Earticle

초록

영어

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.

목차

Abstract
 1. 서론
 2. 이론적 배경과 가설의 설정
  2.1 기술 불확실성에 대한 가설
  2.2 학습 불확실성에 대한 가설
 3. 연구방법론
  3.1 표본의 구성
  3.2 변수의 정의
  3.3 방법론 및 분석결과
 4. 결론 및 시사점
 References

키워드

저자

• 김지연 [ Ji Yeon Kim | Assistant Professor, School of Business, Hoseo University, 268, Anseo-dong, Cheonan, Chungnam, 31499, South Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  JITAM [Journal of Information Technology Applications and Management]

• 간기

  격월간

• pISSN

  1598-6284

• eISSN

  2508-1209

• 수록기간

  1999~2026

• 십진분류

  KDC 005 DDC 005