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Building on both the uncanny valley and construal level theories, the analyses detailed in this paper aims to address customers’ explicit and implicit attitudes toward various service robots, categorized by the degree of their human-like appearance, namely, mechanoids (low human-likeness), humanoids (medium human-likeness) and realistic robots (high human-likeness).

The analyses reflect a mixed-method approach, across three studies. A qualitative study uses focus groups to identify consensual attitudes. An experiment measures self-reported, explicit attitudes toward the three categories of robots. Another experiment explores customers’ implicit attitudes (unconscious and unintentional) toward robots, using three implicit association tests.

Customers express both positive and negative attitudes toward service robots. The realistic robots lead to both explicit and implicit negative attitudes, suggesting that customers tend to reject these robots in frontline service settings. Robots with lower human-likeness levels generate relatively more positive attitudes and are accepted to nearly the same extent as human employees in hospitality and tourism contexts.

Because customers reject, both consciously and unconsciously, very human-like robots in service encounters, managers should leverage this key finding, along with the more detailed results, to inform their strategic introduction of robots into hospitality frontline service settings.

The combined qualitative and quantitative studies specify and clarify customers’ implicit and explicit attitudes toward robots with different levels of human-likeness, in the real-world setting of hospitality and tourism services. Such insights can inform continued research into the effects of these service innovations.

This study, first, reviews the existing literature on electronic word-of-mouth (eWOM) and, using communication theory, examines its impact on its readers’ decision-making processes. Second, this paper aims to propose some elements of eWOM communications that might be further researched.

A literature review of relevant academic articles produced 97 works related to social communication theory, eWOM and new artificial intelligence trends in hospitality. Thereafter, potential avenues for future research were explored.

The study results showed: valence, relevance, understandability and visual cues are the most important antecedents of message usefulness and the reader’s behavioral intentions; source credibility is the sender characteristic that most affects the reader’s behavioral intentions and consumer susceptibility to interpersonal influence is the receiver characteristic that most influences their attitudes and behavioral intentions. In addition, the study highlights four relevant aspects for future research. First, more research into online fake reviews is needed to better understand sender motivations. Second, companies should actively manage negative reviews. Then, the careful choice of platforms on which companies promote their products/services. Finally, the role of artificial intelligence in increasing the effectiveness of eWOM in the hospitality industry.

This paper integrates – grounded on communication theory – results from previous studies about the central elements of communication (message, sender and receiver) and discusses the main trends in hospitality-related eWOM. In addition, the paper examines the potential of specific eWOM elements as future lines of research, in particular: fake reviews, strategies for dealing with negative reviews, the eWOM platform used and artificial intelligence applications.

Este estudio, en primer lugar, revisa la literatura existente sobre el boca-oído electrónico (eWOM) y, utilizando la teoría de la comunicación, examina su impacto en los procesos de toma de decisiones de sus lectores. En segundo lugar, proponemos algunos elementos de las comunicaciones eWOM que podrían investigarse más adelante.

Una revisión de la literatura de artículos académicos relevantes produjo 97 trabajos relacionados con la teoría de la comunicación social, eWOM y nuevas tendencias de inteligencia artificial en hotelería. A partir de entonces, se exploraron posibles vías de investigación futura.

Los resultados del estudio señalaron: 1) la valencia, la relevancia, la comprensibilidad y las señales visuales son los antecedentes más importantes de la utilidad del mensaje y las intenciones de comportamiento del lector; 2) La credibilidad de la fuente es la característica del emisor que más afecta las intenciones de comportamiento del lector; 3) La susceptibilidad del consumidor a la influencia interpersonal es la característica del receptor que más influye en sus actitudes e intenciones de comportamiento. Además, el estudio destaca cuatro aspectos relevantes para futuras investigaciones. Primero, se necesita más investigación sobre las reseñas falsas en línea para comprender mejor las motivaciones del emisor. En segundo lugar, las empresas deben gestionar activamente las críticas negativas. Luego, la cuidadosa elección de las plataformas en las que las empresas promocionan sus productos/servicios. Por último, el papel de la inteligencia artificial en el aumento de la eficacia de eWOM en la industria hotelera.

Este artículo integra –con base en la teoría de la comunicación– resultados de estudios previos sobre los elementos centrales de la comunicación (mensaje, emisor y receptor) y analiza las principales tendencias en eWOM relacionadas con la hostelería. Además, el artículo examina el potencial de elementos específicos de eWOM como líneas futuras de investigación, en particular: revisiones falsas, estrategias para lidiar con críticas negativas, la plataforma eWOM utilizada y aplicaciones de inteligencia artificial.

Palabras clave: eWOM, Teoría de comunicación, Revisiones falsas, Revisiones negativas, Inteligencia artificialTipo de artículo: Revisión de la literatura

本研究, 首先, 回顾了现有的关于电子口碑（eWOM）的文献, 并利用传播理论, 研究了它对读者决策过程的影响。其次, 我们提出了一些可能需要进一步研究的电子口碑传播的要素。

对相关学术文章的文献回顾产生了97篇与社会传播理论、eWOM和酒店业新的人工智能趋势有关的作品。此后, 对未来研究的潜在途径进行了探讨。

研究结果显示。1）价值、相关性、可理解性和视觉线索是信息有用性和读者行为意图的最重要的前因; 2）来源的可信度是最能影响读者行为意图的发送者特征; 3）消费者对人际影响的易感性是最能影响他们态度和行为意图的接受者特征。此外, 该研究还强调了未来研究的四个相关方面。首先, 需要对网上虚假评论进行更多的研究, 以更好地了解发送者的动机。其次, 公司应该积极管理负面评论。然后, 谨慎选择公司推广其产品/服务的平台。最后, 人工智能在提高酒店业eWOM的有效性方面的作用。

本文以传播理论为基础, 整合了以往关于传播中心要素（信息、发送者和接受者）的研究结果, 并讨论了与酒店业相关的电子WOM的主要趋势。此外, 本文还研究了特定的eWOM要素作为未来研究方向的潜力, 特别是：虚假评论、处理负面评论的策略、使用的eWOM平台和人工智能应用。

关键词：eWOM, 传播理论, 虚假评论, 负面评论, 人工智能。

The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry.

In this study, a review was carried out on the Web of Science (WoS) database with the assistance of bibliometric analysis techniques. Cluster analysis was also employed for this to group important data to determine the relationships and to visualize the areas in which the studies are concentrated. The thematic content analysis method was used to reveal on which customer experiences and on which methods the focuses were.

On the subject of experiences of service robots, the greatest number of publications was in 2021. In terms of country, China has come to the fore in the distribution of publications. As a result of thematic content analysis, it was determined that the leading factor was the main dimension of emotional experience. In terms of sub-dimensions, social interactions attracted more attention. Most of the studies discussed were not based on any theory. Apart from these, the Technology Acceptance Model (TAM), the Service Quality Model (SERVQUAL) and Perceived Value Theory (PVT) were featured more prominently among other studies.

In this study, only the WoS database was reviewed. In future studies, it would be possible to make contextual comparisons by scanning other databases. In addition to quantitative research designs, social dimensions may be examined in depth following qualitative research methods. Thus, various comparisons can be made on the subject with mixed-method research designs. Experimental research designs can also be applied to where customers have experienced human-robot interactions (HRIs).

In the hospitality industry, it is critical to uncover every dimension of guests' robot acceptance. This study, which presents the current situation on this basis, guides future projections for the development of guest experiences regarding service robots in the hospitality industry.