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This paper investigates how unstructured knowledge transfer is managed in ICT teams. In this context, unstructured knowledge refers to knowledge that is not supported by organisational strategy or any formal structure due to its ad hoc and versatile nature. The research utilises empirical material produced for use by the organisation, thus offering a realistic picture of transferring knowledge. Before knowledge management can be supported, it is necessary to understand how it is transferred and externalised in teams. To increase required understanding, this qualitative research investigated how team members in practice utilised knowledge that was created in the team, and how they attempted to support each other to benefit from existing knowledge. In the analysis, three frameworks were used, namely SECI, CIP and ba.

This research discusses the SECI Model of Knowledge Conversion as it relates to the 10 Central and Eastern European Countries (CEECs) that are now part of the European Union (EU). The socio-economic conversion from socialism to capitalism of these societies is unique in historical precedence, whereby utilising the contextual models in knowledge conversion are applicable for understanding the implications of such a phenomenon. The results indicate that there is a unique set of variables that need to be considered within this context and for future similar situations.

A partially mixed-methods case study in a Fortune 50 technology company was conducted to delineate the interaction between organisational culture (OC) types (competitive, bureaucratic and clan) and intra-organisational knowledge sharing (KS). This study provided empirical evidence that show differences in KS horizontally (peer-to-peer) and vertically (between direct-report and manager) within an organisation. By focussing on “socialization” adopted from the organisational knowledge creation theory, the iceberg theory and the competing values framework, we addressed an unexamined area within the body of knowledge. Survey data of 82 employees and interview data of 23 employees were analysed. Multivariate analysis of covariance (MANCOVA) was used to analyse the quantitative survey data. The qualitative interview data were analysed through content analysis. A triangulation design was then followed to merge the data through an equivalent status ($\mathrm{\text{QUAN}}+\mathrm{\text{QUAL}}$) interpretation to derive meta-inferences. MANCOVA displayed a statistically significant interaction between OC and KS via socialisation. The triangulated results showed that OC types distinctly impacted KS via socialisation with differences between seeking, contributing and the direction of knowledge flow (vertical and horizontal). The empirical evidence shows that organisations must consider the direction of knowledge flow (vertical or horizontal) when enforcing cultural values to drive KS via socialisation. Similarly, researchers should not ignore the directional knowledge sharing paradigm, nor the organisational knowledge creation theory, when examining intra-organisational KS.

Although knowledge has been cited as one of the most important strategic assets, the creation and sharing of knowledge at the organizational level is a difficult process that will not proceed without incentives and conscious efforts by management. The complexity of knowledge management (KM) is further compounded by the influence of a wide variety of factors such as leadership, ba, organizational culture, organizational control and individual work styles.

Based on a large dataset gathered from a questionnaire survey of a multi-national Japanese pharmaceutical company and its subsidiary in the US, we compare how the aforementioned organizational factors influence KM, expressed through the SECI model of socialization, externalization, combination and internalization. The results of a structural equation modeling path analysis show that a single model of KM should not be applied unilaterally to both organizations, although part of the same company, and instead may need to be adapted to each stage of KM maturity.