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The web of connections between tourism companies: Structure and dynamics

Author

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  • da Fontoura Costa, Luciano
  • Baggio, Rodolfo

Abstract

Tourism destination networks are amongst the most complex dynamical systems, involving a myriad of human-made and natural resources. In this work we report a complex network-based systematic analysis of the Elba (Italy) tourism destination network, including the characterization of its structure in terms of several traditional measurements, the investigation of its modularity, as well as its comprehensive study in terms of the recently reported superedges approach. In particular, structural (the number of paths of distinct lengths between pairs of nodes, as well as the number of reachable companies) and dynamical features (transition probabilities and the inward/outward activations and accessibilities) are measured and analyzed, leading to a series of important findings related to the interactions between tourism companies. Among the several reported results, it is shown that the type and size of the companies influence strongly their respective activations and accessibilities, while their geographical position does not seem to matter. It is also shown that the Elba tourism network is largely fragmented and heterogeneous, so that it could benefit from increased integration.

Suggested Citation

  • da Fontoura Costa, Luciano & Baggio, Rodolfo, 2009. "The web of connections between tourism companies: Structure and dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(19), pages 4286-4296.
    • Handle: RePEc:eee:phsmap:v:388:y:2009:i:19:p:4286-4296
    DOI: 10.1016/j.physa.2009.06.034
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    Citations

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    Cited by:

    1. Armindo Frias & João Cabral & à lvaro Costa, 2015. "Logistic optimization in tourism networks," ERSA conference papers ersa15p1451, European Regional Science Association.
    2. Williams, Nigel L. & Inversini, Alessandro & Ferdinand, Nicole & Buhalis, Dimitrios, 2017. "Destination eWOM: A macro and meso network approach?," Annals of Tourism Research, Elsevier, vol. 64(C), pages 87-101.
    3. Werner, Kim & Dickson, Geoff & Hyde, Kenneth F., 2015. "Learning and knowledge transfer processes in a mega-events context: The case of the 2011 Rugby World Cup," Tourism Management, Elsevier, vol. 48(C), pages 174-187.
    4. Hernández, Juan M. & González-Martel, Christian, 2017. "An evolving model for the lodging-service network in a tourism destination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 296-307.
    5. Oviedo-García, M. Ángeles, 2016. "Tourism research quality: Reviewing and assessing interdisciplinarity," Tourism Management, Elsevier, vol. 52(C), pages 586-592.
    6. Meead Saberi & Hani S. Mahmassani & Dirk Brockmann & Amir Hosseini, 2017. "A complex network perspective for characterizing urban travel demand patterns: graph theoretical analysis of large-scale origin–destination demand networks," Transportation, Springer, vol. 44(6), pages 1383-1402, November.

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