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This study aims to explore the factors affecting customers’ attitudes to the adoption of robots in hotels and travel agencies.

Structural equation modelling was used to test the extended technology acceptance model based on data collected from 570 customers of hotels and travel agencies.

The findings revealed that hotel customers have more positive attitudes to service robots than their peers in travel agencies.

This research contributes to the literature on robots in tourism and responds to the call to investigate customers’ attitudes to the adoption of robots in developing countries.

探究消费者对旅游和酒店业采用机器人的态度

本研究旨在探索影响酒店旅游服务中使用机器人消费者态度的因素

基于570个酒店和旅行社消费者的数据, 运用结构方程来检测TAM延伸模型

研究结果显示酒店消费者比旅行社消费者对服务机器人有更加积极的态度

本研究对以发展中国家为研究背景, 关于消费者对服务机器人的态度的旅游文献做出了贡献

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.