Title | ||
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A holistic model for inter-plant knowledge transfer within an international manufacturing network |
Abstract | ||
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Purpose This paper aims to provide a holistic view to support the choice of appropriate strategy for conducting a knowledge transfer (KT) project in an international manufacturing network (IMN) environment. It proposes a model that includes multiple aspects of a KT project along with guidelines on each aspect. Design/methodology/approach To achieve the research goals, multiple case study method was adopted. Data have been collected by conducting semi-structured interviews regarding five KT projects in three multinational corporations. Data were triangulated by means of comparisons to complementary data acquired through observations and archival documents. Findings The results of this paper detail the key issues of five KT projects. Furthermore, the paper proposes an aggregated model comprising the main aspects and strategies for a KT project within an IMN. Research limitations/implications Despite the abundant research on KT area, not many research projects provide holistic views on KT process. The focus has rather been sectional and concentrated on each specific aspect within the KT. Practical implications The paper guides practitioners to identify multiple aspects in KT that will eventually increase the odds for successfully performing such projects. Originality/value The proposed learning network model improves the performance of KT projects by providing a holistic view including several factors that the organization should emphasize to succeed with inter-plant KT. |
Year | DOI | Venue |
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2020 | 10.1108/JKM-10-2017-0473 | JOURNAL OF KNOWLEDGE MANAGEMENT |
Keywords | DocType | Volume |
Knowledge driven organizations,Knowledge management,Knowledge transfer,Engineering,International manufacturing network | Journal | 24.0 |
Issue | ISSN | Citations |
3.0 | 1367-3270 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
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Farhad Noruzi | 1 | 0 | 0.34 |
Daniel Stenholm | 2 | 2 | 0.82 |
Peter Sjögren | 3 | 0 | 0.34 |
Dag Bergsjö | 4 | 14 | 3.21 |