• Journal of Information Technology Applications and Management
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• v.20 no.4
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• pp.1-18
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• 2013

Big data has become a worldwide topic. Despite this, big data accurately understand and acquire the business to take advantage of companies that were only very few. The purpose of this study is to investigate the factors that effect Korean firm's adopting big data system. Empirical test was conducted to verify hypotheses using extended technology acceptance model and we analyzed factors which affect the behavioral intention of big data System. Based upon previous researches, we have selected organization innovation, organization slank, organization information system infra maturity, perceived benefits of big data system, perceived usefulness, perceived ease of use, behavioral intention as variables and proposed a research model based on survey questionnaires. From those, we drew that perceived usefulness and perceived ease of use influenced the behavioral intention. The results of this study will increase the users' awareness on big data system and contribute to develop a way to enable the introduction of new technologies.

• Journal of Digital Convergence
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• v.10 no.7
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• pp.93-98
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• 2012

The rapid change of business environments request the company to act more smart and intelligent in making business strategies and planning the business processes. To meet this requirement, we need to have smart Business Intelligent System(hereinafter "BI") in the company. On the one hand, many korean companies had already installed BI system, and the other hand some companies have plans to implement BI Systems additionally to their Information System. It is very important to have the pictures which factors are critical to the successful implementation of BI, and to survey which critical success factor(hereinafter CSF) are important compared to each factors. In this paper data was gathered from companies already have their BI Systems. We measured IT-Infra maturity, User Education, and Company Organization, and Company Business Strategy, which are the critical success factors for the BI System. After surveying the CSF of BI System, we measured the weights among these factors by AHP. Factor analysis resulted in 6 major factors (Eigenvalue > 1.0), and the AHP analysis showed the list of CSF's weight list according to its significance priorities. The results of this paper could be the valuable references for the implementing process of the BI System in korean company.