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Network analysis approach to map tourism mobility

Author

Listed:
  • Rosario D’Agata
  • Simona Gozzo
  • Venera Tomaselli

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Abstract

The spatial distribution of tourists is uneven and it can include some areas at regional and/or sub-regional level. The social–economic and environmental impacts of tourism, are concentrated in different areas. Some recent contributions show the usefulness and the effectiveness of network analysis (NA) approach in revising the organization of tourist facilities and services. This paper proposes to apply methods borrowed from NA to map the spatial distribution of tourism mobility in Sicily. So, we analyze the network features of tourism in a multi-destinations net. By means of traditional measures of NA, we propose to measure the links among destinations. The study aims to connect destinations, represented as nodes, to define a territorial network of tourism demand. In the specific instance, the degree centrality, closeness centrality, betweenness centrality are used to localize central areas and the main routes. We test survey data collected on a sample of tourists leaving from airports and ports of the main Sicilian cities, who visited two destinations at least. Then, we study tourism mobility on those areas selected by tourists. Finally, employing measures derived from NA, the work attempts to set out territorial networks. This approach could be useful to plane tourism development policies. Copyright Springer Science+Business Media B.V. 2013

Suggested Citation

  • Rosario D’Agata & Simona Gozzo & Venera Tomaselli, 2013. "Network analysis approach to map tourism mobility," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(6), pages 3167-3184, October.
  • Handle: RePEc:spr:qualqt:v:47:y:2013:i:6:p:3167-3184
    DOI: 10.1007/s11135-012-9710-7
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    File URL: http://hdl.handle.net/10.1007/s11135-012-9710-7
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    References listed on IDEAS

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    1. Rodolfo Baggio & Chris Cooper, 2009. "Knowledge transfer in a tourism destination: the effects of a network structure," The Service Industries Journal, Taylor & Francis Journals, vol. 30(10), pages 1757-1771, November.
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    Cited by:

    1. Chao-Chan Wu, 2016. "Constructing a weighted keyword-based patent network approach to identify technological trends and evolution in a field of green energy: a case of biofuels," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 213-235, January.
    2. Juan Brida & Marta Disegna & Raffaele Scuderi, 2014. "The behaviour of repeat visitors to museums: review and empirical findings," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(5), pages 2817-2840, September.
    3. Antonino Mario Oliveri, Anna Maria Parroco, Franco Vaccina, 2012. "Tourist mobility and destination competitiveness," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - Italian Review of Economics, Demography and Statistics, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 66(2), pages 213-234.
    4. Yongli Li & Chong Wu & Zizheng Wang, 2015. "An information-theoretic approach for detecting communities in networks," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1719-1733, July.
    5. Hong, Tao & Ma, Tao & Huan, Tzung-Cheng (T.C.), 2015. "Network behavior as driving forces for tourism flows," Journal of Business Research, Elsevier, vol. 68(1), pages 146-156.
    6. Chao-Chan Wu, 2016. "Constructing a weighted keyword-based patent network approach to identify technological trends and evolution in a field of green energy: a case of biofuels," Quality & Quantity: International Journal of Methodology, Springer, vol. 50(1), pages 213-235, January.

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