The Influence of Space on Tourist Activity: Supply, Demand, Competitiveness, Sustainability and Innovation

Dear colleagues,

If there is an economic activity in which the variable “space” is especially important, this activity is tourism. Many applied studies consider that tourism variables are distributed uniformly or randomly in space, when this is almost never the case, since patterns of spatial distribution, causality, etc. could be detected. On the other hand, a highly significant percentage of the analysis of tourist destinations currently being carried out considers that these destinations are independent of each other, when really, the greater or lesser proximity between them determine, in almost all cases, the existence of a dependence (or spatial interaction) among them.

On the other hand, the geolocation by GPS coordinates of the variables used to explain the tourist development of a destination opens up new perspectives in the scientific study of tourism. Other technologies, such as geotagging in social networks, hashtag analysis, smartphone apps or Bluetooth technology are allowing researchers to analyze tourism movements in much greater detail.

For all the above reasons, the objective of this Special Issue is to cover/compile the leading applied research at international level on methodologies applied to the relationship between tourism and space, demonstrating in this way that the analysis of tourism cannot be alien to its territorial component. In this Special Issue, we intend to show that the new tools of spatial statistics applied to tourism not only contribute to solve the problem derived from marginalizing the variable “space” in current tourism analyses but also generate much richer results, both from a quantitative and a qualitative point of view, that those offered by traditional techniques.

Possible topic areas for this Special Issue might include but are not limited to the following:

• Univariate and bivariate spatial autocorrelation between tourism variables;
• Spatial clusters;
• Spatial interaction models;
• Cooperation (or competition) among tourism destinations;
• GIS geoprocesses applied to tourism;
• Geographical weighted regression;
• Distribution of tourism spatial point patterns;
• Spatiotemporal point processes in tourism;
• Movement patterns of tourists within a destination;
• Regional analysis of tourism;
• Creation of tourist itineraries.

This issue will demonstrate that tourism phenomenon cannot be analyzed leaving aside its spatial component.

References:

• Lee, Y., Pennington-Gray, L., Kim, J. (2019): “Does location matter?. Exploring the spatial pattern of food service in a tourism destination”. Tourism Management, 71, 18-33. https://doi.org/10.1016/j.tourman.2018.09.016
• Patuelli, R, Mussoni, M., Candela, G. (2013): “The effects of World Heritage Sites on domestic tourism: a spatial interaction model for Italy”. Journal of Geographical Systems, 15, 369-402. DOI: 10.1007/s10109-013-0184-5
• Pavlyuk, D. (2011): “Application of the spatial stochastic frontier model for analysis of a regional tourism sector”. Transport and Telecommunication, 12 (2), 28-38.
• Rodríguez-Rangel, C., Sánchez-Rivero, M. (2019): “Analysis of the spatial distribution pattern of tourist activity: an application to the volume of travelers in Extremadura”. In Trends in Tourist Behavior: new products and experiences from Europe, Artal-Tur, A., Kozak, M, Kozak, N. Eds., 225-245. Springer International Publishing.
• Sánchez-Martín, J.M.; Rengifo-Gallego, J.I.; Blas-Morato, R. (2019): “Hot Spot Analysis versus Cluster and Outlier Analysis: An Enquiry into the Grouping of Rural Accommodation in Extremadura (Spain)”. ISPRS Int. J. Geo-Inf., 8(4), 176; https://doi.org/10.3390/ijgi8040176
• Sánchez-Martín, J.M.; Rengifo-Gallego, J.I.; Martín-Delgado, L.M. (2018): “Tourist Mobility at the Destination Toward Protected Areas: The Case-Study of Extremadura”. Sustainability, 10(12), 4853; https://doi.org/10.3390/su10124853
• Yun, H.J., Kang, D.J., Lee, M.J. (MJ) (2018): “Spatiotemporal distribution of urban walking tourists by season using GPS-based smartphone application”. Asia Pacific Journal of Tourism Research, 1-15. https://doi.org/10.1080/10941665.2018.1513949
• Zhong, L., Sun, S., Law, R. (2019): “Movement pattern of tourists”. Tourism Management, 75, 318-322.

Prof. Marcelino Sánchez-Rivero
Prof. José Manuel Sánchez-Martín
Guest Editors

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• spatial analysis
• GIS
• geoprocesses
• spatial autocorrelation
• spatial clusters
• geographical weighted regression
• geostatistical analysis
• network analysis