Search results

The purpose of this paper is to explore how the continued interest in the concept of “miniaturism” has seen the micropub develop into the new format of the microbar and examines the drivers of this trend. It then reflects on the possible implications of the rise of the microbar concept on the future of the urban tourism destination landscape.

This is a conceptual paper that is built on the natural curiosity of future studies to use an understanding of the present to predict what will happen next and what the implications of those developments will be.

The paper provides a clear definition of the microbar and identifies four distinctive drivers behind its conception, linked to changes in consumer behaviour. These cover the rise of the micro-break, the need for responsible urban regeneration, consumers desire for immediate and unique experiences and increasingly diverse populations. The paper predicts that these trends will drive an increase in microbars leading to greater tourist mobility in the urban tourism destination, more fragmentation and heterogeneity of products and services as well as an intensification in the need for authentic experiences and opportunity driven development giving rise to a hybrid form of guerrilla hospitality. Ultimately the authors predict that the venue will become more important than the specific location when consumers view the landscape of the urban tourism destination.

The focus of previous academic research has been on the historic development of the micropub and its impact on regeneration and communities, but very little literature has examined the rise of the microbar and the potential implications for the urban tourism destination.

The literature on the factors generating loyalty towards tourism destinations has seldom focussed its attention on relationship marketing, which has left a gap in the understanding of destination loyalty. This paper aims to examine the influence of relationship quality on rural destination loyalty, approaching this through the variables of trust, attachment and satisfaction.

This study used a quantitative methodology based on an on line survey conducted in Spain. The sample consisted of 464 tourists who participate in rural tourism. The analysis of the proposed model was carried out based on the partial least squares method.

The results confirm that the model has a substantial to moderate explanatory capacity for overall satisfaction and loyalty, in which overall satisfaction acts as a mediator between the variables that make up relationship quality in reference to loyalty.

The main limitations of this research arise from the scarcity of works which aim to understand relationship quality in tourism destinations. To broaden results, it should be applied in other tourism destinations, products, services and experiences.

Destination managers should give relationships a special role in their tourism development programmes in rural tourism contexts.

Rural tourism destinations and companies are generally small-sized organisations that need managerial tools. These can benefit from developing sustainable relationships.

The significant role played by relationship quality regarding destination loyalty is studied in detail in this model.

La literatura sobre los factores que generan lealtad a los destinos turísticos poco ha centrado su atención en el marketing relacional, lo que ha dejado un vacío en la comprensión de la lealtad al destino. Este artículo examina la influencia de la calidad relacional en la lealtad a los destinos rurales, a través de las variables confianza, apego y satisfacción.

Este estudio usa una metodología cuantitativa basada en una encuesta on line realizada en España. La muestra estaba formada por 464 turistas que practican turismo rural. El análisis del modelo propuesto fue llevado a cabo con el método partial least squares.

Los resultados confirman que el modelo tiene una capacidad explicativa sustancial-moderada para la satisfacción global y la lealtad, en la que la satisfacción global actúa como mediadora entre las variables que conforman la calidad relacional y la lealtad.

La principal limitación de esta investigación surge de la escasez de trabajos cuyo objetivo se centra en la comprensión de la calidad relacional en los destinos turísticos. Para ampliar los resultados, habría de aplicarse en otros destinos, productos, servicios y experiencias turísticas.

Los gestores de destinos deberían otorgar un papel especial a las relaciones en sus programas de desarrollo turístico en el medio rural.

Los destinos y empresas de turismo rural son por lo general organizaciones de pequeñas dimensiones que necesitan herramientas para la gestión. Ellas pueden beneficiarse del desarrollo de relaciones sostenibles.

El papel significativo que juega la calidad relacional con respecto a la lealtad al destino, estudiado en detalle en este modelo.

Marketing relacional, Calidad relacional, Lealtad, Destinos rurales, Partial least squares (PLS)

Artículo de investigación

The tourist industry has to adopt a big data-driven foresight approach to enhance decision-making in a post-COVID international landscape still marked by significant uncertainty and in which some megatrends have the potential to reshape society in the next decades. This paper, considering the opportunity offered by the application of the quantitative analysis on internet new data sources, proposes a prediction method using Google Trends data based on an estimated transfer function model.

The paper uses the time-series methods to model and predict Google Trends data. A transfer function model is used to transform the prediction of Google Trends data into predictions of tourist arrivals. It predicts the United States tourism demand in Italy.

The results highlight the potential expressed by the use of big data-driven foresight approach. Applying a transfer function model on internet search data, timely forecasts of tourism flows are obtained. The two scenarios emerged can be used in tourism stakeholders’ decision-making process. In a future perspective, the methodological path could be applied to other tourism origin markets, to other internet search engine or other socioeconomic and environmental contexts.

The study raises awareness of foresight literacy in the tourism sector. Secondly, it complements the research on tourism demand forecasting by evaluating the performance of quantitative forecasting techniques on new data sources. Thirdly, it is the first paper that makes the United States arrival predictions in Italy. Finally, the findings provide immediate valuable information to tourism stakeholders that could be used to make decisions.