Predicting the time to first citation for medical articles using survival analysis and the association between this time and citation counts
Thailand is transitioning to a knowledge-based economy that relies on a highly skilled workforce and the leveraging of innovative research. This has led to top universities aiming to become world-class institutions. However, Thai universities’ citation indicators still need to be improved, meaning t...
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Veröffentlicht in: | Scientometrics 2025-01 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Thailand is transitioning to a knowledge-based economy that relies on a highly skilled workforce and the leveraging of innovative research. This has led to top universities aiming to become world-class institutions. However, Thai universities’ citation indicators still need to be improved, meaning that bibliometric research is needed to find appropriate new strategies for achieving this. We investigated bibliometric data for Thailand and made a comparison with Malaysia. Appropriate models for predicting the time to first citation were also found. Survival analysis and Cox regression were applied in the prediction models. The sample used consisted of 2000 medical articles with authors from four universities. Slight differences were found between the bibliometric data for Thailand and Malaysia. The journal quality was found to be a strong predictor of the time to first citation. Several other statistically significant main variables and interaction variables were found, including the number of citations. Citation counts remain a recognized indicator of research potential. Faster publication can increase the number of citations, but care needs to be taken regarding self-citation. It is notable that Malaysian universities have a higher proportion of cross-disciplinary publications compared with Thai universities. |
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ISSN: | 0138-9130 1588-2861 |
DOI: | 10.1007/s11192-025-05237-x |