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Accelerating Knowledge Adoption: Information Systems Change Management – A Perspective of Social Network Structure

Accelerating Knowledge Adoption: Information Systems Change Management – A Perspective of Social Network Structure

Hung-Chun Huang, Frederick Leslie Davy, Hsin-Yu Shih, Chwei-Jen Fan
Copyright: © 2018 |Pages: 16
ISBN13: 9781522552017|ISBN10: 1522552014|EISBN13: 9781522552024
DOI: 10.4018/978-1-5225-5201-7.ch079
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MLA

Huang, Hung-Chun, et al. "Accelerating Knowledge Adoption: Information Systems Change Management – A Perspective of Social Network Structure." Technology Adoption and Social Issues: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2018, pp. 1689-1704. https://doi.org/10.4018/978-1-5225-5201-7.ch079

APA

Huang, H., Davy, F. L., Shih, H., & Fan, C. (2018). Accelerating Knowledge Adoption: Information Systems Change Management – A Perspective of Social Network Structure. In I. Management Association (Ed.), Technology Adoption and Social Issues: Concepts, Methodologies, Tools, and Applications (pp. 1689-1704). IGI Global. https://doi.org/10.4018/978-1-5225-5201-7.ch079

Chicago

Huang, Hung-Chun, et al. "Accelerating Knowledge Adoption: Information Systems Change Management – A Perspective of Social Network Structure." In Technology Adoption and Social Issues: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 1689-1704. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5201-7.ch079

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Abstract

Learning faster is important in personal competitive advantage. However, to accelerate a group of people's learning efficiency is more complicated than individual practice. Learning efficiency is highlighting research in information systems change management as well as knowledge management. In practice, knowledge is difficult to manage directly. On the other hand, managing knowledge behaviors can achieve knowledge management. A teamwork structure is a micro-social system and internal collaboration network. Therefore, different teamwork structures conduct different knowledge behaviors. Social influence theories provide an interpretation that different social proximity distinguish contagion effects. This study applies the social network perspective to explore the knowledge behaviors of computer software developers. Therefore, the finding of this study shows that controlling network redundancy can enhance knowledge diffusion efficiency. Furthermore, if team fails to manage knowledge diffusion, they will offset the timing of competitive advantage in technological upgrade. Based on this finding, this study suggests a new thinking for implementation of information systems, change management, and strategic planning.

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