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• W4310365411 endingPage "100175" @default.
• W4310365411 startingPage "100175" @default.
• W4310365411 abstract "Organizational learning research is based on the idea that individuals can learn more together than alone. Network connections between members of an organization allow them to engage in a mutual learning process whereby they share what they discover and potentially learn and improve their performance at a faster rate. Existing research highlights the importance of network structure in facilitating mutual learning, with a centralized network expected to improve learning and performance when the unfamiliar assignment is complex. An example of an unfamiliar complex assignment is new product development. The features of a new product and how those features should be combined are unknown. In a centralized network, members are connected to a focal individual but disconnected from each other. The disconnects facilitate individual search and experimentation, increasing the odds that a superior solution will be discovered. To understand how network centralization affects mutual learning and performance when an unfamiliar assignment is complex, this chapter offers a theory-building exercise. The exercise is motivated by a conflicting empirical result. Recent research indicates that for a complex task, individuals learning in a decentralized network, a network that contains a relatively large number of direct and indirect relationships, can outperform individuals learning in a centralized network. The exercise amounts to puzzling through the empirical results. Putting the pieces together suggests that the requirements for mutual learning can be met in either a centralized or decentralized network. Moreover, communication timing appears to be critical. When communication across relationships is delayed, individuals working in a decentralized network can explore a diverse set of ideas while maintaining the ability to exploit a proven idea. When communication across connections is not delayed, a centralized network produces better outcomes. The results of the theory-building exercise suggest a contingency: the ideal network for a complex assignment could depend on the rate of communication across network connections." @default.
• W4310365411 created "2022-12-09" @default.
• W4310365411 creator A5021100663 @default.
• W4310365411 date "2022-12-01" @default.
• W4310365411 modified "2023-09-26" @default.
• W4310365411 title "Mutual learning in networks: Building theory by piecing together puzzling facts" @default.
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• W4310365411 doi "https://doi.org/10.1016/j.riob.2022.100175" @default.
• W4310365411 hasPublicationYear "2022" @default.
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