Predictors of citations
An analysis of highly-cited-papers in hospitality and tourism research using a machine learning approach
Dados Bibliográficos
| ID | 21699722 |
|---|---|
| Autores | Eray Polat (0000-0003-1470-4298, Gümüşhane University, autor correspondente), Fatih Çelik (0000-0002-7960-4477, Trabzon University), Hasan Evrim Arici (0000-0003-3429-4513, Kastamonu University), Mehmet Ali Koseoglu (0000-0001-9369-1995, Metropolitan State University) |
| Ano | 2026 |
| Volume | 29 |
| Fascículo | 6 |
| Páginas | 1117-1138 |
| Data de publicação | 2026-03-19 |
| Peer Reviewed | Sim |
| Open Access | Não |
| Tipo | ARTICLE |
| Periódico | Current Issues in Tourism (JOURNAL) |
| Identificadores do periódico | ISSN: 1368-3500 • E-ISSN: 1747-7603 |
| Editora | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/13683500.2024.2446410 |
| OpenAlex | W4405873933 |
| Idioma | EN |
| Citações recebidas | 3 |
| Referências citadas | 72 |
In the dynamic nature of hospitality and tourism (H&T) research, it is increasingly difficult to distinguish highly-cited-papers (HCPs) due to the rapid proliferation of publications. This study employs machine learning techniques to identify the predictors of citation counts in H&T research over both short-term (5-year) and long-term (20-year) periods using HCPs. The analysis integrates a theoretical framework comprising normative theory and social constructivist theory. The findings indicate that international citation, PlumXmetrics, and early citations are the most effective determinants in both periods. Furthermore, while the importance of international citations is evident in both periods, the order of importance of the other two predictors changes. PlumXmetrics are more important in the long-term, while early citations are more important in the short-term. In conclusion, this comprehensive and up-to-date study of citation dynamics provides valuable insights for scholars and other stakeholders interested in enhancing the visibility and influence of H&T literature
Business · Citation · Data science · Geography · Hospitality · Library science · Normative · Political science · Sociology · Tourism · Visibility · Computer Science · Diverse Aspects of Tourism Research · Hospitality and Tourism Education · Psychology · Wine Industry and Tourism · Marketing
Which factors help authors produce the highest impact research? Collaboration, journal and document properties
Characteristics of highly cited papers
Factors affecting number of citations
PDP
Random Forests
Past, present and future
Measuring the influence of non-scientific features on citations
How the high-impact papers formed? A study using data from social media and citation
Automatic prediction of citability of scientific articles by stylometry of their titles and abstracts
Impact of the reference list features on the number of citations
The relationship between highly-cited papers and the frequency of citations to other papers within-issue among three top information science journals
Beyond addressing multicollinearity
Identifying potential breakthrough research
Identification of the most important external features of highly cited scholarly papers through 3 (i.e., Ridge, Lasso, and Boruta) feature selection data mining methods
Covid-19
Article Contribution and Subsequent Citation Rates
Citation practices in tourism research
| Obras citantes distintas | 3 |
|---|---|
| Citações por ano | 3 |
| Intervalo de citações | 2025 - 2026 (2) |
| Velocidade de citação | current |
| Altamente citado | Não |
| Tipos de citação | Neutras: 3 |