Boundary Spanning: A Machine-Learning Approach
نویسندگان
چکیده
In recent years, the ability to mine, manage, and examine big data has sparked a strong interest among scholars and managers to leverage data science and machine-learning approaches for enhancing the efficiency and effectiveness of various areas of knowledge management. The success of today’s enterprises increasingly depends on the efficiency and quality of their cross-boundary knowledge flows and processes (Marrone, 2010). Various information systems, specifically emerging enterprise social media (ESM) technologies, are used to increase the transparency and openness of knowledge flows with the aim of enhancing team effectiveness, collaboration, knowledge sharing, and innovation.
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