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            <title xml:lang="en">The effect of social networks, organizational coordination structures, and knowledge heterogeneity on knowledge transfer and aggregation</title>
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            <idno type="halRefHtml">&lt;i&gt;Journal of Evolutionary Economics&lt;/i&gt;, 2023, 33 (2), pp.249-278. &lt;a target="_blank" href="https://dx.doi.org/10.1007/s00191-023-00811-z"&gt;&amp;#x27E8;10.1007/s00191-023-00811-z&amp;#x27E9;&lt;/a&gt;</idno>
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                <term xml:lang="en">Sustainable Development Goals</term>
                <term xml:lang="en">Cross-unit brokerage</term>
                <term xml:lang="en">Knowledge aggregation</term>
                <term xml:lang="en">Knowledge transfer</term>
                <term xml:lang="en">Knowledge heterogeneity</term>
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              <p>Previous research has established the benefits of knowledge for firm competitive advantage. Knowledge does not, however, seamlessly transfer around an organization. Research suggests that the organizations coordination structures, the heterogeneity of knowledge within an organization, and social network structure are three critical factors that can enable and constrain the transfer and aggregation of knowledge that are held by individuals and units. These three factors, however, have rarely been examined together. We use an agent based model to simulate different configurations of the three factors. We find that in decentralized coordination structures, when there is a relatively high degree of knowledge homogeneity across units, there is an advantage for actors to have a social network structure that crosses unit boundaries. This is not the case in a centralized coordination structure where there is an advantage for actors to have social network structures that remain within unit boundaries. The exception is when actors have cross-unit brokerage ties that are embedded in social networks that have a small world structure, regardless of knowledge heterogeneity. At the unit level, we find that for both centralized and decentralized reporting structures, variability of knowledge aggregation across units is higher when there is greater knowledge homogeneity between units. Overall, our results are robust to various changes in the initial parameters.</p>
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