디지털융복합연구 (Journal of Digital Convergence)

  • 제17권4호
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  • Pages.65-73
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  • 2019
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  • 2713-6434(pISSN)
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  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
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패널회귀분석을 이용한 글로벌 선사의 재무요인 특성분석에 관한 연구

An analysis of Financial Factors' Characteristic for Global Shipping Companies using Panel Regression Analysis

  • 오재균 (인천대학교 동북아물류대학원) ;
  • 여기태 (인천대학교 동북아물류대학원)
  • Oh, Jae-Gyun (Graduate School of Logistics, Incheon National University) ;
  • Yeo, Gi-Tae (Graduate School of Logistics, Incheon National University)
  • 투고 : 2019.01.28
  • 심사 : 2019.04.20
  • 발행 : 2019.04.28
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초록

연구는 부채비율을 종속변수로 하고 ROE(자기자본 이익률), 매출액, 유동비율, 자본총계, 운임지수인 SCFI(Shanghai Containerized Freight Index)를 독립변수로 하여 패널회귀분석을 실시하였다. GLS 분석결과, 유동비율의 경우 부채비율에 부(-)의 영향을 끼쳤고, 매출액의 경우 부채비율에 정(+)의 영향을 끼쳤다. 또한 자본총계는 부채비율에 부(-)의 영향을 미쳤다. 하지만 ROE의 경우 가설과는 다르게 부채비율에는 부(-)의 영향을 끼쳤고, SCFI지수는 유의미하지 않았다. 본 연구의 시사점으로 글로벌 선사의 부채비율이 높아질수록 글로벌 선사가 규모의 경제를 달성해 매출이 증가한 것을 확인했다. 하지만 타인자본 투입을 통한 규모의 경제실현은 매출액 증가에는 도움은 되지만, 당기순이익에는 영향을 미치지 못함을 확인하였다. 선사는 영업력을 확대하고 대형 컨테이너선을 확보하는 등의 화주 신뢰성을 확보하는 전략에 병행해야 한다. 향후 연구에서는 환율, 세계 경제 성장률, 제조업 생산지수 등을 고려한 분석이 필요하다.

This study performed Panel Regression Analysis (PRA) with the debt ratio as a dependent variable and the ROE (return on equity), sales volume, current ratio, total capital, and Shanghai Containerized Freight Index (SCFI) as an independent variable. According to the GLS analysis, the current ratio to liabilities ratio was negative, and for sales, the ratio of liabilities was positive. Capital totals also had a negative impact on the debt ratio. However, ROE, unlike the hypothesis, had negative effects on the liability ratio, and the SCFI index was not significant. As implications of this research, the company confirmed that its sales increased as the debt ratio of global shipping companies rose, achieving economies of scale. However, it was confirmed that the actual size of the economy through the injection of other capital would help increase sales but not affect net profit. Shipping companies should expand their business power and secure large container vessels to secure credibility of shippers. In the future research, an analysis considering exchange rate, global economic growth rate, and manufacturing production index is needed.

키워드

Table 1. Debt ratio for 9 years of global shipping company

DJTJBT_2019_v17n4_65_t0001.png 이미지

Table 2. Sales for 9 years of global shipping company

DJTJBT_2019_v17n4_65_t0002.png 이미지

Table 3. Total capital of global shipping company

DJTJBT_2019_v17n4_65_t0003.png 이미지

Table 4. Definition of variables

DJTJBT_2019_v17n4_65_t0004.png 이미지

Table 5. Correlation analysis

DJTJBT_2019_v17n4_65_t0005.png 이미지

Table 6. VIF Analysis

DJTJBT_2019_v17n4_65_t0006.png 이미지

Table 7. GLS and LR Test, Wooldridge analysis result

DJTJBT_2019_v17n4_65_t0007.png 이미지

Table 8. Results of Hausman test

DJTJBT_2019_v17n4_65_t0008.png 이미지

Table 9. Fixed-effects model and F-Test

DJTJBT_2019_v17n4_65_t0009.png 이미지

참고문헌

  1. C. B. Lee & J. H. No. (2010). An Empirical Study on Improving Competitiveness of Korean Shipping Industry, Journal of Korea Port Economic Associatio, 26(3), 259-278.
  2. KMI. (2017). KMI Weekly report Reflections of Hanjin Shipping Incident and Shipping Reconstruction Plan, 45.
  3. Ministry of Maritime Affairs and Fisheries. (2018). Five-year plan for shipping reconstruction (2018-2022).
  4. H. S. Bae. (2015). An Empirical Study on the Estimation of Adequate Debt ration in Korean Shipping Industry: Focused on Water Transport, Journal of Korean Navigation and Port Research, 39(1), 69-75. https://doi.org/10.5394/KINPR.2015.39.1.69
  5. R. B. Kim & K. M. Ahn. (2016). Effect Analysis of Foreign Exchange Gain & Loss and Counter-measures, Journal of Ocean Development, 25, 5-24.
  6. H. K. Lee & Y. S. Ha. (2017). Comparative Analysis on factors of Competitiveness among the Container Shipping Companies in Korea, The Journal of shipping and logistics, 33(1), 143-161. https://doi.org/10.37059/tjosal.2017.33.1.143
  7. Y. S. HA & J. S. SEO. (2017). An Analysis of the Competitiveness of Major Liner Shipping Companies, The Asian Journal of Shipping and Logistics, 33(2), 53-60. https://doi.org/10.1016/j.ajsl.2017.06.002
  8. K. Y. Hwang & J. S. Koo. (2011). An Evaluation on the International Competitiveness of Korean and Global Container Shipping Company through a Comparative Analysis on the Efficiency, International Commerce and Information Review, 13(1), 123-144.
  9. T. E. Notteboom & B. Vernimmen. (2009). The effect of high fuel costs on liner service configuration in container shipping, Journal of Transport Geography, 17(5), 325-337. https://doi.org/10.1016/j.jtrangeo.2008.05.003
  10. T. H. Lee & W. C. Ahn, (2016), Analysis of the Stability and Impulse-Response of Shipping Lines in Korea, The Journal of shipping and logistics, 90, 199-218.
  11. K. Y. Jo, J. G. Oh, T. H. Nam & G. T. Yeo. (2017). A Study on the Factor and Influences of Decision Making for the Inland Trnsportation of Shippers, Journal of Digital Convergence, 15(10), 123-132. https://doi.org/10.14400/JDC.2017.15.10.123
  12. J. H. Na, K. W. Kim & H. S. Bang. (2015). A Study of Risk Management Strategies for Korean Shipping Companies, The Journal of shipping and logistics, 31(1), 185-207. https://doi.org/10.37059/tjosal.2015.31.1.185
  13. Y. J. Shin, Y. H. Lee. (2003). A Study on Actual Condition and Promoting Competitive Power of Korean Shipping Companies on Korea-China Liner Service, KOREA INTERNATIONAL COMMERCIAL REVIEW, 18(5), 37-56.
  14. H. H. Kim, K. D. Sung. J. W. Jeon & G. T. Yeo. (2016). Analysis of the Relationship Between Freight Index and Shipping Company's Stock Price Index, Journal of Digital Convergence, 14(6), 157-165. https://doi.org/10.14400/JDC.2016.14.6.157
  15. S. Y. Kwon & B. Y. Moon. (2009). Decomposed Return on Equity, Future Profitability, and Value Relevance over the Firm Life Cycle, Korean management review, 38(5), 1213-1249.
  16. D. J. Yang, D. Y. Ko & S. S. Yoon. (2009). The Effect of Leverage on the Accounting Choices for Loss-Reporting Firms, Journal of Business Research, 24(2), 81-106. https://doi.org/10.22903/JBR.2009.24.2.81
  17. Y. H. Par, I. M. Song, S. I. Pae & S. J. Park. (2011). Problems in system of uniform 200% debt-equity ratio and suggestions for system improvement, Korean Accounting Journal, 20(4), 287-328.
  18. C. H. Na, I. H. Kim & J. K. Ko. (2015). Earnings Management and Target Debt Ratios of Priority Debt Control Public Enterprises, Korean Accounting Journal, 24(4), 163-198.
  19. J. J. Jeong & J. S. Jeon. (2015). Relational Context between Debt and Profitability of Local Public: 16 Local Development Corporation created by Metropolitan Local Government, Korean journal of local finance, 20(3), 121-151.
  20. Y. J. Shin. (2015). The Effect of Firm Characteristics on Capital Structure : Evidence from Korean Unlisted Small and Medium-Sized Firms, Korea Journal of Business Administration, 28(2), 675-695.
  21. M. Heikal, M. Khaddafi & A. Ummah. (2014). Influence Analysis of Return on Assets (ROA), Return on Equity (ROE), Net Profit Margin (NPM), Debt To Equity Ratio (DER), and current ratio (CR), Against Corporate Profit Growth In Automotive In Indonesia Stock, International Journal of Academic Research in Business and Social Sciences, 4(12), 101-114.
  22. D. W. Kim & J. S. Yu. (2014). The Development of Housing Unsold Ratio Determinants Model and Applications, Korean Association For Housing Policy Studies, 22(1), 149-178.
  23. I. H. Oh & Y. R. Park. (2016). Analysis on Effects of IT Utilization on Firm Performances, Industrial Innovation Research, 32(4). 1-28.
  24. Y. S. Yang & J. E. Lee. (2014). The Effects of Depth and Breadth of International Experience on the Export Performance of SMEs: Focus on the SMEs in Gwangju and Jeonnam Provinces, South Korea, The Journal of shipping and logistics, 82, 517-538.
  25. S. Muratsirin. (2017). A panel data analysis on the costs of Turkish electricity distribution companies, Energy Strategy Reviews, 18, 250-259. https://doi.org/10.1016/j.esr.2017.10.004
  26. C. I. Choi. (2008). Panel model: Time series analysis and cross section analysis at once, Planning and policy, 2008.6(320), 120-127.
  27. J. J. Song. (2008). SPSS/AMOS Statistic Method, Seoul: 21st Century History.
  28. X. Lin & K. S. Kim. (2013). Empirical Analysis on the Factors Affecting the Consumption of Aquatic Products in China Using Panel Data, The Journal of Fisheries Business Administration, 44(2), 19-33. https://doi.org/10.12939/FBA.2013.44.2.019