Purpose -The purpose of this study is to explore cultural factors influencing knowledge sharing strategies in virtual communities of practice.Design/methodology/approach -A qualitative research design was employed. Data collection was based on in-depth interviews. The authors assumed that such factors as degree of collectivism, competitiveness, the importance of saving face, in-group orientation, attention paid to power and hierarchy, and culture-specific preferences for communication modes, would explain differences in knowledge seeking and sharing patterns.Findings -The results showed that these factors had different levels of importance among employees in the three participating countries. The issue of saving face was less important than expected in China. Modesty requirements as well as a high degree of competitiveness among employees were found to be serious barriers to information sharing in China, but not in Russia and Brazil. Perceived differences in power and hierarchy seemed to be less critical in all three countries than initially assumed.Research limitations/implications -Since this study was conducted among the online community members of Caterpillar Inc., the results could be affected by factors unique to this specific case. Thus, future research should investigate the influence of other factors such as the organizational culture, or occupational groups on knowledge sharing strategies.Practical implications -Before any introduction of country-specific knowledge sharing systems, a cultural needs assessment should be conducted.Originality/value -The impact of national culture factors on knowledge sharing has been largely neglected in the literature, and the findings will assist knowledge managers charged with the design of flexible knowledge management systems.

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Object-oriented (OO) metrics are used mainly to predict software engineering activities/efforts such as maintenance effort, error proneness, and error rate. There have been discussions about the effectiveness of metrics in different contexts. In this paper, we present an empirical study of OO metrics in two iterative processes: the short-cycled agile process and the long-cycled framework evolution process. We find that OO metrics are effective in predicting design efforts and source lines of code added, changed, and deleted in the short-cycled agile process and ineffective in predicting the same aspects in the long-cycled framework process. This leads us to believe that OO metrics' predictive capability is limited to the design and implementation changes during the development iterations, not the long-term evolution of an established system in different releases.

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