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In the competitive realm of destination branding, understanding the factors that lead tourists to develop a deep emotional connection with a destination’s brand is essential. At the heart of this emotional bond lies destination brand love – an exceptionally profound sentiment transcending mere satisfaction or preference. This concept has recently garnered attention from both tourism academia and industry practice. However, there remains a void in exploring the factors and mechanisms that pave the way for tourists to develop deep affection for a destination’s brand. This study examines the influences of self-congruence and destination immersion on destination brand love. In addition, the linkages from the four facets of self-congruence to destination brand love via the mediating role of destination brand immersion are also scrutinized.

With data collected from 421 tourists in Vietnam, the partial least squares structural equation modeling (PLS-SEM) approach was applied to test the research model and hypotheses.

The results reveal that (1) ideal and ideal social self-congruence impact destination brand love, (2) all four facets of self-congruence impact destination brand immersion and (3) there is an indirect effect of the four facets of self-congruence on destination brand love, mediated by destination brand immersion.

The study’s findings provide evidence that destination characteristics must be symbolic of the destination brand and consistent with its image among tourists, which is essential in understanding the complex behavior of tourists. Indeed, the results indicate that facets of self-congruence significantly influence both destination brand immersion and destination brand love. Therefore, destination marketers should develop marketing strategies that emphasize personal relevance to the tourist destination to increase their sympathy and love for the destination.

Adapting self-congruence theory and the psychology of flow theory, this study presents a model that elucidates both the direct and indirect relationships among the four facets of self-congruence: destination brand immersion and destination brand love based on the aspects of congruence between tourists and destinations. From this, it helps to explore the factors and mechanisms that pave the way for tourists to develop deep affection for a destination’s brand.

Mobile apps usually have a short lifespan, and this prevents the majority from surviving long enough to generate revenue for their developers. To address this issue, this study aims to recognize the role of engagement and immersion and develops a cognitive-affective theoretical framework to associate these factors with the lifespan of an app. Moreover, the authors focus on gaming apps because of their dominance on mobile platforms, and because a few of them become lucrative while the majority perish within a few weeks.

This study uses a longitudinal survey-based approach to collect data on one of the popular gaming apps (Pokémon Go), which received international attention. The design focuses on identifying factors that extend the lifespan of the app and affects users’ decision to continue or stop using the app over time. The authors use the survival analysis and structural equation modeling to analyze the theoretical framework.

The authors find the centrality of the users’ experience of immersion to extend the mobile app lifespan. Engagement influences immersion and immersion predicts users’ decision to continue or stop using the app. Users’ experience of immersion increases the probability of the apps’ survival by 12%.

To the best of the authors’ knowledge, this is the only study that proposes a theoretical framework, meticulously investigates the factors that can lead to survival of a mobile app and uses longitudinal data for the empirical analysis.

In order to encourage customers to try experience virtual tourism, researchers and practitioners pay more attention on how to improve customers' perception of authenticity.

Using the theory of cross-sensory compensation, through 4 experiments, this study examines the impact of social interaction and cross-sensory strategies on the relationship between virtual reality (VR) and improving customers' perception of authenticity and customer experience.

Through experimental research, this paper finds that (1) VR immersion has a significant positive impact on perception of authenticity, which in turn acts on customers' virtual tourism experience. (2) In addition, social interaction strengthens the relationship between VR immersion and customers' perception of authenticity. (3) The cross-sensory compensation has a positive effect on VR immersion to enhance customers' perception of authenticity.

The research conclusion provides a direction for further discussion on how to improve customers' perception of authenticity and provides theoretical guidance and reference for the virtual tourism industry.

Augmented reality (AR) is transforming the business and interactive marketing landscape. This research aims to investigate consumers' degree of involvement and if a feeling of immersion and presence influences AR shopping satisfaction, comparing high- and low-immersive AR experiences.

This paper uses a quantitative approach. Two studies were carried out: a high-immersive AR experiment with 173 participants and a low-immersive AR experience with 222 participants. Findings were analyzed using partial least square structural equation modeling with SmartPLS.

Results indicate the antecedents of immersion and presence differ when it comes to different immersive AR levels. In a high-immersive AR experience, flow, information seeking and novelty are attributes related to immersion, while enjoyment and personalization are related to presence. Contrastingly, in a low-immersive AR experience, only flow is related to immersion, while information seeking, novelty and personalization are related to presence. These results highlight the role of immersion and presence as mediators for AR shopping satisfaction experience.

This study's originality lies in the use of a rival model for analysis. Findings suggest a contingent perspective of AR experience, depending on high- or low-immersion experience, so companies must pay attention for how to measure AR experiences to increase involvement and satisfaction.

Luxury as a construct warrants an assessment of entities promoting themselves as luxurious offerings. Therefore, this study attempts to evaluate the experiencescapes of luxury trains operating in developed and developing countries to assess the presence of luxury values in the elements affecting tourists' experiences and immersion.

Two different types of luxury trains were selected from across developed and developing countries for a holistic assessment of the experiencescapes. Through netnography and hermeneutic interpretation, this study analyzes 218 experiential descriptions on Tripadvisor from luxury trains of Australia, UK, Peru and India.

Although luxury trains in both the regions entailed financial, functional, social and individual value, they struggled to offer these values in conjunction. While the positioning of luxury trains in developing countries under the “inaccessible luxury” segment is exaggerated, developed countries were also found to struggle with customer service and management.

By emphasizing on areas within the control of the service providers, short-haul luxury trains can be a better fit in developing countries. Better usability testing and employee training should be undertaken to improve the functional values of luxury in long-haul luxury trains of developed countries.

This article not only assesses the validity of luxury trains' positioning but also provides new insights into the nature of the tourist immersion process. Having extensively discussed experiences in the backdrop of luxury, it contributes to the progression of literature on luxury trains, experiencescapes and immersion.

Brand storytelling is an effective marketing tool. However, when choosing whether to tell more or tell less, it remains unclear which of these two narrative styles is most effective. This study aims to examine whether blank-leaving(less) leads to favourable brand attitudes and compares its effects on consumers’ story immersion, to non-blank-leaving(more).

Two experiments were conducted to test the hypotheses. In Study 1, a single-factorial design was used with 252 participants assigned at random to one of two narrative conditions: blank-leaving or non-blank-leaving. Study 2 replicated Study 1 and investigated the moderating role of implicit mindsets.

The results show that a blank-leaving narrative style increases favourable brand attitudes. Consumers present deeper immersion in the brand story that uses blank-leaving, as compared to non-blank-leaving, leading to a more favourable brand attitude. Furthermore, this effect is stronger for individuals with growth mindsets.

Telling the brand story using a blank-leaving narrative style is more effective in catching consumers’ attention than non-blank-leaving. In particular, a blank-leaving narrative is a good approach for targeting consumers who have a growth mindset.

To the best of the authors’ knowledge, this research is the first to investigate and compare the effects of blank-leaving and non-blank-leaving narrative styles on brand attitudes in the context of storytelling marketing.

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R²) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

The purpose of the paper is to propose a shift from the ideal of immersion to a practice of “committed localism” in the ethnographic study of relational work in the post-bureaucratic and service-based economy.

The paper is based on ethnographic fieldwork following management consultancy projects in a hospital and a manufacturing company in Denmark. The approach was predicated on committed attention to the everyday of consultancy work activities and associated relational dynamics. This involved being present at the client sites, observing and listening in concrete situations of interaction and engaging in conversations with the multiple actors involved, both external consultants and members of client organisations.

The paper shows how “committed localism” was practiced in the ethnographic study of management consultancy as it is relationally accomplished in and through concrete situations of interaction between consultants and different actors in client organizations and the associated meaning production of the involved actors.

The paper develops the notion of “committed localism”, originally introduced by George Marcus, into a methodological concept to challenge the conventional ideal of immersion as the hallmark of “proper” ethnography. Such a shift is particularly pertinent for the ethnographic study of relational processes involving multiple actors occupying different positions in the temporary social spaces of contemporary workplaces.

The purpose of this paper is to investigate how gamification in advertising affects the effectiveness of advertising on social media.

Drawing from the gamification literature, immersion, achievement and social interaction features were identified as features, and advertising effectiveness factors were brand attention, brand liking and recall. A questionnaire was used for collecting data, and a structural equation modeling approach was applied to examine the model.

The results indicated that immersion, achievement and social interaction features affect advertising effectiveness. Furthermore, advertising effectiveness factors had a significant effect on purchase intentions.

The study contributes to the combination of gamification in advertising by offering characteristics for gamification that can enhance advertising effectiveness through brand attention, liking and recall. Finally, it provides managerial guidance on how they can use gamification in their advertising process.

Building on the “needs–affordances–features” framework, the authors explored how users are motivated by their needs to actualize the feature-enabled affordances and engage in the metaverse.

The data were collected through semi-structured and in-depth interviews with 35 participants. The authors applied thematic analysis to summarize the key features and affordances, supplemented by frequency analysis to explore the significance of the features. Sentiment analysis was employed to explicate the relationship between user affordance sentiments and engagement.

The key features of the metaverse portal components—hardware, software and content—afford user behaviors. The features of mechanics and physics engines are important for user engagement in the metaverse. The affordances are related to needs satisfaction and user engagement. Mental immersion was frequently mentioned by the participants, implying that it is significant to afford mental immersion in the metaverse.

The findings of the study provide a rich understanding for practitioners in the metaverse on how to use the features to afford user behaviors and engage them. The authors identified the key elements of user engagement that can be used to guide metaverse game designers.

This study provides a rich and systematic understanding of features, affordances, needs satisfaction and engagement in the metaverse. Going beyond a fragmented view, the findings conclude a research framework that weaves features, affordances, needs and engagement together.