BIBLIOMETRIC ANALYSIS OF PUBLICATIONS ON RECOMMENDER SYSTEMS IN TOURISM: WEB OF SCIENCE CASE

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ÇUHADAR M.

Advances in Hospitality and Tourism Research, cilt.14, sa.2, ss.193-231, 2026 (ESCI, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 14 Sayı: 2
  • Basım Tarihi: 2026
  • Doi Numarası: 10.30519/ahtr.1542430
  • Dergi Adı: Advances in Hospitality and Tourism Research
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus, CAB Abstracts
  • Sayfa Sayıları: ss.193-231
  • Anahtar Kelimeler: artificial intelligence, bibliometric analysis, machine learning, recommender systems, tourism
  • Açık Arşiv Koleksiyonu: AVESİS Açık Erişim Koleksiyonu
  • Süleyman Demirel Üniversitesi Adresli: Evet

Özet

This study conducts a comprehensive bibliometric analysis of 495 scholarly publications on recommender systems (RSs) in tourism indexed in the Web of Science database, with the aim of mapping research trends, identifying influential contributions, and revealing key scholarly networks. The findings indicate that artificial intelligence (AI) and machine learning (ML) constitute the dominant technological drivers, with computer science and information systems serving as the leading disciplinary domains. Notably, there is a growing interdisciplinary integration with social sciences, environmental studies, and business-related research. Europe and Asia emerge as the primary contributors, particularly Spain, China, and Italy, which demonstrate strong research output and collaborative networks. Co-authorship and co-citation analyses reveal four major research clusters centred on hybrid recommendation models, deep learning approaches, and personalized user experience optimization. The results underscore the field’s accelerating interdisciplinary expansion and its concentration within specific global hubs. By systematically mapping the intellectual landscape, identifying existing research gaps, and outlining future research trajectories, this study offers valuable insights for academics, practitioners, and policymakers seeking to understand the evolution, current state, and potential impact of RSs within the tourism sector.