IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v12y2020i18p7470-d411878.html
   My bibliography  Save this article

Innovative Tools for Tourism and Cultural Tourism Impact Assessment

Author

Listed:
  • Tarmo Kalvet

    (Institute of Baltic Studies, Lai 30, 51005 Tartu, Estonia
    Department of Business Administration, Tallinn University of Technology 5, 19086 Tallinn, Estonia)

  • Maarja Olesk

    (Institute of Baltic Studies, Lai 30, 51005 Tartu, Estonia)

  • Marek Tiits

    (Institute of Baltic Studies, Lai 30, 51005 Tartu, Estonia
    Department of Business Administration, Tallinn University of Technology 5, 19086 Tallinn, Estonia)

  • Janika Raun

    (Department of Geography, Institute of Ecology and Earth Sciences, Faculty of Science and Technology, University of Tartu, 51005 Tartu, Estonia)

Abstract

The importance of data and evidence has increased considerably in policy planning, implementation, and evaluation. There is unprecedented availability of open and big data, and there are rapid developments in intelligence gathering and the application of analytical tools. While cultural heritage holds many tangible and intangible values for local communities and society in general, there is a knowledge gap regarding suitable methods and data sources to measure the impacts and develop data-driven policies of cultural tourism. In the tourism sector, rapid developments are particularly taking place around novel uses of mobile positioning data, web scraping, and open application programming interface (API) data, data on sharing, and collaborative economy and passenger data. Based on feedback from 15 European cultural tourism regions, recommendations are developed regarding the use of innovative tools and data sources in tourism management. In terms of potential analytical depth, it is especially advisable to explore the use of mobile positioning data. Yet, there are considerable barriers, especially in terms of privacy protection and ethics, in using such data. User-generated big data from social media, web searches, and website visits constitute another promising data source as it is often publicly available in real time and has low usage barriers. Due to the emergence of new platform-based business models in the travel and tourism sector, special attention should be paid to improving access and usage of data on sharing and collaborative economy.

Suggested Citation

  • Tarmo Kalvet & Maarja Olesk & Marek Tiits & Janika Raun, 2020. "Innovative Tools for Tourism and Cultural Tourism Impact Assessment," Sustainability, MDPI, vol. 12(18), pages 1-30, September.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7470-:d:411878
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/12/18/7470/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/12/18/7470/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Versichele, Mathias & de Groote, Liesbeth & Claeys Bouuaert, Manuel & Neutens, Tijs & Moerman, Ingrid & Van de Weghe, Nico, 2014. "Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent, Belgium," Tourism Management, Elsevier, vol. 44(C), pages 67-81.
    2. Rodolfo Baggio & Miriam Scaglione, 2018. "Strategic visitor flows and destination management organization," Information Technology & Tourism, Springer, vol. 18(1), pages 29-42, April.
    3. Daniele Barchiesi & Helen Susannah Moat & Christian Alis & Steven Bishop & Tobias Preis, 2015. "Quantifying International Travel Flows Using Flickr," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-8, July.
    4. Donghwan Ki & Sugie Lee, 2019. "Spatial Distribution and Location Characteristics of Airbnb in Seoul, Korea," Sustainability, MDPI, vol. 11(15), pages 1-16, July.
    5. Yamilé Pérez Guilarte & Daniel Barreiro Quintáns, 2019. "Using Big Data to Measure Tourist Sustainability: Myth or Reality?," Sustainability, MDPI, vol. 11(20), pages 1-19, October.
    6. Csaba Sidor & Branislav Kršák & Ľubomír Štrba & Michal Cehlár & Samer Khouri & Michal Stričík & Jaroslav Dugas & Ján Gajdoš & Barbora Bolechová, 2019. "Can Location-Based Social Media and Online Reservation Services Tell More about Local Accommodation Industries than Open Governmental Data?," Sustainability, MDPI, vol. 11(21), pages 1-21, October.
    7. Siiri Silm & Rein Ahas, 2014. "Ethnic Differences in Activity Spaces: A Study of Out-of-Home Nonemployment Activities with Mobile Phone Data," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 104(3), pages 542-559, May.
    8. Raun, Janika & Ahas, Rein & Tiru, Margus, 2016. "Measuring tourism destinations using mobile tracking data," Tourism Management, Elsevier, vol. 57(C), pages 202-212.
    9. Christian Longhi & Jean-Bernard Titz & Lucas Viallis, 2014. "Open Data: Challenges and Opportunities for the Tourism Industry," Palgrave Macmillan Books, in: Marcello M. Mariani & Rodolfo Baggio & Dimitrios Buhalis & Christian Longhi (ed.), Tourism Management, Marketing, and Development, chapter 0, pages 57-76, Palgrave Macmillan.
    10. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    11. Saluveer, Erki & Raun, Janika & Tiru, Margus & Altin, Laura & Kroon, Jaanus & Snitsarenko, Tarass & Aasa, Anto & Silm, Siiri, 2020. "Methodological framework for producing national tourism statistics from mobile positioning data," Annals of Tourism Research, Elsevier, vol. 81(C).
    12. Kati Nilbe & Rein Ahas & Siiri Silm, 2014. "Evaluating the Travel Distances of Events Visitors and Regular Visitors Using Mobile Positioning Data: The Case of Estonia," Journal of Urban Technology, Taylor & Francis Journals, vol. 21(2), pages 91-107, April.
    13. Gunter, Ulrich & Önder, Irem, 2016. "Forecasting city arrivals with Google Analytics," Annals of Tourism Research, Elsevier, vol. 61(C), pages 199-212.
    14. Christian Longhi & Jean-Bernard Titz & Lucas Viallis, 2014. "Open data: Challenges and opportunities for the tourism industry," Post-Print halshs-00924731, HAL.
    15. Marcello M. Mariani & Rodolfo Baggio & Dimitrios Buhalis & Christian Longhi (ed.), 2014. "Tourism Management, Marketing, and Development," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-35435-8, December.
    16. Mikel Zubiaga & Jose Luis Izkara & Alessandra Gandini & Itziar Alonso & Unai Saralegui, 2019. "Towards Smarter Management of Overtourism in Historic Centres Through Visitor-Flow Monitoring," Sustainability, MDPI, vol. 11(24), pages 1-23, December.
    17. Douglas S. Noonan & Ilde Rizzo, 2017. "Economics of cultural tourism: issues and perspectives," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(2), pages 95-107, May.
    18. Xiang, Zheng & Du, Qianzhou & Ma, Yufeng & Fan, Weiguo, 2017. "A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism," Tourism Management, Elsevier, vol. 58(C), pages 51-65.
    19. Katerina Volchek & Anyu Liu & Haiyan Song & Dimitrios Buhalis, 2019. "Forecasting tourist arrivals at attractions: Search engine empowered methodologies," Tourism Economics, , vol. 25(3), pages 425-447, May.
    20. Steve MacFeely, 2019. "The Big (data) Bang: Opportunities and Challenges for Compiling SDG Indicators," Global Policy, London School of Economics and Political Science, vol. 10(S1), pages 121-133, January.
    21. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2017. "‘You will like it!’ using open data to predict tourists' response to a tourist attraction," Tourism Management, Elsevier, vol. 60(C), pages 430-438.
    22. Jamie Berryhill & Kévin Kok Heang & Rob Clogher & Keegan McBride, 2019. "Hello, World: Artificial intelligence and its use in the public sector," OECD Working Papers on Public Governance 36, OECD Publishing.
    23. Chua, Alvin & Servillo, Loris & Marcheggiani, Ernesto & Moere, Andrew Vande, 2016. "Mapping Cilento: Using geotagged social media data to characterize tourist flows in southern Italy," Tourism Management, Elsevier, vol. 57(C), pages 295-310.
    24. Alain Dupeyras & Neil MacCallum, 2013. "Indicators for Measuring Competitiveness in Tourism: A Guidance Document," OECD Tourism Papers 2013/2, OECD Publishing.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Olena Kasian, 2023. "Analysis of factors in managing digital entrepreneurship development in tourism in Ukraine: challenges and opportunities," Technology audit and production reserves, PC TECHNOLOGY CENTER, vol. 4(4(72)), pages 12-19, August.
    2. Kristýna Tuzová & Antonín Vaishar & Milada Šťastná & Martina Urbanová, 2023. "The Impacts of COVID-19 on the Visitor Attendance of Cultural and Natural Heritage: A Case Study of the South Moravian Region," Sustainability, MDPI, vol. 15(19), pages 1-20, September.
    3. Zoltán Kovács & György Vida & Ábel Elekes & Tamás Kovalcsik, 2021. "Combining Social Media and Mobile Positioning Data in the Analysis of Tourist Flows: A Case Study from Szeged, Hungary," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    4. Linda Ghirardello & Maximilian Walder & Michael de Rachewiltz & Greta Erschbamer, 2022. "Cultural Sustainability from the Local Perspective: The Example of Transhumance in South Tyrol," Sustainability, MDPI, vol. 14(15), pages 1-13, July.
    5. Marta Casanova & Simonetta Acacia & Stefano Francesco Musso & Stefania Traverso & Federico Rottura & Cristina Olivieri, 2022. "Contemporary Architecture in Genoa since 1945—Knowledge and Use through Geoservices for the Citizen," Sustainability, MDPI, vol. 14(11), pages 1-18, May.
    6. Tomasz Duda, 2023. "More Regionality than Globality – New Trends and Challenges of Contemporary Cultural Tourism," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 27-34.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marie Al-Ghossein & Talel Abdessalem & Anthony Barré, 2018. "Open data in the hotel industry: leveraging forthcoming events for hotel recommendation," Information Technology & Tourism, Springer, vol. 20(1), pages 191-216, December.
    2. Zoltán Kovács & György Vida & Ábel Elekes & Tamás Kovalcsik, 2021. "Combining Social Media and Mobile Positioning Data in the Analysis of Tourist Flows: A Case Study from Szeged, Hungary," Sustainability, MDPI, vol. 13(5), pages 1-15, March.
    3. Tao Liu & Ying Zhang & Huan Zhang & Xiping Yang, 2021. "A Methodological Workflow for Deriving the Association of Tourist Destinations Based on Online Travel Reviews: A Case Study of Yunnan Province, China," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
    4. Guizzardi, Andrea & Pons, Flavio Maria Emanuele & Angelini, Giovanni & Ranieri, Ercolino, 2021. "Big data from dynamic pricing: A smart approach to tourism demand forecasting," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1049-1060.
    5. A Fronzetti Colladon & B Guardabascio & R Innarella, 2021. "Using social network and semantic analysis to analyze online travel forums and forecast tourism demand," Papers 2105.07727, arXiv.org.
    6. Veronika Mooses & Siiri Silm & Tiit Tammaru & Erki Saluveer, 2020. "An ethno-linguistic dimension in transnational activity space measured with mobile phone data," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-13, December.
    7. Pantano, Eleonora & Priporas, Constantinos-Vasilios & Stylos, Nikolaos, 2017. "‘You will like it!’ using open data to predict tourists' response to a tourist attraction," Tourism Management, Elsevier, vol. 60(C), pages 430-438.
    8. Ana Muñoz-Mazón & Laura Fuentes-Moraleda & Angela Chantre-Astaiza & Marlon-Felipe Burbano-Fernandez, 2019. "The Study of Tourist Movements in Tourist Historic Cities: A Comparative Analysis of the Applicability of Four Different Tools," Sustainability, MDPI, vol. 11(19), pages 1-26, September.
    9. Huy Quan Vu & Shah Jahan Miah & Haiyang Xia & Gang Li & Birgit Muskat & Rob Law, 2023. "Advancing reliability assessment of venue-reference social media data for enhanced domestic tourism development," Information Technology & Tourism, Springer, vol. 25(3), pages 433-451, September.
    10. Ling Tang & Chengyuan Zhang & Tingfei Li & Ling Li, 2021. "A novel BEMD-based method for forecasting tourist volume with search engine data," Tourism Economics, , vol. 27(5), pages 1015-1038, August.
    11. Josef Zelenka & Tracy Azubuike & Martina Pásková, 2021. "Trust Model for Online Reviews of Tourism Services and Evaluation of Destinations," Administrative Sciences, MDPI, vol. 11(2), pages 1-21, March.
    12. Tosporn Arreeras & Mikiharu Arimura & Takumi Asada & Saharat Arreeras, 2019. "Association Rule Mining Tourist-Attractive Destinations for the Sustainable Development of a Large Tourism Area in Hokkaido Using Wi-Fi Tracking Data," Sustainability, MDPI, vol. 11(14), pages 1-17, July.
    13. Michał Roman & Monika Roman & Arkadiusz Niedziółka, 2020. "Spatial Diversity of Tourism in the Countries of the European Union," Sustainability, MDPI, vol. 12(7), pages 1-16, March.
    14. Judita Peterlin & Maja Meško & Vlado Dimovski & Vasja Roblek, 2021. "Automated content analysis: The review of the big data systemic discourse in tourism and hospitality," Systems Research and Behavioral Science, Wiley Blackwell, vol. 38(3), pages 377-385, May.
    15. Chunla Liu & Yingjie Qin & Yufei Wang & Yue Yu & Guanghui Li, 2022. "Spatio-Temporal Distribution of Tourism Flows and Network Analysis of Traditional Villages in Western Hunan," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    16. Gang Xie & Xin Li & Yatong Qian & Shouyang Wang, 2021. "Forecasting tourism demand with KPCA-based web search indexes," Tourism Economics, , vol. 27(4), pages 721-743, June.
    17. F. Antolini & L. Grassini, 2019. "Foreign arrivals nowcasting in Italy with Google Trends data," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(5), pages 2385-2401, September.
    18. Purva Grover & Arpan Kumar Kar, 2017. "Big Data Analytics: A Review on Theoretical Contributions and Tools Used in Literature," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 18(3), pages 203-229, September.
    19. Ashish K. Rathore & Arpan K. Kar & P. Vigneswara Ilavarasan, 2017. "Social Media Analytics: Literature Review and Directions for Future Research," Decision Analysis, INFORMS, vol. 14(4), pages 229-249, December.
    20. Edmond H. C. Wu & Jihao Hu & Rui Chen, 2022. "Monitoring and forecasting COVID-19 impacts on hotel occupancy rates with daily visitor arrivals and search queries," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(3), pages 490-507, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:12:y:2020:i:18:p:7470-:d:411878. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.