Managing project-based learning is becoming an increasingly important part of project management. This article presents a comparative case study of 12 cases of knowledge transfer between temporary inter-organizational projects and permanent parent organizations. Our set-theoretic analysis of these data yields two major findings. First, a high level of absorptive capacity of the project owner is a necessary condition for successful project knowledge transfer, which implies that the responsibility for knowledge transfer seems to in the first place lie with the project parent organization, not with the project manager. Second, none of the factors are sufficient by themselves. This implies that successful project knowledge transfer is a complex process always involving configurations of multiple factors. We link these implications with the view of projects as complex temporary organizational forms in which successful project managers need to cope with complexity by simultaneously paying attention to both relational and organizational processes.
The current paper combines arguments from the social capital and group cognition literature to explain two different processes through which communication network structures and intra group conflict influence groups' cognitive complexity (GCC). We test in a sample of 44 groups the mediating role of intra group conflict in the relationship between communication network density and fragmentation on the one hand and groups' cognitive complexity on the other hand. The results show that network fragmentation has a positive effect on GCC by fostering task conflict, while network density has a positive impact on GCC by reducing relationship conflict in student groups. The paper makes an important contribution to both theory and practice in the field of collaborative learning, by exploring how groups' affective and a cognitive dynamics impact on emergent collective cognitive structures.
Visualization is an important aspect of both exploration and communication of categorical as well as relational data. Graphical displays of policy networks are particularly attractive, since they enable authors to display in a compact way the relevant actors in a network, how they are related to each other, and what the overall structure looks like. Sociograms were early companions of social network analysis, but have received surprisingly little attention during the following decades. Only in the last few years has easy accessibility to quality computing and graphic equipment revived a now rapidly growing interest.In this paper, we analyze the problem of visualizing policy networks. We first argue why network visualization is important and non-trivial. Then we show that current methods are somewhat ad hoc in their attempt to convey information contained in a network.Our main contribution is a systematic approach to network visualization, closely following the general principles of information visualization. It provides a generic formalization which may serve as a guideline for further developments.
KEY WORDS • algorithm • network visualization • sociogram
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.