Performance-related differences of bibliometric statistical properties of research groups: Cumulative advantages and hierarchically layered networks

In this paper we distinguish between top-performance and lower performance groups in the analysis of statistical properties of bibliometric characteristics of two large sets of research groups. We find intriguing differences between top-performance and lower performance groups, but also between the two sets of research groups. Particularly these latter differences are interesting, as they may indicate the influence of research management strategies. Lower performance groups have a larger scale-dependent cumulative advantage than top-performance groups. We also find that regardless of performance, larger groups have less not-cited publications. We introduce a simple model in which processes at the micro level lead to the observed phenomena at the macro level. Top-performance groups are, on average, more successful in the entire range of journal impact. We fit our findings into a concept of hierarchically layered networks. In this concept, the network of research groups constitutes a layer of one hierarchical step higher than the basic network of publications connected by citations. The cumulative size-advantage of citations received by a group looks like preferential attachment in the basic network in which highly connected nodes (publications) increase their connectivity faster than less connected nodes. But in our study it is size that causes an advantage. In general, the larger a group (node in the research group network), the more incoming links this group acquires in a non-linear, cumulative way. Moreover, top-performance groups are about an order of magnitude more efficient in creating linkages (i.e., receiving citations) than the lower performance groups.