A Framework to Assess the Citation Performance of Complex Innovation Systems

Abstract

Scientometric indicators are useful to evaluate the relevance of scientific research, to prepare rankings, and to evaluate and inform research policies. That is why the choice of appropriate indicators is a matter of primary concern. This article aims to introduce a framework to decide the appropriate type of indicator for assessing the citation-based performance of complex innovation systems. The framework is two-fold: First, it brings the methodology to decide when the use of standard average based indicators is granted, and when scale-invariant indicators are mandatory. Second, it provides the procedures to build scale-invariant indicators to assess the relative impact of complex innovation systems. The framework is validated empirically through the evaluation of the relative impact of the Chilean science system in 2017. The result suggests that the Chilean science system has characteristics of a complex innovation system such as the distribution of citations fits to a power law with an exponential cutoff −2.77±0.09 and a power-law correlation between the size of the system and its impact 1.29±0.11. Furthermore, the framework shows to be efficient to compare fields of vastly different sizes.