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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.
COVID-19 Vaccines, Healthcare Policies and Stock Markets: Are There Winners and Losers?
(Taylor and Francis Group, 2023-05-24) Diaz, Ricardo F; Herrador Alcaide, Teresa Carmen; Sánchez-Robles Rute, Blanca
Purpose: This paper focuses on the stock market performance of a set of biopharmaceutical companies listed in the US stock exchange in response to news about the unfolding of the COVID pandemic and the development of COVID-19 vaccines. Methods: We analyze the short-term impact of some episodes by means of event analysis. We consider two categories of events: news related to the expansion of the pandemic and information about the development of COVID-19 vaccines. Results: We find that the impact during the first months of the pandemic news impacted the returns of the pharmaceutical firms, but the effect was not large, in general. The only exceptions are two small biotechnological firms, Moderna and Novavax, are exceptions since they registered large positive abnormal returns, which vanished over time. Encouraging announcements about the success of Phase III results had a positive impact the share prices of Pfizer, Moderna and Novavax. Our results also suggest that the emergency authorization provided by the US regulatory agency to the Pfizer vaccine was anticipated several days in advance and welcomed by the market. The announcement of a deal to supply vaccines between Moderna and the European Commission have generated large positive returns for this company. Conclusion: Our findings have policy implications. First, financial markets have supported and reinforced government strategies to fight the pandemic, characterized by funding of promising projects, building diversified vaccine portfolios and expediting approvals by regulatory agencies. Second, our findings suggest that not all drug developers have automatically obtained large profits from the design and manufacturing of COVID-19 vaccines, according to the behaviour of stock prices. These results cast doubts over attempts to discredit the efficacy of COVID-19 vaccines with the argument that they are primarily a means to obtain large and quick profits by pharmaceuticals, or than vaccination campaigns are driven by economic goals rather than by public health considerations.
Do trade and investment agreements promote foreign direct investment within Latin America? Evidence from a Structural Gravity Model
(MDPI, 2020-10-30) Bengoa, Marta; Sánchez-Robles Rute, Blanca; Shachmurove, Yochanan
Latin America has experienced a surge in foreign direct investment (FDI) in the last two decades, in parallel with the ratification of major regional trade agreements (RTAs) and bilateral investment treaties (BITs). This paper uses the latest developments in the structural gravity model theory to study if the co-existence of BITs and two major regional agreements, Mercosur and the Latin American Integration Association (ALADI), exerts enhancing or overlapping effects on FDI for eleven countries in Latin America over the period 1995–2018. The study is novel as it accounts for variations in the degree of investment protection across BITs within Latin America by computing a quality index of BITs. It also explores the nature of interactions (enhancing/overlapping effects) between RTAs and BITs. The findings reveal that belonging to a well-established regional trade agreement, such as Mercosur, is significantly more effective than BITs in fostering intra-regional FDI. Phasing-in effects are large and significant and there is evidence of enhancing effects. Results within the bloc are heterogeneous: BITs exert a positive, but small effect, for middle income countries. However, BITs are not effective in attracting FDI in the case of middle to low income countries, unless these countries ratify BITs with a high degree of investment protection.
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.
Efficiency and Super-Efficiency in the CRO Industry, 2012–2021: A Two-Stage Exploration
(Wiley, 2024-10-31) Díaz, Ricardo F.; Sánchez-Robles Rute, Blanca
This paper explores the productivity of contract research organizations (CROs) by computing and exploring efficiency and super-efficiency data envelopment analysis (SDEA) scores for a sample of companies over 2012–2021. Main findings suggest that CRO efficiency and super-efficiency is high and has increased more than 25% over 2012–2021. The top positions in the rankings according to efficiency are not limited to a few companies; in contrast, many firms in the sample are able to reach a top position in at least one concept of efficiency, suggesting the high degree of rivalry and competition in this industry. A second-stage preliminary analysis of variables associated with efficiency suggests that best performers implement a sound human capital policy, with controlled costs. Moreover, they also have a careful short-term cash-flow management, with brief collection periods. Big and small firms outperform the rest of the companies, suggesting the presence of increasing returns and niche advantages in some stages of the supply chain. Finally, results suggest that the COVID pandemic had an asymmetric impact on CROs, affecting positively only large CROs.
Efficiency of European oil companies: an empirical analysis
(Springer Nature, 2022-11-12) Sánchez-Robles Rute, Blanca; Herrador Alcaide, Teresa Carmen; Hernández Solís, Montserrat
We explore the efficiency in the oil industry employing a sample of around 300 companies operating in Europe over 2010–2019. We construct efficiency scores by means of DEA non-parametric techniques. Average efficiency in the sample is modest, 0.27, and decreasing over time. We examine the association of efficiency with economic and financial variables. Results suggest that size is closely associated to efficiency. Large (in the top 10th percentile of income) and very small firms are more efficient, ceteris paribus, whereas medium size and small firms exhibit lower levels of efficiency. Firms which have strived more to implement sustainable technologies and cut greenhouse emissions are more efficient too. Increases in employee costs and decreases in financial solvency jeopardize efficiency, which displays a positive correlation with economic activity and oil prices. As a robustness test, we have repeated the exercise by means of the Simar-Wilson methodology, which confirms our main results regarding efficiency levels and trends and correlations with other variables. Our findings suggest that an industry consolidation is foreseeable in the future.
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.
Non-parametric analysis of efficiency: An application to the pharmaceutical industry
(MDPI, 2020-09-07) F. Díaz, Ricardo; Sánchez-Robles Rute, Blanca
Increases in the cost of research, specialization and reductions in public expenditure in health are changing the economic environment for the pharmaceutical industry. Gains in productivity and efficiency are increasingly important in order for firms to succeed in this environment. We analyze empirically the performance of efficiency in the pharmaceutical industry over the period 2010–2018. We work with microdata from a large sample of European firms of different characteristics regarding size, main activity, country of origin and other idiosyncratic features. We compute efficiency scores for the firms in the sample on a yearly basis by means of non-parametric data envelopment analysis (DEA) techniques. Basic results show a moderate average level of efficiency for the firms which encompass the sample. Efficiency is higher for companies which engage in manufacturing and distribution than for firms focusing on research and development (R&D) activities. Large firms display higher levels of efficiency than medium-size and small firms. Our estimates point to a decreasing pattern of average efficiency over the years 2010–2018. Furthermore, we explore the potential correlation of efficiency with particular aspects of the firms’ performance. Profit margins and financial solvency are positively correlated with efficiency, whereas employee costs display a negative correlation. Institutional aspects of the countries of origin also influence efficiency levels.
Outsourcing of research and development and efficiency: a DEA non-parametric analysis of the contract research organisations industry
(Taylor & Francis, 2022-12-14) Díaz, Ricardo F.; Sánchez-Robles Rute, Blanca
Outsourcing to Contract Research Organisations (CROs) has become a widespread practice by bio-pharmaceutical firms seeking to reduce the costs associated with the development of new products. This study empirically analyses the efficiency of the CROs industry by looking at a sample of firms operating internationally over 2012–2020. We compute Data Envelopment Analysis (DEA) efficiency scores for each firm and year. The average bootstrap efficiency in the sample is 0.665, robust across specifications and increasing over 2012–2020. The best performing firms are PPD Australia, Centre Recherches Biologiques and Oy Medfiles. Our results suggest that very large and very small companies outperform the rest in terms of efficiency, which points to the co-existence of increasing returns to scale and niche competitive advantages in the industry.
Success factors of startups in research literature within the entrepreneurial ecosystem
(MDPI, 2022-08-12) Sevilla Bernardo, Javier; Sánchez-Robles Rute, Blanca; Herrador Alcaide, Teresa Carmen
What are the most important factors for the success of a startup? This study aims to shed light on this issue through the statistical analysis of a bibliographical sample of 60 recent articles. Through a detailed study of the selected literature, but from the perspective of business experience, we have identified the comparative relevance of those factors that recent research has highlighted as the main drivers of start-up success. Our analysis allows us to define a core of seven practical business success factors supported by the academic literature (Core-7 SF). This core makes it possible to identify the intersection between success in business practice and academic research. Our Core-7 SF shows that the most important variable to predict the success of a start-up is the Idea, followed by the CEO’s Leadership, the Business Model, the Marketing approach, and the Entrepreneurial Team. In addition, we found some differences between the geographic areas of affiliation of the authors, suggesting that cultural characteristics influence the weight given to the various reasons for success.
Successful entrepreneurship, higher education and society: from business practice to academia
(Nature, 2024-10-23) Sevilla Bernardo, Javier; Herrador Alcaide, Teresa Carmen; Sánchez-Robles Rute, Blanca
This research explores the coverage of success factors for entrepreneurship in higher education through the lens of the actual practice in prosperous company launchings. Accordingly, the paper analyzes how universities prioritize the importance of the success factors in entrepreneurship identified by business practitioners. Through the text analysis of a set of syllabi of courses on entrepreneurship we find that the success factors underlined in the teaching-learning process are the idea, business model, CEO, finance, and marketing. The exploration of a collection of recent papers on entrepreneurship education suggests that the factors emphasized by researchers are CEO, social impact, team, and formation. We find differences in the teaching-learning and research spheres regarding the ranking of success factors. Teaching-learning focuses on more traditional aspects of entrepreneurship and firm management, associated with key functional areas in companies. Research, in contrast, emphasizes social and psychological aspects and pays more attention to recent trends in management, like gender, diversity, and social impact. This suggests that research enjoys more flexibility and capacity for quick adaptation to new trends and ideas in society than teaching. Our findings imply that the process of teaching-learning in entrepreneurship must strive to remain closer to the reality of firms to prioritize the transmission and development of knowledge and skills more in accord with business practice.
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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