This day is devoted to the study of the problem of organizational design and information flow in networks. Recently, scholars started to apply information theory to the study of organizational structures, and the corresponding information processing principles of organizations (Christensen and Knudsen, 2010). This gives rise to the more general question how information theory and network theory can be applied to study questions of strategic organization.
Concerning information flow in networks, there has been some current results, some of which have been achieved in Jürgen Jost's group. Given the success of the application of information theory to questions of organizational design, we want to share these results with scholars studying organizational design.
To apply the theory of information flow in networks, the relevant quantities, like information transfer or storage need to be carefully defined, in order to distinguish what is new at each node from what that node can derive from its own history and to quantify information flow and thereby make different structures comparable. Also, aspects of forgetting can be analyzed within such a framework. This may become relevant, for instance, when a member of an organization is replaced by a new one. Secondly, the impact of the network structure, like the presence or absence of certain motifs, can be analyzed. We suppose that this can be relatively directly translated into organizational structures. For instance, starting from a hierarchical structure, we should answer the question how a limited number of crosslinks should be inserted so as to optimize the information flow. In any case, the expertise in network analysis in Jürgen Jost's group can directly be applied to evaluate designs of organizational networks. Thirdly, information transfer and storage typically vary a lot between a transient phase and a final equilibrium. The transient phase can be interpreted as some kind of a learning process, and in fact, one can analyze the effect of particular learning rules. (These issues have been intensively investigated in the neural network literature; we also possess expertise in this field.)