Search results

Mianzi can powerfully influence tourists’ behavior. Compared with product brands, destination brands are more multidimensional, consisting of intangible and tangible elements. Therefore, this paper aims to explore the relationships among the Chinese culture-related variable mianzi, destination product quality, destination service quality, destination brand value, destination brand resonance, destination brand self-congruity and destination overall brand equity.

A questionnaire survey was conducted in 2021, yielding 475 valid responses from tourists who had traveled to Hainan, China. Data was analyzed using structural equation modeling.

The results showed that mianzi plays a significant role in shopping destination brand equity, and the mianzi effect shapes tourists’ positive perceptions of destination product and service quality. Meanwhile, destination product quality and service quality enhance shopping destinations’ overall brand equity through destination brand value, brand resonance and brand self-congruity.

This study, focusing on shopping destinations, presents a novel view of brand equity. The research also uncovers influencing factors (e.g. product quality and service quality) that further enrich the destination brand equity model. Finally, findings offer valuable insights for academic research and the practical development of shopping destinations.

面子能有力地影响游客的行为。与产品品牌相比, 目的地品牌更加多维, 由无形要素和有形要素构成。因此, 本文旨在探讨与中国文化相关的变量面子、目的地产品质量、目的地服务质量、目的地品牌价值、目的地品牌共鸣、目的地品牌自我一致和目的地整体品牌资产之间的关系。

2021年对去过中国海南旅游的游客进行问卷调查, 最终获取了 475 份有效问卷。

果表明, 结果表明面子在购物目的地品牌资产中发挥着重要作用, 面子效应塑造了游客对目的地产品和服务质量的积极认知。同时, 目的地产品质量和服务质量通过目的地品牌价值、品牌共鸣和品牌自我一致提升了购物目的地的整体品牌资产。

本研究以购物目的地为重点, 提出了一种新颖的品牌资产观点。研究还发现了一些影响因素（如产品质量和服务质量）, 进一步丰富了目的地品牌资产模型。最后, 研究结果为学术研究和购物目的地的实际发展提供了宝贵的见解。

Mianzi puede influir poderosamente en el comportamiento de los turistas. En comparación con las marcas de producto, las marcas de destino son más multidimensionales y constan de elementos intangibles y tangibles. Por lo tanto, este artículo pretende explorar las relaciones entre la variable mianzi relacionada con la cultura china, la calidad del producto del destino, la calidad del servicio del destino, el valor de la marca del destino, la resonancia de la marca del destino, la autocongruencia de la marca del destino y el valor general de la marca del destino.

En 2021 se llevó a cabo una encuesta por cuestionario, que arrojó 475 respuestas válidas de turistas que habían viajado a Hainan, China. Los datos se analizaron mediante un modelo de ecuaciones estructurales.

Los resultados mostraron que el mianzi desempeña un papel significativo en el valor de marca de los destinos de compras, y que el efecto mianzi determina las percepciones positivas de los turistas sobre la calidad de los productos y servicios del destino. Por su parte, la calidad de los productos y servicios del destino mejora el valor de marca global de los destinos de compras a través del valor de marca del destino, la resonancia de la marca y la autocongruencia de la marca.

Este estudio, centrado en los destinos de compras, presenta una visión novedosa del valor de marca. La investigación también descubre factores influyentes (por ejemplo, la calidad del producto y la calidad del servicio) que enriquecen aún más el modelo de valor de marca del destino. Por último, los resultados ofrecen valiosas perspectivas para la investigación académica y el desarrollo práctico de los destinos de compras.

This study aims to examine the interaction effects of chatbots’ language style and customers’ decision-making journey stage on customer’s service encounter satisfaction and the mediating role of customer perception of emotional support and informational support using the construal level theory and social support theory as conceptual frameworks.

This study used a scenario-based experiment with a 2 (chatbot’s language style: abstract language vs concrete language) × 2 (decision-making journey stage: informational stage vs transactional stage) between-subjects design.

Findings show that during the informational stage, chatbots that use abstract language style exert a strong influence on service encounter satisfaction through emotional support. During the transactional stage, chatbots that use concrete language style exert a strong impact on service encounter satisfaction through informational support.

Findings provide some suggestions for improving customer–chatbot interaction quality during online service encounters.

This study offers a novel perspective on customer interaction experience with chatbots by investigating the chatbot’s language styles at different decision-making journey stages.

This study aims to provide an overview of the evolution of knowledge on smart destinations and identify the key issues addressed in the smart destination research domain, the main themes and sub-themes and research gaps in smart destination research as well as the future research agenda to address those gaps.

A bibliometric analysis of 409 studies published on smart destinations literature was conducted using the Bibliometrix R-package to provide a comprehensive review of studies published on smart destinations and identify the main research themes, gaps in the literature and future research opportunities.

Based on the research findings, a conceptual model of smart destination research has been proposed. This conceptual model can serve as a foundation for further knowledge generation in this research area. The findings also shed light on future research directions, highlighting research opportunities for the exploitation of cutting-edge innovations and digitalization across various dimensions of smart destinations.

Although past research has paid attention to the theme of smart destinations, this work advances scientific knowledge by providing a foundation for a new smart destination management paradigm focusing on accessibility, sustainability, digitization, experience co-creation and creativity as milestones.

本研究旨在提供关于智慧目的地知识演变的概览, 并确定智慧目的地研究领域中涉及的关键问题、主要主题和子主题, 以及智慧目的地研究的研究空白, 同时提出未来研究议程以填补这些空白。

本研究利用 Bibliometrix R 软件对发表的409篇智慧目的地文献进行了文献计量分析, 以全面回顾关于智慧目的地的研究, 并确定主要研究主题、文献中的空白以及未来的研究机会。

基于研究结果, 本研究提出了智慧目的地研究的概念模型。该概念模型可作为进一步知识生成的基础。研究发现还为未来研究方向提供了启示, 强调了利用先进创新和数字化技术在智慧目的地各个维度上进行研究的机会。

尽管过去的研究关注了智慧目的地的主题, 但本研究通过提出以可达性、可持续性、数字化、体验共创和创意为里程碑的新智慧目的地管理范式, 推进了科学知识的发展。

This paper aims to examine the impact of metaverse experiences on customers’ offline behavioral intentions: How do customers’ visits to a hospitality business’s virtual property in the metaverse affect their intentions to visit the physical property in the real world?

Based on the general learning model and social cognitive theory, this research hypothesizes the positive impact of metaverse experiences on customers’ visit intentions and explores two boundary conditions for positive impact: user–avatar resemblance and servicescape similarity. Two experimental studies were conducted.

Metaverse experience has a significant impact on customers’ visit intentions, and this impact is moderated by user–avatar resemblance and servicescape similarity.

This research addresses the call for empirical studies regarding the effects of metaverse experience on people’s behavioral intentions.

As one of the earliest empirical studies on the marketing effects of the metaverse, this research provides a basis for future metaverse studies in the hospitality field.

This study aims to offer an overview of hospitality and tourism research on artificial intelligence (AI) and its impact on the industry. More specifically, this study examines hospitality and tourism AI research trends in hospitality and tourism customer service experience creation and delivery, service failure and recovery, human resources and organizational behavior. Based on the review, this study identifies the challenges and opportunities and provides directions for future studies.

A narrative synthesis approach was used to review the hospitality and tourism research on AI and its impact on various aspects of the industry.

AI and AI applications in customer service experience creation and delivery and its possible effects on employees and organizations are viewed as a double-edged sword. Although the use of AI and AI applications offers various benefits, there are also serious concerns over the ethical use of AI, the replacement of human employees by AI-powered devices, discomfort among customers and employees and trust toward AI.

The paper offers an updated holistic overview of AI and its implications in different facets of the hospitality and tourism industry. Challenges and opportunities are discussed to foster future discussions on the use of AI among scholars and industry professionals.

This paper highlights the effects of supervisor bullying (SBL) on work–family conflict (WFC), employee voice behavior (EVB), working compulsively (WCO) and working excessively (WEX), as well as the effects of WFC, EVB and WEX on employees' sleeping problems.

Data were gathered from 473 five-star hotel employees, and their responses were analyzed using AMOS v.23.

SBL significantly lowers EVB while significantly increasing WFC. SBL increases WEX and WCO levels, which may be considered a short-term positive outcome of SBL.

This paper will help improve understanding of employee reactions to an emotionally charged workplace occurrence.

Existing tourism review articles have limited review topics and cover a relatively short period. This review paper aims to extend the coverage of the previous literature and enhances the completeness of tourism-related studies to provide comprehensive tourism-related literature from 1945 (World War II onward) to 2022. Specifically, this paper reveals the major research themes present in published tourism research during this time period and highlights the evolution of tourism research from the preliminary phase, the transversal phase, to the growth phase.

The present study visualizes tourism research through networks of coauthors and their countries and regions, cocitation analysis of keywords and explores the thematic evolution of tourism research after the World War II (i.e., 1945–2022) from Web of Science and Google Scholar through bibliometric analysis.

Findings reveal that the themes of tourism research in the past years can be divided into seven major research themes. The tourism research evolution from World War II to 2022 can be categorized into three stages: preliminary (1945–1970), transversal (1971–2004) and growth (2005–2022). In addition, the research themes of tourism are not static but evolve according to the dynamics of the society and the industry, and that seven main research themes have been formed, namely, “heritage tourism,” “medical tourism,” “adventure tourism,” “dark tourism,” “sustainable tourism,” “rural tourism” and “smart tourism.”

The present study expands and refines the comprehensive literature in tourism research, as well as reveals the trends and dynamics in tourism research through network analysis and thematic evolution research methods.

现有的旅游评论文章在审查主题方面有限, 并且涵盖的时间相对较短。本综述文章扩展了先前文献的涵盖范围, 增强了与旅游相关研究的完整性, 提供了从1945年（第二次世界大战之后）到2022年的全面旅游相关文献。具体而言, 本文揭示了此期间发表的旅游研究中的主要研究主题, 并突出了旅游研究从初步阶段、横向阶段到增长阶段的演变。

本研究通过共同作者及其国家的网络、关键词的共同引用分析, 将旅游研究可视化, 并探索二战后旅游研究的主题演变。本研究通过文献计量学分析, 将 Web of Science (WoS) 和 Google Scholar 中的旅游研究（即 1945–2022 年）可视化。

研究结果显示, 过去几年的旅游研究主题可分为七大研究主题。从第二次世界大战到 2022 年的旅游研究演变可分为三个阶段：初步阶段（1945–1970 年）、横向阶段（1971–2004 年）和成长阶段2005–2022 年）。此外, 旅游的研究主题并不是静态的, 而是根据社会和行业的动态而演变, 形成了七个主要研究主题, 即“遗产旅游”、“医疗旅游”、“冒险旅游”、“黑暗旅游”、“可持续旅游”、“乡村旅游”和“智慧旅游”。

本研究通过网络分析和主题演变研究方法扩展和完善了旅游研究方面的综合文献, 并揭示了旅游研究的趋势和动态。

Los artículos de revisión existentes sobre turismo tienen temas de revisión limitados y cubren un periodo relativamente corto. Este artículo de revisión amplía la cobertura de la bibliografía anterior y mejora la exhaustividad de los estudios relacionados con el turismo para ofrecer una bibliografía exhaustiva sobre el turismo desde 1945 (Segunda Guerra Mundial en adelante) hasta 2022. En concreto, este documento revela los principales temas de investigación presentes en la investigación turística publicada durante este periodo de tiempo y destaca la evolución de la investigación turística desde la fase preliminar, la fase transversal, hasta la fase de crecimiento.

El presente estudio visualiza la investigación turística a través de redes de coautores y sus países y regiones, análisis de co-citación de palabras clave, y explora la evolución temática de la investigación turística después de la Segunda Guerra Mundial (es decir, 1945–2022) a partir de Web of Science y Google Scholar mediante análisis bibliométricos.

Los resultados revelan que los temas de la investigación turística de los últimos años pueden dividirse en siete grandes temas de investigación. La evolución de la investigación turística desde la Segunda Guerra Mundial hasta 2022 puede clasificarse en tres etapas: preliminar (1945–1970), transversal (1971–2004) y de crecimiento (2005–2022). Además, los temas de investigación del turismo no son estáticos, sino que evolucionan según la dinámica de la sociedad y de la industria, y que se han formado siete temas principales de investigación, a saber: “turismo patrimonial”, “turismo médico”, “turismo de aventura”, “turismo oscuro”, “turismo sostenible”, “turismo rural” y “turismo inteligente”.

El presente estudio amplía y perfecciona la amplia bibliografía existente en el campo de la investigación turística, además de revelar las tendencias y la dinámica de la investigación turística mediante el análisis de redes y los métodos de investigación de evolución temática.

This paper aims to examine the reaction of energy inflation to geopolitical risks in the European Economic Area between 1990 and 2015.

This study applies the nonparametric time-varying coefficient panel data model with fixed effects. In addition, to further reveal potential tail effects that may not have been captured by conditional mean-based regressions, the method of moments quantile regression was also used.

The findings of this study are as follows: first, as European countries get exposed to geopolitical tensions, it is expected that energy prices will surge. Second, the ability of geopolitical risk to trigger energy inflation in recent times is not as powerful as it used to be. Third, countries with a lower inflation rate, when exposed to geopolitical risks, experience smaller increases in energy inflation compared to countries with a higher inflation rate.

The findings of this study lead us to the conclusion that transitioning from nonrenewable to renewable energy use is one channel through which the sampled countries can battle the energy inflation, which geopolitical risks trigger. A sound macroeconomic policy for inflation control is a complementary channel through which the same goal can be achieved.

Given the increasing level of energy inflation and geopolitical risks in the world today, this study is an attempt to reveal the time-varying characteristics of the relationship between these variables in European countries using a nonparametric time-varying coefficient panel data model and method of moments quantile regression with fixed effects.

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。