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Cambios en el comportamiento turístico tras la COVID-19: hacia un nuevo perfil del turista y del viaje de ocio en España
(Asociación Española de Profesores Universitarios de Matemáticas para la Economía y la Empresa (ASEPUMA), 2023) Mendieta Aragón, Adrián
El efecto disruptivo de la COVID-19 en la industria turística ha generado nuevas necesidades y motivaciones en los viajes turísticos. Este estudio evalúa los efectos de la pandemia en el perfil y características de los viajes de ocio realizados por los residentes en España. A partir de los microdatos de la Encuesta de Turismo de Residentes del INE, se utiliza el modelo de regresión logística para examinar la relación entre el perfil socioeconómico y demográfico del viajero y las características del viaje con el tipo de destino (internacional o doméstico) para los años 2019-2021. La comparación de los resultados estimados en cada año revela que la motivación del viaje al extranjero difiere significativamente entre los diferentes perfiles de turistas, excepto por razón de género. Los resultados también constatan que las características del viaje fueron Significativamente diferentes antes y después de la pandemia. Además, se confirma un cambio significativo en las preferencias del tipo de alojamiento y transporte, junto con una reducción de las diferencias de duración de los viajes a destinos nacionales e internacionales.
Consumer behaviour in e-Tourism: Exploring new applications of machine learning in tourism studies
(Universidad de Alicante, 2023-07-17) Mendieta Aragón, Adrián; Garín Muñoz, María Teresa
Los mercados digitales han alterado la forma en que interactúan los agentes económicos y han cambiado el comportamiento de los turistas. Además, la pandemia de COVID-19 ha demostrado que es necesario monitorear la evolución del comportamiento del consumidor digital y los factores que influyen en él, ya que son elementos dinámicos que evolucionan en el tiempo. Este artículo analiza las desigualdades digitales y valida los principales factores que influyen en los turistas para reservar servicios turísticos en línea. Esta investigación utiliza un conjunto de microdatos con 69.752 y 23.779 observaciones para analizar el modo de reserva de los servicios de alojamiento y transporte, respectivamente, obtenidos de la Encuesta de Turismo de Residentes del Instituto Nacional de Estadística durante el periodo 2016-2021. El artículo confirma variaciones en el perfil del consumidor online y en las características del viaje. Uno de los hallazgos más relevantes es la reducción de la brecha generacional en la contratación online de servicios turísticos. Sin embargo, subsisten desigualdades digitales, como las desigualdades regionales y otras basadas en el nivel de estudios y los ingresos de los turistas. También se destaca que diferentes tipos de viajes, dependiendo del destino, el tipo de alojamiento o transporte, tienen una propensión diferente a reservarse a través de canales de compra digitales. La accesibilidad a las fuentes de big data y los avances recientes en los modelos de aprendizaje automático también han hecho evolucionar las metodologías para analizar el comportamiento del consumidor digital y deben incorporarse a los estudios de turismo. Este estudio compara el rendimiento predictivo de diferentes metodologías en el contexto del turismo electrónico. En particular, evaluamos la potencial capacidad predictiva que podría obtenerse usando técnicas de aprendizaje automático para explicar el comportamiento del consumidor en e-Tourism y lo usamos como punto de referencia para compararlo con los resultados obtenidos usando métodos estadísticos tradicionales. Las métricas de evaluación predictivas seleccionadas muestran que el modelo estadístico de regresión logística mejora la capacidad predictiva de la red neuronal Multilayer Perceptron y presenta valores muy cercanos la máxima capacidad predictiva alcanzada por el algoritmo Random Forest.
Drones in Hospitality and Tourism: A literature review and research agenda
(Emerald, 2023-05-15) Sevilla Sevilla, Claudia; Mendieta Aragón, Adrián; Ruiz Gómez, Luis Manuel
Drones have become an important element within hospitality and tourism. The main objective of this study is to identify the corpus of knowledge and create a research agenda that establishes appropriate guidelines for future study of drone application in hospitality and tourism. This work has undertaken utilising a mixed methods approach that combines quantitative and qualitative research and includes a review of the literature related to the study of drone use in hospitality and tourism. The mixed methods review identified gaps in the research, potential areas of study to enhance the scientific literature, and potential uses of drones in tourism and hospitality for researchers, consumers, and industry professionals. This study makes an original contribution by establishing an integrated framework, which lead to a synthesis of the research corpus and provided a holistic conceptualisation of the relationship between tourism and drones. In addition, the research agenda proposed will help boost and consolidate this emerging field of research.
Effects of COVID-19 on the tourism sector in the European Union: Economic analysis for the case of Spain
(AUDESCO, Asociación Universitaria Europea de Estudios Comunitarios, 2023) Mendieta Aragón, Adrián
Esta investigación constata el desigual impacto de la COVID-19 sobre las economías del principal destino turístico del mundo, Europa. En concreto se estudia en profundidad el caso de España, que experimentó la mayor caída del PIB de la Unión Europea. Esta investigación tiene como objetivo analizar el efecto de la pandemia sobre los indicadores macroeconómicos, así como el comportamiento de los turistas residentes y los extranjeros que visitan España. Los resultados destacan la importancia del turismo doméstico en la recuperación del sector y los nuevos hábitos turísticos de los consumidores, como el aumento de las reservas “last-minute” y la mayor duración de los viajes.
Evolution of the internet gender gaps in Spain and effects of the Covid-19 pandemic
(ELSEVIER, 2022) Garín Muñoz, María Teresa; Pérez Amaral, Teodosio; Valarezo Unda, Angel; https://orcid.org/0000-0001-8315-8134
There is a widely accepted belief in new technologies that the digital divide in using a service will disappear as the service reaches an advanced level of maturity. The work presented here shows that this idea is debatable. Data from Spain, a country where daily internet users are 75.9 percent of the population, prove that the gender gap still exists. The paper explores if this gap can be entirely explained by the socioeconomic differences between men and women. We build a micro panel model and incorporate a set of socioeconomic variables (age, education, income, employment status, digital skills, and resident population) that allow us to isolate the effects of gender on the decision to become a daily Internet user. The results conclude that the Internet gap is a phenomenon with a specific gender component. Other things being equal a woman negatively affects the probability of using the Internet. Applying a similar model to 15 Internet services, we obtain that gender is always significant to explain the likelihood of being a user of each service. However, in some services (7 out of 15), the effect is favorable to women, and for other services (8), the gender effect favors men. The work concludes by analyzing the impact of the first wave of the Covid-19 pandemic on the use of Internet services, paying particular attention to its possible implications for the gender gap.
Foreign Tourism in Andalusia: A Dynamic Panel Data Analysis
(Taichung: Asia University, Taiwan, 2020-07) Mendieta Aragón, Adrián; Garín Muñoz, María Teresa
This paper studies the main determinants of the inbound international tourism in Andalusia and quantify its incidence. Based on the classical theoretical framework for tourism demand, we incorporate dynamics into the model by adding the lagged dependent variable as an explanatory variable, along with the per capita income of the tourist's country of origin, the relative prices between the origin and destination countries and the cost of travel. The empirical model is applied to a panel data set consisting of 21 countries of origin of the tourists for the period 2008–2018. Data were collected from the Hotel Occupancy Survey (HOS), published by the National Statistics Institute of Spain (INE). The results have been obtained using the GMM-DIFF estimator of Arellano and Bond. The parameters estimated reflect a high level of consumer loyalty and the importance of the word-of-mouth effect. Moreover, the income elasticity indicates that the demand for tourism in Andalusia may be considered as a luxury good. Prices have a negative relationship with tourism demand. The cost of travel, which has a negative effect, is statistically significant to explain the number of tourists' arrivals and, however, it is not significant for the overnight stays model.
Tackling the challenge of peer learning in hybrid and online universities
(Springer, 2022-10-20) Mendieta Aragón, Adrián; Arguedas Sanz, Raquel; Ruiz Gómez, Luis Manuel; Navío Marco, Julio
Peer learning is not fully developed or researched in online and hybrid higher education. This research analyses a peer learning experience in the asynchronous part of hybrid teaching, in one of the largest blended universities in Europe, promoting students to act as teachers of their peers, by preparing digital content (videos) for the course. This article studies whether there are behaviour patterns and different perceptions associated between students who act as teachers, and those who only act as students. The results indicate, among other findings, that students demand this type of activities, and value them very positively. Specifically, the “teachers” consider that this activity increases their motivation for the subject and their performance; they also consider that it significantly improves their creativity and communication skills, and they would definitely participate in the project again. The assessment of the students who merely view the materials is also very positive, and they prefer a learning method through classmate videos than the traditional learning method with printed materials. The research is also a boost to finding ways to promote learning among equals in non-classroom teaching in digital environments
Tourism usage of digital collaborative economy platforms in Europe: Situation, behaviours, and implications for the digital policies
(ELSEVIER, 2024) Mendieta Aragón, Adrián; Rodríguez Fernández, Laura; Navío Marco, Julio
This study analyses how the intensity of the use of digital sharing economy platforms has evolved in the European Union in recent years, including during the pandemic, and whether there are differences between European regions. In the digital field, work has begun on regulations and public policies that coexist with different policies in the regions and municipalities. Using spatial econometric techniques, this study provides a comparative analysis of space and time that identifies regional inequalities in terms of the intensity of demand for accommodations offered on digital sharing economy platforms. In particular, different clusters of high-intensity collaborative tourism were detected, and spatial spillover effects and interdependencies between European regions in collaborative tourism were recognised, identifying a positive spatial autocorrelation in the intensity rate of collaborative tourism. The effect of tourist destination saturation on the use of accommodation on these platforms was also observed. Several digital public policy implications were discussed, promoting regulatory coordination at the interregional and pan-European levels to avoid inequalities and imbalances across Europe.
Twitter's capacity to forecast tourism demand: the case of way of Saint James
(Emerald Publishing, 2024-04-25) Mendieta Aragón, Adrián; Navío Marco, Julio; Garín Muñoz, María Teresa
Purpose – Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination. Design/methodology/approach – This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables. Findings – The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism. Originality/value – This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

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