Search results

This study aims to explore tourism live streamers’ motivations of sharing their travel experiences based on the grounded theory.

The use of purposive and snowball sampling methods was used to conduct 22 in-depth semi-structured interviews. The manuscript was analyzed based on the grounded theory.

This study identifies five tourism live streamers’ motivations of sharing their travel experience, including information sharing, entertainment, self-presentation, monetary incentives and socialization. Information sharing and entertainment are identified as the most important motivations of travel livestreaming (TLS) among the motivations. Monetary incentive is identified as a new motivation for tourism live streamers compared to other social media users.

This study provides valuable suggestions for livestreaming platforms and tourism product providers to attract more tourism live streamers and better serve them.

To the best of the authors’ knowledge, this is one of the first studies to offer empirical findings and discussions on tourism live streamers’ motivations of sharing their travel experiences.

本研究旨在基于扎根理论探讨旅游直播主分享旅游体验的动机。

使用目的性和滚雪球抽样方法进行了22个深入的半结构化访谈。 本研究采用扎根理论对数据进行分析。

本研究发现了五种旅游直播主分享旅游体验的动机, 包括信息共享、娱乐、自我展示、金钱激励和社交。信息共享和娱乐被认为是旅游直播最重要的动机。与其他社交媒体的用户相比, 货币激励被认为是旅游直播的新动机。

本研究为直播平台和旅游产品提供商提供有用的建议, 以吸引更多的旅游直播者并更好地为他们服务。

这是对旅游直播主分享旅游体验的动机提供实证研究结果和讨论的首批研究之一。

este estudio tiene como objetivo explorar las motivaciones de los transmisores en vivo del turismo para compartir sus experiencias de viaje según la teoría fundamentada.

Des méthodes d'échantillonnage raisonné et boule de neige ont été utilisées pour mener 22 entrevues semi-structurées approfondies. Le manuscrit a été analysé sur la base de la théorie ancrée.

este estudio identifica las motivaciones de cinco transmisores en vivo del turismo para compartir su experiencia de viaje, incluido el intercambio de información, el entretenimiento, la autopresentación, los incentivos monetarios y la socialización. El intercambio de información y el entretenimiento se identifican como las motivaciones más importantes de la transmisión en vivo de viajes (TLS) entre las motivaciones. El incentivo monetario se identifica como una nueva motivación para el transmisor en vivo del turismo en comparación con los usuarios de otras redes sociales.

este estudio proporciona sugerencias útiles para que las plataformas de transmisión en vivo y los proveedores de productos turísticos atraigan a más transmisores turísticos en vivo y les brinden un mejor servicio.

este es uno de los primeros estudios que ofrece hallazgos empíricos y debates sobre las motivaciones de los transmisores en vivo del turismo para compartir sus experiencias de viaje.

This study aims to investigate the influence of the reviewed establishment’s price level and the user’s social network size and reputation status on consumers’ tendency to post more visual imagery content. Furthermore, it explores the moderating effects of user experiences and geographic distance on these dynamics.

This study adopts a multi-method approach to explore both the determinants behind the sharing of user-generated photos in online reviews and their internal mechanisms. Using a comprehensive secondary data set from Yelp.com, the authors focused on restaurant reviews from a prominent tourist destination to construct econometric models incorporating time-fixed effects. To enhance the robustness of the authors’ findings, the authors complemented the big data analysis with a series of controlled experiments.

The reviewed establishments price level and the users reputation status and social network size incite corresponding motivations conspicuous display “reputation seeking” and social approval motivating users to incorporate more images in reviews. “User experiences can amplify the influence of these factors on image sharing.” An increase in the users geographical distance lessens the impact of the price level on image sharing, but it heightens the influence of the users reputation and social network size on the number of shared images.

As a result of this study, high-end establishments can increase their online visibility by leveraging user-generated visual content. A structured rewards program could significantly boost engagement by incentivizing photo sharing, particularly among users with elite status and extensive social networks. Additionally, online review platforms can enhance users’ experiences and foster more dynamic interactions by developing personalized features that encourage visual content production.

This research, anchored in trait activation theory, offers an innovative examination of the determinants of photo-posting behavior in online reviews by enriching the understanding of how the intricate interplay between users’ characteristics and situational cues can shape online review practices.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.

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。

This case study provides in-depth, practical knowledge to develop business strategies for the management program. After reading this case study, the students will be able to learn about the challenges and problems that service firms face during a crisis, the drastic changes in the market environment due to a crisis and the analysis tools that can be used when analyzing the shifted market environment. By analyzing this case study, students will be trained for the decision-making that arises in the process of crisis management in the hotel industry.

Nam Nghi Resort, situated on the picturesque Phu Quoc Island in Vietnam, experienced the tumultuous period of the COVID-19 pandemic. Before the pandemic, Nam Nghi was a thriving five-star resort, deeply rooted in Vietnamese culture and renowned for its luxurious amenities and breathtaking location. However, the onset of COVID-19 brought unprecedented challenges to the hospitality industry, leading to a sharp decline in tourism and revenue. Despite the adversity, Nam Nghi implemented risk management practices successfully and displayed resilience and adaptability. Through rigorous cost minimization, strategic facility upgrades and targeted marketing efforts, Nam Nghi managed to navigate the crisis and gradually rebuild its business as travel restrictions eased. As the industry began to show signs of recovery, the general manager faced new challenges in restoring the resort’s prepandemic vitality. The challenge remained of understanding changing consumer values and market dynamics.

This case study can be used as class material for Master of Business Administration (MBA) students. In particular, MBA students in the hospitality industry such as hotels, resorts, travel agencies and restaurants are the target audience.

Teaching notes are available for educators only.

CSS 12: Tourism and hospitality.

Artificial intelligence is one of the most significant and active fields of study in the last few years. Artificial intelligence-derived robotic technologies known as chatbots are gaining interest from both academic and industry sectors. By analyzing the development and patterns of research on the chatbot phenomena within the tourism field, this study seeks to develop a theoretical framework for the interaction between chatbots and tourism.

The Web of Science (WoS) database’s 33 articles on chatbots related to travel and hospitality were examined between 2019 and 2024 using VOSviewer software for bibliometric and thematic content analysis.

Research on chatbots for tourism and hospitality appears to be in its early stages. The factors influencing tourists' intentions to use chatbots have been thoroughly researched; the attitudes, perceptions and behavioral intentions of destinations, travel agencies and restaurant patrons regarding chatbots were examined, and it was found that the quantitative research approach was dominant. In addition, the majority of the studies are based on a particular theory or model.

This is one of the first attempts to directly comprehend and depict the interconnected structures of studies on the interaction between chatbots and tourism through the use of network analysis. Furthermore, the study’s findings can offer academics a comprehensive viewpoint and a reference manual for more accurate assessment and oversight of the chatbot-tourism interaction. Regarding the lack of research on the topic and the fragmented structure of the studies that exist, it is imperative to provide both a comprehensive overview and a roadmap for future investigations into the usage of chatbots in the travel and hospitality sector.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.

Drawing on the stimulus–organism–response framework, this study examined the environmental stimuli driving tourists' internal, or organismic, states. In addition, the authors investigated the association of the identified organismic variables with the response variables during the COVID-19 pandemic. Specifically, the study examined how the associations between tourists' anticipation of recovery and the national government's smart governance, on one hand, and tourists' desire to travel domestically, their attitude toward domestic travel and their willingness to exhibit prosocial behaviors, on the other, further drive the satisfaction they derive from domestic travel.

The authors used an online questionnaire to collect self-report, single-wave data from individuals residing in India, an emerging market (N = 421).

The findings demonstrate (1) the association of anticipated recovery on the desire to travel and prosocial behavior; (2) the association of smart governance on attitude (although negative); (3) the association of desire, attitude and prosocial behavior on satisfaction; and (4) the lack of any moderation effect for perceived severity.

This study is the first empirical study to investigate the impact of tourists' perceptions and dispositions and the efficacy of the national government on tourists' desire to travel domestically and on their satisfaction with domestic travel. The findings can help emerging market multinationals and global brands engage better with domestic consumers in emerging markets within the context of the current pandemic. In addition, the findings can help to prepare these players to handle future disruptions caused by global health contingencies.

Using the stimulus–organism–response (SOR) theoretical model, this empirical research aims to examine and validate how tourists’ interactions with 360-degree virtual reality (VR) videos incorporating Web navigability and visual interface design quality (stimulus) on travel websites can make tourists more engaged and then satisfied (organism), which could make them more likely to visit destinations and spread electronic word of mouth (e-WOM) (response).

Using the convenience sampling method, 975 responses were collected through a questionnaire. The data were analysed using Smart-PLS 4 software to investigate the hypothesised relationships.

The findings demonstrate that 360-degree VR videos significantly create Web user engagement, and Web user engagement is significantly associated with Web user satisfaction. The result shows that Web user engagement and satisfaction impact the intention to visit the tourist destination. Additionally, Web user satisfaction impacts e-WOM. Lastly, navigability and visual interface design quality are significantly moderated between 360-degree VR videos and Web user engagement.

This research only examined the tourists’ behavioural intentions with 360-degree VR videos during the pre-travel phase. In contrast, future research may investigate how tourists behave with VR during the on-site and post-travel phases.

Tourism marketers should not only adopt 360-degree VR but also integrate Web navigability and visual interface design to boost Web users’ engagement on tourism websites.

This study advances the study of VR from the tourists’ psychological perspective. Moreover, the SOR theory has been re-examined from the VR and technology tourism perspectives. It provides a general understanding of the behavioural aspects of tourists in developing countries.

利用刺激-有机体反应（SOR）理论模型, 本实证研究检验并验证了游客与旅游网站上结合了网络导航性和视觉界面设计质量（刺激）的360度虚拟现实(VR)视频的互动如何使游客更投入、更满意（有机体）, 这可能使他们更有可能访问目的地并传播电子口碑（响应）。

采用方便抽样法, 通过问卷调查收集了975份回复。使用Smart-PLS 4软件对数据进行分析, 以调查假设的关系。

研究结果表明, 360度虚拟现实(VR)视频显著提高了网络用户参与度, 网络用户参与与网络用户满意度显著相关。结果表明, 网络用户参与度和满意度对旅游目的地的访问意愿有影响。此外, 网络用户满意度也会影响电子口碑。最后, 在360度虚拟现实(VR)视频和网络用户参与度之间, 导航性和视觉界面设计质量显著适中。

这项研究只考察了游客在旅行前阶段使用360度虚拟现实(VR)视频的行为意图。相比之下, 未来的研究可能会调查游客在现场和旅行后阶段使用虚拟现实(VR)的行为。

旅游营销人员不仅应采用360度虚拟现实(VR), 还应将网络导航性和视觉界面设计相结合, 以提高网络用户对旅游网站的参与度。

本研究从游客的心理角度推进了虚拟现实(VR) 的研究。此外, 还从虚拟现实(VR)和科技旅游的角度重新审视了SOR 理论。它提供了对发展中国家游客行为方面的一般了解。

Utilizando el modelo teórico estímulo-organismo-respuesta (SOR), esta investigación empírica examinó y validó cómo las interacciones de los turistas con los vídeos de RV de 360 grados que incorporan la navegabilidad web y la calidad del diseño de la interfaz visual (estímulo) en los sitios web de viajes pueden hacer que los turistas se sientan más comprometidos y luego satisfechos (organismo), lo que podría hacerles más propensos a visitar los destinos y a difundir el e-WOM (respuesta).

Utilizando el método de muestreo por conveniencia, se recogieron 975 respuestas a través de un cuestionario. Los datos se analizaron mediante el software Smart-PLS 4 para investigar las relaciones hipotetizadas.

Los resultados demuestran que los vídeos de RV de 360 grados generan un compromiso significativo de los usuarios de la web y que el compromiso de los usuarios de la web se asocia significativamente con su satisfacción. El resultado muestra que el compromiso y la satisfacción del usuario web repercuten en la intención de visitar el destino turístico. Además, la satisfacción del usuario web influye en el e-WOM. Por último, la navegabilidad y la calidad del diseño de la interfaz visual son significativamente moderadas entre los vídeos de RV de 360 grados y el compromiso del usuario web.

Esta investigación sólo examinó las intenciones de comportamiento de los turistas con los vídeos de RV de 360 grados durante la fase previa al viaje. En cambio, en futuras investigaciones se podría estudiar cómo se comportan los turistas con la RV durante las fases in situ y posterior al viaje.

Los profesionales del marketing turístico no sólo deberían adoptar la RV de 360 grados, sino también integrar la navegabilidad web y el diseño de la interfaz visual para potenciar el compromiso de los internautas en los sitios web turísticos.

Este estudio avanza en el estudio de la RV desde la perspectiva psicológica del turista. Además, se ha reexaminado la teoría S-O-R desde las perspectivas de la RV y el turismo tecnológico. Proporciona una comprensión general del aspecto conductual de los turistas en los países en desarrollo.

The importance of service firms cooperating with digital platforms is widely acknowledged. The authors study three contractual relationships (fixed-cost, cost-sharing, and profit-sharing) between service firms (specifically hotels) and digital platforms in a highly fragmented service supply chain to examine which of these contract types optimizes profits.

The authors extend prior models analyzing the optimal expected total profit from the travel service firm (hotel)–digital platform relationship, providing new insights into each contract type’s ability to coordinate decentralized systems and optimize profits for both parties.

This study finds that fixed cost contracts cannot coordinate the decentralized system. Cost-sharing contracts can coordinate the decentralized system but only allow one channel profit split. In contrast, profit-sharing contracts may not always perfectly coordinate the decentralized system but support alternative profit allocations. Practically, both profit-sharing and cost-sharing contracts are preferable to fixed-cost contracts.

The paper includes implications for travel service firm managers to consider when structuring contracts with digital platforms to focus on profit optimization. Profit-sharing contracts are most preferable when cost and revenue data are fully shared between parties, while cost-sharing contracts are preferable over fixed-cost contracts.

This study extends prior investigations into the utility of different contract types on the optimal profit of a travel service firm (hotel)-digital platform provider relationship. The research fills a gap in the literature concerning the contracts used in these relationship types.