Knowledge sharing processes are a central feature of the functioning of government. This has become even more evident with the rise of digital government initiatives, as these have a networking effect on bureaucracies. With multiple agencies and multidisciplinary knowledge coming together, it is necessary to combine and reconnect the required knowledge. Based on empirical data from four digital government projects (DGPs) in Switzerland and the United States of America, a theoretical model for knowledge sharing in DGPs is proposed. The model ties together processes and content of knowledge sharing through two task dimensions, each of them subdivided into two phases: (1) Conception and implementation of the project, and (2) Exploration and exploitation of knowledge. I show that the implementation of DG requires a balanced mix of exploration and exploitation of knowledge, where exploration is more important in the conceptual phase, and exploitation becomes more fruitful in the implementation phase. I found that DGPs rely on sparse networks during the conceptual phase of the project, and tend to employ teams or tightly-bound groups as the project moves towards implementation.

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