| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 974045 | Physica A: Statistical Mechanics and its Applications | 2016 | 7 Pages |
•We propose a tacit knowledge transmission model on networks with even mixing.•Two routes of tacit knowledge transmission are considered.•We derive the threshold that governs whether or not a kind of tacit knowledge can be shared.•The degree distribution of the users’ contact network has an important impact.
Due to the popular use of online social networks in today’s world, how to propagate employees’ tacit knowledge via online social networks has attracted managers’ attention, which is critical to enhance the competitiveness of firms. In this paper, we propose a tacit knowledge transmission model on networks with even mixing based on the propagation property of tacit knowledge and the application of online social networks. We consider two routes of transmission, which are contact through online social networks and face-to-face physical contact, and derive the threshold that governs whether or not a kind of tacit knowledge can be shared in an organization with few initial employees who have acquired it. The impact of the degree distribution of the users’ contact network on the transmission is investigated analytically. Some numerical simulations are presented to support the theoretical results. We perform the sensitivity analysis of the threshold in terms of the propagation parameters and confirm that online social networks contribute significantly to enhancing the transmission of tacit knowledge among employees.
