A Predictive Model of the Knowledge-Sharing Intentions of Social Q&A Community Members: A Regression Tree Approach

Previous research on the factors affecting knowledge sharing has focused on the relationships between a limited number of variables. However, it is unclear how these factors interact with each other and jointly influence knowledge-sharing intentions. Drawing on social cognitive theory (SCT), this pa...

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Veröffentlicht in:International journal of human-computer interaction 2022-02, Vol.38 (4), p.324-338
Hauptverfasser: Cai, Yang, Yang, Yongyong, Shi, Wendian
Format: Artikel
Sprache:eng
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Zusammenfassung:Previous research on the factors affecting knowledge sharing has focused on the relationships between a limited number of variables. However, it is unclear how these factors interact with each other and jointly influence knowledge-sharing intentions. Drawing on social cognitive theory (SCT), this paper performs a decision tree analysis to predict the knowledge-sharing intentions of social question-and-answer (Q&A) community members based on a multitude of environmental and individual factors, including a sharing culture, motivations, and individual characteristics. Data from 1,007 users were collected, and a regression tree model was built using the R package rpart. The results show that high levels of knowledge-sharing intentions occur among those who strongly enjoyed sharing and who perceived fairness within the community. For those who had a moderate or low level of enjoyment, their willingness to share knowledge was jointly affected by the sharing culture and extrinsic motivations.
ISSN:1044-7318
1532-7590
DOI:10.1080/10447318.2021.1938393