Skip to main navigation menu Skip to main content Skip to site footer

Boundary conditions for the implementation of smart management systems in tourist destinations

DOI:

https://doi.org/10.15678/IER.2020.0604.03

Abstract

Objective: Purpose of this paper is twofold: (1) to indicate the business and technological foundations of smart tourism, as well as prospects for its further development; (2) to indicate factors and barriers to the development of smart tourism management system in Poland. The paper then discusses a series of challenges currently neglected in the practical smart tourism agendas and the academic literature.

Research Design & Methods: A combination of 3 methods was used: mind mapping, STEEP analysis and semi-structured interview with 48 experts, representing tourism industry new-tech sector. All the interviewees were interviewed in Jan/Feb 2020.

Findings: The article presents the general concept of the smart tourism and smart tourism destination (STD) development and identifies opportunities and threads to the development of smart tourism in Poland.

Contribution & Value Added: The article is an important value from the point of view of tourism industry practitioners (destination managers). The study contributes with valuable insights on how the chances of implementing smart tourism assumptions are perceived in Poland. The final diagram gives the idea of big data availability and usability in tourism and its impact on management efficiency.

Keywords

smart tourism, big data, STEEP analysis, data-based tourism experience, Internet of Things, IoT, tourism market

pdf

Author Biography

Magdalena Kachniewska

PhD in tourism economics. Member of Tourism Research Working Group and Scientific Council of e-TravelForum. Chairperson in “New.Tech.New.Travel” contest. Strategic Management and Social Marketing expert specialising in ICT applications in tourism and hospitality.


References

  1. Ahas, R., Aasa, A., Roose, A., Mark, U., & Silm, S. (2008). Evaluating passive mobile positioning data for tourism surveys: An Estonian case study. Tourism Management, 29(3), 469-486.
  2. Anttiroiko, A. V., Valkama, P., & Bailey, S. J. (2014). Smart cities in the new service economy: building platforms for smart services. AI and Society, 29(3), 323-334.
  3. Artola, C., Pinto, F., & Pedraza, P. D. (2015). Can internet searches forecast tourism inflows? Inter-national Journal of Manpower, 36(1), 103-116.
  4. Baggio, R.,& Del Chiappa, G. (2014). Real and virtual relationships in tourism digital ecosystems. Information Technology and Tourism, 14(1), 3-19.
  5. Bick, M., Bruns, K., Sievert, J., & Jacob, F. (2012). Value-in-use of mobile technologies. In A. Back, M. Bick,M.Breunig, K.Pousttchi, &F. Thiesse, (Eds.) MMS 2012: Mobile und ubiquitäreinfor-mationssysteme (pp. 56-67). KöllenDruck & Verlag.
  6. Bollier, D., & Firestone, C. (2010). The promise and peril of big data. Aspen.
  7. Cooper, M., & Macneil, N. J. (2005). Virtual reality mapping: IT tools for the divide between knowledge and action in tourism. Tourism Recreation Research, 30(3), 61-68.
  8. Femenia-Serra F., & Perea-Medina, M. J. (2016)., Analysis of Three Spanish Potential Smart Tour-ism Destinations. Paper presented at the 6th International Conference On Tourism (ICOT). Naples.
  9. Frederiksen, L. (2012). Big data. Public Services Quarterly, 8(4), 345-349.
  10. Gavalas, D., & Kenteris, M.(2011). A pervasive web-based recommendation system for mobile tourist guides. Personal and Ubiquitous Computing 15(7), 759-70.
  11. Girardin, F., Fiore, F. D., Ratti, C., & Blat, J. (2008). Leveraging explicitly disclosed location infor-mation to understand tourist dynamics: A case study. Journal of Location Based Services, 2(1), 41-56.
  12. González-Reverté, F. (2019). Building Sustainable Smart Destinations: An Approach Based on the Development of Spanish Smart Tourism Plans.Sustainability, 11(23), 1-24.
  13. Govers, R., Go, F. M., & Kumar, K. (2007). Promoting tourism destination image. Journal of Travel Research, 46(1), 15-23.
  14. Gretzel, U., Sigala, M., Xiang, Z., & Koo, C. (2015). Smart tourism: foundations and developments. Electronic Markets, 25(3), 179‐188.
  15. Guttentag, D. A. (2010). Virtual reality: Applications and implications for tourism. Tourism Man-agement, 31(5), 637-651.
  16. Hawelka, B., Sitko, I., Beinat, E., Sobolevsky, S., Kazakopoulos, P., & Ratti, C. (2014). Geo-located Twitter as proxy for global mobility patterns. Cartography and Geographic Information Sci-ence, 41(3), 260-271.
  17. Hendrik, H., & Perdana, D. H. F. (2014). Trip guidance: A linked data based mobile tourists guide. Advanced Science Letters, 20(1), 75-79.
  18. Irudeen, R., & Samaraweera, S. (2013). Big data solution for Sri Lankan development: A case study from travel and tourism. Paper presented at the 2013 International Conference on Advances in ICT for Emerging Regions, ICTer 2, Colombo.
  19. Jeng, J., & Fesenmaier, D. R. (2002). Conceptualizing the travel decision-making hierarchy: A re-view of recent developments. Tourism Analysis, 7(1), 15-32.
  20. Kachniewska, M. (2014). Tourism value added creation through a user-centric context-aware digi-tal system.University of Szczecin Scientific Journal, 836, Economic Problems of Tourism, 4 (28), 103-118.
  21. Ka´da´r, B. (2014). Measuring tourist activities in cities using geotagged photography. Tourism Geographies, 16(1), 88-104.
  22. Kim, J. J., & Fesenmaier, D. R. (2015). Designing tourism places: Understanding the tourism expe-rience through our senses. In 2015 Tourism Travel and Research Association International Conference Proceedings. Portland, Oregon.
  23. Komninos, N. (2008). Intelligent Cities and Globalisationof Innovation Networks. Routledge.
  24. Kurilovas, E. (2016). Evaluation of quality and personalisation of VR/AR/MR learning systems. Behaviour& Information Technology, 35(11), 998-1007.
  25. Lamsfus, C., Wang, D., Alzua-Sorzabal, A., & Xiang, Z. (2014). Going mobile: Defining context for on-the-go travelers. Journal of Travel Research, 54(6), 691-701.
  26. Li, D., & Yang, Y. (2020) GIS Monitoring of Traveler Flows Based on Big Data.In J.Neidhardt, W.Wörndl (Eds.), Information and Communication Technologies in Tourism 2020. United Kingdom, January 08-10, 2020. Retrieved from: https://enter2020.ifitt.org/
  27. Lopez de Avila, A. (2015). Smart Destinations: XXI Century Tourism. Presented at the ENTER2015 Conference on Information and Communication Technologies in Tourism, Lugano, Switzer-land, February 4-6, 2015.
  28. Manyika, J., Chui, M., Brown, B.,Bughin, J., Dobbs, R., Roxburgh, Ch., & Hung Byers,A. (2011).Big Data: The Next Frontier for Innovation. McKinsey Global Institute.
  29. Mariani, M., Baggio, R., Fuchs, M., &Höpken, W. (2018). Business Intelligence and Big Data in Hospitality and Tourism: A Systematic Literature Review. International Journal of Contempo-rary Hospitality Management, 30(12), 3514‐3554.
  30. Masseno, M., &Santos, Ch. (2018) Between Footprints: Balancing Environmental Sustainability and Privacy in Smart Tourism Destinations.United World Law Journal, 1(II), 96-11.
  31. Meeker, W. Q., & Hong, Y. (2014). Reliability meets big data: Opportunities and challenges. Quali-ty Engineering, 26(1), 102-116.
  32. Olsen, M., & Connolly, D. (2000). Experience-based Travel: How Technology Is Changing the Hospi-tality Industry. Cornell Hospitality Quarterly, 41(1), 30-40.
  33. Scharl, A., Lalicic, L., &Önder, I. (2020). Tourism Intelligence and Visual Media Analytics for Desti-nation Management Organizations. In J.Neidhardt, W. Wörndl (Eds.), Information and Com-munication Technologies in Tourism 2020. Proceedings of the International Conference in Sur-rey, United Kingdom, January 08-10, 2020.
  34. Shoval, N., Isaacson, M., & Chhetri, P. (2013). GPS, Smartphones, and the future of tourism re-search. In A. A. Lew, C. M. Hall, & A. M. Williams (Eds.), The Wiley Blackwell companion to tourism (251-261). Blackwell.
  35. Song, H., Liu, H. (2017). Predicting Tourist Demand Using Big Data. InZ. Xiang, D. R. Fesenmaier (Eds.) Analytics in Smart Tourism Design. Springer.
  36. Swan, M. (2013). The quantified self: Fundamental disruption in big data science. Big Data, 1(2), 85-99.
  37. Tachizawa, E. M., Alvarez-Gil, M. J., & Montes-Sancho, M. J. (2015). How smart cities will change supply chain management. Supply Chain Management, 20(3), 237-248.
  38. Townsend, P. (2017).The Dark Side of Technology. Oxford University Press.
  39. Vasavada, M., &Padhiyar, Y. J. (2016). “Smart Tourism”: Growth for Tomorrow.Journal for Re-search, 01(12).
  40. Versichele, M., Neutens, T., Delafontaine, M., & Van de Weghe, N. (2012). The use of Bluetooth for analyzing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent Festivities. Applied Geography, 32(2), 208-220.
  41. Vu, H. Q., Li, G., Law, R., & Ye, B. H. (2015). Exploring the travel behaviors of inbound tourists to Hong Kong using geotagged photos. Tourism Management, 46, 222-232.
  42. Yang, X., Pan, B., Evans, J. A., &Lv, B. (2015). Forecasting Chinese tourist volume with search engine data. Tourism Management, 46, 386-397.

Downloads

Download data is not yet available.

Similar Articles

131-140 of 215

You may also start an advanced similarity search for this article.