Research trends on guest experience with service robots in the hospitality industry: a bibliometric analysis


YÖRÜK T., AKAR N., Özmen N. V.

European Journal of Innovation Management, 2023 (SSCI) identifier

  • Publication Type: Article / Article
  • Publication Date: 2023
  • Doi Number: 10.1108/ejim-09-2022-0530
  • Journal Name: European Journal of Innovation Management
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus, ABI/INFORM, Aerospace Database, Communication Abstracts, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: Bibliometric analysis, Customer experiences, Hotel service robots
  • Akdeniz University Affiliated: Yes

Abstract

Purpose: The purpose of this study is to reveal the research trends in guest experiences of service robots in the hospitality industry. Design/methodology/approach: 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. Findings: 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. Research limitations/implications: 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). Originality/value: 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.