Abstract
In this article, the cross-flow phenomenon is considered from the approach of the analysis by digital footprint method, based on geotagging. The goal of the study is to test the cross-logistic approach to characterize the tourist flow of the museum clusters, based on TripAdvisor data. The empirical database included 221 museums united into 36 museums clusters. During the research, hypotheses concerning the dependence between the logistic flow value indicators and locations of the museums in the cluster were verified by Spearman's rank correlation test. The identification of the hub system type, based on the logistic flow model of each museum cluster, was determined by the graph method in Gephi. As a result, it was found that the intensity of cross-flow does not depend on the proximity of museums in the museum cluster. However, the average distance between cluster museums make potential effect on the cross-flow intensity. Moreover, it has been proven that the museum cluster is based on the hub system in terms of managing the tourist flow. Four models were identified: two-node, triangle, single and mixed hub. Two-node model of the museum cluster, based on the line strong connection between 2 museums, has been identified as the most common logistic structure.
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This article is an output of a research project implemented as part of the Basic Research Program at the National Research University Higher School of Economics (HSE University).
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Polomarchuk, A. (2022). Tourist Cross-Flows of the Museum Clusters. In: Beskopylny, A., Shamtsyan, M. (eds) XIV International Scientific Conference “INTERAGROMASH 2021". Lecture Notes in Networks and Systems, vol 246. Springer, Cham. https://doi.org/10.1007/978-3-030-81619-3_57
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