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Identifying Researchers’ Publication Strategies by Clustering Publication and Impact Data

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Abstract

Identifying strategies for researchers has been a problem investigated from different perspectives, such as choosing research topics or the effect of partner selection. Its importance lies in the effect these choices have in the long term and the importance of taking them into account at the beginning of the scientific career. This study aims to identify publication strategies through behavioral observations for researchers belonging to the engineering area. We analyzed 3,156 researchers affiliated to Mexican National Researchers System with publication data from 2007 to 2016. Publication strategies are defined as a combination of two-year productivity and collaboration indicators, and their success is reflected in terms of citations received in a three-year time window. Using clustering techniques, we identified differentiated patterns aligned with a given citation level. As a result of our case study, we identified low-impact and high-impact publication strategies used by Mexican researchers, which in turn can be used for designing long-term strategies for researchers. Our methodology can be used to discover publication strategies in other areas and geographical regions.

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Notes

  1. Conacyt. Sistema nacional de investigadores. https://www.conacyt.gob. mx/index.php/el-conacyt/sistema-nacional-de-investigadores.

  2. Gobierno de Mexico. Datos abiertos de Mexico. https://www.datos.gob. mx/

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Acknowledgements

Partial financial support was received from CONACYT and Tecnologico de Monterrey.

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Authors and Affiliations

  1. Tecnológico de Monterrey, Av. Eugenio Garza Sada 2501, Col. Tecnológico, 64849, Monterrey, NL, Mexico

    Gilberto Ayala-Bastidas, Hector G. Ceballos, Sara E. Garza & Francisco J. Cantu-Ortiz

Authors
  1. Gilberto Ayala-Bastidas
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  2. Hector G. Ceballos
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  3. Sara E. Garza
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  4. Francisco J. Cantu-Ortiz
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Correspondence to Hector G. Ceballos.

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Appendix A: Multiple Regression Coefficients

Appendix A: Multiple Regression Coefficients

We present the coefficients of the regression models, which can be used for explaining the relevance of every productivity and collaboration indicator on citation.

See Tables

Table 6 OLS Regression Results with Cites in 3-years as dependent attribute and Least Squares method for Productive dataset
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6,

Table 7 OLS Regression Results with Cites in 3-years as dependent attribute and Least Squares method for Collaborative dataset
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7,

Table 8 OLS Regression Results with Cites in 3-years as dependent attribute and Least Squares method for Collaborative dataset
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8, and

Table 9 OLS Regression Results with Cites in 3-years as dependent attribute and Least Squares method for Complete dataset
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9.

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Ayala-Bastidas, G., Ceballos, H.G., Garza, S.E. et al. Identifying Researchers’ Publication Strategies by Clustering Publication and Impact Data. Pub Res Q 37, 347–363 (2021). https://doi.org/10.1007/s12109-021-09832-7

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