MOBITUR: advancing smart tourism planning with ai for sustainable mobility management. A testing in a regional context

Arbués, P., Baños, J. F., Mayor, M., & Suárez, P. (2016). Determinants of ground transport modal choice in long-distance trips in Spain. Transportation Research Part A: Policy and Practice, 84, 131-143. https://doi.org/10.1016/j.tra.2015.06.010

Baptista, J., Stein, M. K., Klein, S., Watson-Manheim, M. B., & Lee, J. (2020). Digital work and organisational transformation: Emergent Digital/Human work configurations in modern organisations. The Journal of Strategic Information Systems, 29(2), 101618. https://doi.org/10.1016/j.jsis.2020.101618

Buitrago, E.M, Cabrera-Puig, M., Santos, J-A.C, Custódio-Santos, M. & Yñiguez, R. (2024): Artificial Intelligence and Sustainable Tourism Planning: A Hetero-Intelligence Methodology Proposal. Tourism & Management Studies, 20 (SI), 45-59, https://doi.org/10.18089/tms.2024SI04

Calinski, T., & Harabasz, J. (1974). A dendrite method for cluster analysis. Communications in Statistics, 3(1), 1–27. https://doi.org/10.1080/03610927408827101

Bustamante, A., Sebastia, L., & Onaindia, E. (2020). Bitour: a business intelligence platform for tourism analysis. ISPRS International Journal of Geo-Information, 9(11), 671. https://doi.org/10.3390/ijgi9110671

Camatti, N., Essenfelder, A. H., & Giove, S. (2024). Mapping the exposure of tourism to weather extremes: the need for a spatially-explicit gridded dataset for disaster risk reduction. Environmental Research Letters, 19(6), 064008. https://doi.org/10.1088/1748-9326/ad3e91

Celdrán, M. A., Mazón, J.-N., & Giner Sánchez, D. (2018). Open Data y turismo. Implicaciones para la gestión turística en ciudades y destinos turísticos inteligentes. Investigaciones Turísticas, (15), 49–78. https://doi.org/10.14198/INTURI2018.15.03

Chen, Z., Alfred, R., & Eboy, O. V. (2021). Modeling Tourism Using Spatial Analysis Based on Social Media Big Data: A Review. Computational Science and Technology: 7th ICCST 2020, Pattaya, Thailand, 29–30 August, 2020, 437-451.

Chen, J., Shoval, N., & Stantic, B. (2024). Tracking tourist mobility in the big data era: insights from data, theory, and future directions. Tourism Geographies, 26(8), 1381-1411. https://doi.org/10.1080/14616688.2024.2341249

Christensen, J., Hansen, J. M., & Wilson, P. (2025). Understanding the role and impact of Generative Artificial Intelligence (AI) hallucination within consumers’ tourism decision-making processes. Current Issues in Tourism, 28(4), 545-560. https://doi.org/10.1080/13683500.2023.2300032

Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-1(2), 224–227. https://doi.org/10.1109/TPAMI.1979.4766909

Dhoundiyal, H., & Mohanty, P. (2022). Artificial intelligence and robotics driving Tourism 4.0: An exploration. In Handbook of Technology Application in Tourism in Asia (pp. 1265-1285). Singapore: Springer Nature Singapore.

Doborjeh, Z., Hemmington, N., Doborjeh, M., & Kasabov, N. (2022). Artificial intelligence: a systematic review of methods and applications in hospitality and tourism. International Journal of Contemporary Hospitality Management, 34(3), 1154-1176. https://doi.org/10.1108/IJCHM-06-2021-0767

Dogru, T., Line, N., Mody, M., Hanks, L., Abbott, J. A., Acikgoz, F., ... & Zhang, T. (2025). Generative artificial intelligence in the hospitality and tourism industry: Developing a framework for future research. Journal of Hospitality & Tourism Research, 49(2), 235-253. https://doi.org/10.1177/10963480231188663

Dwivedi, Y.K., Pandey, N., Currie, W., & Micu, A. (2024). Leveraging ChatGPT and other generative artificial intelligence (AI)-based applications in the hospitality and tourism industry: practices, challenges and research agenda. International Journal of Contemporary Hospitality Management, 36 (1), 1-12. https://doi.org/10.1108/IJCHM-05-2023-0686

Flores-Crespo, P., Bermudez-Edo, M., & Garrido, J. L. (2022). Smart tourism in Villages: Challenges and the Alpujarra Case Study. Procedia Computer Science, 204, 663-670. https://doi.org/10.1016/j.procs.2022.08.080

Giorgino, T. (2009). Computing and visualizing dynamic time warping alignments in R: the dtw package. Journal of statistical Software, 31, 1-24. https://doi.org/10.18637/jss.v031.i07.

Gobierno de Murcia (2022). Tourism strategic framework of Murcia 2022-2032, Comunidad Autónoma de la Región de Murcia (2022). URL https://www.murciaturistica.es/es/plan_estrategico/

Gössling, S. (2021) Tourism, technology and ICT: a critical review of affordances and concessions. Journal of Sustainable Tourism 29 (5) (2021) 733–750. https://doi.org/10.1080/09669582.2021.1873353

Günther, W. A., Mehrizi, M. H. R., Huysman, M., Deken, F., & Feldberg, F. (2022). Resourcing with data: Unpacking the process of creating data-driven value propositions. The Journal of Strategic Information Systems, 31(4), 101744. https://doi.org/10.1016/j.jsis.2022.101744

Hall, G., Sigala, M., Rentschler, R., & Boyle, S. (2019). Motivations, mobility and work practices; the conceptual realities of digital nomads. In Information and Communication Technologies in Tourism 2019: Proceedings of the International Conference in Nicosia, Cyprus, January 30–February 1, 2019 (pp. 437-449). Springer International Publishing.

Hamid, R. A., Albahri, A. S., Alwan, J. K., Al-Qaysi, Z. T., Albahri, O. S., Zaidan, A. A., ... & Zaidan, B. B. (2021). How smart is e-tourism? A systematic review of smart tourism recommendation system applying data management. Computer Science Review, 39, 100337. https://doi.org/10.1016/j.cosrev.2020.100337

Hardy, A., & Aryal, J. (2020). Using innovations to understand tourist mobility in national parks. Journal of Sustainable Tourism, 28(2), 263-283. https://doi.org/10.1080/09669582.2019.1670186

Henriques, H.J.G., Almeida, C.R., & Ramos, C.M.Q. (2024). The Application of artificial intelligence in the tourism industry: a systematic literature review based on Prisma methodology. Journal of Tourism, Sustainability and Well-Being, 12(1), 65-86. https://doi.org/10.34623/hkqk-ht95

Insch, A. (2020). The challenges of over-tourism facing New Zealand: Risks and responses. Journal of Destination Marketing & Management, 15, 100378. https://doi.org/10.1016/j.jdmm.2019.100378

Islam, M.R.,Abdul Kader, M., Miah, S.. Akter, A. Ulhaq, A. (2021). Discovering tourist preference for electing destinations: a pattern mining based approach, Asia Pacific Journal of Tourism Research, 26 (10), 1081–1096. doi:10.1080/10941665.2021.1954676.

Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651–666. https://doi.org/10.1016/j.patrec.2009.09.011

Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202

Keogh, E., & Ratanamahatana, C. A. (2005). Exact indexing of dynamic time warping. Knowledge and Information Systems, 7(3), 358–386. https://doi.org/10.1007/s10115-004-0154-9

Kim, M. J., Hall, C. M., & Chung, N. (2024). The influence of AI and smart apps on tourist public transport use: applying mixed methods. Information Technology & Tourism, 26(1), 1-24. https://doi.org/10.1007/s40558-023-00272-x

Koo, I., Zaman, U., Ha, H., & Nawaz, S. (2025). Assessing the interplay of trust dynamics, personalization, ethical AI practices, and tourist behavior in the adoption of AI-driven smart tourism technologies. Journal of Open Innovation: Technology, Market, and Complexity, 11(1), 100455. https://doi.org/10.1016/j.joitmc.2024.100455

Kovács, Z., Smith, M., Teleubay, Z., & Kovalcsik, T. (2023). Measuring visitor flows using mobile positioning data in three Hungarian second-tier cities. International Journal of Tourism Cities, 9(3), 656-674. https://doi.org/10.1108/IJTC-03-2023-0049

Lau, B. P. L., Marakkalage, S. H., Zhou, Y., Hassan, N. U., Yuen, C., Zhang, M., & Tan, U. X. (2019). A survey of data fusion in smart city applications. Information Fusion, 52, 357-374. https://doi.org/10.1016/j.inffus.2019.05.004

Li, X., Law, R., Xie, G., & Wang, S. (2021). Review of tourism forecasting research with internet data. Tourism Management, 83, 104245. doi:10.1016/j.tourman.2020.104245

MacQueen, J. (1967, June). Classification and analysis of multivariate observations. In 5th Berkeley Symp. Math. Statist. Probability (pp. 281-297). Los Angeles LA USA: University of California.

Maltese, I., & Zamparini, L. (2023). Sustainable mobility choices at home and within destinations: A survey of young Italian tourists. Research in Transportation Business & Management, 48, 100906. https://doi.org/10.1016/j.rtbm.2022.100906

Manoharan, G., Rao, C. G., Ashtikar, S. P., Kumar, S., & Nivedha, M. (2024). Voyage Virtuoso: Artificial Intelligence in Transforming Tourism. In Utilizing Smart Technology and AI in Hybrid Tourism and Hospitality (pp. 79-97). IGI Global Scientific Publishing.

Mariani, M., Baggio, R., Fuchs, M., & Höepken, W. (2018). Business intelligence and big data in hospitality and tourism: a systematic literature review. International Journal of Contemporary Hospitality Management, 30(12), 3514-3554.doi:10.1108/ JHTT-12-2018-0118.

Masiero, L., Hrankai, R., & Zoltan, J. (2022). The role of intermodal transport on urban tourist mobility in peripheral areas of Hong Kong. Research in Transportation Business & Management, 100838. https://doi.org/10.1016/j.rtbm.2022.100838

Mason, P. (2020). Tourism impacts, planning and management. Routledge.

Mendoza-Moreno, J. F., Santamaria-Granados, L., Fraga Vázquez, A., & Ramirez-Gonzalez, G. (2021). OntoTouTra: Tourist Traceability Ontology Based on Big Data Analytics. Applied Sciences, 11(22), 11061. doi:10.3390/ app112211061.

Mich, L. (2022). AI and Big Data in Tourism: Definitions, Areas, and Approaches. In Applied Data Science in Tourism: Interdisciplinary Approaches, Methodologies, and Applications (pp. 3-15). Cham: Springer International Publishing.

Ministerio de Transportes, Movilidad y Agenda Urbana (2020). Análisis de la movilidad en España con tecnología Big Data durante el estado de alarma para la gestión de la crisis del COVID-19.

Park, S., Xu, Y., Jiang, L., Chen, Z., & Huang, S. (2020). Spatial structures of tourism destinations: A trajectory data mining approach leveraging mobile big data. Annals of Tourism Research, 84, 102973. https://doi.org/10.1016/j.annals.2020.102973.

Polo-Peña, A. I., Frías-Jamilena, D. M., Peco-Torres, F., & Rodríguez-Molina, M. Á. (2025). Experience and artificial intelligence in hospitality and tourism: a review of reviews and a bibliometric analysis. International Journal of Contemporary Hospitality Management. 21 May 2025; 37 (7): 2306–2326. https://doi.org/10.1108/IJCHM-07-2024-0988

Puig-Cabrera, M., & Foronda-Robles, C. (2025). Multi-level evolutionary model for smart tourism transition: A pilot test in the Andalusian region (Spain). European Journal of Tourism Research, 41, 4118. https://doi.org/10.54055/ejtr.v41i.4126

Roman, M., Roman, M., Niedziólka, A. (2020). Spatial diversity of tourism in the countries of the European Union. Sustainability, 12 (7) (2020). https://doi.org/10.3390/su12072713

Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65. https://doi.org/10.1016/0377-0427(87)90125-7

Sakoe, H., & Chiba, S. (1978). Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustics, Speech, and Signal Processing, 26(1), 43–49. https://doi.org/10.1109/TASSP.1978.1163055

Sánchez-Martín, J.M., M. Sánchez-Rivero, M. Rengifo-Gallego, J. (2020). Water as a tourist resource in Extremadura: Assessment of its attraction capacity and approximation to the tourist profile, Sustainability, 12 (4). doi:10.3390/su12041659.

Soares, J. C., Domareski Ruiz, T. C., & Ivars Baidal, J. A. (2022). Smart destinations: a new planning and management approach?. Current Issues in Tourism, 25(17), 2717-2732. https://doi.org/10.1080/13683500.2021.1991897

Swain, C., Sahoo, M. N., Satpathy, A., Muhammad, K., Bakshi, S., Rodrigues, J. J., & de Albuquerque, V. H. C. (2020). METO: Matching-theory-based efficient task offloading in IoT-fog interconnection networks. IEEE Internet of Things Journal, 8(16), 12705-12715. https://doi.org/10.1109/JIOT.2020.3025631

UNWTO (2023). World Tourism Barometer, 2023 January.

Veiga, C., Santos, M. C., Águas, P., & Santos, J. A. C. (2018). Sustainability as a key driver to address challenges. Worldwide Hospitality and Tourism Themes, 10(6), 662-673. https://doi.org/10.1108/WHATT-08-2018-0054

Viana-Lora, A., Domenech, A., & Gutiérrez, A. (2023). COVID-19 and tourist mobility at destinations: a literature review and emerging research agenda. Journal of Tourism Futures, 9(1), 21-34. https://doi.org/10.1108/JTF-04-2021-0090

Vu, H. Li, R. Law, I. (2020) Discovering highly profitable travel patterns by high-utility pattern mining, Tourism Management, 77 (2020) 104008. https://doi.org/10.1016/j.tourman.2019.104008.

Wilson, B., & Cong, C. (2020). A survey of municipal open data repositories in the US. International Journal of E-Planning Research (IJEPR), 9(4), 1-22.

Zhao, R., Wang, F., & Zheng, W. (2022). Data‐driven inference of interactions among multiple tourist attractions for hourly demand forecasting. International Journal of Tourism Research, 24(5), 701-713. https://doi.org/10.1002/jtr.2532