• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.97-108
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• 2011

Small IT service organizations operate their business with limited resources and workforce in comparison with large enterprises, and they could be categorized in various types based on the method of value creation. But the recent studies on information security have been conducted and they were focused on the construction of general information security countermeasure, without considering size of the business and characteristic. Hence we have undergone the process of classifying information assets. Then we extracted and categorized the information assets considering characteristics of small organization's size and business process. Specifically we have classified the information assets according to business scenario design through qualitative observation method. Then we have validated the classified information assets by utilizing statistical method. We may anticipate that this study results could be basic data for developing the differentiated information security countermeasures for small IT service organization.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.139-142
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• 2005

Recently research interest in Knowledge Management (KM) has grown rapidly. Companies regard intellectual capital as important asset and strive to deploy KM in an organization to gain a competitive edge. Many organizations currently engage in knowledge management in order to leverage knowledge both within their organization and externally to their shareholders and customers. Most of the previous research related to KM are dedicated to investigate the role of information technology in extracting, capturing, sharing, coverting organizational knowledge. Knowledge workers, however, are paid less attention though they are the key players in KM activities such as knowledge creation, dissemination, capture and conversion. We regard knowledge workers as a major component of KM and starting point of understanding organizational knowledge activities. Therefore we adopt a method to understand and analyze knowldge workers' social relationships. In this paper we investigate Social Network Analysis (SNA) as a tool for analyzing knowledge network. We introduce the basic concept of SNA and suggest a framework for implementing knowledge network by explaining how SNA can be used for analyzing knowledge network. We also propose a numerical method for identifying knowledge workers using SNA after classifying knowledge workers. The suggested method is expected to help understanding key knowledge players within an organization.