SynthesisF1000Research2026
Mapping Research Trends in AI-Based Tourism and Hospitality Marketing: A Bibliometric and Thematic Review.
Synthesis in F1000Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
- Mapping Research Trends in AI-Based Tourism and Hospitality Marketing: A Bibliometric and Thematic Review.F1000Research · 2026Pooled it
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) has fundamentally transformed tourism and hospitality marketing through enhanced data-driven decision-making, personalized customer experiences, and intelligent destination management. However, the field lacks a comprehensive synthesis of its intellectual landscape and thematic evolution, limiting understanding of research trajectories and emerging directions. Methods: A systematic literature review following the SPAR-4-SLR procedure was conducted on 320 peer-reviewed papers published between 2003 and 2025, sourced from the Scopus database. Publication trends, leading journals, prolific authors, trending areas, and bibliographic coupling of documents and countries were visualized using bibliometric analysis tools (VOSviewer and Biblioshiny). Thematic analysis employed keyword co-occurrence networks to identify emerging research themes. Results: Academic publications on AI in tourism and hospitality demonstrated a significant surge during 2017-2020, reflecting the industry's growing emphasis on smart marketing applications. Thematic analysis identified four major research clusters: (i) Digital Influence and Tourist Behaviour Analytics; (ii) AI-Enabled Smart Tourism and Commerce Ecosystems; (iii) Technology-Driven Hospitality and Experience Innovation; and (iv) Data-Driven Decision Making in Predictive Tourism Modelling. Conclusions: This bibliometric and thematic assessment reveals the evolving intellectual landscape of AI applications in tourism and hospitality marketing, documenting substantive research growth and the emergence of distinct thematic clusters that shape current and future research agendas in this dynamic field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.