Optimal research team composition: data envelopment analysis of Fermilab experiments

Abstract

We employ data envelopment analysis on a series of experiments performed in Fermilab, one of the major high-energy physics laboratories in the world, in order to test their efficiency (as measured by publication and citation rates) in terms of variations of team size, number of teams per experiment, and completion time. We present the results and analyze them, focusing in particular on inherent connections between quantitative team composition and diversity, and discuss them in relation to other factors contributing to scientific production in a wider sense. Our results concur with the results of other studies across the sciences showing that smaller research teams are more productive, and with the conjecture on curvilinear dependence of team size and efficiency.

Sandro Radovanović

Assistant Professor at University of Belgrade

My research interests include machine learning, development and design of decision support systems, decision theory, and fairness and justice concepts in algorithmic decision making.