Indicators for complex innovation systems

[Sylvan Katz]

Katz, J. S., 2006: Indicators for complex innovation systems. Research 
Policy, 35, 893-909.

Preprint
<http://www.sussex.ac.uk/Users/sylvank/pubs/ICIS-RP.pdf>

ABSTRACT

Performance indicators such as national wealth (GDP per capita), R&D 
intensity (GERD/GDP) and scientific impact (citations/ paper) are used to 
compare innovation systems. These indicators are derived from the ratio of 
primary measures such as population, GDP, GERD and papers. Frequently they 
are used to rank members of an innovation system and to inform decision 
makers. This is illustrated by the European Research Area S&T indicators 
scoreboard used to compare the performance of member states.

A formal study of complex systems has evolved over the past few decades 
from common observations made by researchers from many fields. Complex 
systems are dynamic and many of their properties emerge from the 
interactions among the entities in them. They also have a propensity to 
exhibit power law or scaling correlations between primary measures used to 
characterize them.

Katz [Katz, J.S., 2000. Scale independent indicators and research 
assessment. Science and Public Policy 27, 23?36] showed that scientific 
impact (citations/paper) scales with the size of the group (papers). In 
this paper it will be shown that two other common measures, R&D intensity 
and national wealth, scale with the sizes of European countries and 
Canadian provinces. Some of these scaling correlations are predictable. 
These findings illustrate that a performance indicator derived from the 
ratio of two measures may not be properly normalized for size.

This paper argues that innovation systems are complex systems. Hence 
scaling correlations are expected to exist between the primary measures 
used to characterize them. These scaling correlations can be used to 
construct scale-independent (scale-adjusted) indicators and models that are 
truly normalized for size. Scale-independent indicators can more accurately 
inform decision makers how groups of different sizes contribute to an 
innovation system. The ranks of member groups of an innovation system by 
scale-independent indicators can be subtly and profoundly different than 
the ranks given by conventional indicators. The differences can result in a 
shift in perspective about the performance of members of an innovation 
system that has public policy implications.


Keywords: Complex system; Emergent; Indicator; Power law; Innovation system

Dr. J. Sylvan Katz, Visiting Fellow
SPRU, University of Sussex
http://www.sussex.ac.uk/Users/sylvank

Adjunct Professor
Mathematics & Statistics, University of Saskatchewan

Associate Researcher
Institut national de la recherche scientifique, University of Quebec