Improving the resident–tourist relationship in urban hotspots

References

• Andereck, K. L., Valentine, K. M., Knopf, R. C., & Vogt, C. A. (2005). Residents’ perceptions of community tourism impacts. Annals of Tourism Research, 32(4), 1056–1076. https://doi.org/10.1016/j.annals.2005.03.001
   Web of Science ®Google Scholar
• Ap, J. (1992). Residents' perceptions on tourism impacts. Annals of Tourism Research, 19(4), 665–690. https://doi.org/10.1016/0160-7383(92)90060-3
   Web of Science ®Google Scholar
• Ashworth, G., & Page, S. J. (2011). Urban tourism research: Recent progress and current paradoxes. Tourism Management, 32(1), 1–15. https://doi.org/10.1016/j.tourman.2010.02.002
   Web of Science ®Google Scholar
• Beritelli, P., & Laesser, C. (2011). Power dimensions and influence reputation in tourist destinations: Empirical evidence from a network of actors and stakeholders. Tourism Management, 32(6), 1299–1309. https://doi.org/10.1016/j.tourman.2010.12.010
   Web of Science ®Google Scholar
• Bi, J. W., Liu, Y., Fan, Z. P., & Zhang, J. (2019). Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews. Tourism Management, 70, 460–478. https://doi.org/10.1016/j.tourman.2018.09.010
   Web of Science ®Google Scholar
• Blau, P. (2017). Exchange and power in social life. Routledge.
   Google Scholar
• Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022. https://doi.org/10.5555/944919.944937
   Web of Science ®Google Scholar
• Cawley, G. C., & Talbot, N. L. C. (2010). On over-fitting in model selection and subsequent selection bias in performance evaluation. Journal of Machine Learning Research, 11, 2079–2107. https://doi.org/10.5555/1756006.1859921
   Web of Science ®Google Scholar
• Cheung, K. S., & Li, L. H. (2019). Understanding visitor–resident relations in overtourism: Developing resilience for sustainable tourism. Journal of Sustainable Tourism, 27(8), 1197–1216. https://doi.org/10.1080/09669582.2019.1606815
   Web of Science ®Google Scholar
• Chua, A., Servillo, L., Marcheggiani, E., & Moere, A. V. (2016). Mapping Cilento: Using geotagged social media data to characterize tourist flows in Southern Italy. Tourism Management, 57, 295–310. https://doi.org/10.1016/j.tourman.2016.06.013
   Web of Science ®Google Scholar
• Deery, M., Jago, L., & Fredline, L. (2012). Rethinking social impacts of tourism research: A new research agenda. Tourism Management, 33(1), 64–73. https://doi.org/10.1016/j.tourman.2011.01.026
   Web of Science ®Google Scholar
• DGE. (2016). 82.6 million foreign tourists in France in 2016. Études Économiques, Direction Générale des Entreprises, Retrieved Octorber 28, 2018, from https://www.entreprises.gouv.fr/files/files/directions_services/etudes-et-statistiques/4p-DGE/2017-06-4p-N71-EVE-ENGLISH.pdf
   Google Scholar
• Font, X., & McCabe, S. (2017). Sustainability and marketing in tourism: Its contexts, paradoxes, approaches, challenges and potential. Journal of Sustainable Tourism, 25(7), 869–883. https://doi.org/10.1080/09669582.2017.1301721
   Web of Science ®Google Scholar
• Gibson, C. (2019). Critical tourism studies: New directions for volatile times. Tourism Geographies, 1–19. https://doi.org/10.1080/14616688.2019.1647453
   Google Scholar
• Greene, D., & Cross, J. P. (2015). Unveiling the political agenda of the European parliament plenary: A topical analysis [Paper presentation]. Proceedings of the ACM Web Science Conference, Oxford, UK. (Article No. 2) https://doi.org/10.1145/2786451.2786464
   Google Scholar
• Guo, Y., Barnes, S. J., & Jia, Q. (2017). Mining meaning from online ratings and reviews: Tourist satisfaction analysis using Latent Dirichlet Allocation. Tourism Management, 59, 467–483. https://doi.org/10.1016/j.tourman.2016.09.009
   Web of Science ®Google Scholar
• Hall, P. (1970). A horizon of hotels. New Society, 15, 389–445.
   Google Scholar
• Heo, C. Y., Blal, I., & Choi, M. (2019). What is happening in Paris? Airbnb, hotels, and the Parisian market: A case study. Tourism Management, 70, 78–88. https://doi.org/10.1016/j.tourman.2018.04.003
   Web of Science ®Google Scholar
• Hofmann, T. (1999). Probabilistic latent semantic indexing. Proceedings of the Twenty-Second Annual International SIGIR Conference on Research and Development in Information Retrieval (pp. 50–57). https://doi.org/10.1145/312624.312649
   Google Scholar
• Jacobs, B. J. D., Donkers, B., & Fok, D. (2016). Model-based purchase predictions for large assortments. Marketing Science, 35(3), 389–404. https://doi.org/10.1287/mksc.2016.0985
   Web of Science ®Google Scholar
• Jacobsen, J. K. S., Iversen, N. M., & Hem, L. E. (2019). Hotspot crowding and over-tourism: Antecedents of destination attractiveness. Annals of Tourism Research, 76, 53–66. https://doi.org/10.1016/j.annals.2019.02.011
   Web of Science ®Google Scholar
• Joppe, M. (2018). Tourism policy and governance: Quo vadis? Tourism Management Perspectives, 25, 201–204. https://doi.org/10.1016/j.tmp.2017.11.011
   Web of Science ®Google Scholar
• Ketchen, D. J., Jr., & Shook, C. L. (1996). The application of cluster analysis in Strategic Management Research: An analysis and critique. Strategic Management Journal, 17(6), 441–458. https://doi.org/10.1002/(SICI)1097-0266(199606)17:6 < 441::AID-SMJ819 > 3.0.CO;2-G
   Web of Science ®Google Scholar
• Kim, G., Duffy, L. N., & Moore, D. (2020). Tourist attractiveness: Measuring residents’ perception of tourists. Journal of Sustainable Tourism, 28(6), 898–916. https://doi.org/10.1080/09669582.2019.1708919
   Web of Science ®Google Scholar
• Lalicic, L. (2020). Solastalgia: An application in the overtourism context. Annals of Tourism Research, 82, 102766. https://doi.org/10.1016/j.annals.2019.102766
   Web of Science ®Google Scholar
• Laurini, R. (2017). Geographic knowledge infrastructure: Applications for territorial intelligence and smart cities. Elsevier.
   Google Scholar
• Lim, J., & Lee, H. C. (2020). Comparisons of service quality perceptions between full-service carriers and low-cost carriers in airline travel. Current Issues in Tourism, 23(10), 1261–1276. https://doi.org/10.1080/13683500.2019.1604638
   Web of Science ®Google Scholar
• Lin, Z., Chen, Y., & Filieri, R. (2017). Resident-tourist value co-creation: The role of residents' perceived tourism impacts and life satisfaction. Tourism Management, 61, 436–442. https://doi.org/10.1016/j.tourman.2017.02.013
   Web of Science ®Google Scholar
• Luo, J. M., Vu, H. Q., Li, G., & Law, R. (2019). Tourist behavior analysis in gaming destinations based on venue check-in data. Journal of Travel & Tourism Marketing, 36(1), 107–118. https://doi.org/10.1080/10548408.2018.1494088
   Web of Science ®Google Scholar
• Luo, J. M., Vu, H. Q., Li, G., & Law, R. (2020). Topic modelling for theme park online reviews: Analysis of Disneyland. Journal of Travel & Tourism Marketing, 37(2), 272–285. https://doi.org/10.1080/10548408.2020.1740138
   Web of Science ®Google Scholar
• Maxim, C. (2016). Sustainable tourism implementation in urban areas: a case study of London. Journal of Sustainable Tourism, 24(7), 971–989. https://doi.org/10.1080/09669582.2015.1115511
   Web of Science ®Google Scholar
• Mazanec, J. A. (2017). Determining long-term change in tourism research language with text-mining methods. Tourism Analysis, 22(1), 75–83. https://doi.org/10.3727/108354217X14828625279771
   Web of Science ®Google Scholar
• McGuire, K. A., Kimes, S. E., Lynn, M., Pullman, M. E., & Lloyd, R. C. (2010). A framework for evaluating the customer wait experience. Journal of Service Management, 21(3), 269–290. https://doi.org/10.1108/09564231011050760
   Web of Science ®Google Scholar
• Mody, M., Suess, C., & Dogru, T. (2019). Not in my backyard? Is the anti-Airbnb discourse truly warranted? Annals of Tourism Research, 74(C), 198–203. https://doi.org/10.1016/j.annals.2018.05.004
   Google Scholar
• Monterrubio. (2016). The impact of spring break behaviour: An integrated threat theory analysis of residents' prejudice. Tourism Management, 54, 418–427. https://doi.org/10.1016/j.tourman.2015.12.004
   Web of Science ®Google Scholar
• Namberger, P., Jackisch, S., Schmude, J., & Karl, M. (2019). Overcrowding, overtourism and local level disturbance: How much can Munich handle? Tourism Planning & Development, 16(4), 452–472. https://doi.org/10.1080/21568316.2019.1595706
   Web of Science ®Google Scholar
• Novy, J., & Colomb, C. (2019). Urban tourism as a source of contention and social mobilisations: A critical review. Tourism Planning & Development, 16 (4), 358–375. https://doi.org/10.1080/21568316.2019.1577293
   Web of Science ®Google Scholar
• Office du Tourisme et des Congrès (OTCP). (2019). Tourism in Paris - Key Figures 2018. Retrieved October 5, 2019, from https://pro.parisinfo.com/etudes-et-chiffres/key-figures-english-version/annual-key-figures
   Google Scholar
• O’Reilly, A. M. (1986). Tourism carrying capacity: Concept and issues. Tourism Management, 7(4), 254–258. https://doi.org/10.1016/0261-5177(86)90035-X
   Google Scholar
• Papadimitriou, C. H., Raghavan, P., Tamaki, H., & Vempala, S. (2000). Latent semantic indexing: A probabilistic analysis. Journal of Computer and System Sciences, 61(2), 217–235. https://doi.org/10.1006/jcss.2000.1711
   Web of Science ®Google Scholar
• Pasquinelli, C., & Trunfio, M. (2020). Overtouristified cities: An online news media narrative analysis. Journal of Sustainable Tourism, 28(11), 1805–1824. https://doi.org/10.1080/09669582.2020.1760871
   Web of Science ®Google Scholar
• Pearce, P. L. (2019). Are tourists interesting? In P. L. Pearce (Ed.), Tourist behaviour. The essential companion (pp. 1–19). Edward Elgar.
   Google Scholar
• Phi, G. T. (2020). Framing overtourism: A critical news media analysis. Current Issues in Tourism, 23(17), 2093–2097. https://doi.org/10.1080/13683500.2019.1618249
   Web of Science ®Google Scholar
• Raun, J., Ahas, R., & Tiru, M. (2016). Measuring tourism destinations using mobile tracking data. Tourism Management, 57, 202–212. https://doi.org/10.1016/j.tourman.2016.06.006
   Web of Science ®Google Scholar
• Romão, J., Kourtit, K., Neuts, B., & Nijkamp, P. (2018). The smart city as a common place for tourists and residents: A structural analysis of the determinants of urban attractiveness. Cities, 78, 67–75. https://doi.org/10.1016/j.cities.2017.11.007
   Web of Science ®Google Scholar
• Samuel, H. (2019). Paris set to ban tourist buses from city centre due to overtourism, Traveller.com.au. Retrieved October 4, 2019, from https://www.traveller.com.au/paris-set-to-ban-tourist-buses-from-city-centre-due-to-overtourism-h1fw8c
   Google Scholar
• Scuderi, R., & Nogare, C. D. (2018). Mapping tourist consumption behaviour from destination card data: What do sequences of activities reveal? International Journal of Tourism Research, 20 (5), 554–565. https://doi.org/10.1002/jtr.2205
   Web of Science ®Google Scholar
• Selby, M. (2012). Geographies of tourism and the city. In J. Wilson (Ed.), The Routledge handbook of tourism geographies (pp. 232–239). Routledge.
   Google Scholar
• Sharpley, R. (2014). Host perceptions of tourism: A review of the research. Tourism Management, 42, 37–49. https://doi.org/10.1016/j.tourman.2013.10.007
   Web of Science ®Google Scholar
• Shoval, N. (2018). Urban planning and tourism in European cities. Tourism Geographies, 20(3), 371–376. https://doi.org/10.1080/14616688.2018.1457078
   Web of Science ®Google Scholar
• Sobolevsky, S., Bijic, I., Belyi, A., Sitko, I., Hawelka, B., Arias, J. M., & Ratti, C. (2015). Scaling of city attractiveness for foreign visitors through big data of human economical and social media activity. In IEEE International Congress on Big Data, pp. 600–607.
   Google Scholar
• Stringam, B. B., Gerdes, J., & Vanleeuwen, D. M. (2010). Assessing the importance and relationships of ratings on user-generated traveler reviews. Journal of Quality Assurance in Hospitality & Tourism, 11(2), 73–92. https://doi.org/10.1080/1528008X.2010.482000
   Google Scholar
• The Guardian. (2019). Mona Lisa fans decry brief encounter with their idol in Paris. Louvre visitors complain of being moved on in seconds after spending hours in queue. Retrieved September 23, 2019, from https://www.theguardian.com/world/2019/aug/13/mona-lisa-fans-face-scandalous-queues-after-portrait-relocated
   Google Scholar
• Torres-Delgado, A., Palomeque, F.L. (2014). Measuring sustainable tourism at the municipal level. Annals of Tourism Research, 49, 122–137, https://doi.org/10.1016/j.annals.2014.09.003.
   Google Scholar
• Trattner, C., Helic, D., & Strohmaier, M. (2014). Tag clouds. In R. Alhajj & J. Rokne (Eds.), Encyclopedia of social network analysis and mining. Springer.
   Google Scholar
• Van der Borg, J., Costa, P., & Gotti, G. (1996). Tourism in European heritage cities. Annals of Tourism Research, 23(2), 306–321. https://doi.org/10.1016/0160-7383(95)00065-8
   Web of Science ®Google Scholar
• Vu, H. Q., Leung, R., Rong, J., & Miao, Y. (2016). Exploring park visitors’ activities in Hong Kong using geotagged photos. In Proceedings of 23rd Information and Communication Technologies in Tourism, pp. 183–196. https://doi.org/10.1007/978-3-319-28231-2_14
   Google Scholar
• Vu, H. Q., Li, G., & Law, R. (2019). Discovering implicit activity preferences in travel itineraries by topic modeling. Tourism Management, 75, 435–446. https://doi.org/10.1016/j.tourman.2019.06.011
   Web of Science ®Google Scholar
• Vu, H. Q., Li, G., & Law, R. (2020). Cross-country analysis of tourist activities based on venue-referenced social media data. Journal of Travel Research, 59(1), 90–106. https://doi.org/10.1177/0047287518820194
   Web of Science ®Google Scholar
• Washington Post. (2019). These are the cities overtourism could threaten next. Retrieved October 5, 2019, from https://www.washingtonpost.com/travel/2019/06/18/these-are-cities-overtourism-could-threaten-next/
   Google Scholar
• Williams, J., & Lawson, R. (2001). Community issues and resident opinions of tourism. Annals of Tourism Research, 28(2), 269–290. https://doi.org/10.1016/S0160-7383(00)00030-X
   Web of Science ®Google Scholar
• World Tourism Organization (UNWTO). (2018). ‘Overtourism’? – Understanding and managing urban tourism growth beyond perceptions, executive summary. World Tourism Organization.
   Google Scholar
• World Tourism Organization (UNWTO) and IPSOS. (2019). Global survey on the perception of residents towards city tourism: Impact and measures. UNWTO. https://doi.org/10.18111/9789284421107.
   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. https://doi.org/10.1016/j.tourman.2016.10.001
   Web of Science ®Google Scholar
• Yoo, K. H., & Lee, W. (2015). Use of Facebook in the US heritage accommodations sector: An exploratory study. Journal of Heritage Tourism, 10(2), 191–201. https://doi.org/10.1080/1743873X.2014.985228
   Web of Science ®Google Scholar
• Zhang, H-y., Ji, P., Wang, J-q., & Chen, X-h. (2017). A novel decision support model for satisfactory restaurants utilizing social information: A case study of TripAdvisor.com. Tourism Management, 59, 281–297. https://doi.org/10.1016/j.tourman.2016.08.010
   Web of Science ®Google Scholar