Abstract
With the fast develo** knowledge economy, one of the major challenges facing enterprise managers is aligning knowledge management (KM) with business strategy and processes, especially after an enterprise has applied Enterprise Resource Planning (ERP). Since knowledge sharing (KnS) is one of the most critical steps in KM activities, it is necessary to study the effective sharing of tacit knowledge in ERP enterprises. In an ERP environment, KnS system should have two functions. One is to support the enterprise business and the other is to support employees’ communication. Most researches have thus far focused on the first function trying to find out management mechanism to improve the effect of KnS while ignoring the other function. In the KnS with the communication function, this research finds out that knowledge is exchanged naturally and freely. The KnS system can also make employees feel better about their work by making greater contribution to building an active culture environment to support knowledge exchange. In this paper, these two types of KnS are called business-oriented knowledge-sharing and subject-oriented knowledge-sharing. It also designs their constructions, propose their management mechanism and discuss some relevant practice problems. When these two types of KnS are applied in ERP enterprises they not only can provide channels for employees to exchange knowledge, but can also help enterprises to get tacit knowledge from ERP users and to make tacit knowledge more effectively be converted to explicit knowledge. Though ERP and KnS are performed as two separate systems, this research provides guidance to enterprise managers to develop tacit knowledge-sharing system on their ERP implementation and keep the same goal with it.
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© 2007 IFIP International Federation for Information Processing
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Sun, B. (2007). A Study on Tacit Knowledge Sharing in ERP Enterprises. In: Xu, L.D., Tjoa, A.M., Chaudhry, S.S. (eds) Research and Practical Issues of Enterprise Information Systems II. IFIP — The International Federation for Information Processing, vol 254. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-75902-9_86
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DOI: https://doi.org/10.1007/978-0-387-75902-9_86
Publisher Name: Springer, Boston, MA
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