The conundrum of research productivity: a study on sociologists in Italy
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This paper aims to understand the influence of institutional and organisational embeddedness on research productivity of Italian sociologists. We looked at all records published by Italian sociologists in Scopus from 1973 to 2016 and reconstructed their co-authorship patterns. We built an individual productivity index by considering the number and type of records, the impact factor of journals in which these records were published and each record’s citations. We found that sociologists who co-authored more frequently with international authors were more productive and that having a stable group of co-authors had a positive effect on the number of publications but not on citations. We found that organisational embeddedness has a positive effect on productivity at the group level (i.e., sociologists working in the same institute), less at the individual level. We did not found any effect of the scientific disciplinary sectors, which are extremely influential administratively and politically for promotion and career in Italy. With all caveats due to several limitations of our analysis, our findings suggest that internationalisation and certain context-specific organisational settings could promote scientist productivity .
KeywordsSociologists Italy Research productivity Internationalisation Co-authorship
- Abramo, G., D’Angelo, C. A., & Di Costa, F. (2008). Assessment of sectoral aggregation distortion in research productivity measurements. Research Evaluation, 17(2), 111–121. Retrieved from http://rev.oxfordjournals.org/content/17/2/111.short.
- Abramo, G., D’Angelo, C. A., & Di Costa, F. (2017). The effects of gender, age and academic rank on research diversification. Scientometrics, 1–15.Google Scholar
- ANVUR. (2014). Confronto tra dimensione e qualita delle strutture universita. Retrieved from http://www.anvur.org/rapporto/stampa.php.
- Becher, T., & Trowler, P. (2001). Academic tribes and territories: Intellectual enquiry and the culture of disciplines. London: McGraw-Hill Education.Google Scholar
- Bellotti, E., Guadalupi, L., & Conaldi, G. (2016a). Comparing fields of sciences: Multilevel networks of research collaborations in Italian Academia. In Multilevel network analysis for the social sciences (pp. 213–244). Springer.Google Scholar
- Blackburn, R. T., Behymer, C. E., & Hall, D. E. (1978). Research note: Correlates of faculty publications. Sociology of Education, 132–141.Google Scholar
- Burt, R. S. (2005). Brokerage and closure: An introduction to social capital. Oxford: Oxford University Press.Google Scholar
- Butts, C. T. (2016). Sna: Tools for social network analysis. Retrieved from https://CRAN.R-project.org/package=sna.
- Chatzimichael, K., Kalaitzidakis, P., & Tzouvelekas, V. (2016). Measuring the publishing productivity of economics departments in Europe. Scientometrics, 1–20.Google Scholar
- Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695. Retrieved from http://igraph.org.
- de Price, D. J. S. (1970). Citation measures of hard science, soft science, technology, and nonscience. In C. E. Nelson & D. K. Pollock (Eds.), Communication among scientists and engineers (pp. 3–22). Lexington, MA: Heath.Google Scholar
- Garfield, E. (1980). Premature discovery or delayed recognition-why. Current Contents, 21, 5–10.Google Scholar
- Hancock, K. J., & Baum, M. (2010). Women and academic publishing: Preliminary results from a survey of the ISA membership. In The international studies association annual convention, new orleans, la.Google Scholar
- Hlavac, M. (2015). Stargazer: Well-formatted regression and summary statistics tables. Cambridge, USA: Harvard University. Retrieved from http://CRAN.R-project.org/package=stargazer.
- Kuzhabekova, A. (2011). Impact of co-authorship strategies on research productivity: A social-network analysis of publications in russian cardiology (PhD thesis). University of Minnesota.Google Scholar
- Long, J. S. (1978). Productivity and academic position in the scientific career. American Sociological Review, 889–908.Google Scholar
- Long, J. S., & McGinnis, R. (1981). Organizational context and scientific productivity. American Sociological Review, 422–442.Google Scholar
- Meho, L. I., & Yang, K. (2007). Impact of data sources on citation counts and rankings of LIS faculty: Web of Science versus Scopus and Google Scholar. Journal of the Association for Information Science and Technology, 58(13), 2105–2125.Google Scholar
- Narin, F., & Whitlow, E. S. (1991). Measurement of scientific cooperation and coauthorship in cec-related areas of science. Commission of the European Communities Directorate-General Telecommunications, Information Industries and Innovation.Google Scholar
- National agency for the evaluation of the university and research systems. (2013). Retrieved from http://www.unive.it/nqcontent.cfm?a_id=161248.
- Nygaard, L. P. (2015). Publishing and perishing: An academic literacies framework for investigating research productivity. Studies in Higher Education, 1–14.Google Scholar
- R Core Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/.
- Rumsey, A. R. (2006). The association between co-authorship network structures and successful academic publishing among higher education scholars.Google Scholar
- Shapin, S. (2009). The scientific life: A moral history of a late modern vocation. Chicago: University of Chicago Press.Google Scholar
- van der Loo, M. (2014). The stringdist package for approximate string matching. The R Journal, 6(1), 111–122. Retrieved from https://CRAN.R-project.org/package=stringdist.
- Weick, K. E. (2016). Perspective construction in organizational behavior. Annual Review of Organizational Psychology and Organizational Behavior, (0).Google Scholar
- Wickham, H. (2009). Ggplot2: Elegant graphics for data analysis. Springer-Verlag New York. Retrieved from http://ggplot2.org.
- Wickham, H., & Francois, R. (2016). Dplyr: A grammar of data manipulation. Retrieved from https://CRAN.R-project.org/package=dplyr.
- Wilsdon, J., Allen, L., Belfiore, E., Campbell, P., Curry, S., Hill, S., … others. (2015). The metric tide: Report of the independent review of the role of metrics in research assessment and management. hefce.Google Scholar
- Zuur, A., Ieno, E., Walker, N., Saveliev, A., & Smith, G. (2009). Mixed effects models and extensions in ecology with r. gail m, krickeberg k, samet jm, tsiatis a, wong w, editors. New York, NY: Spring Science and Business Media.Google Scholar