Tour guiding technologies: a bibliometric analysis, mapping trends and future research agenda
İlker Şahin et al.
Abstract
Purpose This study aims to map research trends and innovations in tour guiding technologies including robotics, artificial intelligence (AI), augmented reality (AR) and virtual reality (VR) alongside an examination of their integration into tour guiding profession. Design/methodology/approach A systematic bibliometric methodology was used, analyzing 205 documents filtered from an initial pool of 1,506 articles. Data were processed and visualized using VOSviewer and Biblioshiny to uncover research patterns, collaborations and thematic clusters. Co-citation analysis, bibliographic coupling and comparative evaluations were used to highlight key research foci and methodologies. Findings The study identifies core research themes, theoretical foundations and emerging trends to provide a comprehensive understanding of the field. The co-citation analysis reveals significant emphasis on electronic tourist guides, context-aware tour guiding systems, AR, tour guide robots and tour guiding applications. Widely used theoretical frameworks include the technology acceptance model (TAM), unified theory of acceptance and use of technology (UTAUT) and computers as social actors (CASA) paradigm. Overall, the findings highlight dominant scholarly directions and practical applications of technological advancements in tour guiding. Originality/value This study contributes uniquely to the literature by offering a comprehensive mapping of technological integration in tour guiding. It identifies critical research clusters, theoretical underpinnings and emerging themes, while providing actionable recommendations for future research and industry practice. The proposed roadmap emphasizes how robotics, AI, AR and VR can enhance the effectiveness, accessibility and appeal of the tour guiding profession.
2 citations
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.25 × 0.4 = 0.10 |
| M · momentum | 0.55 × 0.15 = 0.08 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.