54 research outputs found
What is a complex innovation system?
Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too
Recommended from our members
Scale-independent Indicators and Research Evaluation
Does the size of institution or system affect the amount of recognition it receives, the impact it has on others and the degree to which it collaborates? Is it possible to optimise size to maximise recognition, impact and co-operation? This paper demonstrates that some conventional indicators used in research evaluation may fail to account for the non-linearity between size and performance. This can result in an over- and under-estimation of the research performance of both large and small institutions and nations. This paper shows that a power law relationships exists between recognition or impact and (a) the publishing size of scientific communities within an OECD science system and (b) the publishing size of a research community across OECD science systems or institutions in a science system. Also, a power law relationship exists between the amount of various types of collaboration and the ublishing size of institutions. It also shows that there are power law relationships between publishing size and HERD or number of researchers. The exponent of the power law is sometimes greater than 1.0 indicating the existence of a "Matthew effect". Other times it is less than 1.0 indicating an "inverse Matthew effect". A power law is the common signature of a scale-independent process that can be typified by a geometric fractal and other self-similar properties. A new class of scale-independent indicators is developed to overcome the inequity produced by some non-linear characteristics commonly measured when evaluating research performance
Recommended from our members
Bibliometric indicators and the social sciences
Social science research is published in a wider variety of publication types and addresses more national issues than natural science research. This makes the construction of internationally comparable bibliometric indicators somewhat problematic. However, in internationally oriented fields, like economics and psychology, bibliometric indicators can provide a reasonable measure of the publishing size and impact of these research communities. The UK share of the world publications in the social sciences and behavioural sciences increased between 1981 and 1998 according to data derived from the National Science Indicators on diskette (NSIOD) produced by the Institute for Scientific Information (ISI). The UK has its largest percentage share of world papers in environmental studies and geography & development. Its strongest growth in percentage share of world papers was in the management sciences. The UK share of psychology publications grew from 7% to 10% and economics publications grew from 10% to 13% over the 18-year time interval. England displayed its greatest growth in the percentage share of UK publications in rehabilitation, Scotland in communications, Wales in library & information sciences and North Ireland in psychology. It is shown in this report that the conventional impact indicator (citations/paper) gives a distorted view of the UK's impact because impact increases non-linearly with publishing size. A new indicator, the relative international citation impact (RICI) indicator that has been corrected to account for the non-linear relationship between impact and publishing size, is introduced. Using a sequence of fourteen 5-year overlapping time periods, the RICI indicator portrays a different picture of the impact of UK psychology and economics research than the conventional impact indicator. It shows that UK impact exceeded the US impact in psychology across all 13 time intervals and it matched or exceeded the US impact in economics in 8 out of the 13 interval
Software and Peer-Review: the Rousseau case
Brendan and Ronald Rousseau's article with the downloadable software is an exciting and long over due experiment for Cybermetrics. However, it raises aninteresting question. Should the software and user documentation be subject to critical peer-review?Peer reviewe
- …