Publisher : Korean Institute of Navigation and Port Research
DOI : 10.5394/KINPR.2010.34.9.719
Title & Authors
Operational Performance Evaluation of Korean Major Container Terminals Lu, Bo; Park, Nam-Kyu;
As the competition among the container terminals in Korea has become increasingly fierce, every terminal is striving to increase its investments constantly and lower its operational costs in order to maintain the competitive edge and provide satisfactory services to terminal users. The unreasoning behavior, however, has induced that substantial waste and inefficiency exists in container terminal production. Therefore, it is of great importance for the terminal to know whether it has fully used its existing infrastructures and that output has been maximized given the input. From this perspective, data envelopment analysis (DEA) provides a more appropriate benchmark. This study applies three models of DEA to acquire a variety of analytical results about the operational efficiency to the Korean container terminals. According to efficiency value analysis, this study first finds the reason of inefficiency. It is followed by identification of the potential areas of improvement for inefficient terminals by applying slack variable method and giving the projection results. Finally, return to scale approach is used to assess whether each terminal is in a state of increasing, decreasing, or constant return to scale. The results of this study can provide terminal managers with insight into resource allocation and optimization of the operating performance.
Efficiency;Korean major container terminals;Data envelopment analysis;Throughput;Performance;
An Analysis of Container Port Efficiency in ASEAN, Journal of Navigation and Port Research, 2012, 36, 7, 535
Features Selection based on Fuzzy Entropy for Data Envelopment Analysis Applied to Transport Systems, Transportation Research Procedia, 2014, 3, 602
Avriel, M., Penn, M., and Shpirer, N., (2000), "Container ship stowage problem: complexity and connection to the colouring of circle graphs", Discrete Applied Mathematics 103, 271–279.
Andersen, P. and Petersen, N. C., (1993) "A procedure for ranking efficient units in data envelopment analysis", Management Science, 39, 1261–1264.
Banker, R. D., Charnes, A. and Cooper, W. W., (1984), "Some models for estimating technical and scale inefficiencies in data envelopment analysis", Management Science, 30, 1078–1092.
Barros, C. P., and Athanassiou, M. (2004) "Efficiency in European seaports with DEA: Evidence from Greece and Portugal", Maritime Economics and Logistics, 6(2), 122–140.
Chu, C., and Huang, W., (2002), "Aggregate crane handling capacity of container terminals: the port of Kaohsiung", Maritime Policy and Management 29 (4), 341–350.
Charnes, A., Cooper, W. W. and Rhodes, E., (1978), "Measuring the efficiency of decision making unit", European Journal of Operational Research, 2, 429–444.
Cheon S.H., David E., and Song,D.-W., (2010), "Evaluating impacts of institutional reforms on port efficiency changes: Ownership, corporate structure, and total factor productivity changes of world container ports", Transportation Research Part E 46 (2010) 546–561.
Cullinane, K.P.B., Ji, P., and Wang, T.-F., (2005), "The relationship between privatization and DEA estimates of efficiency in the container port industry", Journal of Economics and Business 57 (2005) 433–462
Cullinane K., Wang, T.-F., and Song, D.-W., (2006), "The technical efficiency of container ports: Comparing data envelopment analysis and stochastic frontieranalysis", Transportation Research Part A 40 (2006) 354–374
Forsund, F.R., Lovell, C. A. K. and Schmidt, P., (1980), "A survey of frontier production functions and their relationship to efficiency measurement", Journal of Econometrics, 13, 5–25.
Forsund, F.R., and Sarafoglou, N., (2002), "On the origins of data envelopment analysis", Journal of Productivity Analysis 17, 23–40.
Itoh, H. (2002), "Efficiency changes at major container ports in Japan: A window application of data envelopment analysis", Review of Urban and Regional Development Studies, 14(2), 133–152.
Kim, K.H., (1997), "Evaluation of the number of rehandles in container yards", Computers and Industrial Engineering 32 (4), 701–711.
Kim, K.H., and Bae, J.W., (1998), "Re-marshaling export containers in port container terminals", Computers and Industrial Engineering 35 (3/4), 655–658.
Kim, K.H., and Kim, H.B., (1998), "The optimal determination of the space requirement and the number of transfer cranes for import containers", Computers and Industrial Engineering 35 (3/4), 427–430.
Kim, K.H., and Kim, K.Y., (1999), "An optimal routing algorithm for a transfer crane in port container terminals", Transportation Science 33 (1), 17–33.
Le-Griffin, H. D., and Murphy, M., (2006), "Container terminal productivity: experiences at the ports of Los Angeles and Long Beach"
Lin, L. C. and Tseng, C. C., (2007), "Operational performance evaluation of major container ports in the Asia-Pacific region", MARIT. POL. MGMT., DECEMBER 2007 VOL. 34, NO. 6, 535–551.
Liu, Z., (1995), "The comparative performance of public and private enterprises: the case of British ports", Journal of Transport Economics and Policy 29 (3), 263–274.
Robinson, D., (1999), "Measurements of Port Productivity and Container Terminal Design: A Cargo Systems Report. IIR Publications, London"
Roll, Y., & and Hayuth, Y., (1993), "Port performance comparison applying data envelopment analysis (DEA)", Maritime Policy and Management, 20(2), 153–161.
Song, D. W., Cullinane, K. P. B., and Wang, T.F., (2003), "An application of DEA window analysis to container port production efficiency" In International association of maritime economists annual conference.
Tongzon, J., and Heng, W., (2005), "Port privatization, efficiency and competitiveness: some empirical evidence from container ports (terminals)", Transportation Research A: Policy and Practice 39 (5), 405–424.
Wilson, I.D., and Roach, P., (2000), "Container stowage planning: a methodology for generating computerised solutions", Journal of the Operational Research Society 51 (11), 248–1255.