바로가기메뉴

본문 바로가기 주메뉴 바로가기

logo

Measuring the Efficiency of Maritime Transport Companies

The Journal of Distribution Science / The Journal of Distribution Science, (P)1738-3110; (E)2093-7717
2017, v.15 no.11, pp.59-72
https://doi.org/https://doi.org/10.15722/jds.15.11.201711.59
Kang, Hyo-Won
Kim, Young-Min
  • Downloaded
  • Viewed

Abstract

Purpose - This paper evaluated the efficiency performance of the three major maritime transport markets and examined the determinants of the performance. The firms' revenue fluctuates with the changes of the economic cycle; hence it is important for them to set up business strategies to improve efficiencies. A lack of efficiency measurements for shipping firms leads to a significant gap in determining their overall performance. Research design, data, and methodology - Each of DEA scores was adopted for the evaluation and panel regression was used to examine the impact of determinants on the performance. The analysis included 50 shipping firms from three maritime transport markets as follows; 15 firms of container liners, 18 firms of bulk carrier and 17 firms of tanker carriers, and its period was from 2010 to 2016. Results - In the CCR model, container liners were the highest, tanker carriers were the second, and bulk carriers were the lowest in operation efficiency and financial efficiency. By region, operation efficiency and financial efficiency was high in the order of America, Asia, and Europe. Conclusions - This study suggests business strategies for maritime transport companies based on the analytical results of determinants of operational and financial efficiency.

keywords
Maritime Transport, Data Envelopment Analysis, Container Liners, Bulk Carriers, Tanker Carriers

Reference

1.

Asmild, M., Paradi, J. C., Aggarwall, V., & Schaffnit, C. (2004). Combining DEA Window Analysis with the Malmquist Index Approach in a Study of the Canadian Banking Industry. Journal of Productivity Analysis, 21(1), 67-89.

2.

Asmild, M., & Tam, F. (2007). Estimating global frontier shifts and global Malmquist indices. Journal of Productivity Analysis, 27(2), 137-148.

3.

Bang, H. S., Kang, H. W., Martin, J., & Woo, S. H. (2012). The impact of operational and strategic management on liner shipping efficiency: A Two-stage DEA Approach. Maritime Policy & Management, 39(7), 653-672.

4.

Banna, H., Ahmad, R., & Koh, E. H. Y. (2015). Determinants of Commercial Banks’ Efficiency in Bangladesh: Does Crisis Matter?. Journal of Asian Finance, Economics and Business, 4(3), 19-26.

5.

Bates, L. J., Mukherjee, K., & Santerre, R. E. (2006). Market structure and technical efficiency in the hospital services industry: A DEA approach. Medical Care Research and Review, 63(4), 499–524.

6.

Beamon, B. M. (1999). Measuring supply chain performance. International Journal of Operations and Production Management, 19(3), 275-292.

7.

Bichou, K. (2011). A two-stage supply chain DEA model for measuring container-terminal efficiency. International Journal of Shipping and Transport Logistics, 3(1), 6-26.

8.

Carvalho, P., & Marques, R. C. (2012). Using non-parametric technologies to estimate returns to scale in the Iberian and international seaports. International Journal of Shipping and Transport Logistics, 4(3), 286-302.

9.

Casu, B., & Molyneux, P. (2003). A comparative study of efficiency in European banking. Applied Economics, 35(17), 1865-1876.

10.

Chang, P., & Lee, J. (2012). A fuzzy DEA and knapsack formulation integrated model for project selection. Computers and Operations Research, 39(1), 112-125.

11.

Chen, X., Skully, M., & Brown, K. (2005). Banking efficiency in China: Application of DEA to pre and post – deregulation eras: 1993-2000. China Economic Review. 16(3), 229-245.

12.

Chen, Y., & Iqbal, Ali, A. (2004). DEA Malmquist productivity measure: New insights with an application to computer industry. European Journal of Operational Research, 159(1), 239-249.

13.

Chiou, Y. C., & Chen, Y. H. (2006). Route-based performance evaluation of Taiwanese domestic airlines using data envelopment analysis. Transportation Research Part E: Logistics and Transportation Review, 42(2), 116-127.

14.

Chow, C. K. W., Fung, M. K. Y., & Law, J. S. (2010). Estimating technical efficiencies of airports in the Greater China: Stochastic output distance function method vs. Data envelopment analysis method. International Journal of Shipping and Transport Logistics, 2(3), 284-299.

15.

Cullinane, K., & Gong, X. (2002). The mispricing of transportation initial public offerings in the Chinese mainland and Hong Kong. Maritime Policy and Management, 29(2), 107-118.

16.

Cullinane, K., Wang, T. F., Song, D. W., & Ji, P. (2006). The technical efficiency of container ports:Comparing data envelopment analysis and stochastic frontier analysis. Transportation Research Part A, 40(4), 354-374.

17.

Davidova, S., & Latruffe, L. (2007). Relationships between Technical Efficiency and Financial Management for Czech Republic Farms. Journal of Agricultural Economics, 58(2), 269-288.

18.

Estache, A., Tovar, B., & Trujillo, L. (2008). How efficient are African electricity companies? Evidence from the Southern African countries. Energy Policy, 36(6), 1969-1979.

19.

Fethi, M. D., & Pasiouras, F. (2010). Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey. European Journal of Operational Research, 204(2), 189-198.

20.

Grammenos & Arkoulis. (2002). Macroeconomic Factors and International Shipping Stock Returns. International Journal of Maritime Economics. 4(1), 81-99.

21.

Hawawini, G., Subramanian, V., & Verdin, P. (2003). Is performance driven by industry or firm specific factor? A new look at the evidence. Strategic Management Journal, 24(1), 1-16.

22.

Ishaq, M. I., Waqas, M., Hussian, N., & Khaliq, W. (2012). A Review on Triple-A Supply Chain Performance. East Asian Journal of Business Management, 2(2), 35-39.

23.

Jenssen, J. I., & Randøy, T. (2006). The performance effect of innovation in shipping companies. Maritime Policy & Management, 33(4), 327-343.

24.

Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard-Measure that drive performance. Harvard Business Review, 70(1), 71-79.

25.

Kim, J. H. (2016). Port Co-operation between Public and Private Sector. East Asian Journal of Business Management, 6(1), 13-17.

26.

Lambertides, N., & Louca, C. (2008). Ownership structure and operating performance: Evidence from the European maritime industry. Maritime Policy &Management, 35(4), 395-409.

27.

Lam, J. S. L., Yap, W. Y., & Cullinane, K. (2007). Structure, conduct and performance on the major liner shipping routes 1. Maritime Policy & Management, 34(4), 359-381.

28.

Li, X. (2012). Study on Logistics Industry Cooperation between Shandong and South Korea. International Journal of Industrial Distribution & Business, 3(2), 23-27.

29.

Liao, S. C. (2014). Fuzzy and Multi Criteria Decisions for Business Management in Product Design Industries. International Journal of Industrial Distribution &Business, 5(3), 5-14.

30.

Liu, F. H. F., & Wang, P. H. (2008). DEA Malmquist productivity measure: Taiwanese semiconductor companies. International Journal of Production Economics, 112(1), 367-379.

31.

Lun, V., Pang, A., & Panayides, P. M. (2010). Organizational growth and firm performance in the international container shipping industry. International Journal of Shipping and Transport Logistics, 2(2), 206-223.

32.

Lun, V. Y. H., & Marlow, P. (2011). The impact of capacity on firm performance: A study of the liner shipping industry. International Journal of Shipping and Transport Logistics, 3(1), 57-71.

33.

Luo, X. (2003). Evaluating the profitability and marketability efficiency of large banks An application of data envelopment analysis. Journal of Business Research, 56(8), 627-635.

34.

Merikas, A., Gounopoulos, D., & Karli, C. (2010). Market performance of US-listed Shipping IPOs. Maritime Economics & Logistics, 12(1), 36-64.

35.

Noorizadeh A., Mahdiloo, M., & Saen, R. F. (2013). Using DEA cross-efficiency evaluation for suppliers ranking in the presence of non-discretionary inputs. International Journal of Shipping and Transport Logistics, 5(1), 95-111.

36.

Panayides, P. M., & Lambertides, N. (2011). Sustainable performance in Transportation: The Case of shipping companies. Logistics and Sustainable Transport, 2(2), 1-21.

37.

Randoy, T., Down, J., & Jenssen, J. (2003). Corporate Governance and Board Effectiveness in Maritime Firms. Maritime Economics & Logistics, 5(1), 40-54.

38.

Salehi, M., Khaksar, J., & Torabi, E. (2014). Islamic Banking Ranking Efficiency Based on a Decision Tree in Iran. East Asian Journal of Business Management, 4(2), 5-11.

39.

Shadkam, E., & Bijari, M. (2015). The Optimization of Bank Branches Efficiency by Means of Response Surface Method and Data Envelopment Analysis: A Case of Iran. Journal of Asian Finance, Economics and Business, 2(2), 13-18.

40.

Tsai, H. C., Chen, C. M., & Tzeng, G. H. (2006). The comparative productivity efficiency for global telecoms. International Journal of Production Economics, 103(2), 509-526.

41.

Upadhaya, B., Munir, R., & Blount, Y. (2014). Association between Performance Measurement Systems and Organizational Effectiveness. International Journal of Operations & Production Management, 34(7), 853-875.

42.

Wiegmans, B., Bu L., & Kim N. S. (2013). Deep-sea container carrier performance: How efficient Are the respective container carriers. International Journal of Shipping and Transport Logistics, 5(1), 55-74.

43.

Woo, S. H., Pettit, S. J., & Beresford, A. K. C. (2011). Port evolution and performance in changing logistics environments. Maritime Economics and Logistics, 13(3), 250-277.

44.

Wu, H., Wu, J., Liang, L., & Li, Y. (2012). Efficiency assessment of Chinese logistics firms using DEA. International Journal of Shipping and Transport Logistics, 4(3), 212-234

45.

Wu, J., & Liang, L. (2009). Performances and benchmarks of container ports using data envelopment analysis. International Journal of Shipping and Transport Logistics, 1(3), 295-310.

46.

Yang, C. C., Lu, C. S., & Marlow, P. B. (2009). Assessing resources, logistics service capabilities, innovation capabilities and the performance of container shipping services in Taiwan. International Journal of Production Economics, 122(1), 4-20.

47.

Yeh, Q. J. (1996). The Application of Data Envelopment Analysis in Conjunction with Financial Ratios for Bank Performance Evaluation. Journal of the Operational Research Society, 47(8), 980-988.

48.

Yoo, Y. H., & Kim, S. C. (2011). Logistics Development Strategy in Korea; Focussing on 3PL. International Journal of Industrial Distribution & Business, 2(1), 17-22.

49.

Zhatkanbaev, E. B., Mukhtar, E. S., & Suyunchaliyeva, M. M. (2015). Innovative Mechanisms in the Procurement Logistics of Kazakhstan. Journal of Asian Finance, Economics and Business, 2(3), 33-36.

50.

Zhou, G., Min, H., Xu, C., & Cao, Z. (2008). Evaluating the comparative efficiency of Chinese third-party logistics providers using data envelopment analysis. International Journal of Physical Distribution &Logistics Management, 38(4), 262-279.

The Journal of Distribution Science