Advertisement

Assessing the Competitiveness of Greek Coastal Destinations

  • Spyros Niavis
  • Dimitrios TsiotasEmail author
Conference paper
  • 48 Downloads
Part of the Springer Proceedings in Business and Economics book series (SPBE)

Abstract

This chapter assesses the competitiveness of the Greek coastal destinations, in a comparative context. To do so, it develops various indicators which help destinations to conceptualize both their dynamics and their structural advantages. To better depict the competitiveness of destinations, the indicators are formulated by using the user-generated data being available at the TripAdvisor website. Under this data-mining process, the benchmarking can highlight critical features of the tourism industry, which cannot be revealed when analysis is based on the typical official data. The results signify a gap of competitiveness between the insular and non-insular destinations but also they reveal some critical features of the tourism-supply, which can facilitate the sustainable development of all Greek destinations.

Keywords

Destinations’ benchmarking Indicators Data-mining TripAdvisor 

References

  1. 1.
    Apostolopoulos Y, Leontidou L, Loukissas P (2014) Mediterranean tourism: facets of socioeconomic development and cultural change. Routledge, LondonCrossRefGoogle Scholar
  2. 2.
    Bramwell B (ed) (2004) Coastal mass tourism: diversification and sustainable development in southern Europe, vol 12. Channel View, ClevedonGoogle Scholar
  3. 3.
    Niavis S, Tsiotas D (2019) Assessing the tourism performance of the Mediterranean coastal destinations: a combined efficiency and effectiveness approach. J Destin Market Manag 14:100379.  https://doi.org/10.1016/j.jdmm.2019.100379 CrossRefGoogle Scholar
  4. 4.
    Farmaki A (2012) A supply-side evaluation of coastal tourism diversification: the case of Cyprus. Tour Plan Dev 9(2):183–203.  https://doi.org/10.1080/21568316.2011.634431 CrossRefGoogle Scholar
  5. 5.
    Cracolici MF, Nijkamp P (2009) The attractiveness and competitiveness of tourist destinations: a study of southern Italian regions. Tour Manag 30(3):336–344.  https://doi.org/10.1016/j.tourman.2008.07.006 CrossRefGoogle Scholar
  6. 6.
    Sigala M (2004) Using data envelopment analysis for measuring and benchmarking productivity in the hotel sector. J Travel Tour Mark 16(2–3):39–60CrossRefGoogle Scholar
  7. 7.
    Assaf AG, Tsionas EG (2015) Incorporating destination quality into the measurement of tourism performance: a Bayesian approach. Tour Manag 49:58–71.  https://doi.org/10.1016/j.tourman.2015.02.003 CrossRefGoogle Scholar
  8. 8.
    Barros CP, Machado LP (2010) The length of stay in tourism. Ann Tour Res 37(3):692–706.  https://doi.org/10.1016/j.annals.2009.12.005 CrossRefGoogle Scholar
  9. 9.
    Tsiotas D, Sdrolias L, Aspridis G, Skodova-Parmova D, Dvorakova-Liskova Z (2020, forthcoming) Size-distribution analysis in the study of urban systems: evidence from Greece. Int J Comput Econ EconometGoogle Scholar
  10. 10.
    TripAdvisor (2018) TripAdvisor. Available at https://www.tripadvisor.com. Accessed 1 Jan 2018
  11. 11.
    Hellenic Statistical Authority – HSA (2018) Hotels, rooms for rent and tourist campsites. Available at http://www.statistics.gr/en/statistics/-/publication/STO12/. Accessed 28 Dec 2018
  12. 12.
    Norusis M (2004) SPSS 13.0 statistical procedures companion. Prentice Hall, Upper Saddle River, NJGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of ThessalyVolosGreece

Personalised recommendations