Estudio Longitudinal de la estacionalidad turísticas en España usando Redes Neuronales
Resumen
España se ha convertido en un referente en cuanto al turismo ya que el número de visitantes se ha multiplicado de forma extraordinaria, se ha pasado de un modelo turístico uniforme, a lo largo y ancho de la península, a un modelo nuclear. Las variaciones coyunturales asociadas al ciclo económico asociado al turismo tienen un indiscutible impacto económico en las comunidades autónomas. En este trabajo se estudió la estacionalidad de los turistas en épocas prepandémica. Para este propósito se usaron las redes neuronales artificiales para predecir el tipo de turista que está vinculado con los periodos estivales. De ahí que fue usada cómo técnica la red neuronal artificial que consiguió un 86,90% de acierto. Los resultados relevantes se direccionaron a que los turistas nacionales frente a los extranjeros tuvieron mayor participación de estacionalidad a lo largo del año, mientras que los extranjeros son mayormente significativos en periodos estivales.
Descargas
Citas
Aditya, F., Nasution, S. M., Virgono, A. Traffic Flow Prediction Using SUMO Application with K-Nearest Neighbor (KNN) Method. International Journal of Integrated Engineering 2020; 12(7): 98-103.
Al-Bakri, N. F., Yonan, J. F., Sadiq, A. T., Abid, A. S. Tourism companies assessment via social media using sentiment analysis. Baghdad Science Journal 2022; 19(2): 422-429.
Alkan, T., Dokuz, Y., Ecemiş, A., Bozdağ, A., & Durduran, S. S. Using machine learning algorithms for predicting real estate values in tourism centers. Soft Computing 2022; 1-13.
Allcock, J. Seasonality. En Tourism Marketing and Management Handbook. S. Witt y L. Moutinho (eds.), Prentice Hall 1994, New York pp; 191-208.
Amato, G., Falchi, F. kNN based image classification relying on local feature similarity. In Proceedings of the Third International Conference on Similarity Search and Applications 2010: 101-108.
Ashworth, J.; Thomas, B. Patterns of seasonality in employment in tourism in the United Kingdom. Applied Economics Letter 6 1999; (11): 735-739.
Baron, R.V. (1975): Seasonality in Tourism-A Guide to the Analysis of Seasonality and Trends for Policy Making, Technical Series 1975; 2, Economist Intelligence Unit, London.
Baum, T.; Hagen, L., Responses to seasonality: the experiences of peripheral destinations. International Journal of Tourism Research 1999; 1(5): 299-312.
Butler, R. Seasonality in tourism: issues and problems. En Tourism. The State of the Art. A. Seaton (Edit.) Wiley Chichester 1999: 332-340
BUTLER, R.W., «Seasonality in tourism: Issues and implications», en BAUM, T. y LUNDTORP, S. (Eds.): Seasonality in tourism 2001; Pergamon-Elsevier, Oxford: 5-22.
Carneiro, J., Meira, J., Novais, P., & Marreiros, G. (2021). Using machine learning to predict the users ratings on tripadvisor based on their reviews. In Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection: International Workshops of PAAMS 2021, Salamanca, Spain, October 6–9, 2021, Proceedings 19: 127-138.
Chadha, S., Mittal, S., & Singhal, V., An Insight of Script Text Extraction Performance using Machine Learning Techniques. International Journal of Innovative Technology and Exploring Engineering (IJITEE) 2019; 9(1).
COWELL, F. Measuring Inequality, Second edition. New York: Prentice Hall.
Duro, J.A. (2008): «La concentración temporal de la demanda turística en España y sus regiones: un análisis empírico a partir de índices de desigualdad», Revista de Análisis Turístico 2008; 6: 36-48.
Duro, J. A., Farré, F. X., Estacionalidad turística en las provincias españolas: medición y análisis. Cuadernos de Turismo 2015; (36): 157-174.
Hernández, R., Fernández, C., Baptista, P., Metodología de la Investigación 2010. México D.F.: Mcgraw-HILL / Interamericana Editores, S.A. de C.V.
Fernández-Morales, A., «Decomposing seasonal concentration», Annals of Tourism Research 2003; 30 (4): 942-956.
Fernández-Morales, A. y Cruz-Mayorga, M.C. «Seasonal concentration of the hotel demand in Costa del Sol: A decomposition by nationalities», Tourism Management 2008; 29: 940-949.
Flores Ruiz, D., Bago Sotillo, E., & Barroso González, M. de la O. Comportamiento del turismo nacional y crecimiento en España. Revista Investigaciones Turísticas 2018, 16, 68–86. https://doi.org/10.14198/inturi2018.16.04
Georgantzas, N.C. Cyprus’ hotel value chain and profitability. System Dynamics Review 2003; 19(3):175-212
Getz, D.; Nilsson, P.A. Responses of family businesses to extreme seasonality in demand: case of Bornholm, Denmark. Tourism Management 2004; 25(1): 17-30.
GINI, C., Variabilità e mutabilità, C.Cuppini, Bologna 1912.
Gutiérrez Cordero, M. de L., Segovia-Vargas, M. J., y Escamilla, M. R. Análisis del Riesgo de Caída de Cartera en Seguros: Metodologías de “Inteligencia Artificial” vs “Modelos Lineales Generalizados.” Economía Informa 2017; 407: 56–86. https://doi.org/https://doi.org/10.1016/j.ecin.2017.11.004
Hapsari, I., & Surjandari, I. Visiting time prediction using machine learning regression algorithm. In 2018 6th International Conference on Information and Communication Technology (ICoICT) 2018: 495-500.
Instituto de estudios turísticos (IET). Balance del turismo año 2009 [Balantur] 2010. http://estadisticas.tourspain.es/es-ES/estadisticas/analisisturistico/balantur/anuales/Balance turismo en España en 2009.pdf
KOENIG-LEWIS, N. y BISCHOFF, E. (2005): «Seasonality research: the state of the art», International Journal of Tourism Research 2005; 7: 201-219.
Kokate, S., Gaikwad, A., Patil, P., Gutte, M., Shinde, K., Traveler's Recommendation System Using Data Mining Techniques. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) 2018: 1-5.
Krakover, S. Partitioning seasonal employment in the hospitality industry. Tourism Management 2000; 2(3):461-471
Kuvan, Y.; Akan, P. Resident’s attitudes toward general and forest-related impacts of tourism: the case of Belek, Antalya. Tourism Management 2005; 26(5):691-706.
Leal, F., Malheiro, B., & Burguillo, J. C. Trust and reputation modelling for tourism recommendations supported by crowdsourcing. In Trends and Advances in Information Systems and Technologies 2018;1 (6) :829-838. Springer International Publishing.
López, J. y López, L.La concentración estacional en las regiones españolas desde una perspectiva de la oferta turística, Revista de Estudios Regionales 2006, 77, pp. 77-104.
López Bonilla, J. M., López Bonilla, L. M. Variabilidad estacional del mercado turístico en Andalucía. Estudios y perspectivas en turismo 2007; 16(2): 150-172.
Lundtorp, S. «Measuring tourism seasonality» en: BAUM, T. y LUNDTORP, S. (Eds.), Seasonality in tourism 2001: 23-50, Pergamon-Elsevier, Oxford.
Lusseau, D.; Higham, J.E.S. Managing the impacts of dolphin-based tourism through the definition of critical habitats: the case of bottlenose dolphins (Tursiops spp.) in Doubtful Sound, New Zeeland. Tourism Management 2004; 25(6): 657-667.
Mariwa, S. O., Tunduny, T. K. a Web-Based Application for Making Low-Cost Vacation Reservations for Tourists Using the K-Nearest Neighbors Algorithm. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 2021; 48, 67-76.
Martín, J.M., Jiménez, J. y Molina, V., (2014): Impacts of seasonality on environmental sustainability in the tourism sector based on destination type: an application to Spain’s Andalusia region, Tourism Economics 2014, 20 (1), pp. 123-142.
Referencias
Aditya, F., Nasution, S. M., Virgono, A. Traffic Flow Prediction Using SUMO Application with K-Nearest Neighbor (KNN) Method. International Journal of Integrated Engineering 2020; 12(7): 98-103.
Al-Bakri, N. F., Yonan, J. F., Sadiq, A. T., Abid, A. S. Tourism companies assessment via social media using sentiment analysis. Baghdad Science Journal 2022; 19(2): 422-429.
Alkan, T., Dokuz, Y., Ecemiş, A., Bozdağ, A., & Durduran, S. S. Using machine learning algorithms for predicting real estate values in tourism centers. Soft Computing 2022; 1-13.
Allcock, J. Seasonality. En Tourism Marketing and Management Handbook. S. Witt y L. Moutinho (eds.), Prentice Hall 1994, New York pp; 191-208.
Amato, G., Falchi, F. kNN based image classification relying on local feature similarity. In Proceedings of the Third International Conference on Similarity Search and Applications 2010: 101-108.
Ashworth, J.; Thomas, B. Patterns of seasonality in employment in tourism in the United Kingdom. Applied Economics Letter 6 1999; (11): 735-739.
Baron, R.V. (1975): Seasonality in Tourism-A Guide to the Analysis of Seasonality and Trends for Policy Making, Technical Series 1975; 2, Economist Intelligence Unit, London.
Baum, T.; Hagen, L., Responses to seasonality: the experiences of peripheral destinations. International Journal of Tourism Research 1999; 1(5): 299-312.
Butler, R. Seasonality in tourism: issues and problems. En Tourism. The State of the Art. A. Seaton (Edit.) Wiley Chichester 1999: 332-340
BUTLER, R.W., «Seasonality in tourism: Issues and implications», en BAUM, T. y LUNDTORP, S. (Eds.): Seasonality in tourism 2001; Pergamon-Elsevier, Oxford: 5-22.
Carneiro, J., Meira, J., Novais, P., & Marreiros, G. (2021). Using machine learning to predict the users ratings on tripadvisor based on their reviews. In Highlights in Practical Applications of Agents, Multi-Agent Systems, and Social Good. The PAAMS Collection: International Workshops of PAAMS 2021, Salamanca, Spain, October 6–9, 2021, Proceedings 19: 127-138.
Chadha, S., Mittal, S., & Singhal, V., An Insight of Script Text Extraction Performance using Machine Learning Techniques. International Journal of Innovative Technology and Exploring Engineering (IJITEE) 2019; 9(1).
COWELL, F. Measuring Inequality, Second edition. New York: Prentice Hall.
Duro, J.A. (2008): «La concentración temporal de la demanda turística en España y sus regiones: un análisis empírico a partir de índices de desigualdad», Revista de Análisis Turístico 2008; 6: 36-48.
Duro, J. A., Farré, F. X., Estacionalidad turística en las provincias españolas: medición y análisis. Cuadernos de Turismo 2015; (36): 157-174.
Hernández, R., Fernández, C., Baptista, P., Metodología de la Investigación 2010. México D.F.: Mcgraw-HILL / Interamericana Editores, S.A. de C.V.
Fernández-Morales, A., «Decomposing seasonal concentration», Annals of Tourism Research 2003; 30 (4): 942-956.
Fernández-Morales, A. y Cruz-Mayorga, M.C. «Seasonal concentration of the hotel demand in Costa del Sol: A decomposition by nationalities», Tourism Management 2008; 29: 940-949.
Flores Ruiz, D., Bago Sotillo, E., & Barroso González, M. de la O. Comportamiento del turismo nacional y crecimiento en España. Revista Investigaciones Turísticas 2018, 16, 68–86. https://doi.org/10.14198/inturi2018.16.04
Georgantzas, N.C. Cyprus’ hotel value chain and profitability. System Dynamics Review 2003; 19(3):175-212
Getz, D.; Nilsson, P.A. Responses of family businesses to extreme seasonality in demand: case of Bornholm, Denmark. Tourism Management 2004; 25(1): 17-30.
GINI, C., Variabilità e mutabilità, C.Cuppini, Bologna 1912.
Gutiérrez Cordero, M. de L., Segovia-Vargas, M. J., y Escamilla, M. R. Análisis del Riesgo de Caída de Cartera en Seguros: Metodologías de “Inteligencia Artificial” vs “Modelos Lineales Generalizados.” Economía Informa 2017; 407: 56–86. https://doi.org/https://doi.org/10.1016/j.ecin.2017.11.004
Hapsari, I., & Surjandari, I. Visiting time prediction using machine learning regression algorithm. In 2018 6th International Conference on Information and Communication Technology (ICoICT) 2018: 495-500.
Instituto de estudios turísticos (IET). Balance del turismo año 2009 [Balantur] 2010. http://estadisticas.tourspain.es/es-ES/estadisticas/analisisturistico/balantur/anuales/Balance turismo en España en 2009.pdf
KOENIG-LEWIS, N. y BISCHOFF, E. (2005): «Seasonality research: the state of the art», International Journal of Tourism Research 2005; 7: 201-219.
Kokate, S., Gaikwad, A., Patil, P., Gutte, M., Shinde, K., Traveler's Recommendation System Using Data Mining Techniques. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA) 2018: 1-5.
Krakover, S. Partitioning seasonal employment in the hospitality industry. Tourism Management 2000; 2(3):461-471
Kuvan, Y.; Akan, P. Resident’s attitudes toward general and forest-related impacts of tourism: the case of Belek, Antalya. Tourism Management 2005; 26(5):691-706.
Leal, F., Malheiro, B., & Burguillo, J. C. Trust and reputation modelling for tourism recommendations supported by crowdsourcing. In Trends and Advances in Information Systems and Technologies 2018;1 (6) :829-838. Springer International Publishing.
López, J. y López, L.La concentración estacional en las regiones españolas desde una perspectiva de la oferta turística, Revista de Estudios Regionales 2006, 77, pp. 77-104.
López Bonilla, J. M., López Bonilla, L. M. Variabilidad estacional del mercado turístico en Andalucía. Estudios y perspectivas en turismo 2007; 16(2): 150-172.
Lundtorp, S. «Measuring tourism seasonality» en: BAUM, T. y LUNDTORP, S. (Eds.), Seasonality in tourism 2001: 23-50, Pergamon-Elsevier, Oxford.
Lusseau, D.; Higham, J.E.S. Managing the impacts of dolphin-based tourism through the definition of critical habitats: the case of bottlenose dolphins (Tursiops spp.) in Doubtful Sound, New Zeeland. Tourism Management 2004; 25(6): 657-667.
Mariwa, S. O., Tunduny, T. K. a Web-Based Application for Making Low-Cost Vacation Reservations for Tourists Using the K-Nearest Neighbors Algorithm. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences 2021; 48, 67-76.
Martín, J.M., Jiménez, J. y Molina, V., (2014): Impacts of seasonality on environmental sustainability in the tourism sector based on destination type: an application to Spain’s Andalusia region, Tourism Economics 2014, 20 (1), pp. 123-142.
Meira, J., Carneiro, J., Bolón-Canedo, V., Alonso-Betanzos, A., Novais, P., & Marreiros, G. Anomaly detection on natural language processing to improve predictions on tourist preferences. Electronics 2022, 11(5), 779.
Michalska-Dudek, I., Dudek, A. Evaluation of Quality of Neural Network Models and Discriminant Analysis in ROPO Forecasting. In: Jajuga, K., Dehnel, G., Walesiak, M. (eds) Modern Classification and Data Analysis. SKAD 2021. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Cham. https://doi.org/10.1007/978-3-031-10190-8_14
Nugraha, N. B., & Alimudin, E. (2020). Mobile application development for tourist guide in Pekanbaru City. In Journal of Physics: Conference Series 2020; 1430(1): 012038. IOP Publishing.
UNWTO, World Tourism Barometer 2010; 8(2), http://www.unwto.org/facts/eng/pdf/barometer/ UNWTO_Barom10_2_en_excerpt.pdf
Uriel Jiménez, E. Precios y competitividad en el sector turístico, en Uriel JIMÉNEZ, E.; HERNÁNDEZ MARTÍN, R. (Coord.): Análisis y tendencias del turismo Pirámide 2004:119-138.
Ortega Aguaza, B. Determinants of regional labour productivity growth: A study for the hospitality sector in Spain. INVESTIGACIONES REGIONALES-Journal of REGIONAL RESEARCH 2013; (25): 89-110.
Ozaslan, I. N., Degirmenci, A., Karal, O. Tourism Demand Forecasting for Turkey by Using Adaboost Algorithm. In 2022 Innovations in Intelligent Systems and Applications Conference (ASYU) 2022: 1-5.
Perelli, O. El turismo en Madrid: el reto de un proyecto colectivo. Economistas 2005; 23(104): 326-334.
Popescu, A., Grefenstette, G., Moëllic, P. A. Mining tourist information from user-supplied collections. In Proceedings of the 18th ACM conference on Information and knowledge management 2009: 1713-1716.
Puspasari, S. Machine Learning for Exhibition Recommendation in a Museum’s Virtual Tour Application. International Journal of Advanced Computer Science and Applications 2022; 13(4).
Rahman, M. M., Zaki, Z. B. M., Alwi, N. H. B. M., Monirul Islam, M. (2019). A hybrid approach to improve recommendation system in E-tourism. In Emerging Technologies in Data Mining and Information Security: Proceedings of IEMIS 2018; 1: 787-797.
Riswanto, E., RobiIn, B. (2019, May). Mobile Recommendation System for Culinary Tourism Destination using KNN (K-nearest neighbor). In Journal of Physics: Conference Series 2019; 1201(1): 012039.
Roy, P., Setu, J. H., Binti, A. N., Koly, F. Y., Jahan, N. Tourist Spot Recognition Using Machine Learning Algorithms. In Intelligent Communication Technologies and Virtual Mobile Networks: Proceedings of ICICV 2022: 99-110.
Roselló, J.; Riera, A.; Sausó, A. The economic determinants of seasonal patterns. Annals of Tourism Research 2004; 31(3):697- 71.
Rubi, M. A., Bijoy, M. H. I., Chowdhury, S., Islam, M. K. Machine Learning Prediction of Consumer Travel Insurance Purchase Behavior. In 2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) 2022: 1-5.
Saito, N., Ogawa, T., Asamizu, S., Haseyama, M. A tourism category classification method based on estimation of reliable decision. In 2016 IEEE 5th Global Conference on Consumer Electronics 2016: 1-2
SECRETARIA GENERAL DE TURISMO. Plan del Turismo Español. Horizonte 2020 Ministerio de Industria, Comercio y Turismo 2007.
Shah, S., Thakkar, A., & Rami, S. A novel approach for making recommendation using skyline query based on user location and preference. Indian Journal of Science and Technology 2016; 9(30).
Shrestha, D., Wenan, T., Gaudel, B., Shrestha, D., Rajkarnikar, N., Jeong, S. R., Preliminary analysis and design of a customized tourism recommender system. In Evolutionary Computing and Mobile Sustainable Networks: Proceedings of ICECMSN 2021: 541-561.
Tapak, L., Abbasi, H., & Mirhashemi, H. Assessment of factors affecting tourism satisfaction using K-nearest neighborhood and random forest models. BMC research notes 2019; 12(1): 1-5.
Valiente, G. C., Forga, J. M. P., & Romero, A. B. (2016). Turismo en España, más allá del sol y la playa. Evolución reciente y cambios en los destinos de litoral hacia un turismo cultural. Boletín de La Asociación de Geógrafos Españoles 2016; 71: 431–454. https://doi.org/10.21138/bage.2289
Villada, F., Arroyave, D., y Villada, M. Pronóstico del Precio del Petróleo mediante Redes Neuronales Artificiales. Información Tecnológica 2014; 25: 145–154. Recuperado desde https://scielo.conicyt.cl/scielo.php?script=sci_arttextypid=S0718-07642014000300017ynrm=iso
WANHILL, S., Tackling seasonality: A technical note, International Journal of Tourism Management 1980; 1(4): 84-98.
Waitt, G., Social impacts of Sydney Olympics. Annals of Tourism Research 2003; 30 (1): 194-215.
Wang, S. Hate crime analysis based on artificial intelligence methods. In E3S Web of Conferences 2021; 251: 01062.
Wenan, T., Shrestha, D., Gaudel, B., Rajkarnikar, N., Jeong, S. R., analysis and evaluation of TripAdvisor data: a case of Pokhara, Nepal. In Intelligent Computing & Optimization: Proceedings of the 4th International Conference on Intelligent Computing and Optimization 2021 (ICO2021); 3: 738-750.
Yuensuk, T., Limpinan, P., Nuankaew, W. S., Nuankaew, P., Information Systems for Cultural Tourism Management Using Text Analytics and Data Mining Techniques. International Journal of Interactive Mobile Technologies 2022, 66(8).
Derechos de autor 2023 Jimmy Patricio Torres-Bastidas, Susana Magdalena Cobeña-Cobeña, Bertha Haydee Vásquez-Guevara, Jenny Fabiola Montes-Párraga, Tanya Negrete-Ontaneda, Fabricio Rolando Marcillo-Vera
Esta obra está bajo licencia internacional Creative Commons Reconocimiento-NoComercial-SinObrasDerivadas 4.0.
