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The Influence of Attachment Styles on Knowledge Sharing in Social Media Environments

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Hybrid Learning (ICHL 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7411))

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Abstract

Social media have become very popular. The number of social media users, and the number of interactions among them, is huge. The social media environment plays host to a range of activities, including the exchange of photos and video media, the exchange of ideas and comments, and the building of personal and career networks. Accordingly, the social media environment also serves as a useful supplement to informal learning outside the classroom for both full-time students and adult learners. It is thus crucial that educators understand the determinants of online knowledge sharing. In this study, an existing model framework is adapted to explore the motivational factors that drive knowledge sharing among individuals in the social media environment, particularly to determine whether there are any attachment style differences in online knowledge sharing. The hypothesized relationships between the motivational factors identified and online knowledge sharing behavior are then tested using a survey questionnaire administered to 3,590 post-secondary students applying to a local university. The results indicate that perceived attachment motivation (the need to form a relationship) and perceived relationship commitment (the need to maintain a relationship) are important determinants of online knowledge sharing. Further analysis of attachment styles reveals that high attachment-style individuals rate the need to form relationships more highly than their low attachment-style counterparts. However, the results are the reverse for the need to maintain a relationship. The implications for the encouragement of knowledge sharing behavior in the social media environment are discussed.

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Ma, W.W.K., Sun, K., Ma, J. (2012). The Influence of Attachment Styles on Knowledge Sharing in Social Media Environments. In: Cheung, S.K.S., Fong, J., Kwok, LF., Li, K., Kwan, R. (eds) Hybrid Learning. ICHL 2012. Lecture Notes in Computer Science, vol 7411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32018-7_22

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  • DOI: https://doi.org/10.1007/978-3-642-32018-7_22

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32017-0

  • Online ISBN: 978-3-642-32018-7

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