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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.

Tourists’ resource integration both offers opportunities and presents challenges to tourism service providers. Focussing on the tour guide perspective, the purpose of this paper is to explore how tour guides experience knowledge/information-based asymmetry in encounters with tourists and identifies the roles and coping strategies used by guides to facilitate service co-production.

Critical incident technique is used in qualitative interviews with 47 tour guides in Scotland, broadly representative of the Scottish tour guiding context. 107 critical incidents were analysed, with an average of 2.32 incidents per interview. Narrative analysis of the incidents was performed inductively in four iterative steps using QSR NVivo.

Three resource asymmetry incident categories are identified: probing – Guide-Oracle is questioned by inquiring tourists and copes through diverting, evasion, and follow-up strategies; learning – Guide-Magpie learns from expert tourists through acknowledging and co-delivery; and negotiation – Guide-Diplomat with greater knowledge helps misguided tourists save face through appeasing, following the official line and tactfully correcting.

The paper contributes to service co-production research in tourism by theorising about contexts where knowledge/information asymmetry exists between tour guides and tourists, particularly where fluid power relations between guides and knowledgeable tourists occur or where misguided tourists co-produce the service by prioritising own meanings. Findings highlight the importance of soft skills and other non-content capabilities of guides, and suggestions are offered for effective training and resource sharing/ learning initiatives for tour guiding services.

游客资源整合为旅游服务提供商提供了机遇, 同时也带来了挑战。本文以导游视角为重点, 探讨了导游在与游客接触中如何体验知识/信息不对称, 并识别了导游用于促进服务共同生产的角色和应对策略。

本研究采用关键事件技术（CIT）进行质性访谈, 对象为苏格兰的47名导游, 广泛代表苏格兰导游环境。分析了107个关键事件, 每次访谈平均2.32个事件。对事件的叙述分析在QSR NVivo中通过四个迭代步骤进行归纳性分析。

确定了三个资源不对称的事件类别：1）探询 - 导游-神谕被询问, 通过转移、回避和后续策略来应对询问的游客; 2）学习 - 导游-喜鹊通过承认和共同交付从专业游客中学到经验; 3）协商 - 导游-外交官以更多知识帮助误导的游客保全体面, 通过安抚、追随官方路线和巧妙纠正来应对。

本文通过理论化导游和游客之间存在知识/信息不对称的情境, 特别是在导游和知识丰富的游客之间存在流动权力关系的情况下, 或者误导的游客通过优先考虑自己的意义来共同生产服务的情境, 为旅游服务的共同生产研究做出了贡献。研究结果强调了导游的软技能和其他非内容能力的重要性, 并提出了关于为导游服务提供有效培训和资源共享/学习倡议的建议。

La integración de recursos de los turistas ofrece oportunidades y presenta desafíos para los proveedores de servicios turísticos. Centrándose en la perspectiva de los guías turísticos, este artículo explora cómo los guías turísticos experimentan una asimetría basada en conocimiento/información en encuentros con turistas, e identifica los roles y estrategias de afrontamiento utilizados por los guías para facilitar la coproducción de servicios.

La técnica de incidentes críticos (CIT) se utiliza en entrevistas cualitativas con 47 guías turísticos en Escocia, ampliamente representativos del contexto de los guías turísticos escoceses. Se analizaron 107 incidentes críticos, con una media de 2,32 incidentes por entrevista. El análisis narrativo de los incidentes se realizó de forma inductiva en cuatro pasos iterativos utilizando QSR NVivo.

Se identifican tres categorías de incidentes de asimetría de recursos: 1) Sondeo: los turistas interrogan a Guide-Oracle y lo afronta mediante estrategias de desvío, evasión y seguimiento; 2) Aprendizaje: Guide-Magpie aprende de turistas expertos a través del reconocimiento y la entrega conjunta; y 3) Negociación: el guía-diplomático con mayor conocimiento ayuda a los turistas descarriados a salvar las apariencias apaciguándolos, siguiendo la línea oficial y corrigiendo con tacto.

El artículo contribuye a la investigación de la coproducción de servicios en el turismo al teorizar sobre contextos donde existe asimetría de conocimiento/información entre guías turísticos y turistas, particularmente donde ocurren relaciones de poder fluidas entre guías y turistas conocedores, o donde turistas equivocados coproducen el servicio priorizando propios significados. Los hallazgos resaltan la importancia de las habilidades interpersonales y otras capacidades de los guías no relacionadas con el contenido, y se ofrecen sugerencias para iniciativas efectivas de capacitación e intercambio de recursos/aprendizaje para los servicios de guías turísticos.

Senior travelers are an attractive market segment and increasingly participate in an internet-mediated society. This chapter examines the profile of senior tourists who booked their trip to the Azores using online travel agencies. The purpose is to analyze their motivation factors based on the travel motivation scale for senior tourists, using 17 items related to the motivations for visiting the destination, and to ascertain whether there are different groups of senior tourists based on sociodemographic characteristics, travel motivations, and experiences performed. Using a structured questionnaire and a sample of senior tourists, three distinct clusters are obtained.

This study examines the influencing factors of smart technology use behaviour (STUB), influencing tourist satisfaction and enhancing revisit intention for the Chinese tourism destination. Further, the moderating role of place attachment on the relationship between STUB, tourist satisfaction and revisit intention has been examined.

The study employs quantitative methodology by incorporating the planned behaviour theory to develop the hypotheses. Using an online survey link, 409 responses were collected from the tourists employing a non-probability convenience random sampling technique.

The partial least squire-structural equation modelling (PLS-SEM) results show that social influence significantly affects STUB, tourist satisfaction and revisit intention. Also, the anticipated positive behaviour has positive and significantly affects STUB and revisit intention. Finally, the findings show that tourist satisfaction significantly affects revisit intention in the tourist destinations in China.

A quantitative research design was applied, employing a random sampling technique, and surveys were conducted with tourists only in current research. However, future research can incorporate a wide range of methodology by collecting data from other tourism stakeholders to have an in-depth evaluation of repeat visitation behaviour. Future research can enhance the current conceptual framework by including other relevant variables like negative anticipated emotions at other locations, as the current study was conducted in the Chinese context.

This research adds value to the tourism destination to formulate tourist satisfaction and revisit intention. Implications are provided for a more nuanced understanding and effective planning in tourism destinations while considering smart technology use.

While travelling, tourists like to use mobile technology to share their travel experiences. This study aims to understand how the social value gained by tourists from sharing a travel experience with mobile technology affects their satisfaction with the travel experience through onsite mobile sharing behaviour.

A second-order hierarchical model is constructed to examine the moderated mediating role of onsite mobile sharing behaviour in improving tourists’ travel satisfaction. Through systematic sampling, 304 responses were collected at ten attraction points in Guangzhou and Shenzhen, China.

The results show that, compared with self-centred values (self-presentation and self-identification), other-centred values (building social connection and reciprocity) contribute more to forming social values of sharing. In addition, onsite mobile sharing behaviour partially mediates and moderates the effect of social values on travel satisfaction.

This study applies the social capital theory to identify the value gained by sharing travel experiences and empirically evaluates the impact of these values on the overall value of sharing travel experiences. This study also contributes to tourism research by examining the moderated mediating role of onsite mobile sharing behaviour in improving travel satisfaction. This study helps destination marketing to make strategies to motivate tourists to use mobile technology to share their travel experiences while travelling.

This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention.

Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT.

The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT.

This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits.

First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises.

Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry.

This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

本研究旨在调查游客对使用ChatGPT获取旅游信息的态度和意向。此外, 通过将与ChatGPT相关的感知风险与计划行为理论（TPB）相结合, 本研究探讨了三种感知风险（隐私风险、准确性风险和过度依赖风险）对游客行为意向的影响。

本研究通过两个在线调查平台收集了536名受访者的数据。在线调查问卷评估了游客对ChatGPT使用的感知风险、态度、主观规范、感知行为控制、行为意向以及与其使用ChatGPT相关的人口统计信息。

结构方程建模分析显示, 游客对使用ChatGPT搜索旅游信息的相关风险表示关切, 特别是隐私风险、准确性风险和过度依赖风险。发现感知风险显著影响游客对使用ChatGPT的态度和意向, 与先前有关游客对ChatGPT感知风险的文献中提出的假设一致。

本研究将TPB与ChatGPT中的感知风险相结合, 提供了实证证据。它强调了在考虑游客意向时考虑感知风险的重要性, 并为旅游中生成AI的可持续发展提供了贡献。因此, 它为从业者和政策制定者提供了宝贵的见解。

An increasing number of immersive technologies have been adopted in museum tourism in response to shifting consumer habits in the digital era. In contrast, the authenticity experience of museum tourists relies on genuine relics, the environment and activities, which are ancient or traditional. This raises the question of whether tourists can perceive authenticity in immersive technology-based museum tourism. To address this question, this study aims to explore the impact of virtual reality (VR) attributes on tourists’ presence, tourism authenticity and subsequent behavioral intentions in virtual museums.

Data were collected via scenario-based surveys of participants who had taken virtual museum tours based on VR. A total of 174 effective questionnaires were collected for exploratory factor analysis via SPSS 25. Afterward, 597 questionnaires were obtained for confirmatory factor analysis and path analysis via Mplus 7.4.

A conceptual model of how VR attributes influence presence, authenticity and visit intention was developed. There is a chain intermediary between presence and visit intentions, from original authenticity to interactive authenticity and then to emotional authenticity. Technology readiness and museum familiarity moderate some relationships between VR attributes and presence.

The findings can guide museums in improving the use of VR. For example, managers can improve the quality of virtual systems and adopt various interactive forms to enhance tourists’ participation experiences.

These research findings contribute to the research area of immersive technology adoption, enhance the understanding of tourism authenticity in the new context of technology application and extend the presence-emotion-intention theory.

This study aims to investigate low-carbon footprint travel choices, considering both destination attributes and climate change perceptions, and examine the impacts of nudging (a communication tool to alter individuals’ choices in a predictable way) on tourists’ preferences for carbon mitigation in destinations.

A discrete choice experiment questionnaire was administered to a sample of 958 Hong Kong respondents. Hybrid choice modeling was used to examine the respondents’ preferences for destination attributes and to explain preference heterogeneity using tourists’ climate change perceptions. The respondents’ willingness to pay for the destination attributes was also calculated to measure the monetary value of the attributes.

Destination type, carbon emissions and travel cost had significant effects on tourists’ choices of destination. Nudging increased tourists’ preference for low-carbon footprint choices. Tourists with higher climate change perceptions were more likely than others to select low-carbon destinations with carbon offset projects.

The findings of this study provide an impetus for destination management organizations to support local carbon offset projects, implement policies that mitigate carbon emissions and develop sustainable tourism to fulfill tourists’ demand for low-carbon footprint travel choices. Based on the findings, policymakers could promote sustainable tourism by publishing relevant climate change information on social media.

This study addressed a gap in the literature on tourist travel choice by considering carbon emission-related attributes and climate change perceptions and by confirming the role of nudging in increasing the choice of low-carbon destinations.

The tourism industry is seeing unprecedented growth due to the convergence of the internet and growing travel trends. E-tourism digitises the tourism business, including processes, value chains, infrastructure, services and auxiliary industries, to maximise efficiency and effectiveness. It is in response to the globalisation of the tourism sector, which has spurred the introduction of information and communications technologies (ICTs) during the past four decades. ICT can boost travellers' satisfaction by providing pre-trip information about tourism attractions and allowing them to contact vendors directly, obtain accurate information and get the lowest price.

ICT has made the global tourism sector more competitive by providing pre-trip information about tourism attractions, allowing tourists to contact vendors directly, obtain accurate information and get the lowest price. Search engines, transport capacity and network speeds have increased the number of international travellers who use technology to organise and document their trips. E-tourism reduces seasonality, improves consumer communication and boosts reservations and sales. ICT also affects customer behaviour management and future marketing models and supports tourism industry globalisation by providing practical tools to tourism agents to develop and disseminate their offers globally. Strategic behaviours significantly impact tourism, as eliminating intermediaries shortens the distance between client and provider. ICT is a new way to boost tourism demand, which attracts more tourists and generates more revenue while improving the sector.

This study aims to explore how social media affects decision-making among tourists and whether there is a potential effect of age, which is studied through generations. For this purpose, baby boomers, Gen X, Gen Y and Gen Z tourists are studied and real-time implications are offered.

The study adopts a descriptive and exploratory design where the conceptual model of social media-based decision-making is developed through a review of the literature. Quantitative analysis is conducted on primary data from 600 Indian tourists. This is done using a self-administered questionnaire adopted from Gulati (2022) after checking its validity and reliability. The statistical analysis for hypothesis testing is done using PLS-SEM path modelling on pooled data. To study the categorical moderating effect of generations, partial least squares multigroup analysis (PLS-MGA) is performed as a paired comparison on every successive generation.

After testing every successive younger generation with an older generation through PLS-MGA, none of the pairs found any significant differences in path coefficients, as the values obtained were 0.05 < p < 0.95 for all five paths (SM → NR, SM → IS, SM → E, SM → P, SM → PPB). This indicates all the generations behave in a similar manner irrespective of them being older or younger, and age does not moderate social media’s impact on decision-making among Indian tourists.

The study establishes India as a unique geographical market and suggests tourism marketers to treat all generations at par, irrespective of age, as they behave and interact with social media in a similar manner. But, because this study is restricted to a single geographical location, i.e. India, further regions can be explored for global generalisation. Future research can also explore other demographics for combined, moderated analysis. Findings from the study suggest that marketers should ensure that equal attention is given to all generations as they engage with social media in a similar manner. Targeted marketing using artificial intelligence can help in ensuring custom ads. Personalisation according to generations can also facilitate greater purchases.

The study fills a major population and knowledge gap by exploring a topic that has been highly under-researched. Also, the study adopts an inclusive approach by analysing all the generations, both younger and older, to understand the potential effect of age on moderating the impact that social media has on tourist decision-making. Further, real-time suggestions and implications are offered to tourism marketers with special reference to the Indian tourism industry.