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• W2098985147 abstract "In this paper we extend a multi-agent simulation model for interorganizational learning to explore the issue of learning decay on adaptation performance. Researchers agree that project networks can support the development and exchange of new knowledge among firms, however, the question of learning beyond the firm at the boundaries between firms or at the level of the network remains less explored. Previous research has shown that relational instability in networks can slow learning and that task interdependence moderates the impact of increasing relational instability on project network adaptation performance. Research to date on this phenomenon neglects the effect of forgetting which may impact the performance of project networks where firms work together infrequently. We find these gaps in time between learning events can negatively impact the adaptation rate of relationally unstable project networks. These findings are critical to developing a comprehensive understanding of learning in interorganizational project networks." @default.
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• W2098985147 date "2009-12-13" @default.
• W2098985147 modified "2023-09-23" @default.
• W2098985147 title "Simulating the effect of learning decay on adaptation performance in project networks" @default.
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• W2098985147 doi "https://doi.org/10.5555/1995456.1995825" @default.
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