DOIONLINE

DOIONLINE NO - IJACEN-IRAJ-DOIONLNE-3105

Publish In
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN
Journal Home
Volume Issue
Issue
Volume-3, Issue-10  ( Oct, 2015 )
Paper Title
Inter-Team Boundary Spanning: A Data Science Approach
Author Name
Wietske Van Osch, Charles Steinfield, Yanjie Zhao
Affilition
Michigan State University
Pages
106-110
Abstract
With the ubiquity of data, new opportunities have emerged for the application of data science and machine learning approaches to help enhance the efficiency and effectiveness of knowledge management. With the growing use of social media technologies in enterprise settings, one specific area of knowledge management warranting the use of big data analytics involves cross-boundary knowledge creation and management. The objective of this paper is to develop and test a machine learning approach that can assist knowledge managers in detecting three types of intra-organizational boundary spanning activities with the goal of predicting and improving such important outcomes as team effectiveness, collaboration, knowledge sharing, and innovation. Index Terms- Inter-team Boundary Spanning, Data Science, Machine Learning, Knowledge Management
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