  An original cross sectional dataset referring to a medium sized Italian
university is implemented in order to analyze the determinants of scientific
research production at individual level. The dataset includes 942 permanent
researchers of various scientific sectors for a three year time span (2008 -
2010). Three different indicators - based on the number of publications or
citations - are considered as response variables. The corresponding
distributions are highly skewed and display an excess of zero - valued
observations. In this setting, the goodness of fit of several Poisson mixture
regression models are explored by assuming an extensive set of explanatory
variables. As to the personal observable characteristics of the researchers,
the results emphasize the age effect and the gender productivity gap, as
previously documented by existing studies. Analogously, the analysis confirm
that productivity is strongly affected by the publication and citation
practices adopted in different scientific disciplines. The empirical evidence
on the connection between teaching and research activities suggests that no
univocal substitution or complementarity thesis can be claimed: a major
teaching load does not affect the odds to be a non-active researcher and does
not significantly reduce the number of publications for active researchers. In
addition, new evidence emerges on the effect of researchers administrative
tasks, which seem to be negatively related with researcher's productivity, and
on the composition of departments. Researchers' productivity is apparently
enhanced by operating in department filled with more administrative and
technical staff, and it is not significantly affected by the composition of the
department in terms of senior or junior researchers.
