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This research paper aims to investigate the predictors and outcomes of immersive technology adoption in tourism.

PLS-SEM is used for data collected from tourists visiting the UAE and Egypt to examine predictors and consequences of adoption.

It is revealed that perceived ease of use, enjoyment, immersion, usefulness and attitude towards technology predict immersive technology adoption. It is also revealed that the adoption affects tourists’ perceived value and engagement, which, in turn, affects tourists’ satisfaction and loyalty.

The study has integrated a research model that combines both antecedents and consequences of immersive technology adoption where few empirical investigations were revealed to draw conclusions on this research area. Also, missing relations have been included and tested in the research model.

To understand differences in visitors' travel motivations, this study investigates the relations between personal values and travel motivations as well as the moderating effects of visit experience, age and gender on values–motivations relations among Australian visitors visiting Indonesia.

The multigroup confirmatory factor analysis (MGCFA) was performed using Analysis of Moment Structures (AMOS) to assess the constructs' validity across groups (potential vs repeat visitors; younger vs older visitors; male vs female visitors). A group model comparison thus was run in the multigroup analysis to test whether any differences in values–motivations relationships were significant across the groups.

This study shows that travel motivations are associated with values in a systematic way, and values–motivations relations can vary by age, gender and visit experience. Specifically, self-enhancement values are associated with escape-seeking motivation and conservation values are associated with assurance-seeking motivations. Whilst, there is no associations found between openness to change values and novelty-seeking motivations and between self-transcendence values and interaction-seeking motivations. Further, values influence travel motivations for potential but not repeat visitors and for younger but not older visitors.

Tailoring marketing strategies to align with visitors' personal values and travel motivations is crucial. Further, acknowledging the moderating influences of visit experience, gender and age in values–motivations relations enables destination marketers to create more effective and targeted approaches for diverse demographic groups in marketing, promotions and destination development.

This study for the first time provides a better explanation on how the travel motivations are formed in relation to values, age, gender and visit experience.

Building upon the cognition-affect-behavior (CAB) model and script theory, this research aims to enrich the existing literature on historic town tourism consumption by offering empirical evidence of how the cognitive and affective images of historic towns contributes to tourists' memorable tourism experiences (MTE) and revisit intention, while identifying the cognitive image dimensions that are relevant for evaluating historic towns.

An on-site survey was conducted with 486 local tourists who visited the historic towns in Chengdu. partial least squares-structural equation modeling (PLS-SEM) was utilized to assess both the measurement and structural models.

(1) Cognitive image emerged as a significant predictor of affective image; (2) Both cognitive image and affective image had a positive influence on MTE, in which cognitive image played a more dominant role in shaping MTE; (3) MTE was found to strongly predict revisit intention among tourists; (4) MTE and affective image mediated the relationship between cognitive image and revisit intention.

This research highlights the value of incorporating cognitive and affective constructs in predicting MTE, and the proposed integrated framework of the CAB model and script theory exhibits superior predictive power in understanding tourists' revisit intention.

This research provides empirical insights about how historic towns improve their marketing strategies as short day-trip destinations.

This research provides a novel insight on the applicability of an integrated model combining the CAB model and script theory in explaining the revisit behavior of local tourists within the context of historic towns.

This study aims to predict the effect of cultural distance, perceived risk and electronic word of mouth (eWOM) on higher education institutes' students' destination image. In addition, it examines the mediating role of destination image in relation to students' travel intentions.

An online survey was employed to collect data from 200 graduate and postgraduate students. The partial least squares was employed to analyse the hypothesised relationships.

The results of this study found support for the positive effect of cultural distance and eWOM on destination image. Additionally, the mediating effect of destination image was also supported.

This research confirms the vital role of destination image as an antecedent of students' future intention to visit the destination. Moreover, this study contributes to marketing theory by predicting the critical drivers of higher education students' destination image and discussing their applications in the education sector.

The COVID-19 pandemic has induced tourism destinations to reconsider organisational aspects related to health safety measures, as perceptions of health safety may have become particularly important for tourists. Using data from summer 2020, the period immediately after the outbreak of the pandemic, we investigate the factors that affected tourist perceptions of health safety.

Data come from a survey of tourist-card holders in Trentino, an Italian mountain destination. Through regressions, we assess the conditional correlation between health safety measure evaluations following a holiday and a set of covariates related to the features of the tourist area and the tourists themselves, as well as COVID-19 incidence in their province of residence in the months before the holiday.

Tourist-related features seem not to impact on perceived health safety, whereas some destination- and accommodation-related elements do. In particular, the number of tourist beds affects it negatively, and staying at a hotel does it in a positive way. COVID-19 incidence in one’s home province does not affect perceptions of health safety measures, which suggests a possible sample selection effect and/or the need for more fine-grained data.

This paper is one of the few on the immediate effects of the COVID-19 pandemic using data from a large sample of actual tourists. Our findings point out the importance of the intrinsic features of some places and accommodation in influencing perceptions of safety. We discuss implications for scholars and destination managers.

The purpose of this study is to explore from a place attachment (PA) theory perspective the extent to which and how, a fully immersive virtual reality (VR) experience enhances tourists’ attachment level on-site at a rural destination.

This study applied an exploratory mixed method approach. Respondents were tourists visiting the Lake District National Park who were asked to try a VR experience. In Study 1, interviews were conducted to explore new themes and to develop an enhanced PA framework in VR. Study 1 confirmed existing variables from the literature and highlighted new variables (themes) to be included in the new framework on how PA is formed. In Study 2, surveys were conducted, and the proposed framework analyzed using structural equation modelling (PLS-SEM). To fully understand how VR had an impact on enhancing PA, the moderating effect of tourists’ pre-existing PA was considered.

The findings revealed “Accessibility”, “Memories” and “Increased Place Knowledge” as new themes (variables) and confirmed that these and established variables “Aesthetics” and “Presence” enhance PA, leading to increased loyalty. Significant moderating effects of existing PA were found.

VR serves as a complementary and substitutional tool for tourism. Tailored VR experiences for diverse tourist needs may enhance destination marketing and competitiveness. For tourists with low PA, destinations should focus on promoting activities and highlights to enhance engagement and the experiential understanding of the destination. For tourists with high PA, VR experiences should focus on providing a comprehensive view of the destination and unveiling new places. In both cases, the VR experience leads to deeper engagement with the destination and an increase in PA.

Research on the impact of VR on tourists’ PA is limited. To address this gap, this study’s theoretical contribution lies in developing and testing a PA framework within a VR and tourism context. This also includes the validation of new measurement items developed in relation to the new themes.

This study intend to investigate a theoretical model looking at how particular tourist emotions, such as “joy,” “love,” and “positive surprise,” might predict their behavior by looking at how satisfied they are with their whole experience when visiting spas, and to examine the relationship of emotional experience, destination image, satisfaction and intention to revisit for spa tourism.

A sample of 345 individuals who traveled to Alleppey as domestic tourists participated in the research study. A non-probability (purposive) sampling method in this study. The structural model was analyzed using Structural Equation modeling (SEM), and the path coefficients were examined to test the hypotheses.

The results supported the hypotheses, indicating that specific emotions, image of the destination, and satisfaction significantly impacted tourists' intentions to revisit Alleppey as a spa tourism destination. This study demonstrated that “emotions of joy, love, and positive surprise” have a considerable influence on the image of the destination and satisfaction. The findings reveal a substantial correlation between satisfaction and behavioral intention (“Intention to revisit”). The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location.

The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location. This research offers vital information for developing, planning, and putting into practice tourism policies in the spa tourism sector. This article focuses on domestic travelers who travel to Alleppey, so the conclusions may not be relevant to research utilizing foreign tourists.

According to the literature study, and to the authors` knowledge, only limited number of studies that look at spa tourism from a wellness perspective. Additionally, Alleppey is used in the study as the study’s setting, providing insight into the visitor experiences of this expanding spa tourism business. This study gives understanding about how emotional experience predicts behavioral intentions.

The aim of this study was (1) to investigate the relationship between destination image (DI), destination personality (DP) and behavioral intention (BI) in the context of ski tourism and (2) especially the role of DP in the relationship between DI and BI among ski tourists.

We collected data using WJX.CN (N = 400) to test the hypothesized model. Confirmatory factor analysis (CFA) was used to examine the psychometric properties of the measurement model and partial least squares structural equation modeling (PLS-SEM) was used to test the hypotheses.

The results show that DI directly affects DP and partially affects BI, while DP directly affects ski tourists' BI. In addition, the indirect effect of DP between affective image and BI was significant, showing full mediation, and the indirect effect of DP between cognitive image and BI was significant, showing a partial mediation effect.

The findings enrich the ski tourism literature, contribute to the development of ski tourism in destination cities and the strategic marketing of ski resorts and provide recommendations for ski tourism researchers and marketers.

Given the growth of virtual reality (VR)-based tourism experiences in the past five years, this study aims to investigate the impact of VR-based interactions (ergonomics and embodiment) on memorable experiences and revisit intention mediated by cognitive and emotional responses.

This study has used an exploratory sequential mixed methodology research design to operationalise this research. Study 1 uses qualitative in-depth interviews to explore the proposed research questions, and Study 2 uses a 3 × 3 factorial experimental research design to test the proposed hypothetical model with 355 samples.

The results indicate that embodiment plays a more crucial role than VR ergonomics. Also, the cognitive response in the virtual tour indirectly generates a more memorable experience than the emotional response.

This research uses the theory of technological mediation as an overarching framework to conceptualise the research. Also, the research has applied the tenets of cognitive embodiment theory, metacognitive theory and other related theories to develop the arguments. Thus, the results of this research will extend the holistic understanding of these theories.

This research will guide VR tourism developers in understanding the requirements and expectations of tourists. It also serves as a manual to understand how tourists process the VR tour psychologically.

Very minimal focus was given to understanding the tourists’ interaction with technology in VR tours. The concept of ergonomics and embodiment investigated as an experimental variable is a novel approach in technology-based tourism research.

This research proposes to organise and distil this massive amount of data, making it easier to understand. Using data mining, machine learning techniques and visual approaches, researchers and managers can extract valuable insights (on guests' preferences) and convert them into strategic thinking based on exploration and predictive analysis. Consequently, this research aims to assist hotel managers in making informed decisions, thus improving the overall guest experience and increasing competitiveness.

This research employs natural language processing techniques, data visualisation proposals and machine learning methodologies to analyse unstructured guest service experience content. In particular, this research (1) applies data mining to evaluate the role and significance of critical terms and semantic structures in hotel assessments; (2) identifies salient tokens to depict guests' narratives based on term frequency and the information quantity they convey; and (3) tackles the challenge of managing extensive document repositories through automated identification of latent topics in reviews by using machine learning methods for semantic grouping and pattern visualisation.

This study’s findings (1) aim to identify critical features and topics that guests highlight during their hotel stays, (2) visually explore the relationships between these features and differences among diverse types of travellers through online hotel reviews and (3) determine predictive power. Their implications are crucial for the hospitality domain, as they provide real-time insights into guests' perceptions and business performance and are essential for making informed decisions and staying competitive.

This research seeks to minimise the cognitive processing costs of the enormous amount of content published by the user through a better organisation of hotel service reviews and their visualisation. Likewise, this research aims to propose a methodology and method available to tourism organisations to obtain truly useable knowledge in the design of the hotel offer and its value propositions.