Evaluating seaport policy alternatives: A simulation study of terminal leasing policy and system performance

Maritime Policy and Management

Volumn 27, Issue 3, 2000, Pages 283-301

  Turner, Hugh S ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PERFORMANCE ASSESSMENT; PORT; PRODUCTIVITY;

COMPETITIVENESS; PERFORMANCE ASSESSMENT; PORT; TRANSPORTATION POLICY;

EID: 0033816307     PISSN: 03088839     EISSN: 14645254     Source Type: Journal    
DOI: 10.1080/030888300411112     Document Type: Article

References (43)

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2. ‘Time in system’ is defined as the sum of arrival time, time in queue, service time and departure time
3. Dedicated terminals are defined as terminals under the exclusive control of an ocean carrier through a subsidiary marine terminal operator (MTO). In contrast, a commonuser terminal is one operated by an independent MTO providing service to more than one ocean carrier
4. HEAVER, T., 1995. The implications of increased competition among ports for port policy and management. Maritime Policy Management, 22:125–133.
5. NICOLAOU, S., 1967. Berth planning by evaluation of congestion and cost. Journal of Waterways and Harbors Division, 93:107–132. See, for example, NORITAKE, M. and KIMURA, S., 1983, Optimum number and capacity of seaport berths. Journal of Waterway, Port, Coastal and Ocean Engineering, American Society of Civil Engineers, 109, 323-339; and SCHONFELD, P.and SHARAFELDIEN, O. 1985, Optimal berth and crane combinations in containerports. Journal of Waterway, Port, Coastal and Ocean Engineering, 111, 1060-1074
6. HOLGUIN-VERAS, J., and WALTON, C., 1995. A Categorized and Annotated Bibliography to the Performance Analysis of Port Operations, Austin, TX:Southwest Region University Transportation Center, Center for Transportation Research. A summary of the literature for both analytical models and simulation can be found in
7. VARAPRASAD, N., 1986. Optimum port capacity and operating policies:a simulation study. Transport Policy and Decision-Making, 3:297–312.
8. EVERS, P., 1994. The occurrence of statistical economies of scale in intermodal transportation. Transportation Journal, 33:51–63.
9. SILVER, E., and PETERSON, R., 1985. Decision Systems for Inventory and Production Planning, New York:Wiley. [8] quoting
10. EPPEN, G., and SHRAGE, L., 1981. “Centralized ordering policies in a multi-warehouse system with lead times and random demand”. In Multi-Level Production/Inventory Control Systems:Theories and Practice, Edited by:Schwartz, L., Amsterdam, Holland:North Holland Publishing.
11. Evers, P., and BEIER, F., 1993. The portfolio effect and multiple consolidation points:A critical assessment of the square root law. Journal of Business Logistics, 14:109–125. For a summary, see
12. JANSSON, J., and SHNEERSON, D., 1982. Port Economics, Cambridge, MA:MIT Press.
13. TALLEY, W., 1994. Performance indicators and port performance evaluation. Logistics and Transportation Review, 20:339–352.
14. Defined as the sum of port charges and user costs by Jansson and Shneeson [12], p. 5
15. CHADWIN, M., POPE, J., and TALLEY, W., 1990. Ocean Container Transportation:An Operational Perspective, 11New York:Taylor & Francis.
16. WATSON, W., ENGLAND, G., and ARMOR, B., 1995. “Port of Seattle Terminal 5 expansion and development”. In Ports '95, American Society of Civil Engineers.
17. SHELDON, C., ENGLAND, G., and BONIFACIO, N., 1998. “Organizing to deliver an ‘impossible’ project”. In Ports '98, American Society of Civil Engineers.
18. ARMOUR, W., ENTGLAND, G., and BONIFACIO, N., 1998. “Up and running:Final design and startup of the Terminal 5 expansion at the Port of Seattle”. In Ports '98, American Society of Civil Engineers.
19. Containerization Yearbook International, London, UK:National Magazine Co.
20. UNITED STATES ARMY CORP OF ENGINEERS. 1998. NDC Publications and US WaterwayData CD, Alexandria, VA:Water Resources Support Center, Navigation Data Center.
21. http://www.portseattle.org
22. NICOLAOU, S., 1967. Berth planning by evaluation of congestion and cost. Journal of the Waterways and Harbors Division, American Society of Civil Engineers, 93:107–132.
23. RUDOLF, C., 1995. “A cost comparison of modern container cranes”. In Ports '95, American Society of Civil Engineers.
24. JORDAN, M., 1995. “Dockside container cranes”. In Ports '95, American Society of Civil Engineers.
25. TABERNACLE, J., 1995. A study of the changes in performance of quayside container cranes. Maritime Policy and Management, 22:115–124.
26. KRAMAN, M., HEADLAND, J., and MCNEAL, P., 1998. “Probabilistic analyses of port throughput and berth optimization”. In Ports '98, American Society of Civil Engineers.
27. It is assumed that adequate berthing space exists, even when other terminal resources are busy, or that vessels will adjust speed on the final leg of the voyage to avoid the extra step of anchoring to await a berth
28. If 100% of vessel's TEU capacity was first discharged, then the vessel was reloaded to 100% capacity, the resulting factor would be 200%
29. VANDEVEER, D., 1998. “Port productivity standards for long-term planning”. In Ports '98, American Society of Civil Engineers.
30. UNITED STATES MARITIME ADMINISTRATION. 1997. Congressional Ports Report, I-1Washington, DC:US Department of Transportation.
31. MONGELLUZZO, B., 1998. Port of Seattle opens 160-acre mega-terminal. Journal of Commerce, September 14:15A
32. CSAV, DSR-Senator, Poseidon and Sunmar.
33. VELDMAN, S., 1993. “The optimum size of ship and the impact of user cost—an application to container shipping”. In Current Issues in Maritime Economics, Edited by:Gwilliam, K. M., Dordrecht, Holland:Kluwer Academic. $40 000/day based on, Cost is for a 2400 TEU vessel and is comprised of capital, labour, administrative and auxiliary engine fuel. Cost is in 1996 dollars adjusted from 1993 dollars at a 5% annual rate of inflation. For sensitivity analysis, more conservative estimates of $30 000/day and $20 000/day are included in table 9
34. CORR, O., 1996. Full steam ahead for SSA—expansion deal with Port shows how business is done in a world of shared interests. Seattle Times, December 22:J1 $50 000/acre based on, The higher estimate of $93 000/acre is based on the Port of Seattle's 1998 financial statement, which states that the 1999 minimum rental income for the marine division is $39 558 000. Dividing this by the 426 acres of terminal capacity yields an annual lease rate of $92 859 per acre.
35. Observations during the warm-up period were included
36. The results yield a factor greater than the square root of the number of terminals (6=2:449 compared to (5261.78/864.68)=6.085). Since the square root law assumes identically distributed random variables, such a result is not surprising. TEU capacities for carriers are modelled using unique discrete distributions, thus the assumption of identical distributions necessary to arrive at the same factor as the square root law is not valid in this application
37. See the actions of Atlantic coast seaports in response to Sea-Land/Maersk's 1998 request for a new terminal
38. KRAMAN, M., HEADLAND, J., and MCNEAL, P., 1998. “Probabilistic analyses of port throughput and berth optimization”. In Ports '98, American Society of Civil Engineers.
39. ABRAMS, A., 1991. Allegations of discrimination pit ports against stevedores. Journal of Commerce, September 27:8B
40. AMERICAN SHIPPER. 1991. Independent terminals join forces; Independent Marine Terminal Operators Council formed, 33 October:83
41. TALLY, W., 1988. The role of US ocean ports in promoting an efficient ocean transportation system. Maritime Policy and Management, 15:147–155.
42. TALLEY, K., 1999. The Sea-Land/Maersk and Port of New York and New Jersey Agreement. IAME Newsletter, 24 October:7–8. International Association of Maritime Economists
43. Using APL as an example, there is a 0.049 probability the arriving vessel will have a capacity of 1920 TEU, a 0.029 (0.078-0.049) probability it will have a 2700 TEU capacity, a 0.432 (0.510-0.078) probability it will have a 4340 TEU capacity and a 0.490 (1-0.510) probability it will have a 4832 TEU capacity. Thus, the probabilities sum to 1.0