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How different connectivity patterns of individuals within an organization can speed up organizational learning

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Abstract

Knowledge sharing within a cooperative organization is an important issue since the power of its outcome has been the principal source of competitive advantage over the competitors in the market. However, without a proper collective knowledge management, its utilization as a strategic weapon or competitive advantage becomes difficult and inefficient. From an organizational perspective, the most important aspect of knowledge management is to transfer knowledge. In this regards, organizations must adopt structures that allow them to create and transfer more knowledge. Organizational communication structure affects the nature of human interactions and information flow which in its own turn can lead to a competitive advantage in the knowledge economy. However, in addition to that, social relationships between individuals in an organization can also be utilized to produce positive returns. In this article we emphasize the role of individual structural importance within an organizational informal communication structure as a mechanism for knowledge flow and speeding up organizational learning. Our experimental results indicate the fact that structural position of individuals within their informal communication networks can help the network members to have a better access to ongoing information exchange processes in the organization. The results of our analyses also show that organizational learning through an informal communication network of people in the form of scale-free connectivity pattern is faster comparing to the small-world connectivity style.

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Acknowledgments

This research has been funded by the “Leaders Industry-University Cooperation” Project, supported by the Ministry of Education.

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Correspondence to Somayeh Koohborfardhaghighi or Juntae Kim.

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Koohborfardhaghighi, S., Lee, D.B. & Kim, J. How different connectivity patterns of individuals within an organization can speed up organizational learning. Multimed Tools Appl 76, 17923–17936 (2017). https://doi.org/10.1007/s11042-016-3348-8

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  • DOI: https://doi.org/10.1007/s11042-016-3348-8

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