Search results

User-generated content and online reviews are highly relevant in purchase decision in the hospitality sector, including restaurants, but there is a lack of knowledge about the effect of sharing pictures in this context. This study aims to focus on the relevance of user-generated photos in online platforms for restaurants’ selection.

A research was conducted with a sample of 319 residents of Porto region, who had at least one meal in a restaurant over the 30 days before the answer of the survey and had searched online to select the restaurant.

The results show that while doing online research about restaurants, it is important for potential consumers to find pictures of food and physical evidences of restaurants generated by other users. Findings also show that consumers find user-generated photos especially at websites of reviews, although the importance of restaurant owned platforms, such as official social media pages and websites.

The research results appeal restaurant managers to understand the importance of user-generated photos in online platforms by promoting photo sharing in their restaurants with appropriate marketing activities for that purpose.

This paper expands the state-of-the-art about the importance of user-generated content, focusing on the importance of photos from restaurants shared by consumers in online platforms.

用户生成内容和在线评论, 与酒店行业, 包括饭店业中的购买决策是密不可分的。但是在这个研究领域里, 对于分享照片的影响力还尚未可知。本论文旨在研究在线平台中的用户生成照片对于饭店选择的影响。

本论文采用问卷采样形式, 问卷样本为在30天之内通过上网搜索选择饭店并且就餐至少一次的葡萄牙波尔图地区居民, 有效样本数量为319份。

人们在上网搜索饭店时, 找到食物图片和其他用户生成的有关饭店评论对于消费者决策有着至关重要的作用。本论文结果还表明, 尽管饭店运营的在线平台比如官方社交媒体网页和网站等很重要, 但是消费者在决策中最考虑的因素是那些评论型网站, 消费者会更倾向于找到用户生成的图片来帮助他们的消费决策。

本论文结果对于饭店管理者理解在线平台的用户生成图片的重要性有着很大的启示。本论文建议其管理者应该使用适当的营销手段来促使自己饭店的相关照片得到用户的分享。

本论文拓展了用户生成内容的现有认识, 研究了饭店照片被消费者分享到在线平台的重要性。

线上口碑效应 e-WOM、在线平台 、在线评论 、照片分享 、饭店管理 、社交媒体 、用户生成内容

研究论文

This study aims to explore the quality of user-generated content regarding readability, polarity, word length and diversity, as well as its implications for guest satisfaction in Las Vegas luxury gaming resorts.

This study examined 12,940 textual customer reviews from six luxury hotels in luxury gaming destination resorts via Google Travel gathered from SCTM 3 (Smart Crawling and Text Mining). Moreover, the regression analysis identified the relationship between the variables in the textual customer reviews and the customer’s overall satisfaction.

A key finding of this study revealed that word length moderates the relationship between readability and overall customer satisfaction negatively, whereas it positively moderates the path from sentiment polarity and diversity to overall customer satisfaction.

This study contributes to the relationship between technical aspects of online reviews. The adopted methodology allows us to precisely identify the essential attributes that influence customer satisfaction through textual reviews. Further, the study explores the quality of user-generated content, addressing aspects such as readability, polarity, diversity and word length, providing a unique perspective on how these specific elements directly impact customer satisfaction in this context of hotels in luxury in Las Vegas.

本研究探讨了用户生成内容的可读性、情感倾向、词长和多样性等方面的质量, 以及这些因素对拉斯维加斯豪华博彩度假村顾客满意度的影响。

本研究通过 SCTM 3（智能爬虫与文本挖掘）收集了谷歌旅行上的六家豪华酒店的12,940 条客户评论文本。此外, 回归分析确定了文本客户评论中的变量与客户整体满意度之间的关系。

本研究的一个关键发现是, 词长在可读性与整体顾客满意度之间的关系中起到负面调节作用, 而在情感倾向和多样性与整体顾客满意度之间的路径中起到正面调节作用。

本研究对在线评论的技术方面之间的关系作出了贡献。采用的方法使我们能够精确识别通过文本评论影响顾客满意度的关键属性。此外, 本研究探讨了用户生成内容的质量, 涉及可读性、情感倾向、多样性和词长等方面, 提供了独特视角, 揭示了这些具体元素如何直接影响拉斯维加斯豪华酒店顾客满意度。

The purpose of this paper is to study tourists’ spatial and psychological involvement reflected through tourism destination image (TDI), TDI is divided into on-site and after-trip groups and the two groups are compared in the frame of three-dimensional continuums.

By conducting latent Dirichlet allocation (LDA) modeling to tourism user-generated content, structural topic models are established. The topics separated out from unstructured raw texts are structural themes and representations of TDI. Social network analysis (SNA) reveals the quantitative and structural differences of three-dimensional continuums of the two TDI groups.

The findings reveal that from the stage of on-site to after-trip, tourist perception of TDI shifts from psychologically to functionally-oriented, from common to unique, and from holistic to more attribute focused. Also, it is suggested that from a postmodernism perspective, TDI is never unique, fixed or universal, but has different image perceptions and feedbacks for different tourists.

With the assistance of social sensing, a panoramic view of TDI could be established. Targeted and precision destination marketing and image promotion could be applied out to each individual tourist.

Combining with the perspectives of the tourist-destination space system and the tourism involvement theory, this research proposes a TDI transformation model and an explanation of the internal mechanism. The originality of research also lies in the methodological innovation of social sensing data and the LDA topic model.

本研究针对旅游目的地形象（TDI）及其体现出的游客空间和心理涉入, 将旅游目的地形象划分为在场形象和游后形象, 并将二者在TDI三维连续体（Three-dimensional continuums）框架下进行比较。

本研究应用内容分析法, 通过对旅游用户生成内容（tourism UGC）进行LDA（Latent Dirichlet Allocation）建模, 从非结构化的原始文本中建立起结构化的语义主题模型, 并且应用社会网络分析（Social Network Analysis）, 从定量和结构化的角度揭示了游中与游后目的地形象的差异。

研究发现, 从游中到游后, 游客的目的地形象感知经历了从心理到功能、从一般到特殊、从整体到属性的转变。同时, 基于后现代主义的视角, 旅游目的地形象并不是唯一的、固定的或放之四海而皆准的, 而是在不同的游客感知中有不同的形象和体现。

应用社会感知（Social Sensing）理论可以全面解析旅游目的地形象。同时可以针对特定游客采取精准定点的旅游目的地营销和形象推广手段。

本研究从旅游目的地空间系统和旅游涉入理论视角出发, 提出了旅游目的地形象转变的模型和其内在机制解释, 在方法上创新性地使用了社会感知数据和LDA主题模型。

关键词 旅游目的地形象, 在场形象, 游后形象, 旅游用户生成内容 (tourism UGC), LDA（Latent Dirichlet Allocation）建模, 社会感知

Para estudiar el grado de participación espacial y psicológica de los turistas reflejado en la imagen del destino turístico (TDI), el TDI se divide en grupo en el sitio y grupo posterior al viaje, y los dos grupos se comparan en el marco del continuo tridimensional.

Al modelar la posible asignación de Dirichlet (LDA) del contenido generado por el usuario turístico (UGC), se estableció un modelo de tema estructural. El tema que está separado del texto original no estructurado es el tema estructurado y la representación de TDI. El análisis de redes sociales reveló diferencias en el número y la estructura de los continuos tridimensionales de los dos grupos de TDI.

Los resultados de la encuesta muestran que, desde la escena hasta los viajes, la percepción de los turistas de TDI cambia de orientación psicológica a funcional, de lo ordinario a lo único, y de una atención general a más. Además, se sugiere que desde una perspectiva posmoderna, TDI nunca es único, fijo o universal, sino que tiene diferentes percepciones de imagen y comentarios para diferentes visitantes.

Con la ayuda de la detección social, se podría establecer una vista panorámica de TDI. El marketing de destino y la promoción de imágenes dirigidos y precisos podrían aplicarse a cada turista individual.

Combinando con las perspectivas del sistema espacial de destino turístico y la teoría de la participación turística, esta investigación propone un modelo de transformación TDI y la explicación del mecanismo interno. La originalidad de la investigación también radica en la innovación metodológica de los datos de detección social y el modelo de tema LDA.

The purpose of this paper is to examine the impact of social media sharing on tourists’ willingness to pay more (WPM) at destinations. The moderating effects of tourists’ preferred route in decision-making or obtaining information (i.e. central or peripheral routes) were also examined.

A theoretical model was developed and tested using partial least squares structural equation modeling (PLS-SEM). Moderating effects of central and peripheral routes were tested using PLS multi-group analysis. Data were collected from 478 tourists in Antalya, Turkey, a sea, sun and sand tourist destination.

Findings indicate that importance attached to participant sharing (IPS) and importance attached to non-participant sharing (INPS) are significant antecedents of tourists’ WPM intentions. Moderating effects of tourists’ preferred route in decision-making reveal that the effect of IPS on WPM intention is more influential for those with high central route preferences than those with low central route preferences. While the effects of INPS and IPS on WPM intention is more determinative for those with higher peripheral route preferences.

Although it is known by the practitioners that consumer-generated contents are important, this research suggests and supports that these contents trigger tourists to pay higher prices.

How WPM is motivated by others’ social media sharing was not very clear in the literature. Therefore, this research gap was addressed in part by examining the social media sharing structure in terms of whether others posted on organization-related sites or on personal sites.

标题探索可能性路线在用户生成内容和支付意愿关系中的作用

本研究旨在探讨社交媒体分享对旅游者在目的地的支付意愿（WPM）的影响。还考察了旅游者在决策或获取信息时偏好路线（即中心或外围路线）的调节效应。

本文利用偏最小二乘结构方程模型（PLS-SEM）建立了理论模型并进行了验证, 使用PLS多组分析法检验了中心和外围路线的调节作用。从土耳其安塔利亚的478名游客中收集了数据。安塔利亚是一个拥有海洋、阳光和沙滩的旅游胜地。

结果表明, 游客对参与式分享（IPS）的重视程度和对非参与式分享（INPS）的重视程度是游客支付意愿 (WPM) 的显著前因。旅游者偏好路线在决策中的调节效应表明, IPS对WPM意图的影响, 对中心路线偏好高的游客比中心路线偏好低的游客更为显著。而INPS和IPS对WPM意图的影响对周边路线偏好较高者更具决定性。

尽管用户生成内容的重要性广为从业人员了解, 但本研究表明, 这些内容还能促使游客支付更高的价格。

在现有文献中, 他人的社交媒体分享是如何激励产生WPM的还不是很清楚。因此, 本文通过考察社交媒体分享的结构来填补这一研究空白, 即考察他人的内容是发布在组织相关的网站上还是个人网站上。

关键词: 社交媒体分享, 精化可能性模型, 中心路线, 外围路线, 支付意愿

研究论文

El papel de las rutas ELM (modelo de probabilidad de elección) en la relación entre el contenido generado por usuarios y la disposición a pagar

El propósito de esta investigación es examinar el impacto de la compartición en redes sociales con la disposición de los turistas a pagar más (willness pay more: WPM) en los destinos. También se examinaron los efectos moderadores de la ruta preferida de los turistas en la toma de decisiones u obtención de información (es decir, rutas centrales o periféricas).

Se desarrolló y probó un modelo teórico utilizando modelos de ecuaciones estructurales de mínimos cuadrados parciales (PLS-SEM). Los efectos moderadores de las rutas centrales y periféricas se probaron mediante análisis multigrupo de PLS. Se recopilaron datos de 478 turistas en Antalya, Turquía, un destino turístico de mar, sol y arena.

Los resultados indican que la importancia atribuida a la compartición de los participantes (importance participant sharing: IPS) y la importancia atribuida al la compartición de los no participantes (importance no participant saharing: INPS) son antecedentes importantes de las intenciones de los WPM de los turistas. Los efectos moderadores de la ruta preferida de los turistas en la toma de decisiones revelan que el efecto de IPS en la intención de WPM es más influyente para aquellos con altas preferencias de ruta central que aquellos con bajas preferencias de ruta central. Mientras que los efectos de INPS e IPS en la intención de WPM son más determinantes para aquellos con mayores preferencias de ruta periférica.

Aunque los profesionales saben que los contenidos generados por los consumidores son importantes, esta investigación sugiere y respalda que estos contenidos provocan que los turistas paguen precios más altos.

Al no estar clara en la literatura la relación de la WPM con la compartición en redes sociales y existir una brecha de investigación en este aspecto, este trabajo pretende abordar este tema, examinando la estructura de la compartición en redes sociales en términos de si otros publicaron en sitios relacionados con la organización o en sitios personales.

Compartición en redes sociales, Modelo de probabilidad de elección (ELM), Ruta Central, Ruta periférica, Disposición a pagar más

Trabajo de investigación

The concept of camping has changed over time, with new niche markets appealing to sustainable tourists. Glamping – short for “glamorous camping” – offers a way to experience the positive aspects of camping while minimising the negatives. This paper aims to present the empirical findings of an exploratory study that examined tourists’ Web-reviews to identify the expressive dimensions that describe these travellers’ experience.

A content analysis of Web reviews provided by tourists on glamping booking websites produced a battery of concepts used to assess glamping experiences from the guests’ perspective. Both quantitative and qualitative methods are used.

The analysis identified 11 themes: experience, hotel, learn, host, camping, nature, food, ingredients, different, eco and yoga. The results reveal that, when quality of experience is evaluated through user-generated content, two attributes appear to be involved – functional elements offered by service providers and consumers’ emotional elements.

Web-reviews clearly offer important information to managers in the glamping sector. The present study’s analysis revealed that different market segments (i.e. couples, visitors with families or friends and those travelling alone) share certain aspects of glamping experiences.

随着新兴市场吸引可持续旅游者的目光, 露营概念正在与日改变。Glamping – “豪华露营”的简称 – 指减少负面不便的同时体验露营之美。本论文旨在通过分析网上游客评论以确定豪华露营体验的描述型维度。

本论文采用豪华露营预定网站的游客评论为样本, 进行文本分析, 以探究豪华露营用户体验。本论文采用定量和定性分析相结合的方式进行研究。

文本分析结果确立了11个主题：体验、酒店、学习、主人公、露营、自然、食物、原料、区别、生态和瑜伽。此结果表明, 当豪华露营体验的质量在用户生成内容中评价时, 牵扯其两项特点：服务提供者的功能要素和顾客感知要素。

网站评论向豪华露营的管理者们提供重要信息。本论文分析结果表明每个市场细分（即单独旅行、夫妻旅行、或者家庭旅行、朋友旅行等）对于豪华露营体验有着不同的兴趣点。

用户生成内容 文本分析, 体验, 豪华露营, 可持续性旅游

研究论文

To test the applicability of the user-generated content (UGC) derived from social travel network sites for online reputation management, the purpose of this study is to analyze the spatial clustering of the reputable hotels (based on the TripAdvisor Best-Value indicator) and reputable outdoor seating restaurants (based on ranking indicator).

This study used data mining techniques to obtain the UGC from TripAdvisor. The Hierarchical Density-Based Spatial Clustering method based on algorithm (HDBSCAN) was used for robust cluster analysis.

The findings of this study revealed that best value (BV) hotels and reputable outdoor seating restaurants are most likely to be located in and around the central districts of the urban tourist destinations where population and economic activities are denser. BV hotels' spatiotemporal cluster analysis formed clusters of different sizes, densities and shape patterns.

This study showed that reputable hotels and restaurants (H&Rs) are concentrated within districts near historic city centers. This should be an impetus for applied research on urban investment environments.

The findings would be rational guidance for entrepreneurs and potential investors on the most attractive tourism investment environments.

There has been a lack of studies focusing on analyzing the spatial clustering of the H&Rs using UGC. Therefore, to the best of the authors’ knowledge, this study is the first to map and analyze the spatiotemporal clustering patterns of reputable hotels (TripAdvisor BV indicator) and restaurants (ranking indicator). As such, this study makes a significant methodological contribution to urban tourism research by showing pattern change in H&Rs clustering using data mining and the HDBSCAN algorithm.

为了测试社交旅游网站 (STNS) 的用户生成内容 (UGC) 对在线声誉管理 (ORM) 的适用性, 本研究分析了知名酒店的空间聚类（基于 TripAdvisor 最佳价值指标) 和信誉良好的户外座位 (ODS) 餐厅(基于排名指标)。

该研究使用数据挖掘技术从 TripAdvisor 获取 UGC。 基于（HDBSCAN）算法的分层基于密度的空间聚类方法用于鲁棒聚类分析。

调查结果显示, 最具价值 (BV) 酒店和信誉良好的 ODS 餐厅最有可能位于人口和经济活动较为密集的城市旅游目的地的中心区及其周边地区。 BV 酒店的时空聚类分析形成了不同大小、密度和形状模式的聚类。

目前的文献扔缺乏专注于分析利用 UGC 的酒店和餐厅 (H&R) 空间聚类的研究。 因此, 本研究首次绘制并分析了知名酒店（TripAdvisor BV 指标）和餐厅（排名指标）的时空聚类模式。 因此, 本研究通过利用数据挖掘和 HDBSCAN 算法显示 H&Rs 聚类的模式变化, 为城市旅游研究做出了重要的方法论贡献。

这项研究表明, 著名的 H&R 集中在历史悠久的市中心附近的地区。 这应该是对城市投资环境的应用研究的推动力。

研究结果将为企业家和潜在投资者提供最具吸引力的旅游投资环境的理性指导。

Destination monitoring is crucial to understand performance and identify key points of differentiation. Visitor satisfaction is an essential driver of destination performance. With the fast-growing volume of user-generated content through social media, it is now possible to tap into very large amounts of data provided by travellers as they share their experiences. Analysing these data for consumer sentiment has become attractive for destinations and companies. The idea of drawing on social media sentiment for satisfaction monitoring aligns well with the broader move towards smart destinations and real-time information processing. Thus, this paper aims to examine whether the electronic word of mouth originating from Twitter posts offers a useful source for assessing destination sentiment. Importantly, this research examines what caveats need to be considered when interpreting the findings.

This research focusses on a prominent tourist destination situated on Australia’s East Coast, the Gold Coast. Using a geographically informed filtering process, a collection of tweets posted from within the Gold Coast destination was created and analysed. Metadata were analysed to assess the population of Twitter users, and sentiment analysis, using the Valence Aware Dictionary for Sentiment Reasoning algorithm, was performed.

Twitter posts provide considerable information, including about who is visiting and what sentiment visitors and residents express when sending tweets from a destination. They also uncover some challenges, including the “noise” of Twitter data and the fact that users are not representative of the broader population, in particular for international visitors.

This paper highlights limitations such as lack of representativeness of the Twitter data, positive bias and the generic nature of many tweets. Suggestions for how to improve the analysis and value of tweets as a data source are made.

This paper contributes to understanding the value of non-traditional data sources for destination monitoring, in particular by highlighting some of the pitfalls of using information sources, such as Twitter. Further research steps have been identified, especially with a view to improving target-specific sentiment scores and the future employment of big-data approaches that involve integrating multiple data sources for destination performance monitoring.

The identification of cost-effective ways of measuring and monitoring guest satisfaction can lead to improvements in destination management. This in turn will enhance customer experience and possibly even resident satisfaction. The social benefits, especially at times of considerable visitation pressure, can be important.

The use of Twitter data for the monitoring of visitor sentiment at tourist destinations is novel, and the analysis presented here provides unique insights into the potential, but also the caveats, of developing new, smart systems for tourism.

目的地监控对理解绩效和确立区别关键点至关重要。游客满意是目的地绩效的关键动力。随着社交媒体上用户生成内容的快速增长, 研究其游客提供的大量数据变成可能, 这些数据体现了游客的旅游体验。分析这些消费者情绪的数据对目的地和有关企业的吸引力巨大。研究社交媒介情绪数据和满意度与更广泛地对智慧旅游和实时信息处理等方面的研究和谐一致。因此, 本论文旨在检验Twitter帖子中的在线口碑效应是否成为测量目的地情绪的有用数据。更重要的是, 本论文检验在研究结果中哪些领域应该着重考虑研究。

本论文集中研究了澳大利亚东海岸的一处旅游目的地, 黄金海岸。本论文使用地理信息过滤的处理方式, 有关黄金海岸的tweets为样本, 进行分析。本论文分析了元数据, 使用VADER数算, 检测了Twitter用户人口和情绪分析。

Twitter帖子提供相当多的信息, 包括谁是游客, 当游客发布有关旅游目的地的tweets的时候, 拥有什么样的情绪。研究结果还指出了一些挑战, 包括twitter数据的“杂音”, 用户并不能代表广大研究对象的事实, 特别是国际游客。

本论文强调了几点限制, 如Twitter数据的代表性、积极偏见、大多数tweets千篇一律等。本论文对如何提高分析结果和使用tweets作为数据源的价值提出了几点建议。

本论文对非传统数据以对旅游目的地监控的价值做出贡献, 尤其是强调了使用信息数据的弊端, 如Twitter。未来研究方向应该着重研究目标明确的情绪指数, 以及运用大数据分析方法, 分析多个数据源来检测旅游目的地性能。

本论文确立的经济有效的方法以衡量和监控游客满意度, 对提高目的地管理有着巨大帮助。同时, 这也可以提高游客体验和甚至提高当地居民的满意度。社会利益, 特别有的时候很大的旅游压力, 是巨大的。

This study aims to demonstrate the application of computer-aided text analysis (CATA) software in identifying primary associations and impressions of a specified tourist destination.

The Leximancer software is applied on primary information to analyze the concepts evoked by a destination. Because no specific planning has been done for destination image marketing strategies for rural tourism in Andalusia, this study visualizes and determines clusters of the main attributes associated with this destination.

The analysis identifies the main clusters among associations and impressions of the destination that can be useful in developing strategies.

Only a target segment is studied, with a relatively small sample size.

Leximancer can not only be applied to online user-generated content, but primary information can also be mapped to generate a holistic destination image. Furthermore, identification of the relevant attributes and impressions can serve to identify unique assets to help tourism organizations develop a destination.

Several implications concerning destination marketing are outlined.

Although previous studies have applied Leximancer and other CATA software, the present research uses a new approach. Deriving the primary information on destination image using an unstructured methodology, the concepts evoked by a destination are mapped. Because there is a lack of research on rural tourism in Andalusia and its destination image, its associated attributes are studied.

本论文展示如何使用CATA分析软件来确定一个具体旅游目的地的主要关系和印象。

Leximancer软件主要用于分析一个目的地引发的相关概念。因为安达卢西亚至今未有确定的乡村旅游目的地形象营销策略, 本论文视觉化和决定与此目的地相关的主要因素群。

研究结果指出了此安达卢西亚目的地的主要相关群和印象群, 这些对于指定战略计划有很大帮助。

本论文只研究了单一市场群, 分析样本量较小。

Leximancer不仅可以用来分析用户生成内容, 还可以分析主要信息, 以展示整体旅游目的地形象。此外, 分析指出的相关因素和印象群可以用来确立独特的资源组合, 帮助旅游机构开发旅游目的地。

本论文结构指出了多个旅游目的地营销的相关启示

尽管文献中有关Leximancer和其他CATA软件的使用文章, 本论文创立了新的使用方法。基于对旅游目的地形象的主要信息进行非结构性研究, 本论文对于旅游目的地的概念进行展开论述。由于至今未有针对安达卢西亚的乡村旅游研究以及旅游目的地形象研究, 本研究论述了其相关因素。

关键词 安达卢西亚、旅游目的地形象、旅游目的地因素、CATA软件、Leximancer

The purpose of this paper is to investigate travellers’ behaviour and examine their reactions to high-tech hotels offering robotic services to customers.

Data were gathered from user-generated content within the context of a qualitative research method by analysing the online narratives of travellers at TripAdvisor who visited robotic hotels. Data analysis was realised through content analysis, which revealed various themes and categories of traveller behaviour and reactions to technology.

Results show that robotic services significantly improve the quality of service offered to travellers, while positively affecting travellers’ intention to revisit robotic hotels within the context of customer engagement behaviours.

The results of the present research reveal that the introduction of new technologies in the service industry, such as the robotic butler, can have considerable effects on guest behaviour and attitudes. This field has emerged as a new sub-dimension of customer engagement.

The use of robots will most likely enhance experiences through interaction between customers and robots. Additionally, in cases where social distancing is required, the use of robots in the hospitality and tourism industry may increase the mobility of people wishing to travel by applying social distancing through use of robots in services.

The study contributes to the extant literature by identifying the concept of adoption as a sub-dimension deriving from human–robot interaction, thus generating the novelty of the research.

本论文旨在研究游客行为以及检验其对高科技酒店提供机器人服务给客人的反应。

本论文采用定性分析手段, 采集样本为TripAdvisor游客光顾机器人酒店的在线叙述文本, 即用户生成内容（UGC）。本论文采用文本分析法, 以确定多种游客行为和对科技的反应等多个主题和范畴。

研究结果表明, 机器人服务大大提高游客服务质量, 同时也积极影响游客再光顾机器人酒店的意向, 在顾客参与行为（CEBs）的研究背景下。

本论文研究结果表明, 服务产业的新科技引用, 比如机器人服务员, 能够对顾客行为和态度产生显著的影响。这一研究领域作为顾客参与（CE）的新维度正在兴起。

新技术的引用将提高顾客的服务质量, 从而促成顾客的价值共创。此外, 还可以帮助消除游客对受到健康相关危机影响的担忧; 从业人员应该考虑在其公司、企业、或者机构中采用机器人服务。

机器人的使用将很有可能通过机器人与顾客的交互而提高顾客体验。此外, 在被要求社交隔离的情况下, 在酒店和旅游业中使用机器人将增加人们旅游的流动性。

本论文补充了现有文献, 确立了机器人接纳作为人机交互的第二维度, 从而证实了本文的新颖性。

This paper aims to further the knowledge of what effect destination and tourist social media communications have on destination brand equity.

The authors performed a quantitative study with 433 international tourists and social media users using an online survey and structural equation modeling.

The results show that user-generated content (UGC) and destination-generated content (DGC) both positively affect tourist behavior through the mediating role of destination brand equity. Of the two, UGC is more important for building a positive destination image and more valuable for improving perceived destination quality and value. The results also show that affective image is a powerful predictor of tourist behavior.

The findings provide useful insights for destination management organizations (DMOs) and social media marketing strategies. DMOs need to generate content that was highly relatable and evokes emotion, and encourage tourists to share their own experiences to improve destination brand equity and future behavior.

The study was conducted in the passive, pretrip stage before a travel decision is taken, which offers unique insight into how social media communications affect: destination brand equity and users’ decisions to choose certain destinations over others.

本文旨在进一步了解目的地和旅游社交媒体传播对目的地品牌资产的影响。

本论文使用在线调查和结构方程模型对 433 名国际游客和社交媒体用户进行了定量研究。

结果表明, 用户生成的内容（UGC）和目的地生成的内容（DGC）都通过目的地品牌资产的中介作用对游客行为产生积极影响。两者中, UGC对于建立积极的目的地形象更为重要, 对于提高感知的目的地质量和价值更有价值。结果还表明, 情感形象是旅游行为的有力预测因素。

研究结果为目的地管理组织 (DMO) 和社交媒体营销策略提供了有用的见解。 DMO 需要生成具有高度相关性和唤起情感的内容, 并鼓励游客分享自己的经验, 以提高目的地品牌资产和未来行为。

该研究是在做出旅行决定之前的被动旅行前阶段进行的, 它提供了关于社交媒体传播如何影响：(i) 目的地品牌资产, 以及 (ii) 用户的选择决定某些目的地优于其他目的地的独特见解。