J Navig Port Res > Volume 49(1); 2025 > Article
Journal of Navigation and Port Research 2025;49(1):60-73.
DOI: https://doi.org/10.5394/KINPR.2025.49.1.60    Published online February 28, 2025.
글로벌 컨테이너터미널 운영사의 지리적 다각화와 기업경영성과에 관한 연구
박순환1, 김율성2, 이정민3
1국립한국해양대학교 물류시스템전공 박사수료
2국립한국해양대학교 물류시스템공학과 교수
3국립한국해양대학교 해양컨텐츠융복합협동과정 물류시스템공학전공 박사과정
Effects of Geographical Diversification on Corporate Performance in Global Terminal Operators: A Panel Regression Analysis
Soon-Hwan Park1, Yul-Seong Kim2, Jeong-Min Lee3
1Doctoral Candidate, Logistics System Engineering, Korea Maritime and Ocean University, Busan 49112, Korea
2Professor, Logistics System Engineering, Korea Maritime and Ocean University, Busan 49112, Korea
3Doctoral Researcher, Department of Convergence Interdisciplinary Education, Korea Maritime and Ocean University, Busan 49112, Korea
Correspondence:  Jeong-Min Lee, Tel: 051)410-4890, 
Email: jmjm3646@g.kmou.ac.kr
Received: 20 January 2025   • Revised: 5 February 2025   • Accepted: 17 February 2025
Abstract
This study examined geographical diversification of Global Container Terminal Operator (GTO) and quantified it into an index to analyze its impact on corporate performance. Using panel regression analysis on an eight-year time series dataset from 11 GTOs, empirical results revealed the following. First, GTOs exhibited significant differences in their geographic portfolio strategies. Second, there was a non-linear relationship between intercontinental geographic diversification and Return on Equity (ROE), where the impact was initially negative but became positive beyond a certain level of diversification. Third, GTOs' expansion into developing regions positively influenced their ROE. These findings suggest that GTO should focus on long-term geographic diversification strategies to achieve economies of scale and improve operational efficiency, rather than solely concentrating on short-term performance.
Key Words: global container terminal operators(GTO), geographical diversification, corporate performance, panel regression analysis, port industry
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