Summary The purpose of this paper is to investigate whether geographical concentration can act as a supplement to the Journal Impact Factor (JIF). The results indicate that the use of a geographical concentration measure opens up new possibilities for analyses of the development of geographic diversion over time. In contrast to measures used in earlier studies the precise strength of the geographical concentration index as a measure of diversion is that it represents diversion as a single value that can be followed over time. The results show wider geographic distribution of European economics journals in the 1980s compared to the American economics journals whereas there seems to be no difference in geographic dispersion in the 1990s.
There is a well-established literature on the use of concentration measures in informetrics. However, these works have usually
been devoted to measures of concentration within a productivity distribution. In a pair of recent papers the author introduced two new measures, both based on the Gini ratio,
for measuring the similarity of concentration of productivity between two different informetric distributions. The first of these was derived from Dagum's notion of relative economic affluence;
the second - in some ways analogous to the correlation coefficient - is completely new. The purpose of this study is to develop
a purely empirical approach to comparative studies of concentration between informetric data sets using both within and between measures thereby greatly extending the original study which considered just two data sets for purposes of illustration of
the methods of calculation of the measures.
Relative concentration theory studies the degree of inequality between two vectors (a1,...,aN) and (α1,...,αN). It extends concentration theory in the sense that, in the latter theory, one of the above vectors is (1/N,...,1/N) (N coordinates).
When studying relative concentration one can consider the vectors (a1,...,aN) and (α1,...,αN) as interchangeable (equivalent) or not. In the former case this means that the relative concentration of (a1,...,aN) versus (α1,...,αN) is the same as the relative concentration of (α1,...,αN) versus (a1,...,aN). We deal here with a symmetric theory of relative concentration. In the other case one wants to consider (a1,...,aN) as having a different role as (α1,...,αN) and hence the results can be different when interchanging the vectors. This leads to an asymmetric theory of relative concentration.
In this paper we elaborate both models. As they extend concentration theory, both models use the Lorenz order and Lorenz curves.
For each theory we present good measures of relative concentration and give applications of each model.
It is a well-known empirical fact that when informetric processes are observed over an extending period of time, the entire
shape of the distribution changes. In particular, it has been shown that concentration aspects change. In this paper the recently
introduced co-concentration coefficient (C-CC) is investigated via simple stochastic models of informetric processes to investigate
its time-dependence. It is shown that it is important to distinguish between situations where the zero-producers can be counted
and those where they cannot. A previously published data set is used to illustrate how the empirical C-CC develops in time
and the general features are compared with those derived from the theoretical model.
Authors:M. Bonitz, E. Bruckner, and Andrea Scharnhorst
In this paper we extend our studies to the micro-structure of the Matthew effect for countries (MEC). The MEC allows the ranking
of countries by their Matthew Index. The rank distribution of countries, observable only at a macro-level, has its roots in
re-distribution processes of citations in every journal of the database. These re-distributed citations we call Matthew citations.
Data for 44 countries and 2712 journals (based on theScience Citation Index) are analyzed. The strength of the contribution of the individual journals to the MEC (their number of Matthew citations)
is skewly distributed. Due to this high concentration of the MEC we are able to define a new type of journal the Matthew core
journal: 145 Matthew core journals account for 50% of the MEC. These journals carry a high potential of gaining a surplus
of citations over what is expected and the risk of losing a high number of citations as well.
Concentration of resources continues to be an important issue in the formulation of policy for the support of university research. In this paper, techniques for quantitatively assessing two dimensions of this issue, between and within committee concentrations, are developed. These techniques are applied in an analysis of the peer-adjudicated grants of the National Research Council of Canada for the years 1964–1974 inclusive. Results indicate that although between committee concentrations have responded to changing priorities for university research, within committee concentrations have remained remarkably stable over this decade. This is seen as having important implications for recent attempts at re-orienting university research in Canada.
The applicability of the Bradford law to the R&D expending of firms is examined and its usefulness is proved. It successfully identifies core firms, peripheral firms and minor firms. It also provides a measure to evaluate the degree of R&D concentration to a small number of firms.
Using the artificial example of perfectly stratified samples, we have shown the effect different sampling designs have on the determination of concentration values. More concretely, we have studied the following four cases: sampling of items in the case the number of sources is known (we have further considered the cases when there are many items in every source and when this is not so); sampling of items in the case the number of sources is unknown, and finally, sampling of sources.
This article explores the concentration in the global plant molecular life science research output. In the past 15 years,
especially the share of articles which refer to the model organism A. thaliana has increased rapidly. Citation analyses show an even greater rise in the importance of this organism. Attempts are discussed
to come to a scientometric definition of model organisms. For this purpose a comparison is made with applied microbiology.
However, few shared scientometric characteristics were found which could help characterise model organisms. A distinction
between major economic organisms and model organisms will therefore continue to rely on qualitative data.