다국적기업의 R&D 자회사 전략 : 기술기업 연구개발 특허성과를 중심으로

This study aims to analyze which subsidiary configuration strategy is more effective under uncertainty especially technology base multinational corporations (henceforth MNCs). In previous studies real option theory scholars argue that high breadth subsidiary configuration is most effective strategy because that provides flexibility to MNCs global network. In this study I want unveil more various types of uncertainty such as technology and learning uncertainty which are more important for technology base firm and further more examine the effect of MNCs subsidiary configuration on firm R&D performance each uncertainty case. Empirical study is performed by negative binominal model based on Japanese 108 multinational corporations. The result shows that under technology uncertainty, high breadth subsidiary configuration is better for firm R&D performance but under learning uncertainty high depth subsidiary configuration is better. Thus, the effects of MNCs subsidiary configuration on firm value can differ by types of uncertainty.