[Baggio, R., & Scaglione, M. (2017). Strategic Visitor Flows (SVF) Analysis Using Mobile Data. In Schegg, R., Stangl, B. (Eds.), Information and Communication Technologies in Tourism 2017 (pp. 145–157). Cham: Springer. DOI: 10.1007/978–3-319–51168–9_11.]Open DOISearch in Google Scholar
[Baggio, R., & Scaglione, M. (2018). Strategic visitor flows and destination management organization. Information Technology & Tourism, 18, 29–42. DOI: 10.1007/s40558–017–0096–1.]Open DOISearch in Google Scholar
[Baggio, R. (2016). Big data, business intelligence and tourism: a brief analysis of the literature. In Fuchs, M., Lexhagen, M., Höpken, W. (Eds.), IFITT workshop on the big data and business intelligence in the travel and tourism domain. European Tourism Research Institute (ETOUR). Östersund: Mid-Sweden University.]Search in Google Scholar
[Bastiat, C. F. (2015). Petice za zákaz slunce a jiné absurdity ekonomie [Petitions for the prohibition of the sun and other absurdities of economics]. Prague, Czech Republic: Mises.cz.]Search in Google Scholar
[Beritelli, P. (2019). Transferring concepts and tools from other fields to the tourist destination: A critical viewpoint focusing on the lifecycle concept. Journal of Destination Marketing & Management, 14. DOI: 10.1016/j.jdmm.2019.100384.]Open DOISearch in Google Scholar
[Botta, A., de Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer System, 56(C), 684–700. DOI: 10.1016/j.future.2015.09.021.]Open DOISearch in Google Scholar
[Boyd, D. (2007). Why Youth Social Network Sites: The Role of Networked Publics in Teenage Social Life. In Buckingham, D. (Ed.), Youth, Identity, and Digital Media, Beckman Center Research Publication No. 2007–16. Cambridge, USA: The MIT Press. Retrieved from https://ssrn.com/abstract=1518924.]Search in Google Scholar
[Che, D., Safran, M., & Peng, Z. (2013). From Big Data to Big Data Mining: Challenges, Issues, and Opportunities. In Hong, B., Meng, X., Chen, L., Winiwarter, W., Song, W. (Eds.), DASFAA 2013: Database Systems for Advanced Applications, vol. 7827 (pp. 1–15). Verlag/Berlin/Heidelberg: Springer. DOI: 10.1007/978–3-642–40270–8_1.]Open DOISearch in Google Scholar
[Derakhshan, R., Orlowska, M. E., & Li, X. (2007). RFID Data Management: Challenges and Opportunities. In 2007 IEEE International Conference on RFID, March 26–28 (pp. 175–182). Grapevine, USA: IEEE. DOI: 10.1109/RFID.2007.346166.]Open DOISearch in Google Scholar
[East, D., Osborne, P., Kemp, S., & Woodfine, T. (2017). Combining GPS & survey data improves understanding of visitor behaviour. Tourism Management, 61, 307–320. DOI: 10.1016/j.tourman.2017.02.021.]Open DOISearch in Google Scholar
[EMC Digital Universe with Research & Analysis. (2014). Executive Summary: Data Growth, Business Opportunities, and the IT Imperatives. The Digital Universe of Opportunities: Rich Data and the Increasing Value of the Internet of Things [online]. Retrieved from https://www.emc.com/leadership/digital-universe/2014iview/executive-summary.htm.]Search in Google Scholar
[Francalanci, C., & Hussain, A. (2015). Discovering social influencers with network visualization: evidence from the tourism domain. Information and Communication Technologies in Tourism, 16, 103–125. DOI: 10.1007/s40558–015–0030–3.]Open DOISearch in Google Scholar
[Fuchs, M., Abadzhiev, A., Svensson, B., Höpken, W., & Lexhagen, M. (2013). A knowledge destination framework for tourism sustainability: A business intelligence application from Sweden. Tourism, 61(2), 121–148.]Search in Google Scholar
[Fuchs, M., Höpken, W., & Lexhagen, M. (2014). Big data analytics for knowledge generation in tourism destinations – A case from Sweden. Journal of Destination Marketing & Management, 3, 198–209. DOI: 10.1016/j.jdmm.2014.08.002.]Open DOISearch in Google Scholar
[Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. DOI: 10.1016/j.future.2013.01.010.]Open DOISearch in Google Scholar
[Heerschap, N., Ortega, S., Priem, A., & Offermans, M. (2014). Innovation of tourism statistics through the use of new big data sources. In 12th World Telecommunication/ICT Indicators Symposium (WTIS-14), Tbilisi, Georgia, 24–26 November 2014. ITU: Geneva, Switzerland. 12p. Retrieved from https://www.itu.int/en/ITU-D/Statistics/Documents/events/wtis2014/002INF-E.pdf.]Search in Google Scholar
[Holešinská, A. (2012). Destinační management jako nástroj regionální politiky cestovního ruchu (Destination management as a tool for regional tourism policy). Brno, Czech Republic: Masaryk University.]Search in Google Scholar
[Holland, C. P., Jacobs, J. A., & Klein, S. (2016). The role and impact of comparison websites on the consumer search process in the US and German airline markets. Information Technology and Communication in Tourism, 16, 127–148. DOI: 10.1007/s40558–015–0037–9.]Open DOISearch in Google Scholar
[Höpken W., Ernesti D., Fuchs M., Kronenberg K., & Lexhagen M. (2017). Big Data as Input for Predicting Tourist Arrivals. In Schegg R., Stangl B. (Eds.), Information and Communication Technologies in Tourism 2017 (pp. 187–199). Cham: Springer. DOI: 10.1007/978–3-319–51168–9_14.]Open DOISearch in Google Scholar
[Höpken, W., & Fuchs (2016). Introduction: Special Issue on Business intelligence and big data in the travel and tourism domain. Information and Communication Technologies in Tourism, 16, 1–4. DOI: 10.1007/s40558–016–0054–3.]Open DOISearch in Google Scholar
[Höpken, W., Fuchs, M., & Lexhagen, M. (2013). The knowledge destination – applying methods of business intelligence to tourism. In Wang, J. (Ed.), Encyclopedia of Business Analytics and Optimization. Pennsylvania: IGI Global Publisher.]Search in Google Scholar
[Hwang, Y. H., Gretzel, U., & Fesenmaier, D. R. (2006). Multicity trip patterns: Tourists to the United States. Annals of Tourism Research, 33(4), 1057–1078. DOI: 10.1016/j.annals.2006.04.004.]Open DOISearch in Google Scholar
[Jansen, B. J., & Molina, P. R. (2006). The effectiveness of Web search engines for retrieving relevant ecommerce links. Information Processing & Management, 42, 1075–1098. DOI: 10.1016/j.ipm.2005.09.003.]Open DOISearch in Google Scholar
[Kádár, B. & Gede, M. (2013). Where do tourists go? Visualizing and analysing the spatial distribution of geotagged photography. The International Journal for Geographic Information and Geovisualization, 48(2), 78–88.10.3138/carto.48.2.1839]Search in Google Scholar
[Kambatla, K., Kollias, G., Kumar, V., & Grama. A. (2014). Trends in big data analytics. Journal of Parallel and Distributed Computing, 74(7), 2561–2573 DOI: 10.1016/j.jpdc.2014.01.003.]Open DOISearch in Google Scholar
[Kietzmann, J. H., Hermkens, K. McCarthy, I. P., & Silvestre, B. S. (2011). Social media? Get serious! Understanding the functional building blocks of social media. Business Horizons, 54(3), 241–251. DOI: 10.1016/j.bushor.2011.01.005.]Open DOISearch in Google Scholar
[Kitchin, R. (2013). Big data and human geography: Opportunities, challenges and risks. Dialogues in Human Geography, 3(3), 262–267. DOI: 10.1177/2043820613513388.]Open DOISearch in Google Scholar
[Kurashima, T., Iwata, T., Irie, G., & Fujimura, K. (2010). Travel route recommendation using geotags in photo sharing sites. In CIKM ’10: Proceedings of the 19th ACM international konference on Information and knowledge management, October 26–30 (pp. 579–588). Toronto, Canada: ACM. DOI: 10.1145/1871437.1871513.]Open DOISearch in Google Scholar
[Laney, D. (2001). 3D Data Management: Controlling Data Volume, Velocity, and Variety. In Application Delivery Strategies, File 949. Stamford, USA: META Group Inc. Retrieved from https://blogs.gartner.com/doug-laney/files/2012/01/ad949–3D-Data-Management-Controlling-Data-Volume-Velocity-and-Variety.pdf.]Search in Google Scholar
[Li, J., Xu, L., Tang, L., Wang, S., & Li, L. (2018). Big data in tourism research: A literature review. Tourism Management, 68(October), 301–323. DOI: 10.1016/j.tourman.2018.03.009.]Open DOISearch in Google Scholar
[Li, X., & Wang, Y. C. (2011). China in the eyes of western travelers as represented in travel blogs. Journal o Travel & Tourism Marketing, 28(7), 689–719. DOI: 10.1080/10548408.2011.615245.]Open DOISearch in Google Scholar
[Lo, I. S., McKercher, B., Lo, A., Cheung, C., & Law, R. (2011). Tourism and online photography. Tourism Management, 32(4), 725–731. DOI: 10.1016/j.tourman.2010.06.001.]Open DOISearch in Google Scholar
[Lukoianova, T., & Rubin, V. L. (2014). Veracity Roadmap: Is Big Data Objective, Truthful and Credible? Advances In Classification Research Online, 1(1), 1–13. DOI: 10.7152/acro.v24i1.14671.]Open DOISearch in Google Scholar
[Mack, R. W., Blose, J. E., & Pan, B. (2008). Believe it or not: Credibility of blogs in tourism. Journal of Vacation Marketing, 14(2), 133–144. DOI: 10.1177/1356766707087521.]Open DOISearch in Google Scholar
[Marron, B. A., & de Maine, P. A. D. (1967). Automatic data compression. Communications of the ACM, 10(11), 711–715. DOI: 10.1145/363790.363813.]Open DOISearch in Google Scholar
[Olmedo, M. H. S., Gómez, B. M., Palomares, J. C. G., & Gutiérrez, J. (2018). Tourists’ digital footprint in cities: Comparing Big Data sources. Tourism Management, 66, 13–25. DOI: 10.1016/j.tourman.2017.11.001.]Open DOISearch in Google Scholar
[Önder, I. (2017). Classifying multi-destination trips in Austria with big data. Tourism Management Perspectives, 21, 54–58. DOI: 10.1016/j.tmp.2016.11.002.]Open DOISearch in Google Scholar
[Orellana, D., Bregt, A. K., Ligtenberg, A., & Wachowicz, M. (2012). Exploring visitor movement patterns in natural recreational areas. Tourism Management, 33(3), 672–682. DOI: 10.1016/j.tourman.2011.07.010.]Open DOISearch in Google Scholar
[Philander, K., & Zhong, Y. Y. (2016). Twitter sentiment analysis: Capturing sentiment from integrated resort tweets. International Journal of Hospitality Management, 55, 16–24. DOI: 10.1016/j.ijhm.2016.02.001.]Open DOISearch in Google Scholar
[Press, G. (2013). A Very Short History of Big Data [online]. Forbes, May. Retrieved from https://www.forbes.com/sites/gilpress/2013/05/09/a-very-short-history-of-big-data/#2549c2f865a1.]Search in Google Scholar
[Ritchie, J. B., & Crouch, G. I. (2006). The competitive destination: a sustainable tourism perspective. Wallingford: CABI Publishing.]Search in Google Scholar
[Sabou, M., Onder, I., Brasoveanu, A. M. P., & Scharl, A. (2016). Towards cross-domain data analytics in tourism: a linked data based approach. Information and Communication Technologies in Tourism, 16, 71–101. DOI: 10.1007/s40558–015–0049–5.]Open DOISearch in Google Scholar
[Saluveer, E., Raun, J., Tiru, M., Altin, L., Kroon, J., Snitsarenko, T., Aasa, A., & Silm, S. (2020). Methodological framework for producing national tourism statistics from mobile positioning data. Annals of Tourism Research, 81, 102895. DOI: 10.1016/j.annals.2020.102895.]Open DOISearch in Google Scholar
[Shih, C., Nicholls, S., & Holecek, D. F. (2008). Impact of Weather on Downhill Ski Lift Ticket Sales. Journal of Travel Research, 47(3), 359–372. DOI: 10.1177/0047287508321207.]Open DOISearch in Google Scholar
[Shoval, N., & Isaacson, M. (2007). Tracking tourists in the digital age. Annals of Tourism Research, 34(1), 141–159. DOI: 10.1016/j.annals.2006.07.007.]Open DOISearch in Google Scholar
[Siato, T., Takahashi, A., & Tsuda, H. (2016). Optimal room charge and expected sales under discrete choice models with limited capacity. International Journal of Hospitality Management, 57, 116–131. DOI: 10.1016/j.ijhm.2016.06.006.]Open DOISearch in Google Scholar
[Snijders, C., Matzat, U., & Reips, U. D. (2012). Big Data: Big Gaps of Knowledge in the Field of Internet Science. International Journal of Internet Science, 7(1), 1–5.]Search in Google Scholar
[Stienmetz, J. L., & Fesenmaier, D. R. (2016). Validating Volunteered Geographic Information: Can We Reliably Trace Visitors' Digital Footprints? In Travel and Tourism Research Association: Advancing Tourism Research Globally [online]. Retrieved from https://scholarworks.umass.edu/ttra/2016/Academic_Papers_Visual/24a.]Search in Google Scholar
[Sun, S., Wei, Y., Tsui, K. L., & Wang, S. (2019). Forecasting tourist arrivals with machine learning and internet search index. Tourism Management, 70, 1–10. DOI: 10.1016/j.tourman.2018.07.010.]Open DOISearch in Google Scholar
[Tchetchik, A., Fleischer, A., & Shoval, N. (2009). Segmentation of Visitors to a Heritage Site Using High-resolution Time-space Data. Journal of Travel Research, 48(2), 216–229. DOI: 10.1177/0047287509332307.]Open DOISearch in Google Scholar
[The Guardian. (2012). Hacker advertises details of 117 million LinkedIn users on darknet [online]. Retrieved from https://www.theguardian.com/technology/2016/may/18/hacker-advertises-details-of-117-million-linkedin-users-on-darknet.]Search in Google Scholar
[Thevenot, G. (2007). Blogging as a Social Media. Tourism and Hospitality Research, 7(3/4), 287–289. DOI: 10.1057/palgrave.thr.6050062.]Open DOISearch in Google Scholar
[Vaynerchuk, G. (2013). Jab, Jab, Jab, Right Hook: How to tell your story in a noisy social world. New York, USA: HarperCollins Publishers.]Search in Google Scholar
[Versichele, M., de Groote, L., Bouuaert, M. C., Neutans, T., Moerman, I., & Van de Weghe, N. (2014). Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent, Belgium. Tourism Management, 44, 67–81. DOI: 10.1016/j.tourman.2014.02.009.]Open DOISearch in Google Scholar
[Von Mises, L. (1998). Liberalismus (Liberalism). Prague, Czech Republic: Ekopress.]Search in Google Scholar
[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. DOI: 10.1016/j.tourman.2014.07.003.]Open DOISearch in Google Scholar
[Weaver, A. (2008). When Tourists Become Data: Consumption, Surveillance, and Commerce. Current Issues in Tourism, 11(1), 1–23.10.2167/cit338.0]Search in Google Scholar
[Wöber, K. (2007). Similarities in Information Search of City Break Travelers — A Web Usage Mining Exercise. In Sigala, M., Mich, L., Murphy, J. (Eds.), Information and Communication Technologies in Tourism 2007 (pp. 77–86). Vienna: Springer. DOI: 10.1007/978–3-211–69566–1_8.]Open DOISearch in Google Scholar
[Xiang, Z., & Gretzel, U. (2010). Role of social media in online travel information search. Tourism Management, 31(2), 179–188. DOI: 10.1016/j.tourman.2009.02.016.]Open DOISearch in Google Scholar
[Xiang, Z., Du, Q., Ma, Y., & Fan, W. (2017). A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism. Tourism Management, 58, 51–65. DOI: 10.1016/j.tourman.2016.10.001.]Open DOISearch in Google Scholar
[Ye, Q., Law, R., Gu, B., & Chen, W. (2011). The influence of user-generated content on traveler behavior: An empirical investigation on the effects of e-word-of-mouth to hotel online bookings. Computers in Human Behavior, 27(2), 634–639. DOI: 10.1016/j.chb.2010.04.014.]Open DOISearch in Google Scholar
[Yu, S. C., Choi, W. W., Shin, D. B., & Ahn, J. W. (2014). A Study on Concept and Services Framework of Geo-Spatial Big Data. Journal of Korea Spatial Information Society, 22(6), 13–21. DOI: 10.12672/ksis.2014.22.6.013.]Open DOISearch in Google Scholar
[Zach, F., & Gretzel, U. (2011). Tourist-Activated Networks: Implications for Dynamic Bundling and EN Route Recommendations. Information Technology & Tourism, 13(3), 229–238.10.3727/109830512X13283928066959]Search in Google Scholar
[Zheng, W., Huang, X., & Li, Y. (2017). Understanding the tourist mobility using GPS: Where is the next place? Tourism Management, 59, 267–280. DOI: 10.1016/j.tourman.2016.08.009.]Open DOISearch in Google Scholar
[Zoltan J., & McKercher, B. (2015). Analysing intra-destination movements and activity participation of tourists through destination card consumption. Tourism Geographies, 17(1), 19–35. DOI: 10.1080/14616688.2014.927523.]Open DOISearch in Google Scholar