An investigation of how culture impacts global work: Unpacking the layers of culture

One manifestation of today’s globalization is a new type of work environment where employees who are living in different parts of the world regularly engage in collaborative activity. Because these workers are socialized in different cultural environments, an important research issue is how to understand workers behaviors and effectively manage in this global workplace were workers communicate on a daily basis but do not meet each other and may not even know the life styles of their team members. Based on an ethnographic analysis of GLOBALIS, a multinational firm in the financial sector with IT solution centers in the US, Ireland and India, this paper presents a conceptual model of how culture was impacting the behaviors of global teams at GLOBALIS. In this model the behaviors of globally team members is primarily governed by corporate norms, project requirements and workplace culture. National culture, which has been identified in cross-cultural research as a key factor in global work, is just one of many demographic variables like age, education, professional standards, inter-relationships among sites, etc. that impact workplace culture. Thus, this paper reinforces the current multi-faceted view of culture as a set of forces that impact values and behaviors and it also clarifies some of the clouded opinions on whether or how national culture differences impact today’s globally distributed work

Visualization of semantic similarity

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NONLINEAR APPROACH IN CLASSIFICATION VISUALIZATION AND EVALUATION

In this paper we have proposed the novel methodology to visualize classification scheme in informatics domain. We have mapped a documents collection of ACM (Association for Computing Machinery) Digital Library to a sphere surface. Two main stages of visualization processes complement one another: classification and clusterization. Primarily classified documents were visualized and their further clusterization by means of keywords was crucial in evaluation process. For clusters analysis of given visualization maps nonlinear digital filtering techniques were applied. The clusters of keywords were characterized by a local accuracy. Obtained semantic map was included to validation process