A Study on the Influence of National Culture on Knowledge Sharing

Laitinen, Jouni On The Influence of National Culture on Knowledge Sharing Jyväskylä: University of Jyväskylä, 2013, 78 p. Mathematical Information Systems, Master’s Thesis Supervisor(s): Pawlowski, Jan; Senoo, Dai (Tokyo Institute of Technology) In the global economy, innovations have become more important than ever. Knowledge sharing has been shown to improve both innovation capability and speed. Hence, in order to improve international cooperation among workers and organizations supporting knowledge sharing has become increasingly important. However, the current theories on knowledge sharing have been formed at a too high level of abstraction or leave out essential factors of knowledge sharing to be of any real practical help for practitioners and academics. In order to meet the need for such a theory, this thesis attempted to create a new framework, which encompassed all relevant factors. These are cultural, individual, organizational and technological factors. The framework was created based on a thorough literary review after which the framework was tested against results from semi-structured interviews carried out in both Western organizations and in Japanese organizations. The results from the interviews were then used to modify the presented framework. Based on the results it can be concluded that cultural influences need to be taken into account when studying knowledge sharing. Moreover, culture has an influence on aspects outside of just individuals and organizations. Culture influences trust and certain aspects of technical tools. These six aspects form the core of the framework. In addition, each contains attributes that are influenced by culture. Overall, it can be stated that the research presented in this master ́s thesis is essentially a first stepping-stone towards a new and more encompassing theory on knowledge sharing in international context. Future research should focus on further validating the presented framework by using quantitative methods.