Social network analytics for advanced bibliometrics: referring to actor roles of management journals instead of journal rankings

Impact factors are commonly used to assess journals relevance. This implies a simplified view on science as a single-stage linear process. Therefore, few top-tier journals are one-sidedly favored as outlets, such that submissions to top-tier journals explode whereas others are short of submissions. Consequently, the often claimed gap between research and practical application in application-oriented disciplines as business administration is not narrowing but becoming entrenched. A more complete view of the scientific system is needed to fully capture journalsA ' contributions in the development of a discipline. Simple citation measures, as e.g. citation counts, are commonly used to evaluate scientific work. There are many known dangers of miss- or over-interpretation of such simple data and this paper adds to this discussion by developing an alternative way of interpreting a discipline based on the positions and roles of journals in their wider network. Specifically, we employ ideas from the network analytic approach. Relative positions allow the direct comparison between different fields. Similarly, the approach provides a better understanding of the diffusion process of knowledge as it differentiates positions in the knowledge creation process. We demonstrate how different modes of social capital create different patterns of action that require a multidimensional evaluation of scientific research. We explore different types of social capital and intertwined relational structures of actors to compare journals with different bibliometric profiles. Ultimately, we develop a multi-dimensional evaluation of actor roles based upon multiple indicators and we test this approach by classifying management journals based on their bibliometric environment.