Maritime Cluster Types

1

Analysis on Development Interplay between Port and Maritime Cluster

Jasmine Siu Lee Lam

Division of Infrastructure Systems and Maritime Studies School of Civil and Environmental Engineering

Nanyang Technological University, N1, 50 Nanyang Avenue Singapore 639798

Email: [email protected] Tel: +65 6790 5276 Fax: +65 6791 0676

Wei Zhang

Division of Infrastructure Systems and Maritime Studies School of Civil and Environmental Engineering

Nanyang Technological University, N1, 50 Nanyang Avenue Singapore 639798

Email: [email protected]

Abstract

Recent research shows that maritime clusters can maximize competitive advantages in

maritime and regional development. Thus the creation and promotion of maritime

cluster has been taken as an important policy tool when considering an array of linked

sectors in the maritime industry from the network perspective. Of all the sectors in a

maritime cluster, port plays an important role in cluster development. This paper aims to

study the interrelationship between port development and maritime cluster

development. The analysis starts with an overview of maritime cluster, which is not a

static concept, but an evolutionary one based on the dynamics of its functions. The

development of a maritime cluster can be divided into four categories by the changing of

port and maritime services. They are cargo loading and discharging, value-added

processing and logistics, regional/global supply chain hub, and international maritime

services. The paper then identifies some world famous maritime clusters, which are

already or capable of being the international maritime centre (IMC), commonly regarded

as the most matured stage of maritime cluster. Two case examples, namely London

and Hong Kong, are drawn from these clusters, showing ports contribution to maritime

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cluster development, and reflecting the relationship between port development and

maritime cluster development. In order to study the coordinated development

quantitatively among different ports and maritime clusters, Data Envelopment Analysis

(DEA) is proposed, aiming to evaluate the validity of support and utilization between the

two systems. The paper presents a useful reference for research and policy

suggestions on the interplay between maritime cluster and its port development for

maritime cities and regions en route to higher value generating IMCs.

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1. Introduction

Cluster theory was developed over the last two decades as a tool for better

understanding the economic activities in service or knowledge-based regional

economies. The essence of a cluster is that the value of the whole exceeds the sum of

its parts, and that there is a critical mass - in one geographical place - of remarkable

competitive success in a particular field. Cluster is viewed to gain the advantage of

competitiveness. It reflects firstly the productivity, including accessing efficiently to

information, specialized inputs and employees, institutions, and public goods;

achieving complementarities across businesses; better incentives and performance

measurement. Secondly is innovation, including ability to perceive and respond to

innovation opportunities; and rapid diffusion of improvements. Thirdly is the formation,

including perceiving opportunities for new businesses and lowering barriers to entry,

including the perceived risk of market entry. These are the very reasons that industries

tend to carry on organizing mode in the form of cluster (Porter, 1990). The notion of

industry clusters has been revived in economics and has become central to business

strategists and industrial policy makers (Arthur, 1989; Krugman, 1991; Doeringer and

Terkla, 1995; Appold, 1997; Malmberg and Maskell, 1997; Bathelt et al., 2002; Martin

and Sunley, 2003; Sternberg and Litzenberg, 2004).

This study devotes to the analysis of maritime cluster. When taking reference from

business cluster, also known as industry cluster or competitive cluster, there is no

standard definition for the maritime sector. Often the definition starts with general

industry cluster then focuses on maritime section. For example, Chang (2011) based on

industry cluster and maritime industry, proposed the definition of maritime cluster as a

network of firm, research, development and innovation units and training organizations,

sometimes supported by national or local authorities, which cooperates with the aim of

technology innovation and of increasing maritime industrys performance. In this case,

some traditional areas of the maritime sector are identified, such as inland navigation,

marine aggregates, marine equipment, maritime services, maritime works, navy and

coastguard and offshore supply, recreational boating, seaports, ship building and

shipping. It also includes the coastal and sea-related (marine) recreation and tourism

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and fisheries (Ianca and Batrinca, 2010) in a broader way. What is more, it includes

other marine sectors, including emerging knowledge-intensive businesses and services

in marine science and technology (Kwak et al., 2005).

Of all the maritime sectors, port is regarded as an important one, for it is identified as

playing a core role in the whole maritime world and is taking up a more active role in

supply chains (Rodrigue and Notteboom, 2009). Today, growing international trade is

transforming the world economy into a single system and integrating world transport

activities. Ports are naturally being incorporated into this huge, changing and

competitive system. This is the very reason of resulting in port functions changing to

adapt this dynamic system. At the same time, the functions of maritime cluster are

changing to provide better and more efficient maritime services.

However, maritime cluster is not a once-for-all concept, it is a dynamic one with different

connotations in different development stages. Different historical period means different

cluster functions, vice versa, clusters in different situations reflect quite different stages

of economic and social development. It is such a changing formation and development

concept that any static and definitive claims of what a maritime cluster should be,

seems to be imprecise. However, few address the evolution of this definition and

connotation according to the existing literatures, not to mention this evolution depends

on the changing and development of port functions and maritime services. Though the

development of maritime cluster has close relationship with port, there is yet any

literature on the study of relationship between port and maritime cluster, either

qualitatively or quantitatively. The paper aims to study maritime cluster evolution from

the changing of port and maritime services perspective. Besides, in order to analyze the

contribution of port to maritime cluster, with contributions from other maritime sectors as

comparison, the paper studies the cases of London and Hong Kong. The two typical

examples are selected from the two identified categories of maritime clusters, In

addition, so as to study the coordination development between port and maritime cluster,

Data Envelopment Analysis (DEA) model is proposed, which provides the quantitative

method for future research.

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2. Maritime cluster connotation

2.1 Evolution and classification of maritime cluster

Maritime cluster comprises an array of linked sections in maritime industries. Taking an

overall review throughout famous maritime clusters, such as London, New York,

Rotterdam, Singapore, Hong Kong, etc, it can be observed that most maritime clusters

developed from port production in the early stage. It is interesting to find that maritime

cluster functions are evolved by the changing of port functions in some degree. Port

functions can be as limited as simple berthing facilities, ship/shore or intermodal

interfaces, or extended to trade, logistics and production centres (Bichou and Gray,

2005). Port function is also a changing concept, for they have different categories or

generations evolving with time, based on UNCTAD (1992). The following part discusses

the functions of maritime clusters based on the changing functions of port, see Table 1.

Port roles and functions, but also institutional structuring, as well as operational and

management practices vary significantly from generation to generation (UNCTAD,

1992). First and second generation ports, respectively relating to ship/shore and

industrial interfaces, operate bulk and break bulk cargo in a traditional manner, with the

second generation-type being reliant more on capital than labour. Third generation ports

are the product of the unitisation of sea-trade and multimodal cargo packaging (mainly

in the form of containers) which has led to the development of ports as logistics and

intermodal centres offering value-added services, with technology and know-how being

the major determining factors (Bichou and Gray, 2005). At the same time, the dynamic

definition and function of maritime cluster can be derived from the change in port

functions.

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Table 1 Maritime Cluster Classification Type 1 Type 2 Type 3 Type 4

Scope of activities

Cargo loading and

discharging, Cargo

storage and

distribution,

transportation

facilities,

navigational

service-Quay,

waterfront area

and distribution

channel

Logistics in value-

added processing for

cargo: initially

consolidating and

distributing products,

nearby industrial

processing,

combination,

grouping, packing

and commercial

marketing

Concentration and

distribution of factors

and production and

information, relating to

economic, financial,

technological,

communicational and

international trade

aspects

Variety of

maritime services

provided:

shipping services,

regulators,

industry

associations,

intermediate

services, support

services

Operation characteri-

stics

-Cargo flow

-Simple individual

service

-Low value-added

-Cargo

transformation

-Combined services

-Improved value-

added

-Cargo/information

distribution

-Multiple service

package

-Feature in

maritime services

-Operated by

highly advanced

human capital

Decisive factors

Labour/capital/Nat

ural conditions

Capital Technology/knowhow Knowhow

Main Functions

Cargo handling

and distribution

Value-added

processing

Key node in

global/regional supply

chains

International

maritime service

centre

Position of port in maritime cluster

-Conservative

-Changing point of

transport mode

-Expansionist

-Transport, industrial

and commercial

centre

-Efficiency oriented

-Integrated transport

centre and logistic

platform for international

trade

-Maritime service

oriented

-Varied positions

in different

maritime clusters

Current Examples

Dublin(Ireland),Selangor(Malaysia)

Antwerp (Belgium),

Kaohsiung (Taiwan),

Osaka (Japan)

Hamburg (Germany),

Hong Kong (China),

New York/New Jersey

(USA), Piraeus

(Greece), Rotterdam

(Netherlands),

Singapore, Shanghai

(China), Tokyo (Japan)

London (UK),

Oslo (Norway)

Source: authors

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In the first stage, maritime activities within maritime cluster focus on shipping and port -

cargo loading and discharging mainly. At the commercial level the different maritime

activities do not act together in unison, but make their decisions independently of how

other organizations in the same cluster will react. This was nevertheless quite natural at

the time of pre-containerization, since the commercial relationship between different

activities or the port was casual. Users were more familiar with individual sectors or

different port services, rather than with the maritime cluster in its entirety. As a result,

the main functions in the early maritime cluster are cargo handling and distribution.

London and Rotterdam were the pioneers of the first generation maritime cluster.

Around the Second World War, for example, New York and Hamburg played a big part

of it. Dublin in Ireland and Selangor in Malaysia at their current status (Brett and Roe,

2010; Othman et al., 2011) are considered in this category.

In the second stage, maritime cluster is the centre of cargo allocation and value-added

processing. It consolidates and distributes cargoes initially, including on the spot of

industrial processing, combination, grouping, packing and commercial marketing. It is

the typical centre of logistics and cargo allocation. Maritime activities in this stage are

also carried out in and around port of the second generation. In this category of ports,

governments, port authorities and those who provide port services have a broader

understanding of ports functions. The port is regarded as a transport, industrial and

commercial service centre. Thus ports are allowed to undertake and offer industrial or

commercial services to their users, which are not directly connected to the traditional

loading/discharging activity. Based on a broader conception and management attitude,

port policies, legislation and development strategies are made. As a result, the scope of

port activities is extended to commercial or any other relevant service such as cargo

packing, marking and industrial services such as cargo transformation. Industrial

facilities are built up within the port area. Therefore, maritime cluster develops and

expands towards its hinterland with industries such as iron and steel, heavy metallurgy,

refineries and basic petrochemicals, aluminium, paper pulp making, fertilizers, sugar

and starch, flour milling and various agro-food activities. The second generation

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maritime cluster is not only a transport centre but also industrial and commercial centre.

Second generation maritime clusters enjoy a closer relationship with transport and trade

partners who have built their cargo transformation facilities in the port area. The second

generation maritime clusters also have a closer relationship with the municipality since

they are more dependent on the surrounding city as regards land, energy, water and

manpower supply as well as the land transport connection systems. Therefore, the

second type maritime cluster is regarded as a cargo allocation, logistics and value-

added processing centre. For example, in this period Hong Kong and Singapore were

the creators of this type, followed up with New York, Rotterdam and London (De Langen,

2002; Fisher Associates, 2004; Maunsell Consultants, 2003), which completed the

function transition to this new era, whilst Antwerp and Kaohsiung are current examples.

World trade changes its pattern and develops in depth and in dimension. The multiplicity

of world trade centres calls for an extensive transport network. A greater variety of

transport services should be provided to link the whole world trade complex consisting

of big, medium and small centres. The third generation maritime clusters emerged in the

1980s, principally due to world-wide large scale containerization and intermodalism

combined with the growing requirement of supply chain management. A network

expansion is the first requirement of this new trade pattern. The important characteristic

in the third stage is integrated resources allocation. It integrates not only products but

capital, information and technology as well. When international trade is involved not only

before and after production but during the whole production process, maritime cluster

assumes a very special role, especially, being an important part of global supply chain,

it has the capacity for information processing and distribution. With various kinds of

resources, it engages actively in the international flow of factors of production. Maritime

cluster is regarded as the supply chain hub in global/regional economic and trade

market, enjoying largely the economies of density and scope by the effect of hub-and-

spoke system. Rotterdam, Hong Kong and Singapore are the leaders of this generation

(Janssen, 2006; Maunsell Consultants, 2003).

In the 1990s, the fourth-generation port concept was proposed which was physically

separated but linked through common operators or through a common administration. It

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is mainly the result of the recent vertical and horizontal integration strategies undertaken

by transport operators. However, this time maritime cluster has its new function as a

maritime service centre, so-called the international maritime centre. The details are

discussed below.

2.2 Formation of international maritime centre

The wide range of maritime cluster is as such that it can be viewed as making up of

several subsets. Taking London the worlds biggest maritime services centre as an

example, the maritime services cluster is shown in figure 1. Thus we define maritime

services to include an interconnected supply chain that covers several distinct activities:

Shipping, Intermediate Services, Maritime Governance and Regulation, Support

Services, and Industry Associations.

Fig. 1 Overview of the Maritime Services Cluster in London

Source: Fisher Associates (2004), p.14.

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Some of the intermediate services (specifically those related to marine insurance,

maritime law, and shipping finance) each form a niche market for a subset of the

financial services cluster in London. The port and physical cargo handling do not play a

major role in maritime services cluster. The focus is rather on knowhow which is high-

value and the most difficult to be imitated by competitors.

2.3 World famous maritime clusters

Maritime clusters come in a wide variety of forms depending on the mix of maritime

activities that make up the cluster and their relative weights within the cluster. According

to the analysis on the changing functions of maritime cluster, we can find different

maritime clusters show their generation characteristics differently. London falls into the

fourth-generation category, retaining the leading position. This section studies on

London and other maritime clusters identified as (potential) competitors to the London

maritime cluster. The (potential) competitors to the London cluster are primarily those

that have maritime services as a principal feature of the cluster, or that wish to expand

maritime services as a strategic objective. It is noted that not all maritime clusters as yet

identify themselves as maritime services centre. Several have yet to establish cluster

level institutions to provide support across the maritime activities that constitute the

cluster (Fisher Associates, 2004).

Based on the definition in Section 2.2, the competitive advantages of sixteen maritime

sectors on which to base this exercise are compared in Table 2 - Port, Marine insurance,

Ship Finance & Related Services, Ship registry, Shipowners, Operators & Managers,

Classification Society, Ship Agency and Forwarding, Shipbrokers, Maritime Legal

Services, Ship building and repair, Marine Personnel, Maritime Research, Education

and Training, Information and Communication Technology (ICT) Services, Maritime

Organisations /Associations, Maritime Culture and Heritage and government supporting.

Disadvantages comparison is shown in Table 3. Both tables are derived on the basis of

thorough review of literature and secondary sources, such as Fisher Associates (2004)

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and Hamburg: Wijnolst and Janssens (2006); Hong Kong: Maunsell Consultants (2003);

London: Brownrigg (2006), Dong (2010); New York/New Jersey: ; Oslo: Benito et al.

(2003), Wijnolst (2003), Jakobsen (2006), Reve (2009), Isaksen (2009); Piraeus:

Grammenos and Choi (1999); Rotterdam: De Langen (2002), Nijdam (2003), Wijnolst

(2003), Janssens (2006); Shanghai: Lam and Cullinane (2003); Singapore: Wonga

(2006) ; Tokyo: Shinohara (2006), Shinohara (2010), etc.

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Table 2 Comparison of world famous maritime clusters

Note: denotes maritime clusters have the competitive advantages in the particular aspects.

Source: Authors.

Maritimeadvantages Hamburg HongKong

London NewYork/NewJersey

Oslo Piraeus Rotterdam Shanghai Singapore Tokyo

Port Marineinsurance Financialservice Shipregistry Shipowners,Operators&Managers Shipclassificationsociety Shipagencyandforwarding Shipbrokers Legalservices Shipbuilding&repair Marinepersonnel Research,education&training Informationandcommunicationtechnology(ICT)Services

Regulators:MaritimeOrganisations/Associations/exchangemarket,etc.

Governmentalsupport Maritimecultureandheritage

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Table 3 Maritime cluster threats and disadvantages

Famous maritime cluster

Threats and disadvantages

Hamburg Relative remoteness in geographical location Poor access (eg. No. of intermodal connections) Restriction beyond a regional presence

Hong Kong Concern of being inhibited by government Port competition from mainland China

London The balance of shipping business now exists in Far East High property and salary costs Overall transport infrastructure Unfavourable UK tax measures Insufficient support from government

New York/ New Jersey

Insufficient capacity in port infrastructure Slowing growth of US economy

Oslo Relatively small scale Insufficient internal competition to drive quality and efficiency in

services

Piraeus Not being supported by cluster policies or initiatives Lack of international base of shipping companies, though a large

Greek shipping centre Not having a reputation of major shipping operators

Rotterdam Absence of a large financial services sector

Shanghai Not much value in short term to as a cluster analysis Singapore Hampered by protectionist policies in legal services sector

Corporatist does little to engender a risk-taking commercial culture

Tokyo Insufficient platform of maritime information and intelligence Weak influencing of maritime trading marketing

Source: Authors

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Based on tables 1 to 3 and port status in the various maritime clusters, the classification of maritime clusters can be carried out by the influences of their ports. The categorisation is shown in Table 4.

Table 4 Maritime clusters with/without strong port support

With/Without strong port support Typical world famous maritime clusters

With strong port support Hong Kong, Rotterdam, Hamburg, Singapore, Shanghai Without strong port support London, Oslo, Piraeus

Source: Authors.

3. Case studies of port in maritime cluster

Based on the above discussion, port plays an important part in the whole development

process of maritime cluster, though there are some famous maritime clusters without

port as a prior advantage in its development, such as Oslo. As such, port contribution to

maritime cluster development is an interesting research question which needs to be

compared and further studied.

3.1 Contribution of port in maritime cluster

At the early stage of maritime cluster, maritime activities focus on port production.

Therefore, the port has almost absolute contribution to maritime cluster earnings. With

the change in maritime cluster functions, maritime service activities are increasing. Port

production is not the only or majority of earning resources. The following section takes

maritime clusters of London and Hong Kong as case study to research on the

development relationship between port and maritime cluster.

3.1.1 Case of London

The UK is the leading centre worldwide in the supply of a broad range of professional

and business services to the international maritime community, that are largely

concentrated in London. According to the IFSL (2011) report, London and the UK is a

leading source of capital and expertise for marine insurance, ship-chartering, shipping

finance, ship classification, legal and accounting services and dispute resolution. In

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addition there are a wide range of other skills and facilities based there. Table 5 shows

the increasing international market share of Londons maritime services. Table 6

indicates the rising trend in employment number of maritime service cluster in London,

followed by Table 7 and Fig. 2 which show the overseas earnings of maritime service in

London.

Table 5 International market share of London maritime services (%)

Maritime service category Year 1999

Year 2004

Year 2006

Year 2008

Year 2010

Ship finance 18 17 18 13 15 Insurance - underwriting 19 15 23 17 20 Insurance P&I Clubs 71 67 65 62 62 Lloyds Register 20 19 19 18 16 Tanker charting(estimates) 50 50 50 50 50 Dry bulk chartering (estimates)

30-40 30-40 30-40 30-40 30-40

Second hand tonnage(estimates)

50 50 50 50 50

Source: IFSL (2000, 2005, 2007, 2009)

Table 6 Employment of London maritime service cluster (Person)

Maritime service category Year 1999 Year 2004 Year 2007 Year 2009 Shipbrokering 4000 4498 5000 5000 Ship classification 1300 1734 1700 3000 Insurance service 3700 3030 2950 2950 Law firms 2600 2350 2050 2050 Banking 400 400 200 200 Other service 1800 2050 2400 2400 Total 13800 14062 14300 15600 Sources: IFSL (2000, 2005, 2007, 2009)

Table 7 Overseas earnings of maritime service in London (m)

Maritime service category

Year 1999 Year 2002 Year 2004 Year 2008 Year 2010

Ship brokering 293 322 551 948 744

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Ship classification 47 54 75 72 70 Insurance service 160 170 170 195 472 Legal service 190 190 180 205 208 Ship finance 100 150 170 500 662 Other services 140 160 155 180 60 Total 930 1046 1301 2100 2216 Sources: IFSL (2000, 2003, 2005, 2009, 2011)

Fig. 2 Overseas earnings of maritime service in London (m)

Sources: IFSL (2000, 2003, 2005, 2009, 2011)

As shown in Table 7 and Fig. 2, the growth of total overseas earnings from maritime

service sectors in London is tremendous in the past decade, more than two times of

earnings in year 1999 comparing with 2010. Ship finance enjoyed a more than six-fold

growth, while there is approximately three times increase in earnings from insurance

0

500

1000

1500

2000

2500

1999 2002 2004 2008 2010

Shipbrokering

Shipclassification

Insuranceservice

Legalservice

Shipfinance

Otherservices

Total

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and about two times from brokering in the same period. However, when maritime

services cluster is developing rapidly in London, Port of London does not behave as

prosperous as many maritime service sectors. We see the stagnation or even tiny

downswing of freight handled by Port of London in Fig. 3, contrasting with the

background of enhancement in the international trade and port throughput worldwide.

Fig. 3 Freight handled by Port of London (mt)

Source: DfT Port Statistics, UK(9 June 2011).

The key finding of the above analysis is that, from the experience of London case, the

port does not lead the development of maritime cluster any more. Port is not the main

factor contributing to the maritime cluster in the advanced stage of cluster development,

comparing with the former stages.

3.1.2 Case of Hong Kong

Hong Kong is one of the worlds major container ports and its maritime industry is

estimated to contribute to 2.5% of its GDP. The analysis of maritime business

development in Hong Kong, based on data availability, is about the number and gross

0

10,000

20,000

30,000

40,000

50,000

60,000

70,000

AllfreighttrafficthroughPortofLondon:19652010(thousandtonnes)

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tonnage of ships registered in Hong Kong and authorized insurers - underwriting results

of ship business (see tables 8 and 9 and figure 4).

Table 8 Number and Gross Tonnage of Ships Registered in Hong Kong

At the end of year

No. of vessels Gross tonnage

('000 tons)

No. of vesselsYear-on-year change (%)

Gross tonnageYear-on-year change (%)

1993 597 7751 2.4% 5.9% 1994 592 8003 -0.8% 3.3% 1995 582 8890 -1.7% 11.1% 1996 544 7877 -6.5% -11.4% 1997 484 5658 -11.0% -28.2% 1998 479 6213 -1.0% 9.8% 1999 521 8338 8.8% 34.2% 2000 577 10397 10.7% 24.7% 2001 653 13726 13.2% 32.0% 2002 758 16230 16.1% 18.2% 2003 880 20604 16.1% 26.9% 2004 1009 25565 14.7% 24.1% 2005 1085 29798 7.5% 16.6% 2006 1150 32529 6.0% 9.2% 2007 1227 35697 6.7% 10.6% 2008 1361 39643 10.9% 10.2% 2009 1496 44904 9.9% 13.3% 2010 1735 56510 16.0% 25.8%

Source: Summary Statistics on Shipping Industry of Hong Kong, 2011(3)

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Fig. 4 Gross tonnage from year 1993 to year 2010 (000 tons)


Table 9 Authorized Insurers in Hong Kong - Underwriting Results of Ship Business

Year-on-year change (%) 2002 2003 2004 2005 2006 2007 2008 2009 2010 Gross premiums 15.2 1.6 19.3 4.8 16.8 2.2 32.4 -11.6 23.7 Net premiums 45.7 1.3 15.1 3.6 21.2 -0.1 40.3 -18.1 30 Gross claims paid -42.7 21.8 26.9 2.3 -12.4 159.5 -45.3 11.5 -19.2 Net claims paid -57.6 92.4 -2.2 38.7 -13.7 65.4 -33.9 11.8 -9.5 Net claims incurred 124.1 6.2 -33.5 81.7 -13 35.9 -2.4 -0.2 22


Table 10 shows the ports cargo throughput ranging from year 1993 to year 2010.

Based on the figures of port and typical maritime services in Hong Kong, such as

number and gross tonnage of ships registered in Hong Kong and the authorized

insurers in Hong Kong - underwriting results of ship business, figure 5 summerises the

year-on-year percentage change of these indexes.

0

10000

20000

30000

40000

50000

60000

Grosstonnage('000tons)

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Table 10 Seaborne Cargo Throughput

Year Discharged Loaded Total seaborne cargo throughput

('000 tonnes)

Year-on-year % change

('000 tonnes)


('000 tonnes)


1993 68 226 +15.8 27 873 +13.7 96 100 +15.21994 76 672 +12.4 34 274 +23.0 110 947 +15.41995 87 048 +13.5 40 127 +17.1 127 175 +14.61996 86 694 -0.4 39 145 -2.4 125 838 -1.11997 91 950 +6.1 41 351 +5.6 133 301 +5.91998 90 104 -2.0 37 378 -9.6 127 482 -4.41999 88 621 -1.6 39 601 +5.9 128 222 +0.62000 88 003 -0.7 42 934 +8.4 130 937 +2.12001 88 506 +0.6 42 170 -1.8 130 676 -0.22002 93 444 +5.6 44 857 +6.4 138 301 +5.82003 99 363 +6.3 49 255 +9.8 148 618 +7.52004 104 612 +5.3 54 006 +9.6 158 617 +6.72005 106 695 +2.0 54 772 +1.4 161 467 +1.82006 106 579 -0.1 59 629 +8.9 166 208 +2.92007 109 435 +2.7 67 912 +13.9 177 347 +6.72008 110 220 +0.7 69 755 +2.7 179 974 +1.52009 105 612 -4.2 55 979 -19.7 161 591 -10.22010 114 447 +8.4 67 557 +20.7 182 004 +12.6Source: Census and statistics department (2011)

It can be seen that total seaborne cargo throughput in Hong Kong is not increased as

much as ship gross registered tonnage and ship insurance business, but more steady

than the other businesses.

From the case of London maritime cluster, it can be found that port throughput is

encountering a downturn in the past few years, which contrasts sharply with the

tremendous increase of earnings in many maritime service sectors. It also sees the

changing positions of Port of London and maritime service sectors. Port of London used

to be the world main and leading port. However, the leading position of the port has

disappeared, and is replaced by maritime service business instead, which is

approximately 50% of oversea earnings in the world. The port no longer plays the key

role in maritime cluster development in London.

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Fig. 5 Year-on-year % change of port throughput (tonnes), gross registered tonnage

and ship insurance business

Source: Drawn by authors based on Census and statistics department and Summary Statistics on Shipping Industry of Hong Kong, 2011(3)

100

50

0

50

100

150

200

2002 2003 2004 2005 2006 2007 2008 2009 2010

Grosspremiums Netpremiums

Grossclaimspaid Netclaimspaid

Netclaimsincurred Grosstonnage

Totalseabornecargothroughput

22

In the case of Hong Kong, according to the past tendency, it can be deduced that

dynamics of Hong Kong maritime cluster are driven by both maritime service sectors

and the port. Port of Hong Kong is still one of the leading sea ports in the world, but with

relatively stagnant throughput movement, comparing with the vibrant maritime service

sectors. It seems that the ports significance to the clusters development is relatively

lower than earlier years.

By comparison of maritime clusters in both London and Hong Kong, it can be found that

port is not necessarily the leading influencing factor to maritime cluster development

nowadays. Based on the analysis of the maritime cluster evolution in section 2.1, some

world-famous maritime clusters such as Hong Kong are entering the new generation.

The new era of maritime cluster features maritime service provider and intelligence

capability, It takes over ports leading position of being the unique or main determinant

of maritime cluster development.

3.2 Coordinated development between port and maritime cluster

The above statement is based on conceptual development and qualitative analysis on

port and maritime cluster. As the result shows, ports significance is diminishing as a

maritime cluster advances to become more service oriented. It would be interesting to

know what a proper development degree between these two systems is. The following

part carries on the discussion on the measurement of the coordinated development

between port and maritime cluster in a quantitative way.

3.2.1 Evaluation model selection

From above analysis, we can see that the prompting effect of port on maritime cluster is

changing. Questions concerned here are whether the impact of input and output of the

two systems are coordinated and whether the impact of the input is evident (Liu et al.,

2010). Aiming at the problems, based on some famous maritime clusters as the

research scope, the study selects port and maritime cluster as Decision Making Units.

By analysing input and output data from these two systems, we are able to evaluate the

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coordination development and efficiency validity of support and utilization between

these two systems.

Data analysis techniques used in port research are mainly descriptive statistics (35.5%),

regression (16.9%), DEA (10.2%), Logit model (5.1%) and SFA (4.8%) (Woo, et al.

2011). These techniques, such as DEA, SFA, Logit model, Multi-Criteria Decision

Making (MCDM), Error Correction Model (ECM) and Structural Equation Modelling

(SEM), have more specific purposes and usages than descriptive statistics. The

comparison of these methods is listed in Table 11.

Table 11. Comparison of data analysis techniques used in port research

Data analysis

technique Functions Examples

DEA & SFA

Assess the relative efficiency of port operations

Evaluate the consequence of port reform Evaluate the impact of regulation on port

efficiency

Cullinane and Wang, 2007 Cullinane et al., 2002; Cullinane

et al., 2005

Barros, 2003; Ferrari and Basta, 2009

Logit model

Traditionally determine or predict demand for freight and passengers in transport

economics, using a discrete choice approach

Demand analysis for port services Frequently in port selection studies

Winston, 1985 Anderson et al., 2009; Veldman

et al., 2005

Garcia-Alonso and Sanchez-Soriano, 2009; Magala and

Sammons, 2008; Malchow and

Kanafani, 2001, 2004; Tongzon

and Sawant, 2007

MCDM

Evaluate competitiveness of particular ports

and to develop strategies for competitiveness:

Analytical Hierarchical Process (AHP) PROMETHEE

Lirn et al., 2003, 2004; Ugboma et al., 2006

Castillo-Manzano et al., 2009; Guy and Urli, 2006

24

Technique for Order Performance by Similarity to Ideal Solution (TOPSIS)

Gray Relation Analysis (GRA) Hierarchical Fuzzy Process (HFP)

Celik et al., 2009 Teng et al., 2004; Huang et al.,

2003

Yeo and Song, 2006

ECM

Estimate both short term and long run effects of explanatory time series variables

Forecast by predicting short-run adjustments of the dependent variable

Determine relationships between the variables, such as inter-port dynamics

DeBoef, 2001 Fung, 2001; Hui et al., 2004 Yap and Lam, 2006

SEM

Take a confirmatory approach to the analysis of a structural theory

Examine the channel relationship Examine the impact of peoples perception on

performance

Examine and the Technology Acceptance Model (TAM)

Byrne, 2001 Bichou and Bell, 2007; Lai et

al., 2008

Shang and Lu, 2009 Norzaidi et al., 2009

Source: Compiled by authors, according to references of Lin and Tseng (2005) and

Woo et al. (2011).

As shown in the table above, there are two techniques - SFA and DEA, to measure port

efficiency. The measurement of efficiency can be applied in the study of coordination

development and efficiency validity. However, there are some differences to be

considered when adopting the proper method. By comparing the advantages and

disadvantages of the two methods, DEA is adopted. It is mainly because SFA needs to

assume functional form and distribution type in advance, which is difficult to be applied

in the research of maritime cluster.

3.2.2 Application of DEA model

25

The paper proposes to use the DEA method to evaluate the coordination between port

and maritime cluster development, which is to evaluate the validity of support and

utilization between the two systems. The development of the port might promote

maritime cluster, and vice versa. Therefore, the two systems as input and output

respectively can be counted as a big input-output system. When taking port as the input

system, DEA validity evaluation is to evaluate whether port accommodates to the

demand of maritime cluster development, as well as whether port strongly supports the

clusters progress. When maritime cluster is the input system, it is to measure whether

the cluster has powerfully supported and utilized maritime cluster system.

The suitability of the chosen inputs and outputs is a key concern. In terms of the

approaches towards the selection of input and output variables for port, they can be

classified into two categories according to whether a monetary parameter should be

used or not (Panayides et al., 2009) and such reference can be drawn from the

literature. Though there is no research on maritime cluster inputs or outputs in DEA

method, it can be derived from the relationship between port and city when considering

and choosing the variables of inputs and outputs for maritime cluster, since maritime

cluster is one of the industry clusters within a region economy. According to Li and Lu

(2009), fixed assets investment amount and number of employees are selected as

maritime cluster inputs, with GDP and total sales of retail trade as port city output,

Besides, Liu et al (2010) takes GDP, investment in fixed assets and social retail goods

as variables of economy society. Based on the prior research and maritime cluster

characteristics, such as internationalism, we propose the variables for port and maritime

cluster, as shown in Table 12.

Here CCR input-oriented model in DEA approach is proposed in the port and maritime

cluster development evaluation model, with the objective of focusing on how many

inputs can be reduced by maintaining the same level of output by providing information

purely on technical and scale efficiency. In this way, relationships such as whether the

development of port is coordinated with maritime cluster can it be identified.

26

Table 12 The variables in DEA model

Variables References

Port

Number of employees( 1x )

Roll and Hayuth (1993); Martinez-Budria et al. (1999) labour expenditure; Tongzon (2001); Barros (2003); Barros and Athanassiou (2004); Liu et al. (2010)

Number of Productive Berths ( 2x )

Barros (2003); Park and De (2004); Barros and Athanassiou (2004)

Cargo Throughput(x3)

Martinez-Budria et al. (1999); Tongzon (2001); Valentine and Gray (2001, 2002); Barros (2003); Park and De (2004); Barros and Athanassiou (2004); Min and Park (2005)

Maritime cluster

Total Investment Amount( 1y ) Barros (2003, 2006); Liu et al. (2010)

Total Number of Employees ( 2y )

Roll and Hayuth (1993); Martinez-Budria et al. (1999) labour expenditure; Tongzon (2001); Barros (2003); Barros and Athanassiou (2004); Liu et al. (2010)

GDP from maritime cluster ( 3y )

Park and De (2004); Barros (2006); Liu et al. (2010)

Overseas earnings ( 4y )

Source: Authors.

CCR model assumes there are n Decision Making Units (DMU) and each of them has m

types of input (the consumption of resources) and s types of output (the effect of the

input). When taking port as the input, the relative efficiency is represented by P , which stands for the degree of closeness between actual effective rates of port development

scale and technology and the requirements of the maritime cluster development. The

size of value refers to the adaptability of the port to maritime cluster development. On

the other hand, when taking maritime cluster as input system, the relative efficiency is

represented by M , which stands for the degree of closeness between actual effective rates of maritime cluster supporting and utilizing port and the requirements of to

27

maritime cluster. Using weighted method on P and M , p p m m = + ( + 1p m = ), stands for the linear combinations coefficient of the DMUs. The index represents the coordination of the whole system. It can combine the two indexes of relative efficiency,

and preferably evaluates the coordination degree of port and maritime cluster.

4. Conclusions

The paper studies the influence and contribution of port on maritime cluster

development. It thoroughly develops an original maritime cluster connotation, especially

in the aspects of its formation and relationship with the port within it. Then, it

summarizes maritime cluster development evolution from the perspective of dynamic

port functions. Based on this relationship with port, it categorizes world-famous maritime

clusters into two parts - with/without strong port throughput support. One typical case of

maritime cluster from each of these two groups - London and Hong Kong, is selected

and analysed. In each case, the paper studies the development trends and positions of

maritime sectors within a cluster. It is found that port is not the only main influencing

factor in the advanced generation of maritime cluster, which is recognized as

international maritime cluster with the main function of maritime services centre. In order

to take further analysis as to what extent this coordination development relationship

between port and maritime cluster should be maintained, the study proposes DEA

model to evaluate the two systems. With this method, it provides the reference for

maritime clusters, which are on their way to be international maritime centres, to handle

the development relationship with ports.

This research findings presented are based primarily on evidences from the changing

functions of maritime clusters and case analysis of London and Hong Kong. For the

maritime cluster evolution based on changing port functions, future research can apply

the DEA model for detailed analysis. Future studies could also take into account other

maritime sectors that might be identified as important influencing factors to maritime

cluster development. Besides, maritime service sectors analysed in London and Hong

28

Kong cases are part of maritime service provided in their clusters. Hence, future

researchers could also choose more comprehensive sectors into maritime cluster

analysis, to compare and evaluate the relationship between port and maritime cluster.

What is more, the unique characteristic of each maritime cluster might have its own

dynamic development path with port, which is different from London or Hong Kong.

Future researchers could take steps on different classification of maritime clusters to

make the relationship with port more precisely. As a whole, the paper presents a useful

reference for research and policy suggestions on the interplay between maritime cluster

and its port development for maritime cities and regions en route to higher value

generating IMCs.

29

REFERENCES

Anderson, C.M., Opaluch, J.J., Grigalunas, T.A., 2009. The demand for import services

at US container ports. Maritime Economics and Logistics 11, 156-185.

Appold, S.J., 1997. Agglomeration, interorganizational networks, and competitive

performance in the U.S. metalworking sector. Economic Geography 71, 27-54.

Arthur, W. B., 1989. Competing technologies, increasing returns, and lock-in by

historical events. Economic Journal 99, 116-131.

Barros, C.P., 2003. Incentive regulation and efficiency of Portuguese port authorities.

Maritime Economics and Logistics 5, 5569.

Bathelt, H., Malmberg, A., Maskell, P., 2002. Clusters and knowledge: Local buzz,

global pipelines and the process of knowledge creation. Progress in Human

Geography 28, 31-56.

Benito, G.R.G., Berger, E., Forest, M., 2003. A cluster analysis of the maritime sector in

Norway. International Journal of Transport Management 1, 203-215.

Bichou, K., Bell, M.G.H., 2007. Internationalisation and consolidation of the container

port industry: assessment of channel structure and relationships. Maritime

Economics and Logistics 9, 3551.

Bichou, K., Gray, R., 2005. A critical review of conventional terminology for classifying

seaports. Transportation Research Part A 39, 75-92.

Brett, V. and Roe, M. 2010. The potential for the clustering of the maritime transport

sector in the Greater Dublin Region, Maritime Policy & Management, 37: 1, 1-16

Brownrigg, M., 2006. The United Kingdom's Maritime Cluster. Dynamic European

maritime clusters. Delft: IOS Press.

30

Byrne, B.M., 2001. Structural equation modeling with AMOS basic concepts,

applications, and programming. Lawrence Erlbaum Associates, Mahwah, NJ.

Castillo-Manzano, J.I., Castro-Nuno, M., Laxe, F.G., Lopez-Valpuesta, L., Arevalo-

Quijada, M.T., 2009. Low-cost port competitiveness index: implementation in the

Spanish port system. Marine Policy 33, 591598.

Census and Statistics Department of Hong Kong, 2011. Hong Kong Shipping Statistics.

Chang, Y.-C., 2011. Maritime clusters: What can be learnt from the South West of

England. Ocean & Coastal Management 54, 488-494.

Cullinane, K. P. B. and Wang, T.-F., 2007. Data envelopment analysis (DEA) and

improving container port efficiency. Research in Transportation Economics 17, 517-

566.

Cullinane, K.P. B., Ji, P., Wang, T.-F., 2005. The relationship between privatization and

DEA estimates of efficiency in the container port industry. Journal of Economics and

Business 57, 433462.

Cullinane, K. P. B., Song, D.-W., Gray, R., 2002. A Stochastic frontier model of the

efficiency of major container terminals in Asia: assessing the influence of

administrative and ownership structures. Transportation Research Part A 36, 743

762.

De Langen, P.W., 2002. Clustering and performance: The case of maritime clustering in

the Netherlands. Maritime Policy & Management 29, 209-221.

DeBoef, S., 2001. Testing for cointegrating relationships with near-integrated data.

Political Analysis 9, 7894.

Department for Transport (DfT), 2011. Port0101: All UK ports, all freight traffic, by port

and direction: 1965 - 2010p. (Last updated: 9 June 2011).

31

Doeringer, P.B., Terkla, D.G., 1995. Business strategy and cross-Industry clusters.

Economic Development Quarterly 9, 225-237.

Dong, G., 2010. Research on development of London international maritime service

cluster. Navigation of China 33 80-83, 101Ferrari, C., Basta, M., 2009. Port

concession fees based on the price-cap regulation: a DEA approach. Maritime


Fisher Associates, 2004. The Future of Londons Maritime Services Cluster: A Call for

Action. London: Corporation of London.

Fung, K.-F., 2001. Competition between the ports of Hong Kong and Singapore: a

structural vector error correction model to forecast the demand for container

handling services. Maritime Policy and Management 28, 322.

Garcia-Alonso, L., Sanchez-Soriano, J., 2009. Port selection from a hinterland

perspective. Maritime Economics and Logistics 11, 260269. Grammenos, C.T.,

Choi, C.J., 1999. The Greek shipping industry. International Studies of Management

& organization 29, 34-52.Guy, E., Urli, B., 2006. Port selection and multicriteria

analysis: an application to the MontrealNew York alternative. Maritime Economics

and Logistics 8, 186196.

Huang, W.-C., Teng, J.-Y., Huang, M.-J., Kou, M.-S., 2003. Port competitiveness

evaluation by fuzzy multicriteria grade classification model. Journal of Marine

Science and Technology 11, 5360.

Hui, E.C.M., Seabrooke, W., Wong, G.K.C., 2004. Forecasting cargo throughput for the

Port of Hong Kong: error correction model approach. Journal of Urban Planning 130,

195203.

Ianca, C., Batrinca, G., 2010. Towards a Romanian maritime cluster. Proceedings of the

3rd International Conference on Maritime and Naval Science and Engineering, 94-

99.

32

International Financial Services London (IFSL), 2000, 2003. 2005, 2007, 2009, 2011.

Maritime services, City Business Series

Isaksen, A., 2009. innovation Dynamics of Global Competitive Regional Clusters: The

Case of the Norwegian Centres of Expertise. Regional Studies 43, 1155-1166.

Jakobsen, E.W., 2006. The Norwegian Maritime Cluster. Dynamic European maritime

clusters. Delft: IOS Press.

Janssens, H., 2006. The Dutch Maritime Cluster. Dynamic European maritime clusters.

Delft: IOS Press.

Jenssen, J.I., 2003. Innovation, capabilities and competitive advantage in Norwegian

shipping. Maritime Policy & Management 30, 93-106.

Krugman, P., 1991. Geography and Trade. Cambridge, MA: MIT Press.

Kwak S.-J., Yoo, S.-H., Chang, J.-I., 2005. The role of maritime industry in the Korean

national economy: An input-output analysis. Marine Policy 29, 371-383.

Lai, K.-H., Bao, Y., Li, X., 2008. Channel relationship and business uncertainty:

evidence from the Hong Kong market. Industrial Marketing Management 37, 713

724.

Lam, J.S.L. and Cullinane, K. 2003. Shanghai as an international maritime centre:

implications for the East Asian regional economy, Proceedings of The Eastern Asia

Society for Transportation Studies Conference, Fukuoka, Japan, 29 Oct-1 Nov 2003

Lirn, T.-C., Thanopoulou, H.A., Beresford, A.K.C., 2003. Transhipment port

selection and decision-making behaviour: analysing the Taiwanese case.

International Journal of Logistics: Research and Applications 6, 229244.

Lirn, T.-C., Thanopoulou, H.A., Beynon, M.J., Beresford, A.K.C., 2004. An application of

AHP on transhipment port selection: a global perspective. Maritime Economics and

Logistics 6, 7091.

33

Lin, L.-C., Tseng, L.-A., 2005. Application of DEA and SFA on the measurement of

pperating efficiencies for 27 International Container Ports. Proceedings of the

Eastern Asia Society for Transportation Studies 5, 592-607.

Liu, G., Chen, Y., Qi, S.L., 2010. Coordination analysis between Liaoning province port

and shipping industry and ecnomic society based on DEA, Proceedings of the 2010

IEEE International Conference on Automation and Logistics August 16-20 2010,

Hong Kong and Macau, 490-494.

Ma, S., 2010. What is international shipping centre? Shipping Management 32, 1-5.

Magala, M., Sammons, A., 2008. A new approach to port choice modelling. Maritime


Malchow, M., Kanafani, A., 2001. A disaggregate analysis of factors influencing port

selection. Maritime Policy and Management 28, 265277.

Malchow, M., Kanafani, A., 2004. A disaggregate analysis of port selection.

Transportation Research Part E 40, 317337.

Malmberg, A., Maskell, P., 1997. Towards an explanation of regional specialization and

industry agglomeration. European Planning Studies 5, 25-41.

Martin, R., Sunley, P., 2003. Deconstructing clusters: Chaotic concept or policy

panacea? Journal of Economic Geography 3, 5-35.

Martinez-Budria, E., Diaz-Armas, R., Navarro-Ibanez, M. and Ravelo-Mesa, T., 1999. A

study of the Efficiency of Spanish port authorities using Data Envelopment Analysis,

International Journal of Transport Economics XXVI, 237-253.

Maunsell Consultants, 2003, Study to Strengthen Hong Kongs Role as an International

Maritime Centre. Hong Kong Port and Maritime Board. January 2003.

34

Norzaidi, M.D., Chong, S.C., Murali, R., Salwani, M.I., 2009. Towards a holistic model in

investigating the effects of intranet usage on managerial performance. A study on

Malaysian port industry. Maritime Policy and Management 36, 269289.

Porter, M.E., 1990. The Competitive Advantage of Nations. London: Macmillan.

Othman, M.R., Bruce, G.J. and Hamid, S.A. 2011. The strength of Malaysian maritime

cluster: The development of maritime policy, Ocean & Coastal Management 54,

557-568.

Panayides, P.M., Maxoulis, C.N., Wang, T.F., Ng,K.Y.A., 2009. A Critical Analysis of

DEA Applications to Seaport Economic Efficiency Measurement. Transport review

29, 183-206.

Rodrigue, J.-P., Notteboom, T., 2009. The terminalization of supply chains:

Reassessing the role of terminals in port/hinterland logistical relationships. Maritime

Policy & Management 36, 165-183.

Shang, K.-C., Lu, C.-S., 2009. Effects of safety climate on perceptions of safety

performance in container terminal operations. Transport Reviews 29, 119.

Shinohara, M., 2006. European and Japanese logistics paradigms: an explorative and

comparative study of the dynamics of logistics management. Tokyo: Maruzen-

planet.

Shinohara, M., 2010. Maritime cluster of Japan: Implications for the cluster formation

policies. Maritime Policy & Management 37, 377-399.

Sternberg, R., Litzenberger, T., 2004. Regional clusters in Germany - their geography

and their relevance for entrepreneurial activities. European Planning Studies 12, 767-

791.

35

Teng, J.-Y., Huang, W.-C., Huang, M.-J., 2004. Multicriteria evaluation for port

competitiveness of eight East Asian container ports. Journal of Marine Science and

Technology 12, 264265.

Tongzon, J.L., Sawant, L., 2007. Port choice in a competitive environment: from the

shipping lines perspective. Applied Economics 39, 477492.

Ugboma, C., Ugboma, O., Ocwude, I.C., 2006. An Analytic Hierarchy Process (AHP)

approach to port selection decisions: empirical evidence from Nigerian ports.

Journal of Maritime Economics and Logistics 8, 251266.

UNCTAD, 1992. Port marketing and the challenge of the third generation port. Trade

and development board committee on shipping ad hoc intergovernmental group of

port experts, 13-23.

Veldman, S.J., Buckmann, E.H., Saitua, R.N., 2005. River depth and container port

market shares: the impact of deepening the Scheldt River on the West European

container hub-port market shares. Maritime Economics and Logistics 7, 336355.

Wijnolst N. and Janssens, H., 2006..The German Maritime Cluster. Dynamic European

maritime clusters. Delft: IOS Press

Wijnolst, N., Jenssen, J.I., Sdal, S., 2003. European Maritime Clusters. Delft: Delft

University Press.

Winston, C., 1985. Conceptual developments in the economics of transportation: an

interpretive survey. Journal of Economic Literature 23, 5794.

Woo, S.-H., Pettit, S. J., Kwak, D.-W.,2011. Seaport research: A structured literature

review on methodological issues since the 1980s. Transportation Research Part A

45, 667-685.

Yap, W.Y., Lam, J.L., 2006. Competition dynamics between container ports in East

Asia. Transportation Research Part A 40, 3551.

36

Yeo, G.-T., Song, D.-W., 2006. An application of the hierarchical fuzzy process

to container port competition: policy and strategic implications. Transportation

33, 409422.

Documents

Maritime Cluster Types