gross domestic product (GDP) (Kim, Chen, and Jang 2006; Porto, Garbero and Espinola, 2018)
Historical attractions and cultural attractions are visualized with growing symbols, while natural attractions are visualized with green patterns according to the attractions’ classification
Cultural attractions are concentrated in their largest urban areas; that is, the central sub-province, because the primary goal of this attraction is to serve the residents of the urban area (Günay Aktaş and Baykal, 2016: 12)
Summary
The tourism sector is regarded as a source of economic growth, employment creation and export factor, for developing countries, which hold 10.4% of the world's gross domestic product (GDP) (Kim, Chen, and Jang 2006; Porto, Garbero and Espinola, 2018). International tourism revenues reached US $1,448 billion, with an increase of 4% in 2018. International tourist arrivals increased by 6% worldwide and reached 1.4 billion in 2018 (UNWTO, 2019). Before the COVID-19 outbreak, the number of international tourists was expected to reach 1.8 billion by 2030 (UNWTO, 2019). The economic benefits of tourism have led to intense competition among destinations to get a greater share from tourism, in order that they can stay in the race. The key factors are the attractions in the destinations and the number of tourists visiting such destinations (Dwyer and Kim, 2003; Murphy et al, 2000; Ritchie and Crouch, 1993, 2000)
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