ANALYSIS OF HUB PORT CHOICE FOR CONTAINER TRUNK LINES IN EAST ASIA

ANALYSIS OF HUB PORT CHOICE FOR CONTAINER TRUNK LINES IN EAST ASIA

Hui-huang TAI Assistant Professor Department of Shipping and Transportation Management National Kaohsiung Marine University No.142, Hai-Chuan Rd. Nan-Tzu, 811, Kaohsiung, Taiwan E-mail:[email protected]

Cherng-chwan HWANG Professor Institute of Traffic and Transportation National Chiao Tung University 4F, No. 114, Sec. 1 Chung Hsiao W. Road, 100, Taipei, Taiwan FAX: 886-2-2349-4953 E-mail:[email protected]

Abstract: East Asia is the most blooming area among global container shipping services. Most of the oceangoing lines select major ports such as Busan, Shanghai, Yantian, Hongkong, etc. as the transshipment and hub points. Since the deployment of trunk routes operated by main liners in this region is getting complicated and diversified, it is worth while to comprehend the operations of shipping liner, and the influential factors of hub ports choice in this area. This paper starts with an overall analysis of the performance of hub ports and change of trunk routes deployment based on statistical data of port operations, slots supply and operating routes of main shipping lines etc., collected from various sources. Secondly, the influential factors of selecting hub ports by shipping lines are investigated by conducting a questionnaire survey. Finally, the Gray decision model would be used to rank the relative competitiveness of these major ports from the viewpoints of container liners. Key Words: container shipping, hub ports, trunk routes 1. INTRODUCTION Among the three major global trunk routes, including the Trans-Pacific (T/P), Far East-Europe (F/E) and trans-Atlantic (T/A), T/P carries the highest percentage of worldwide cargo volume (Containerization International, Feb. 2004). Since East Asia is the intermediate district connecting T/P and F/E routes, all the major shipping lines have expanded their service networks and size of fleet in this booming area, in order to increase their carrying capacity to meet the growing demand of container transportation. In East Asia, it becomes more complicated for shipping lines to deploy the trunk routes and select hub ports than North-America and Europe because of the fast growth in cargo volume and port expansions of Mainland China (Tiwari et al., 2003). In container transportation, shipping companies dominate the decision of port choice and there are many factors that may influence the decision of port choice, such as cargo source (Slack,1993; Murphy & Daley, 1994; Song, 2002, 2003), port facilities (Chen, 1997; Cullinane et al., 2002; Fung, 2001), delivery distance (Malchow and Kanafani, 2001; Zohil and Prijon, 1999), port location (Ha, 2003; Malchow and Kanafani, 2001) and operating cost (Tai and Hwang, 2001; Tai, 2000; Wu, 2000), etc. There is a need to explore the degree of influence of these factors on port selection from the viewpoints of shipping companies. In earlier days, most major liners can only select Busan, Kaohsiung, Hongkong and Singapore as hub ports in this region, but with fast growth in cargo volume of China market, as well as vast investment on expansion and modernization of its port facilities, additional new port such as Shanghai, Yantian become available to shipping companies for selection as a hub,

Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp. 907 - 919, 2005

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competition among these major ports in East Asia thus getting serious recently. It is also an interesting problem to compare the relative competitiveness of these ports. This article starts with an overall analysis of the container shipping market in this region, especially on the performance of hub ports and change of trunk routes deployment, which is presented in section 2. In order to explore the important factors resulting in the change of trunk routes deployment, results obtained from a questionnaire survey on the factors influencing hub ports choice of shipping lines are then presented in section 3. Finally, the relative competitiveness of the major ports is ranked by the Gray Decision model based on some selected factors screened from the available data collected in the previous two sections, as presented in section 4. 2. OVERALL ANALYSIS OF THE SHIPPING MARKET

2.1 Cargo Flows East Asia, including Korea, Japan, China, Taiwan, Singapore and other adjacent countries, generates the highest amount of global containerized cargoes. In terms of container exports, China clearly dominates world container exports and nearly double the U.S.A. exports in TEUs, which represents 20% of the world’s containerized exports in 2003. It is predicted that the high growth of exports will be sustained in double-digits through 2005 (Shipping Statistics & Marine Review; SSMR, June/Nov/Dec, 2003). Table 1 shows container cargoes originated in the East Asia region is much greater than that destinated to the region, especially for the cargo flows between East Asia and North America.

Table 1. The Cargo Flows of Container Worldwide, 2001~2005 (Unit：Thousand TEUs)

Origin-destination 2001 2002 2003* 2004* 2005* EA – NA 7,622 8,813 10,190 11,320 12,264 NA – EA 3,897 3,890 4,120 4,333 4,546

Total 11,519 12,703 14,310 15,653 16,810 EA – Europe 4,160 4,293 4,497 4,687 4,937 Europe – EA 2,698 2,800 2,956 3,104 3,260

Total 6,858 7,093 7,453 7,791 8,197 NA – Europe 2,169 2,220 2,295 2,361 2,428 Europe – NA 3,072 3,166 3,318 3,481 3,634

Total 5,241 5,386 5,613 5,842 6,062 Notes: EA (East Asia), NA (North America), * : Predicted amount. Source: Containerization International, Feb. 2003, pp. 5-7, Nov. 2003, pp. 6-7, Jan. 2004, pp. 5-6. 2.2 Shipping Capacity Table 2 shows that the total capacity of all shipping lines has been increasing from 5,266 to 7,751 thousand TEUs since 1997 till 2002, and the global proportion of total capacity owned by the top 20 container lines is also increasing from 50.69% to 61.50%. Besides, the average size of fleet (TC/TS and FC/FS), for both trunk and feeder are enlarged to meet the demand of cargo flows. If we classify the shipping lines by region, then the total capacity of Asian shipping lines, including Evergreen, Cosco, Hanjin, NYK, etc., is rising from 24.37% to 30.52% of the total global capacity.


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Table 2. The Capacity & Fleet of Top 20 Liners in East Asia 1997 (At 1997.11.01.)

Shipping Line

1. Maersk

2. Evergreen

3. P&ON

4. SeaLand

5. Cosco

6. Hanjin

7. APL(NOL)

AC 232,257 228,248 221,531 215,114 201,593 174,526 165,582 AC% 4.41% 4.33% 4.21% 4.09% 3.83% 3.31% 3.14% TC 158,537 169,800 127,031 87,222 128,533 36,727 59,253 TS 41 58 37 29 36 11 16 FC 14,030 23,231 43,187 6,590 90,951 13,636 4,072 FS 14 17 29 8 124 12 7 Shipping

Line 8.

MSC 9.

NYK 10.

MOL 11.

Hyundai 12. Zim

13. YingMing

14. CMACGM

AC 154,185 128,154 115,763 112,958 98,086 96,145 89,658 AC% 2.93% 2.43% 2.20% 2.15% 1.86% 1.83% 1.70% TC 19,888 107,862 87,358 108,271 56,593 80,661 72,031 TS 6 30 27 29 18 28 21 FC 3,039 52,456 25,274 2,299 15,729 10,965 3,328 FS 3 47 25 3 12 10 3 Shipping

Line 15.

OOCL 16. CP

17. K-Line

18.Hapag Lloyd

19. Cho-Yang

20. SCL Total(1997)

AC 85,940 85,016 84,198 73,372 55,882 51,002 2,669,210AC% 1.63% 1.61% 1.60% 1.39% 1.06% 0.97% 50.69%TC 75,364 26,083 64,737 72,143 10,394 2,020 1,550,508TS 20 13 23 19 4 1 467FC 13,326 0 15,461 0 3,365 1,704 342,643FS 13 0 18 0 5 1 351

2002 (At 2002.11.01.) Shipping

Line 1.

AP Moller 2.

MSC 3.

P&ON 4.Evergreen

(LT) 5.Hanjin (Senator)

6. Cosco

7.APL (NOL)

AC 773,931 413,814 406,654 397,600 304,409 255,937 227,749 AC% 9.99% 5.34% 5.25% 5.13% 3.93% 3.30% 2.94% TC 356,212 136,745 198,548 181,500 204,675 136,300 201,400 TS 76 30 49 61 53 36 45 FC 20,415 0 6,560 55,750 4,400 63,150 6,600 FS 10 0 8 43 4 63 7 Shipping

Line 8.CMA \CGM

9. MOL

10.CP Ships

11. NYK

12. K-Line

13. Zim

14. OOCL

AC 225,436 188,326 187,890 177,700 168,413 165,398 157,493 AC% 2.91% 2.43% 2.42% 2.29% 2.17% 2.13% 2.03% TC 140,960 156,410 26,450 102,890 139,450 97,911 129,315 TS 31 37 10 27 34 29 29 FC 0 24,315 0 25,750 20,020 1,400 13,500 FS 0 13 0 23 16 2 19 Shipping

Line 15.China Shipping

16.Hapag- Lloyd

17. Hyundai

18. YML

19.PIL Group

20.CSAV Group Total(2002)

AC 148,212 135,953 122,713 120,319 97,827 90,625 4,766,399AC% 1.91% 1.75% 1.58% 1.55% 1.26% 1.17% 61.50%TC 95,900 115,510 115,850 96,545 20,425 13,664 2,666,660TS 26 24 26 26 8 9 666FC 1,820 960 4,850 19,800 32,150 0 301,440FS 5 1 5 14 26 0 259Notes: 1. AC: the capacity of each liner owned (TEUs), TC & TS: the capacity (TEUs) and amount (No. of ships) that liner owned in trunk routes of East Asia, FC & FS: the capacity (TEUs) and amount (no. of ships) that liner owned in feeder routes of East Asia. 2. TC/TS: the average size of fleet in trunk routes of East Asia, increasing from 3,320 TEUs (1997) to 4,004 TEUs (2002). 3. FC/FS: the average size of fleet in feeder routes of East Asia, increasing from 976 TEUs (1997) to 1,164 TEUs (2002). Source: Containerization International Yearbook, 1998/2003, UNCTAD, Review of Maritime Transportation,

2003, and ISL (SSMR), No.6, No.10~No.12, 1998/2003.


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2.3 General Conditions of Major Ports In East Asia, Hongkong, Singapore, Busan and Kaohsiung have long been ranked within global top 10 ports in terms of annual throughput, but Shanghai has joined the list in resent years. In terms of growth in throughput, the annual growth rate of both Shanghai and Yantian are much greater than all other Asian ports, as shown in Table 3.

Table 3. Basic Data of Asian Major Ports Ports A B C D E F G H I

Tokyo 2,535,841 -12.54% 11 3,686 15 12 10 893,701 50,561 Yokohama 2,303,780 -0.59% 23 6,040 16 18 18 1,943,601 97,874 Kobe 2,010,343 -11.28% 33 9,355 15 17 16 2,258,791 113,190Nagoya 1,872,272 -2.07% 13 3,555 15 15 27 1,175,240 50,756 Osaka 1,502,989 1.95% 13 3,735 14 15 29 941,867 39,941 Busan 8,072,814 7.06% 62 11,040 15 18 18 3,013,340 162,830Hongkong 17,900,000 -1.10% 18 6,059 15 19 27 2,186,700 166,119Kaohsiung 7,540,524 1.54% 22 6,047 15 16 23 1,988,000 73,995 Shanghai 6,340,000 12.95% 18 2,281 13 10 7 858,000 60,800 Yantian 2,700,000 25.70% 5 2,350 15 16 9 1,180,000 64,000 Singapore 15,520,000 -8.92% 61 10,550 16 17 31 3,390,000 74,410 Notes: A&B: Traffic throughput at 2001 & growth rate (%), C: Numbers of berth, D: Total length of berth (M), E: Draft in harbor, F & G: Numbers of trunk / feeder services liners, H: Area of port marshalling Yard (M2), I: Designed capacity in total (TEUs). Source: 1. Containerization International Yearbook, 2003.

2. UNCTAD, Review of Maritime Transportation, 2003. 3. ISL (SSMR), No.6, No.10~No.12, 2003.

In connection with the fast growth in throughput of Shanghai and Yantian, Table 4 traces the change in weekly calls of trunk lines at these ports. It indicates an obvious phenomenon that many major liners have shifted to China ports accordingly.

Table 4. Trunk Frequency Deployments on Major Ports in East Asia (Calls/week) Port / Year Hongkong Busan Shanghai Singapore Yantian Kaohsiung Qingdao

1997 114 69 33 71 22 61 21 2002 120 66 73 68 47 45 41

Port / Year Kobe Tokyo Yokohama Nagoya Ningbo Dalian Tianjin 1997 61 51 49 19 18 16 20 2002 39 34 32 32 22 16 15

Source: 1. Containerization International Yearbook, 1998/2003. 2. UNCTAD, Review of Maritime Transportation, 1998/2003. 3. ISL (SSMR), No.6, No.10~No.12, 1998/2003.

Table 5 and Table 6 further summarized the hub ports selected by different shipping alliances on Trans-Pacific routes and FE/Europe routes in the year 2003 respectively. These two tables reveal that Busan, Hongkong, Shanghai and Yantian are the most frequently selected ports, followed by Kaohsiung.


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Table 5. Selection of Hub Ports by Shipping Alliances/Groups on Trans-Pacific Routes in 2003

Alliances/ Groups

8R S Type of ships(TEUs)

Average Size(TEUs)

Total Capacity(TEUs)

BS SH YT HK KA SP

1CHKY Alliance

14 94 1,702~ 5,592

4,077 383,283 9※ ※ ※ ※ ※ ※

2GRAND Alliance

8 61 3,002~ 5,670

4,279 230,278 ※ ※ ※ ※ ※ ※

3TNWA 9 58 2,920~ 6,400

4,519 260,389 ※ ※ ※ ※ ※ ※

4Gran Americana

6 53 2,758~ 6,600

4,631 236,876 ※ ※ ※ ※ ※ ※

5Evergreen 7 52 1,874~ 4,499

4,175 217,095 ※ ※ ※ ※ ※

6ZIM 2 29 2,935~ 3,956

3,463 100,430 ※ ※ ※ ※

7CSCL 4 24 2,324~ 4,175

2,911 69,864 ※ ※ ※ ※ ※

CMA/CGM 2 14 3,386~ 3,961

3,591 50,279 ※ ※ ※ ※

Notes: 1CHKY Alliance includes Cosco, Hanjin, K-Line, YML. 2GRAND Alliance includes Hapag-Lloyd, NYK, OOCL. 3TNWA(The New World Alliance) includes Hyundai, APL, MOL, MSC. 4Gran Americana based on A. P. Moller Group (Maersk Sea-land). 5Evergreen Group includes INCL, LT, Hatsu. 6ZIM includes Cont Service, Norasia. 7CSCL: China Shipping Group. 8 R: No. of trunk routes, S: No. of ships, BS: Busan, SH: Shanghai, YT: Yantian, HK: Hongkong, KA: Kaohsiung, SP: Singapore. 9※ Hub port of shipping alliance/group. Source：1. SSMR, June, 2003, pp. 9-11, 72-73. 2. Containerization International Yearbook 2003.

Table 6. Selection of Hub Ports by Shipping Alliances/Groups on FE/Europe Routes in 2003

Alliances/ Groups

6R S Type of ships(TEUs)

Average Size(TEUs)

Total Capacity(TEUs)

BS SH YT HK KA SP

CHKY Alliance 8 62 2,799~ 5,600

5,126 317,850 7※ ※ ※ ※ ※ ※

GRAND Alliance

7 60 3,484~ 7,047

5,118 307,170 ※ ※ ※ ※ ※ ※

TNWA 3 23 5,369~ 5,861

5,554 127,745 ※ ※ ※ ※ ※ ※

A. P. Moller Group

3 30 6,139~ 6,600

6,422 192,760 ※ ※ ※ ※ ※ ※

Evergreen 3 29 2,691~ 5,652

4,608 133,635 ※ ※ ※ ※ ※

1ZIM 2 29 2,934~ 3,957

3,463 100,431 ※ ※ ※ ※

CSCL 1 9 4,532 4,532 40,788 ※ ※ ※ ※ ※ 2CMA/CGM

/Norasia 3 24 4,195~

6,404 4,979 119,507 ※ ※ ※ ※

3CMA/CGM /P&ON/Marfret

1 12 2,275 2,275 27,300 ※ ※ ※ ※ ※ ※

4MSC 2 18 3,219~ 6,610

5,103 91,852 ※ ※ ※ ※

5UASC/Senator 1 10 3,800 3,800 38,000 ※ ※ ※ ※ ※ ※

Notes: 1ZIM includes Cont Service. 2 CMA/CGM includes Norasia. 3CMA/CGM includes P&ON, Marfre. 4MSC Group). 5UASC includes Senator (Hanjin Holding). 6 R: No. of trunk routes, S: No. of ships, BS: Busan, SH: Shanghai, YT: Yantian, HK: Hongkong, KA: Kaohsiung, SP: Singapore. 7※ Hub port of shipping alliance/group. Source：1. SSMR, June, 2003, pp. 9-11, 70-72. 2. Containerization International Yearbook 2003.


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2.4 Changes in Routes Deployment Figure 1 depicts the change on deployment of trunk routes in this region. Without Yantian, route deployment is relatively simple in that there are not many alternative choices, as shown in Fig.1-a. As Yantian becomes one of hub ports in the region, more alternatives are available for consideration (Fig.1-b), which not only complicate the problem of routes deployment, but also increase the competition among the four major ports; those are Hongkong, Kaohsiung, Shanghai and Yantian.

KobeBusan

Hongkong

Tokyo

Kaohsiung

Yokohama

Shanghai

Yantian

Singapore

Trans-Pacific Trunk RoutesＴ／Ｐ

Far East/ Europe Trunk RoutesＦ／Ｅ

Fig. 1-a

KobeBusan

Hongkong

Tokyo

Kaohsiung

Yokohama

Shanghai

Yantian

Singapore

The Trunk Routesof Major Shipping Lines

Trans-Pacific Trunk RoutesＴ／Ｐ

Far East/ Europe Trunk RoutesＦ／Ｅ

Fig. 1-b

Figure 1. Change of Trunk Routes in East Asia 3. INFLUENTIAL FACTORS OF HUB PORT CHOICE In order to gain more insights about the relative importance of many possible influential factors on hub ports choice of major liners, a questionnaire survey was conducted, and the results are briefly presented in this section. Some of the data collected from this survey are also used to rank the relative of competitiveness among Shanghai, Kaohsiung, Yantian and Hongkong by the Gray Decision theory in next section. 3.1 Questionnaire Design and Survey The questionnaire form is divided in two parts. Part 1 lists possible influential factors, in which score of each factor would be filled by the persons being surveyed. Factors are selected on the basis of literature review as well as discussions with experts in shipping industry, which are classified into following three categories.


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Category A: internal factors of port, including efficiency of handling facilities, area of marshalling yard, total no. of berth, draft of harbor, level of port charge, type of port authority, and quality of customer service. These 7 items are coded as A1-A7. Category B: external factors of port, including cargo source of hinterland, efficiency of clearance, location of port, convenience of inland transportation, and frequency of trunk and feeder routes. These 5 items are coded as B1-B5. Category C: operational factors of shipping lines, including saving in operating cost, preference of mother port, political considerations, capability of branch/agent, coordination of shipping alliance, and investment of dedicated terminals. These 6 items are coded as C1-C6. The score of each factor is measured by Likert’s 5 scale of rank, in which rank 5 to rank 1 represents “very important”, “important”, “average”, “less important”, and “not important” respectively. Part 2 of the questionnaire form collects basic operational information of the shipping firms being surveyed, which are summarized in Table 7 and Table 8.

Table 7. Basic Data of the Shipping Firms Type of Shipping Co. Samples % Capital(NT$) Samples %

2. Key agents 42 46 3. More than 3,000 million 34 371. Shipping lines/ branches 49 54 2. 300~3,000 million 14 15

1. Less than 300 million 43 47Total 91 100 Total 91 100Region of Shipping Co. Samples % Income(NT$) Samples %

3.Other regions 19 21 3. More than 3,000 million 48 532.Asian companies 26 29 2. 300~3,000 million 27 301.Companies across the Taiwan Strait 46 51 1. Less than 300 million 16 18

Total 91 100 Total 91 100 The questionnaire form is sent out to all the top 20 shipping lines, their branches and key agents spreading in all of the 4 hub ports, including portage and shipping agents, but excluding the freight forwarders that are not dedicated shipping agents of any liner. The survey was conducted during the September, 2004. A total sample of 146 copies of the questionnaire has been sent out, and 91 returned copies of which are examined as valid. 3.2 Analysis of Basic Data Basic data in part 2 of the 91 valid copies of returned questionnaire are summarized in Table 7 and Table 8. Table 8 shows that 96% of the shipping firms have established branches or key agents in Hongkong and Kaohsiung, 89% and 71% in Shanghai and Yantian. Regarding to the calling frequency, most companies have more than 5 calls per week in each port, especially in Hongkong (79%) and Kaohsiung (78%).


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Table 8. Operational Statistics of Shipping Companies in Hub Ports Hub port Shanghai Kaohsiung Yantian Hongkong

Frequency / percent Fq. % Fq. % Fq. % Fq. % Yes 81 89 87 96 65 71 87 96 With or without

branch / Key agents No 10 11 4 4 26 29 4 4 More than 300 thousand TEUs 33 36 36 40 19 21 43 47

200~ 300 thousand TEUs 11 12 8 9 8 9 11 12

150~ 200 thousand TEUs 16 18 14 15 14 15 17 19

100~ 150 thousand TEUs 10 11 13 14 6 7 6 7

50~ 100 thousand TEUs 4 4 4 4 6 7 7 8

30~ 50 thousand TEUs 3 3 5 6 9 10 0 0

10~ 30 thousand TEUs 3 3 4 4 1 1 2 2

Less than 10 thousand TEUs 1 1 3 3 2 2 1 1

Total throughput of each hub port in 2003 (TEUs)

None filled 10 11 4 4 26 29 4 4 Total 91 100 91 100 91 100 91 100

More than 5 calls 53 58 71 78 35 39 72 79 4 calls 16 18 8 9 12 13 5 6 3 calls 4 4 0 0 6 7 5 6 2 calls 7 8 3 3 5 6 1 1 1 calls 1 1 5 6 7 8 4 4

Total calling frequency of each hub port in 2003 (calls/week)

0 calls 10 11 4 4 26 29 4 4 Total 91 100 91 100 91 100 91 100

3.3 Rank of Influential Factors

Table 9. Scores and Ranks of Influential Factors Influential Factors Rank Mean Std. Deviation

B1. Cargo source of hinterland 1 4.407 0.683 A1. Efficiency of handling facilities 2 4.340 0.970 C1. Saving in operating cost 3 4.264 0.929 A4. Draft of harbor 3 4.242 0.808

G1

B5. Frequency of trunk and feeder routes 4 4.143 0.838 B2. Efficiency of clearance 5 4.011 1.080 B3. Location of port 5 4.011 0.937 A5. Level of port charge 6 3.978 1.145 A3. Total no. of berth 6 3.978 0.830 C4. Capability of branch/agent 7 3.934 1.009 B4. Convenience of inland transportation 7 3.934 0.904 A2. Area of marshalling yard 8 3.923 0.922 C6. Investment of dedicated terminals 8 3.923 0.934 A7. Quality of customer service 9 3.868 1.046 C5. Coordination of shipping alliance 10 3.802 0.833

G2

C2. Preference of mother port 11 3.725 1.203 C3. Political considerations 12 3.165 1.195 G3 A6. Type of port authority 13 3.110 1.005


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The mean score and standard deviation of each influential factor are calculated on the basis of the 91 valid samples, and the order of importance for those influential factors is primarily ranked by the mean scores, as summarized in Table 9. Although the differences in average score of many factors are very small, which means these factors are equally important in the choice of hub port, they are roughly divided into 3 groups nevertheless. It seems reasonable that the two factors in G3 are considered less important than the others in G1 and G2 by the shipping firms. The importances of the 5 factors in G1 are also self-explanatory. 4. EVALUATION OF PORT COMPETITIVENESS As mentioned in the previous section that there exists competition among port of Shanghai, Kaohsiung, Yantian and Hongkong. It is thus interesting to compare the relative competitiveness of those four hub ports. There are several methodologies suitable for this problem, but in view of very limited information available at this time, the Gray Decision theory is considered as an appropriate method under this circumstances, it is thus adopted as the evaluation method by using part of the data collected in section 2 and section 3. 4.1 Introduction of Gray Decision Theory When a system is under the status of uncertain or imperfect information, the Gray theory is cited in the literature as a proper tool to describe and model the system, finally make out the clear and definite decision. Gray decision is a mechanism that could transfer the uncertainty of information to explicit instruction (Deng, 2000; Feng & Chiou, 2004). In this study, if the decision of competitiveness among those ports is defined as an event (Table 10), individual port becomes a different alternative (Bi), the collected information (Aj) can be transferred to definite value such that comparisons of all alternatives can be made.

Table 10. Decision Making for an Event on Multi-alternatives

Bi＼Aj A1 A2 … Aj … An B1 U11 U12 … U 1j … U1n B2 U21 U22 … U 2j … U2n … … … … … … … Bm Um1 Um2 … U mj … Umn

In Table 10, Uij means the measure of some information (Aj) against alternative (Bi), if the function M existed and could be mapping from Uij to Rij, if and only if: M(Uij)= Rij, Rij∈［0, 1］, Rij ∈X+; X+ belong to positive space. There are several functions on transfering Uij to Rij (Deng, 2000): A. Upper effect measure: the effect derived from the measure Uij, such as profit, revenue,

throughput, etc., is positive. We could use the following mode to transfer the Uij : Rij = Uij ／

iMAX Uij

B. Lower effect measure: the effect derived from the measure Uij, such as cost, time, etc., is negative. We could use the following mode to transfer the Uij : Rij =

iMIN Uij ／ Uij

C. Medium effect measure: if the measure Uij is belong to neutrality effect, we could use the following mode to transfer the Uij :


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Rij = i

MIN (Uij, Ui0)／i

MAX ( Uij , Ui0) ; Ui0 = (1/m)∑=

m

i 1

Uij

After transference, an overall index for each alternative RiΣ is calculated by suming up the

new measures (Rij) as following equation. Evaluation is then made by comparing the overall index Ri

Σ of each alternative.

RiΣ = (1/n) * ∑

=

n

j 1

Rij , i= 1, 2, 3,…, m.

4.2 Model Application On the issue of port competitiveness, the comparison usually also made by considering factors of both internal conditions and external circumstance of the ports. There are 9 items of information being selected as inputs to the model, which are shown in Table 11.

Table 11. Inputs of Gray Decision Model Item No. Descriptions

1 Average growth rates on container throughput from 1997 to 2001(Unit: %) 2 Total no. of container berths (Unit: No.) 3 Total length of berth (Unit: meter) 4 Max draft on channel/turning basin/container berths (Unit: meter) 5 Numbers of trunk / feeder liners (Unit: No.) 6 Area of marshalling yard (Unit: M2) 7 Designed capacity in port (Unit: TEUs)

8 (ωTEUs) The weight of liners’ throughput in each port (Generated by questionnaire) 9 (ωFQ) The weight of sailing frequency in each port (Generated by questionnaire)

Item 1~7 of Table 11 represents factors of internal conditions of a port, and item 8 & 9 represents external circumstance of a port. Definition and implications on some of these items are further illustrated below. A. The cargo source of hinterland (B1 in Table 9) could be represented by the weight (item 8,

ωTEUs/i) calculated from the returned questionnaire, which is defined as: ωTEUs/i = θi /θall , θi : Sum of throughput (TEUs) in port i for all companies. θall : Sum of throughput (TEUs) of all hub ports for all companies.

B. The density of sailing frequency (B5 in Table 9) reacts to the real running demand of shipping lines on a port. It cloud be represented by the weight (item 9, ωFQ/i) also calculated from the returned questionnaire, which is defined as:

ωFQ/i = λi /λall , λi : Sum of sailing frequency in port i for all companies. λall : Sum of sailing frequency of all hub ports for all companies. C. Comparing with factors of G1 in Table 9, some high ranked items such as A1 (efficiency

of handling facilities) and C1 (saving in operating cost) are omitted due to the difficulties in obtaining accurate data.

D. Cargo source of these 4 hub ports contains both “transshipment cargoes from feeder ports” and “direct shipment cargoes from the hinterland”. The proportion of these two sources of cargoes is different for each of the 4 ports. It would be better to separate these two sources, but due to the limitation of data availability, they are combined together as item 1.


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All of the measure (Uij) could be transferred to Rij using upper effect mode. Table 12 shows all the information (Uij) and the result of transferred measure (Rij).

Table 12. Decision Information for Alternative Port Ports Item No. 1 2 3 4 5 6 7 8(ωTEUs) 9(ωFQ)

Uij 37.89% 18 2,281 13 17 858,000 60,800 0.259 0.252Shanghai (S) Rij 0.39 0.82 0.38 0.87 0.37 0.39 0.37 0.86 0.89

Uij 8.11% 22 6,047 15 39 1,988,000 73,995 0.263 0.282Kaohsiung (K) Rij 0.08 1.00 1.00 1.00 0.85 0.91 0.45 0.88 0.99

Uij 97.25% 5 2,350 15 25 1,180,000 64,000 0.177 0.183Yantian (Y) Rij 1.00 0.23 0.39 1.00 0.54 0.54 0.39 0.59 0.64

Uij 5.69% 18 6,059 15 46 2,186,700 166,119 0.301 0.284Hongkong (H) Rij 0.06 0.82 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Finally, the overall index of each port i is calculated as follows:

RiΣ = (1/n) * ∑

j

Rij , i= S, K, Y, H, j= 1, 2,…, 9.

The result is shown below: ［RS

Σ , RKΣ , RY

Σ , RHΣ］=［0.54, 0.72, 0.53, 0.79］,

iMAX Ri

Σ = 0.79 = RHΣ

Based on those figures, Hongkong is ranked as the hub port with the highest competitiveness, followed by Kaohsiung. 5. CONCLUDING REMARKS Based on the analysis of collected statistics, there are heaviest container flows between the East Asia and North America in the global liner shipping market. The major shipping lines expand their service network of trunk and feeder routes among several hub ports, put into large amount of fleet capacity in this region. It is clear that there exist competition among hub ports in this region, especially among Shanghai, Kaohsiung, Yantian and Hongkong. The result of questionnaire survey indicates that among the 18 influential factors that might affect liners’ hub ports choice, the most important factors are “handling efficiency” and “draft of harbor” that belong to the internal factors of ports, “cargo source of hinterland” and “frequency of routes” that belong to the external factors of ports, and the “saving in operating cost” for shipping lines. For the relative competitveness among these ports, Hongkong is the one with the highest competitiveness, followed by Kaohsiung. But more sophisticated method in company with more data collection work is recommended for further study, to obtain more persuasive result.


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ANALYSIS OF HUB PORT CHOICE FOR CONTAINER TRUNK LINES IN EAST ASIA

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