To share or not to share: the role of motivation in fostering knowledge sharing behaviours on enterprise social networks

Urfa Fazil & Nasir Mehmood

International Journal of Knowledge-Based Development2025https://doi.org/10.1504/ijkbd.2025.151405article
AJG 1
Weight
0.50

What the paper says

Sharing knowledge has become essential for organisational success in the knowledge-driven economy of today. Organisations are using enterprise social networks (ESNs) more and more to encourage knowledge exchange among their staff members. The incentive of individuals to share their knowledge is just one of several elements that affect knowledge sharing behaviour (KSB) on ESN. In order to promote KSB on ESN, this study investigates the function of motivation. The study discovers that motivation considerably moderates the association between KSB and ESNs using survey data from 405 operational personnel working in the telecom industry. In order to match motivation and KSB on ESNs, organisations might use customised incentive schemes. Furthermore, theoretical foundation of the study is Social Capital theory, in order to effectively accept cultural variations, multinational organisations may need to consider a variety of motivational approaches from different countries. The research adds to the expanding body of studies that emphasises the significance of motivation in predicting knowledge-sharing behaviour and linkages within ESNs.

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https://doi.org/https://doi.org/10.1504/ijkbd.2025.151405

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@article{urfa2025,
  title        = {{To share or not to share: the role of motivation in fostering knowledge sharing behaviours on enterprise social networks}},
  author       = {Urfa Fazil & Nasir Mehmood},
  journal      = {International Journal of Knowledge-Based Development},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1504/ijkbd.2025.151405},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.