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This study aims to explore the relationships amongst football fans’ travel motivations (FFTMs), their satisfaction (SAT), their perceived destination image (PDI) and their behavioural intentions (BIs). On the other hand, the mediating effects of SAT on the relationships among FFTMs, PDI and BIs are analyzed.

An approach based on a quantitative research method was used, and the data were gathered from Italian and British tourists who visited Istanbul, aiming to attend the Champions League Final match of Manchester City versus Inter Milan.

Based on 277 applicable surveys, Smart-PLS was conducted to test the conceptual model. The results indicated positive and meaningful relationships amongst FFTMs, SAT, PDI and Bis. Moreover, the results also demonstrated that the effect of FFTMs and PDI on BIs is mediated by SAT.

This research makes a contribution to the football tourism literature by first examining the theory of planned behaviour in conjunction with FFTMs, SAT, PDI and BIs. Furthermore, the findings of this study could offer valuable insights to assist tourism marketers in gaining a deeper understanding of FFTMs, BIs, SAT and PDI.

本研究探讨了足球迷的旅行动机、满意度 (SAT)、感知目的地形象 (PDI) 和旅游后行为(BI) 之间的关系。 另一方面, 分析了 SAT 对 FFTMs、PDI 和 BIs 之间关系的中介效应。

采用定量研究方法, 数据收集对象为前往伊斯坦布尔观看曼城对阵国际米兰的欧洲冠军联赛决赛的意大利和英国游客。

基于 277 份调查问卷, 采用Smart-PLS对概念模型进行了检验。 结果表明, 足球迷的旅行动机、满意度、目的地形象感知及旅游后行为之间存在积极且有意义的关系。此外, 结果还表明, FFTMs 和 PDI 对 BIs 的影响是由 SAT 介导的。

这项研究首先将计划行为理论与 FFTMs、SAT、PDI 和 BIs 结合起来进行检验, 为足球旅游文献做出了贡献。

Este estudio explora las relaciones entre las motivaciones de viaje de los aficionados al fútbol (FFTM), su satisfacción (SAT), su imagen percibida del destino (PDI) y sus intenciones de comportamiento (BI). Por otra parte, se analizan los efectos mediadores de la SAT en las relaciones entre las FFTM, la PDI y las BI.

Se adoptó un enfoque de investigación cuantitativa y se recopilaron datos de turistas italianos y británicos que visitaron Estambul con el objetivo de asistir al partido de la final de la Liga de Campeones entre el Manchester City y el Inter de Milán.

Sobre la base de 277 encuestas aplicables, se llevó a cabo un PLS-Smart para probar el modelo conceptual. Los resultados indicaron relaciones positivas y significativas entre los FFTM, el SAT, el PDI y los BI. Además, los resultados también demostraron que el efecto de los FFTM y el PDI sobre las BI está mediado por el SAT.

Esta investigación contribuye a la literatura sobre el turismo futbolístico al examinar por primera vez la Teoría del Comportamiento Planificado en conjunción con los FFTM, el SAT, el PDI y las BI. Además, los resultados de este estudio podrían ofrecer ideas valiosas para ayudar a los profesionales del marketing turístico a comprender mejor los FFTM, los BI, el SAT y el PDI.

This study aims to develop and test a model of the wellness spa hotel experience. The model proposes that experiencescape dimensions (sensory, functional, social, natural and hospitality culture) are important antecedents of guest satisfaction with a wellness spa hotel experience. The study also tests the relationship between satisfaction, wellness-induced well-being, experience co-creation and word-of-mouth (WOM).

Data was collected in the post-pandemic period, during September–November 2022 from 567 domestic guests who had stayed in a wellness spa hotel in Serbia.

Besides the social experience scape dimension, all other dimensions of experiencescape (sensory, functional, natural and hospitality culture) were found to be positive drivers of guest satisfaction with a wellness spa hotel experience. The relationship between satisfaction, wellness-induced well-being, experience co-creation and WOM was also supported.

This study emphasises the role of experiencescape in concurrence with the antecedents in cultivating guest satisfaction with a wellness spa hotel experience, which further influences wellness-induced well-being, experience co-creation and WOM.

The purpose of this study is to use structural equation modeling to examine the interaction between the variables of corporate image, credibility, trust and satisfaction in the context of a virtual sporting event. The aim is to determine whether these variables have significant relationships with each other and which of them has the greatest influence on the prediction of participants' satisfaction.

A structured questionnaire was used, based on previously validated scales. The survey was administered using the LimeSurvey platform. The sample consisted of a total of 588 participants of the Medellín virtual marathon.

The results of the study reveal significant findings regarding the relationships between the variables of corporate image, credibility, trust, and satisfaction in virtual sporting events. In particular, it is highlighted that trust emerges as the most influential factor in participants' satisfaction, which offers an insightful understanding of the importance of this variable in the user experience in virtual sporting events.

This study emphasizes the importance of brand analysis in the sports environment, stressing that the actions undertaken by managers should highlight both the corporate image and the connections with users, given their fundamental role in customer satisfaction. Likewise, the study of these variables within the sports context provides new knowledge and fills existing gaps within the academy. Limitations include the sample and the lack of consideration of all brand variables.

The need to cultivate a strong and well-managed image to build trust with participants is emphasized for organizers of virtual sporting events. It is crucial to work on establishing long-term credibility, especially in the relatively new context of virtual racing. Maintaining, and building the virtual career offering is essential to strengthening relationships, demonstrating a robust corporate image. In addition, since trust and credibility have a significant impact on participant satisfaction in this type of event, managers must communicate the assurance that virtual careers offer an experience free of uncertainty and risk, which is particularly attractive to a new customer base interested in this format.

This article presents an original contribution by investigating the relationships between corporate image, credibility, trust, and satisfaction in the context of virtual sporting events. It employs a structural equation model to assess the significance and predictive capacity of these variables. Notably, the study identifies trust as the most influential factor in predicting participant satisfaction. These findings offer valuable insights into the relative importance of brand variables in shaping user satisfaction within the virtual sporting event domain. By shedding light on these dynamics, the research aids event managers in making informed resource allocation decisions, contributing to a nuanced understanding of brand impact in this context.

Recommendation systems are a fundamental tool for hotels to adopt a differentiating competitive strategy. The main purpose of this work is to use machine learning techniques to treat imbalanced data sets, not applied until now in the tourism field. These techniques have allowed the authors to analyse the influence of imbalance data on hotel recommendation models and how this phenomenon affects client dissatisfaction.

An opinion survey was conducted among hotel customers of different categories in 120 different countries. A total of 135.102 surveys were collected over eleven quarters. A longitudinal design was conducted during this period. A binary logistic model was applied using the function generalized lineal model (GLM).

Through the analysis of a representative amount of data, the authors empirically demonstrate that the imbalance phenomenon is systematically present in hotel recommendation surveys. In addition, the authors show that the imbalance exists independently of the period in which the survey is done, which means that it is intrinsic to recommendation surveys on this topic. The authors demonstrate the improvement of recommendation systems highlighting the presence of imbalance data and consequences for marketing strategies.

The main contribution of the current work is to apply to the tourism sector the framework for imbalanced data, typically used in the machine learning, improving predictive models.