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Although the number of guest houses in China is increasing rapidly, many of them are not performing well in developing customer loyalty. Self-congruity and functional congruity represent two cost-effective but inadequately researched ways for guest houses to maintain customers. In view of the lack of empirical research explaining the post-purchase behavior of guest house customers, the purpose of this study is to develop a congruity-based customer loyalty model for this specialized type of accommodation.

Based on a review of relevant literature, a robust conceptual framework of customer loyalty comprising satisfaction, self-congruity, functional congruity, perceived value and attractiveness of alternates was constructed. By means of an online panel survey, 828 valid questionnaires were obtained from customers who had stayed in a Chinese guest house within the previous year. Structural equation modeling was conducted to test the conceptual model and the hypothesized relationships among the constructs.

Significant relationships were found between the two congruity constructs in guest houses, which both led to positive customer post-purchase behaviors. The authors found that self-congruity, functional congruity and the attractiveness of alternates did not affect customer loyalty directly; rather, they influenced loyalty indirectly through customer satisfaction.

This study developed a unique, congruity-based model of customer loyalty in the context of guest houses. It enhances the body of knowledge regarding congruity in the field of tourism and hospitality, and it discusses relevant implications of the findings for tourism marketing researchers and for owner-managers of guest houses.

虽然民宿增长迅速, 多数民宿在顾客忠诚上表现较差。自我一致性和功能一致性作为民宿维持顾客的有效手段, 在学术上研究较少。鉴于学界缺乏对民宿顾客购后行为的实证研究, 本研究试图构建一个基于一致性的民宿顾客忠诚模型。

在文献综述基础上, 我们构建了一个基于一致性的顾客忠诚模型。用在线样本库的方法调查了过去一年有过民宿住宿体验的顾客, 最终收集了828份有效问卷。

研究发现, 两个一致性表现对顾客的购后行为存在显著影响。同时, 本研究显示, 自我一致性, 功能一致性和替代者吸引力并不直接影响顾客忠诚, 而是通过影响顾客满意影响忠诚。

基于一致性的新视角, 民宿顾客忠诚模型被重塑。本研究可以加深对接待业自我一致性研究的理解, 并为旅游营销研究提供启示。论文最后还讨论了研究结果对民宿研究和管理者的启示。

Aunque el número de casas de huéspedes en China está aumentando rápidamente, muchas de ellas no están funcionando bien en el desarrollo de la lealtad del cliente. La autocongruencia y la congruencia funcional representan dos formas rentables pero inadecuadamente investigadas para que las casas de huéspedes mantengan clientes. En vista de la falta de investigación empírica que explique el comportamiento posterior a la compra de los clientes de la casa de huéspedes, el presente estudio busca desarrollar un modelo de lealtad del cliente basado en la congruencia para este tipo especializado de alojamiento.

Con base en una revisión de literatura relevante, construimos un marco conceptual robusto de lealtad del cliente que comprende satisfacción, autocongruencia, congruencia funcional, valor percibido y atractivo de alternativas. Mediante una encuesta de panel en línea, obtuvimos 828 cuestionarios válidos de clientes que se habían alojado en una casa de huéspedes china durante el año anterior. Se realizó un modelado de ecuaciones estructurales para probar el modelo conceptual y las relaciones hipotéticas entre los constructos.

Se encontraron relaciones significativas entre las dos construcciones de congruencia en las casas de huéspedes, lo que condujo a comportamientos positivos posteriores a la compra del cliente. Descubrimos que la autocongruencia, la congruencia funcional y el atractivo de las alternativas no afectaban directamente la lealtad del cliente; más bien, influyeron indirectamente en la lealtad a través de la satisfacción del cliente.

Este estudio desarrolló un modelo único de lealtad del cliente basado en la congruencia en el contexto de las casas de huéspedes. Mejora el conjunto de conocimientos sobre congruencia en el campo del turismo y la hospitalidad, y analiza las implicaciones relevantes de los hallazgos para los investigadores de marketing turístico y para los propietarios-gerentes de casas de huéspedes.

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.

Hospitableness lies in the center of hospitality services. With the infusion of artificial intelligence (AI) technology in the hospitality industry, managers are concerned about how AI influences service hospitableness. Previous research has examined the consequences of AI technology based on customers’ assessment while ignoring the key players in service hospitableness – frontline employees (FLEs). This study aims to reveal how AI technology empowers FLEs physically, mentally and emotionally, facilitating hospitableness provision.

As the starting point, the instrument for AI-enabled service attributes was designed based on previous literature, hotel FLE interviews, expert panel and a pilot survey, and then validated using survey data. After that, a paired supervisor-employee sample was recruited in 15 hotels, and 342 valid questionnaires covering the constructs were obtained.

Factor analyses and measurement model evaluation suggest that the four factors, including anthropomorphic, entertainment, functional and information attributes, explain the construct of AI-enabled service attributes well, with high reliability and validity. Additionally, anthropomorphic, functional and information attributes of AI technology have been found to enable FLEs physically, mentally and emotionally, which further lead to increased service hospitableness. The entertainment attributes do not significantly reduce physical and mental fatigue but lead to positive emotions of FLEs significantly. Additionally, psychological job demand moderates the effects of AI-enabled service attributes on physical fatigue.

Practical implications can be made for AI technology application and hospitableness provision, in terms of AI technology analysis, job design and employee workload management.

This research contributes to understanding AI-enabled service attributes and their consequences, extends the conservation of resources theory to AI application context and promotes the research on service hospitableness.

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.