Impact of perceived distances on international tourism

Autoři: Trivik Verma aff001;  Luís Rebelo aff003;  Nuno A. M. Araújo aff003
Působiště autorů: Faculty of Technology, Policy and Management, Delft University of Technology, Delft, the Netherlands aff001;  Institute for Terrestrial Ecosystems, ETH Zürich, Universitätstrasse 16, Zürich, Switzerland aff002;  Departamento de Física, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal aff003;  Centro de Física Teórica e Computacional, Universidade de Lisboa, Lisboa, Portugal aff004
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
prolekare.web.journal.doi_sk: 10.1371/journal.pone.0225315


Worldwide tourism revenues have tripled in the last decade. Yet, there is a gap in our understanding of how distances shape peoples’ travel choices. To understand global tourism patterns we map the flow of tourists around the world onto a complex network and study the impact of two types of distances, geographical and through the World Airline Network, a major infrastructure for tourism. We find that although the World Airline Network serves as infrastructural support for the International Tourism Network, the flow of tourism does not correlate strongly with the extent of flight connections available worldwide. Instead, unidirectional flows appear locally forming communities that shed light on global travelling behaviour since there is only a 15% probability of finding bidirectional tourism between a pair of countries. We find that most tourists travel to neighbouring countries and mainly cover larger distances when there is a direct flight, irrespective of the time it takes. This may be a consequence of one-way cyclic tourism that we uncover by analysing the triangles that are formed by the network of flows in the International Tourism Network.

Klíčová slova:

Clustering coefficients – Decision making – Geographic distribution – Network analysis – Probability distribution – Statistical data – Airports – Network reciprocity


1. Carotenuto F, Tsikaridze N, Rook L, Lordkipanidze D, Longo L, Condemi S, et al. Venturing out safely: The biogeography of Homo erectus dispersal out of Africa. Journal of Human Evolution. 2016;95:1–12. doi: 10.1016/j.jhevol.2016.02.005 27260171

2. Harari YN. Sapiens: A Brief History of Humankind. HarperCollins; 2015. Available from:

3. Idyorough AE. Sociological analysis of social change in contemporary Africa. Deka Publications; 1998.

4. World Tourism Organization. UNWTO Tourism Highlights 2017 Edition; 2017.

5. McIntosh RW, Goeldner CR, Ritchie JB, et al. Tourism: principles, practices, philosophies. Ed. 7. John Wiley and Sons; 1995.

6. McKercher B, Chan A, Lam C. The impact of distance on international tourist movements. Journal of Travel Research. 2008;47(2):208–224. doi: 10.1177/0047287508321191

7. Nicolau JL, Mas FJ. The influence of distance and prices on the choice of tourist destinations: The moderating role of motivations. Tourism Management. 2006;27(5):982–996. doi: 10.1016/j.tourman.2005.09.009

8. Prideaux B. The role of the transport system in destination development. Tourism management. 2000;21(1):53–63. doi: 10.1016/S0261-5177(99)00079-5

9. Khadaroo J, Seetanah B. The role of transport infrastructure in international tourism development: A gravity model approach. Tourism management. 2008;29(5):831–840. doi: 10.1016/j.tourman.2007.09.005

10. Louzada VH, Araujo NA, Verma T, Daolio F, Herrmann HJ, Tomassini M. Critical cooperation range to improve spatial network robustness. PloS one. 2015;10(3):e0118635. doi: 10.1371/journal.pone.0118635 25793986

11. Miguéns J, Mendes J. Travel and tourism: Into a complex network. Physica A: Statistical Mechanics and its Applications. 2008;387(12):2963–2971. doi: 10.1016/j.physa.2008.01.058

12. Albert R, Barabási AL. Statistical mechanics of complex networks. Reviews of modern physics. 2002;74(1):47. doi: 10.1103/RevModPhys.74.47

13. Baggio R. Network science and tourism–the state of the art. Tourism Review. 2017;72(1):120–131. doi: 10.1108/TR-01-2017-0008

14. Bardoscia M, Caccioli F, Perotti JI, Vivaldo G, Caldarelli G. Distress Propagation in Complex Networks: The Case of Non-Linear DebtRank. PLOS ONE. 2016;11(10):1–12. doi: 10.1371/journal.pone.0163825

15. Jeong H, Tombor B, Albert R, Oltvai ZN, Barabasi AL. The Large-Scale Organization of Metabolic Networks. Nature. 2000;407:651–4. doi: 10.1038/35036627 11034217

16. Barabási AL, et al. Network science. Cambridge university press; 2016.

17. Vivaldo G, Masi E, Pandolfi C, Mancuso S, Caldarelli G. Networks of plants: how to measure similarity in vegetable species. Scientific reports. 2016;6:27077. doi: 10.1038/srep27077 27271207

18. Vivaldo G, Masi E, Taiti C, Caldarelli G, Mancuso S. The network of plants volatile organic compounds. Scientific reports. 2017;7(1):11050. doi: 10.1038/s41598-017-10975-x 28887468

19. Cartozo CC, Garlaschelli D, Ricotta C, Barthélemy M, Caldarelli G. Quantifying the taxonomic diversity in real species communities. Journal of Physics A: Mathematical and Theoretical. 2008;41(22):224012. doi: 10.1088/1751-8113/41/22/224012

20. Guimerà R, Danon L, Díaz-Guilera A, Giralt F, Arenas A. Self-similar community structure in a network of human interactions. Phys Rev E. 2003;68:065103. doi: 10.1103/PhysRevE.68.065103

21. Garlaschelli D, Battiston S, Castri M, Servedio VDP, Caldarelli G. The scale-free topology of market investments. Physica A: Statistical Mechanics and its Applications. 2005;350(2):491—499. doi: 10.1016/j.physa.2004.11.040

22. Tsiotas D, Polyzos S. Decomposing multilayer transportation networks using complex network analysis: a case study for the Greek aviation network. Journal of Complex Networks. 2015;3(4):642–670. doi: 10.1093/comnet/cnv003

23. Riecke H, Roxin A, Madruga S, Solla SA. Multiple attractors, long chaotic transients, and failure in small-world networks of excitable neurons. Chaos: An Interdisciplinary Journal of Nonlinear Science. 2007;17(2):026110. doi: 10.1063/1.2743611

24. Poncela J, Gómez-Gardeñes J, Floría LM, Moreno Y. Robustness of cooperation in the evolutionary prisoner’s dilemma on complex networks. New Journal of Physics. 2007;9(6):184. doi: 10.1088/1367-2630/9/6/184

25. Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang DU. Complex networks: Structure and dynamics. Physics Reports. 2006;424(4):175—308. doi: 10.1016/j.physrep.2005.10.009

26. Del Vicario M, Vivaldo G, Bessi A, Zollo F, Scala A, Caldarelli G, et al. Echo chambers: Emotional contagion and group polarization on facebook. Scientific reports. 2016;6:37825. doi: 10.1038/srep37825 27905402

27. OpenFlights. Openflights Dataset; 2017.

28. Cotter CH. A history of nautical astronomy [by] Charles H. Cotter. Hollis & Carter London, Sydney [etc.]; 1968.

29. Opsahl T, Panzarasa P. Clustering in weighted networks. Social Networks. 2009;31(2):155–163. doi: 10.1016/j.socnet.2009.02.002

30. Erdős P, Rényi A. On the Evolution of Random Graphs. Publications of the Mathematical Institute of the Hungarian Academy of Sciences. 1960;5:17–61.

31. Verma T, Araújo NAM, Herrmann HJ. Revealing the structure of the world airline network. Scientific Reports. 2014;4:5638. doi: 10.1038/srep05638 25005934

32. Guimerà R, Mossa S, Turtschi A, Amaral LAN. The worldwide air transportation network: Anomalous centrality, community structure, and cities’ global roles. Proceedings of the National Academy of Sciences. 2005;102:7794. doi: 10.1073/pnas.0407994102

33. Newman MEJ. Fast algorithm for detecting community structure in networks. Phys Rev E. 2004;69:066133. doi: 10.1103/PhysRevE.69.066133

34. McKercher B, Decosta PH. The lingering effect of colonialism on. Tourism Economics. 2007;13(3):453–474. doi: 10.5367/000000007781497746

35. Bastian M, Heymann S, Jacomy M. Gephi: an open source software for exploring and manipulating networks. In: Third international AAAI conference on weblogs and social media; 2009.

36. Newman M. Networks: An Introduction. New York, NY, USA: Oxford University Press, Inc.; 2010.

37. Brohman J. New directions in tourism for third world development. Annals of tourism research. 1996;23(1):48–70. doi: 10.1016/0160-7383(95)00043-7

38. Fagiolo G. Clustering in complex directed networks. Phys Rev E. 2007;76:026107. doi: 10.1103/PhysRevE.76.026107

39. Sandbrook CG. Putting leakage in its place: The significance of retained tourism revenue in the local context in rural Uganda. Journal of International Development: The Journal of the Development Studies Association. 2010;22(1):124–136. doi: 10.1002/jid.1507

40. Watts DJ, Strogatz SH. Collective dynamics of ‘small-world’ networks. Nature. 1998;393:440. doi: 10.1038/30918 9623998

41. Lea J. Tourism and development in the Third World. Routledge; 2006.

42. Newman MEJ. The structure and function of complex networks. SIAM Review. 2003;45:167–256. doi: 10.1137/S003614450342480

Článok vyšiel v časopise


2019 Číslo 12