College of Business Administration

University of Rhode Island

2009/2010 No. 7

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Office of the DeanCollege of Business AdministrationBallentine Hall7 Lippitt RoadKingston, RI 02881401-874-2337www.cba.uri.edu

William A. Orme

Doug Hales, Nik Dholakia, S.W. Lee, Y.T. Chang

Implications for Global Supply ChainsCompetitiveness of Asian and American Ports:

Competitiveness of Asian and American Ports: Implications for Global Supply Chains

ABSTRACT The fastest growing trade circuits today are those that involve Asia: Asia-Americas, Asia-Europe, and intra-Asia. The expansion in trade among these regions is growing at a faster rate than the planned capacity increases for the major/preferred ports and inter-modal service facilities in Asia, North America, and Europe. To exacerbate the problem, the change in global climates and the widening of the Panama Canal will create new shipping channels that may change the way ports compete. This means that a serious imbalance is being created between the planned capacity (both infrastructure and superstructure) at major ports, inter-modal transfer facilities, and the expected demand for the services at such ports and facilities. This imbalance has increased the probability for interruptions along the supply chains that feed the businesses and consumers in these regions - resulting in potentially negative economic and environmental impacts. The capacity-demand imbalances have created an opportunity for ports in the region to compete for the anticipated overflow in main line business and opportunities for new investment. Among the ports most affected by the imbalances are container ports because they handle the vast majority of global trade volume. This means that ports must consider how to compete differently to attract new business and how to attract new investment to support the changes. Previous measures of port competitiveness are insufficient to assist ports in this effort because they do not consider both factors together; i.e. the need to develop infrastructure to attract greater container volume and the need to attract new investment to support the infrastructure. This paper develops a new measurement scale to consider both factors simultaneously, tests the scale using global ports, and then uses the scale to measure 55 of the world’s top container ports to estimate their competitiveness. Since the factors create a theoretical hierarchy, the data analysis is conducted using Analytical Hierarchy Process (AHP). The AHP addresses the macro-level competitive factors that measure the port’s potential to attract new business and investment. Specifically, the proposed instrument is designed to measure the competitiveness among primarily container seaports and their land-based logistical links that support merchandise related trade in Asia, North America, and Europe at a macro-level. Initial data was collected through field observations, and interviews at ports, universities, and businesses in the United

States, Korea, and China. Data for the full study was collected from ports worldwide using a web-based survey instrument. Conceptual discourses within the research team and external experts were used to develop conclusions. To our knowledge, this is the first study to apply AHP to measure global port competitiveness along two dimensions: ‘customer-facing’ competitiveness as well as ‘investment-attracting’ competitiveness.

EXECUTIVE SUMMARY

Trade imbalances, global climate change, and the widening of the Panama Canal have created new dynamics in the way global container ports will compete in the future. Ports currently operate primary as importers, exporters, or transshipment hubs. Prior to the existing economic recession many net importers, such as the US and Europe, suffered from issues ranging from excess wait times to load or off-load cargo, congested intermodal links, to empty containers that tie-up valuable storage space and consume requisite handling resources such as empty container shipping. Primary exporters and hubs, such as China and Korea, suffer from issues ranging from constraints at destination ports, customs clearance issues, and transshipment tracking and management. Global climate changes have allowed shipping channels in northern Europe, Canada, and Asia that normally are iced-over during the winter to remain open longer in winter and open earlier in spring. This has reduced the need for some overland/hinterland traffic and allowed ports to operate longer than in previous years. The widening of the Panama Canal will allow some transshipment volume that previously required transfer to Panamax class ships, to ship directly on larger vessels. This means that some traffic normally transshipped through primarily hub ports could be reduced. This new competition is created because of the development of new shipping channels, since larger vessels will be able to pass through the Panama Canal without transshipment. All of these factors require a change in the way ports compete for new volume as well as investment funds. However, existing models that measure port competitiveness are myopic in that they only measure a few of the competitive factors, or are focused on either Volume Competitiveness (customer-facing) or Investment Competitiveness (investor-facing), but not both. This is a problem since actions taken by ports to increase customer volume may actually harm their ability to attract investors, and visa versa. For example, investors prefer to see highly utilized capital assets, such as gantry cranes, because they must spread the costs of large fixed costs over larger volume. On the other hand, customers prefer lower utilization of key capital assets because as utilization increases, service levels tend to drop – especially as utilization approaches 60%+. The primary purpose of Phase I of this study is to be the first to develop a new measurement instrument that simultaneously measures the competitiveness of global ports based on their ability to attract both new volume and investment, as well as maintain existing competitiveness. The scale is used to develop a score of “Port Competitiveness” for each port where higher values correspond to greater competitiveness. During Phase I, the instrument was pre-tested and pilot-tested on managers, port officials, users, academic experts, and investors at the seven global ports of Busan and Incheon in Korea, Los Angeles/Long Beach in the US, LeHarve in France, Ports of New York/New Jersey in the US, Melbourne in Australia, and Mayaguez in Puerto Rico. To reduce response bias, the instrument was translated into four languages including Korean, Chinese, English, and

French. The intent was to also test the instrument on Chinese ports; however, no Chinese respondents could be recruited in Phase I. Therefore, as part of the Phase II planning, the researchers visited Chinese ports and solicited responses in-person. The results of the pre-test and pilot test demonstrate that the instrument is a valid method of measuring both Volume and Investment Competitiveness in global ports. Internal validity of the instrument was estimated primarily through expert respondents and their similarities across all ports. Evidence of external validity was obtained by comparing the rank scores from the full Phase II study with the history of port rankings for volume growth. The resulting scores generally matched existing global port rankings, with a .73 correlation, with Shanghai, Singapore, Hong Kong, and Busan being ranked as the most competitive ports in the world, and handling the largest cargo volume out of all of the ports in the sample. In Phase II, the researchers solicited participation of 55 out of the top-200 global ports in the full sampling frame. The results indicate that the Korean ports of Busan and Incheon ranked higher in overall Port Competitiveness than their existing actual 2007 volume suggests. This finding suggests that if the ports continue their existing funding levels and implement current plans, they should continue to attract new container volume and investment – both private and public. They ranked ahead of Hong Kong and Rotterdam, which have greater 2007 volume. However, the predictions for 2009 show that Hong Kong is expected to drop to # 10 or 12th in overall container volume and Rotterdam is expected to drop to # 7th or 9th. This provides external validity for the results. Lastly, the affects of the increased use of the Northwest Passage on Asian ports is difficult to predict except that CMA-CGM has developed a relationship with the Port of Boston in anticipation of greater shipping activity in the North Atlantic.

1. Introduction Port Measurement Issues In addressing how global ports will compete for the predicted re-shifting of container volume, traditional measures focus on attracting new container volume and retaining existing volume. Totally separate measures address how well ports attract new investment to improve port infrastructure, superstructure, and facilities. The problem with these measures is that they fail to capture the interaction effects between capturing new business and new investment. This suggests that ports may indulge in activities to improve one factor while harming the other. The purpose of this study is to use a new scale that measures these interaction affects and becomes the first to predict the impacts of the decisions of port administrators on customers and investors. The general Research Question 1 is the following:

What are the factors on which ports compete? How can port administrators predict the impact of their decisions regarding port infrastructure as to become and remain competitive?

The Changing Competitive Environment From the time of the pioneer sailing on April 26, 1956 of Ideal-X, the first containership, from Newark, New Jersey, international trade and transport have been transformed through containerization. The result has been an alteration of the geography of production and distribution1

, with Asia becoming the global center for all types of manufacturing and service creation. Starting with Singapore, Hong Kong, and Busan, many Asian ports have taken full advantage of containerization and associated inter-modal transport methods to create some of the world’s most efficient and competitive ports (Yap and Lam 2006).

In recent years, Asian merchandise trade has grown at a rate higher than the rate of growth of global trade in North America and Europe (see Table 1). Within Asia, of course, the main driver of merchandise trade is China where imports as well as export growth rates in recent years have hovered around 25 percent per year (see Table 1). While merchandise trade growth rates are high for Europe, trade among the European Union member states accounts for most of this growth. Asian trade, on the other hand, is directed significantly outside the region although intra-Asia trade is also growing. Table 2 further dramatizes the very high levels of North America and Europe-linked merchandise trade from China and Korea. In 2005, Asia’s North America and Europe-linked trade was about $1.1 trillion dollars while North America’s and Europe’s combined Asia-linked trade was about $600 billion dollars. Table 1: Share in Merchandise Trade by Global Regions or Countries Region or Country Exports Imports

1990 2000 2005 Percent Change 2000-5

1990 2000 2005 Percent Change 2000-5

North America 16.6 19.5 14.5 4% 19.6 25.8 21.7 6% Europe 49.6 42.0 43.0 11% 50.1 42.4 43.2 10% Asia (Korea, China) 21.8 26.4 27.4 11% 20.3 22.9 24.7 12%

- China 1.8 4.0 7.5 25% 1.5 3.4 6.3 24%

Source: Based on World Trade Organization statistics, available at: http://www.wto.org/english/res_e/statis_e/its2006_e/its06_bysubject_e.htm , accessed on: September 10, 2007. Table 2: Merchandise Trade among North America, Europe, Asia Regions Merchandise Trade with ($billions, 2005):

North America Europe Asia Merchandise North America 824 238 270

1 The preceding sentences are based on 2007 Conference CFP “Globalization and Freight Transportation in a Containerized World”, available at: http://www.gfptt.org/Entities/EventProfile.aspx?list=all&id=5621f7a8-eae8-4847-8e34-a1499c156391, Accessed on March 1, 2007.

Trade from ($billions, 2005)

Europe 398 3201 332 Asia 608 498 1424

Source: Based on WTO statistics, available at: http://www.wto.org/english/res_e/statis_e/its2006_e/its06_bysubject_e.htm , accessed on: September 10, 2007. Asia’s merchandise trade with North America and Europe is increasing faster than the planned capacity expansion for ports located in those regions. Exacerbating the imbalance problem is the fact that for the first time in many centuries, new shipping channels are being created and the usefulness of existing channels are being expanded beyond normal operating seasons. For example, several shipping companies are considering using the Northwest Passage across the top of the world as an alternative to the traditional Pacific routes. Reportedly, this will cut shipping time from Asia to the US east coast by 10%. Global warming effects have allowed the Northeast channels and seaports to operate later in winter season. As new lanes open up the probability of supply chain interruptions increase. This is somewhat counter-intuitive since more channels and extended usefulness should logically translate into improved balance. Instead these changes have led to greater imbalance due to the future ability of the Panama Canal to handle container cargo that was once transshipped through Busan and Los Angeles/Long Beach, reducing the demand on those infrastructures and the associated need for existing capacity and return on premium investments. This activity then increases the business at US east coast ports such as Houston, New Orleans, and Savannah; as well as European ports such as Hull in Great Britain and LeHarve in France. Longer shipping seasons through northern-most channels also reduce the need for developed premium hinterland and seaport capacities, which investors relied on to earn returns. To mitigate these emerging imbalances and potential interruptions, several initiatives have been undertaken, or are being contemplated (Song & Yeo, 2004; Kerr 2006; Anderson et al, 2007, Grigalunas, et al, 2009, et al, 2007; Jacobs & Hall, 2007: G). They include: Extreme pressure on the Long Beach port in California is spawning initiatives to

enhance East Coast and Gulf ports in USA, and to increase volumes to Canadian ports, with surface transport of some of the goods to US.

China’s development push in its own western region has shifted container volume to

inland Yangtze ports - with Shanghai as a hub. This is necessary since 90% of China’s international trade is handled through marine transport.

The intense transshipment competition between major Asian ports such as Busan,

Singapore, and Shanghai has led to major investments in port capacities. Middle East ports such as Dubai Jebel Ali, Jeddah, are making continuing efforts and

Aqaba to upgrade and to become transshipment centers not just for Middle East/Africa but also for South Asia – capturing some of the expected growth through Busan and China.

China has launched aggressive plans to upgrade the infrastructure of its remote

western regions by building a major highway link from its western provinces to the Pakistan port of Gwadar.

Busan has consistently increased its berth capacity among its five member ports to

discourage competition and maintain competitive service levels. This includes the development of the Busan New Port into a super-hub as well as the planned renovation of the existing Busan port. As part of this initiative, aggressive plans to increase hinterland access to the ports through the Siberian Railway are in the concept stages.

The European Union, with the support of agencies such as Geneva-based International

Road Transport Union (IRU), is making concerted efforts to improve transportation infrastructure by developing regular road-rail, inter-modal links, via northern and southern routes, to western China.

To mitigate the increased costs and decreased service levels at some US ports, the

Panama Canal widening project has prompted private firms to invest in increasing capacities on the US Gulf and East Coast ports such as Houston, Savannah and Charleston. In addition, CMA-CGM has chosen the Port of Boston as a transshipment port in the Northeast US. This compliments its Southeast transshipment port in Jamaica.

These initiatives are designed to mitigate the anticipated capacity imbalances that could potentially interrupt important supply chains, harm trade, and weaken national economies. This leads to the second research question: Research Question 2

Will the existing actions by ports improve their competitive positions?

2. Literature Review In addressing Research Question 1, the literature describes ten factors measuring two dimensions of port competitiveness. Included in these ten factors are variables measuring a port’s ability to attract new investment. New investments in port infrastructure can lead to reduced congestion and provides resources to manage growth. The literature on how ports compete has primarily addressed port competition from the viewpoint of the customer (customer-facing) within a country or region (e.g., Song & Yeo, 2004). Other studies either do not specify the context for their findings (i.e., whether the findings apply within a specific region or on a global scale) or they address only a few of the competitive factors predicting volume (e.g., Grigalunas et al, 2009; Brooks, 2000; Foster, 1979; Malchow and Kanafani, 2001; Murphy et al, 1988, 1992; and Slack, 1985). Collectively, these studies identified five major factors affecting port competition from the viewpoint of a customer. These include port location, cargo volume, service level, port

facility, and port expenses (port cost or price). In the Song & Yeo (2004) model, the authors expressly exclude port expenses because the accounting practices in the Chinese ports they studied were heterogeneous – making meaningful comparisons difficult. In this study, the variable ‘port costs’ were included as a subjective factor so that Port Competition can be measured in a more robust manner. In doing so, it is expressly assumed that the port experts, managers, and directors have knowledge of these factors in the absence of objective data. Based on these studies, we adapted general definitions for each of the five competitive factors. Greater levels of each of the following factors are considered to make a port more competitive:

(1) Actual Cargo Volume (not capacity): Carriers and port users view major ports that handle large volumes of containers as preferable. Total volume combining import, export, and transshipment cargo appears to be more important than any single category of volume.

(2) Port Facility Capacity: Port facilities are defined as all tangible assets that are used to

service water-borne cargo. Capacities of these assets are of particular importance to liners and carriers since ports operate during peak and off-peak periods. They include infrastructure, superstructure, and labor assets.

(3) Port Location: Location factors include geographical distance from production

facilities, ease of port and berth entry, potential for expansion, and quality of inter-modal access.

(4) Service Level: The percentage of cargo that will be off-loaded/loaded within the port

management’s promised time period (variance of time promised), as well as the average off-load/load time. This includes operation during peak periods and in adverse weather conditions.

(5) Port Costs: The cost to the liner per TEU for load/off-load service as well as

applicable port duties. From the viewpoint of a liner/user, Cost is a surrogate for port efficiency – so efficiency will not be measured separately (Song and Yeo, 2004).

Perhaps the most important issue with Asia-linked trade today entails the second factor listed above – Port Facility Capacity – because the existing 10,000, 14,000, and planned 18,000 TEU post-Panamax vessels require 16-21 meter, deep draft, multi-berth container ports (World Bank, 2007, Module 2, Pg. 41, Box 12). Currently, neither the US nor Busan (Korea) or China ports can handle all of these vessels when fully loaded (Haralambides and Behrens 2000). While these ports can handle these vessels when partially loaded, because the draft requirement is not as deep, they are appropriate for transshipment purposes. From the viewpoint of a customer/user, this could be especially problematic for developing countries because their fast growth and steady shift to world-class manufacturing will rely on developing reliable and efficient supply chains. The efficiencies created by these larger vessels will necessarily involve accommodating them when fully loaded. Not doing so will increase the probability of supply chain interruptions because of inadequate scale and efficiency of ports. Other well-known Asian-port rivalries (e.g., Busan-Shanghai, Singapore-

Dubai) are motivating these mega-ports to improve their competitiveness for transshipment business by planning to build the capacity to handle the larger vessels. In addition, they are planning greater hinterland capacity to airports, roadways, and rail to improve the efficiencies of imports and exports. In addition to the factors considered important to a customer (customer-facing competitiveness), the literature identifies factors affecting port competitiveness for resources (e.g. Foreign Direct Investment (FDI) and/or governmental funding). We group these factors under the label of Investment Competitiveness. These competitive factors are heavily influenced by public policy and could be used to shape public policy. [Source: World Bank Report, 2007] These factors are:

(1) Legal Framework: This entails the degree of autonomy of port management, including its own judiciary, to work outside of political arenas (similar to US Administrative courts) and the specific agreement between central and local governments describing the powers of port officials.

(2) Institutional Structure: The management structure should be conducive to investment

(Private Sector ports), with proper autonomy and have a cooperative relationship with labor. The labor force should be sufficient and well trained. Table 3 demonstrates the four major port management structures and spells out how they differ with respect to the control over port assets and activities. They are Public Service Ports, Tool Ports, Landlord Ports, and Private Sector Ports. Table 4 describes each management structure – including its strengths and weaknesses. At the extremes, Public Service ports are operated as not-for-profit entities whose primary goal is public service; while Private Sector ports operate solely in the interest of the investors – with the government abdicating its rights for any public good.

(3) Financial Resources: Autonomy to use port revenue for maintenance and expansion,

maintain healthy cash flows, and the capacity to raise funds when needed.

(4) Port Reputation: The use of a mechanism, such as a port sector regulator, to ensure fair competition among the various entities that compete in ports. This involves preventing anti-competitive practices that often take place with port monopolies.

(5) Price: The price that ports charge for basic services including container handling, drayage services, premiums for peak periods, and storage fees.

The literature suggests that the public policy factors are key factors for a port’s competitiveness for investment income. Investment sources include local private, FDI, local governmental, central governmental, and international agencies or intergovernmental. As described in Table 3, since all seaports have some accountability to government public policy can affect the competitiveness of all ports, regardless of purpose. Table 3: Port Management and Operations by Port Type Port Type

Port Management or Operations Aspect

Public Service Port

Tool Port Landlord Port Private Sector Port

Administration Public Public Public Private Nautical Management Public Public Public Private Infrastructure – Nautical Public Public Public Private Infrastructure – Port Public Public Public Private Superstructure – Equipment Public Public Private Private Superstructure – Buildings Public Public Private Private Cargo Handling Public Private Private Private Pilots Mixed Mixed Mixed Mixed Towing Mixed Mixed Mixed Private Mooring Mixed Mixed Mixed Private Dredging Mixed Mixed Mixed Mixed Inter-modal Connections Mixed Mixed Mixed Mixed Note : Mixed – A combination of Public and Private Source: World Bank Report (2007, Module 1, Pg. 9, Box 5) Table 4: Port Types, Missions and Orientations Port Type Description Public Service Ports

Public Service ports have a predominantly public character. The number of service ports is declining. Many former service ports are in transition toward a landlord port structure, such as Colombo (Sri Lanka), Nhava Sheva (India), and Dares Salaam (Tanzania). Under it, the port authority offers the complete range of services required for the functioning of the seaport system. The port owns, maintains, and operates every available asset (fixed and mobile), and cargo handling activities are executed by labor employed directly by the port authority. Service ports are usually controlled by (or even part of) the ministry of transport (or communications) and the chairman (or director general) is a civil servant appointed by, or directly reporting to, the minister concerned.

Tool Ports In the tool port model, the port authority owns, develops, and maintains the port infrastructure as well as the superstructure, including cargo-handling equipment such as quay cranes and forklift trucks. Port authority staff usually operates all equipment owned by the port authority. Other cargo handling on board vessels as well as on the apron and on the quay is usually carried out by private cargo handling firms contracted by the shipping agents or other principals licensed by the port authority. The Port of Chittagong (Bangladesh) is a typical example of the tool port. The Ports Autonomes in France are also examples, in particular the container terminals, which are managed and operated along the principles of the tool port, although for more recent terminals the private terminal operators have made the investment in gantry cranes.

Landlord Ports The landlord port is characterized by its mixed public-private orientation. Under this model, the port authority acts as regulatory body and as landlord, while private companies carry out port operations, especially cargo handling. Examples of landlord ports are Rotterdam, Antwerp, New York, and since 1997, Singapore. Today, the landlord port is the dominant port model in larger and medium-sized ports. In the landlord port model, infrastructure is leased to private operating companies or to industries such as refineries, tank terminals, and chemical plants.

Fully Privatized Ports

Fully privatized ports (which often take the form of a private service port) are few in number, and can be found mainly in the United Kingdom (U.K.) and New Zealand. Many consider full privatization as an extreme form of port reform. It suggests that the state no longer has any meaningful involvement or public policy interest in the port sector. In fully privatized ports, port land is privately owned, unlike the situation in other port management models. This requires the transfer of ownership of such land

from the public to the private sector. In addition, along with the sale of port land to private interests, some governments may simultaneously transfer the regulatory functions to private successor companies.

Source: Adapted from World Bank Report (2007: Module 1)

3. Methodology To address Research Question 2, an empirical study was conducted. The Analytic Hierarchy Process (AHP) methodology was used to analyze the data and is often used in decision-making. Its strength is its ability to utilize both quantitative and qualitative criteria in the same analysis. Saaty (1980) developed the concept of AHP, defining it as “…combining both subjective and objective assessments or perceptions into an integrative framework…” based on ratio scales from pair-wise comparisons. Wedley et al (2001) described the techniques associated with AHP in the following three steps:

(a) Structure a network hierarchy (b) Making pair-wise comparisons to yield priorities (c) Synthesizing the priorities into composite measures of the decision alternatives or

options. According to Song and Yeo (2004, pg. 11) “…due to its applicability in business decision-making, resource allocation, priority rating, and performance evaluation, AHP has been used in a variety of studies. Examples of AHP application include Ramanathan and Ganesh (1995), Chwolka and Raith (2001), Beynon (2002) and Tzeng et al (2002).” A useful feature of AHP is its applicability to measuring intangible and tangible criteria through ratio scales (Badri, 1999). In addition, by breaking problems into separate elements and relating them in a hierarchical, logical manner beginning with a single high-level decision the decision process is clarified. Strategic high-level decisions can be traced in a descending, step-wise manner to lower-level criteria on which the decision will be made. A decision-maker is able to relate the higher-level to the lower-level criteria through a series of pair-wise comparisons (Vargas, 1990). Several studies have applied AHP to maritime decision-making (Song and Yeo, 2004). For example, Frankel (1992) applied it to shipping policies, and Kumar (2002) to shipping liner competition. These studies, however, are limited in that they only utilize the methods analytical and conceptual elements. Haralambides and Yang (2003) applied an improved version of AHP, called fuzzy-set logic, to model shipper choice. This study applies AHP to an empirical investigation of port competitiveness. The data were collected from expert academics, port directors and managers, shippers, carriers, and public officials. Next, a description of the application of the AHP stages to container port competition among Asia, Europe, and the United States is made to measure perceived competitiveness using upper and mid-level objectives.

Step 1: The Decision Hierarchy The first step required for AHP analysis is to establish a network structure. This can be done by:

(a) Identifying the ultimate goal or decision on the top of the hierarchy (b) Establishing one or more mid/lower-level objectives that are the criteria to evaluate

the goal (c) Link the criteria to specific variables on which the criteria are measured (d) Finally, listing identified alternatives on the bottom, which are linked with the higher

level variables, criteria and the ultimate goal of the decision. The ultimate goal of this study is Port Competitiveness, which is positioned at the top of the hierarchy. Next, mid-level goals are Volume Competitiveness and Investment Competitiveness. The third level involves the variables and attributes of port competitiveness, which will be identified using empirical techniques and the literature. These are listed in the middle of the network structure. Finally, specific container ports in countries such as Asia, Europe, India and the U.S. – the port alternatives – are listed at the bottom of the network. Figure 1 illustrates the conceptual framework for port competitiveness derived from the AHP method as described above.

Port Competitiveness

Volume Competitiveness(Customer-facing)

Investment Competitiveness(Owner-facing/Public Policy)

PortLocation

PortFacility

CargoVolume

ServiceLevel Cost Institutional

StructureLegal

FrameworkFinancial

ResourcesPort

ReputationPrice

Figure 1 – AHP Structure for Port Competitiveness Step 2: Determining weights on criteria and alternatives

In this stage, pairwise comparisons are used to determine the relative weights that represent the importance of one criterion over another. The greater the relative weight, the higher the importance of the factor to the decision. The computational procedures are based on Saaty (1980) and were performed using the Excel@ add-on for AHP methods. Step 3: Ranking Alternatives The final step involves summing the multiplied weight values of each criterion to develop scores. Higher scores represent greater port competitiveness.

4. Survey Instrument The survey instrument used to collect data on Customer-Facing Competitiveness was heavily adapted, by permission, from the Song & Yeo (2004) items and scales. In this study new items had to be developed to measure Investment Competitiveness. This made it a much more robust measure using macro-level criteria and three levels of hierarchy to assess competitiveness along two dimensions rather than the single dimension of Song & Yeo (2004). The items measuring Volume Competitiveness were adapted directly from Song & Yeo (2004), except for the items measuring Port Costs, which were excluded from their study. However, as reliable objective cost data were still unavailable for all ports, the items in this study were subjective. While the variables comprising Investment Competitiveness were developed by the World Bank (2007), the items measuring the variables had to be developed from scratch; however to maintain consistency, the structure of these items and responses are consistent with those of ‘Volume Competitiveness’. After initial development of the items measuring Port Cost in Volume Competitiveness and five variables of Investment Competitiveness, they were administered to five academics who are experts in port and maritime affairs. The academics were asked to evaluate the items for readability and content validity. After several iterations and minor revisions, the items were administered to 11 port managers and academics at the ports of Mayaguez, Incheon, Los Angeles/Long Beach, LeHarve, Melbourne, and Busan to evaluate the readability, clarity, and appropriateness for measuring the variables of interest. The general comments from these managers and the response of the researchers are included in Appendix A-Interview Results. As a result, several changes to wording and the instructions were incorporated and reevaluated by the same set of managers and academics until consensus was reached on the appropriateness and readability of all items. This method is consistent with one suggested by Dillman (2001), which involves pretesting and pilot testing survey instruments to ensure reliability prior to administration to a full sample. To pretest the instrument, it was administered to a convenience sample of experts and port administrators through an organization called the Global University – 8 (GU8). The GU8 is

a consortium of eleven international universities located on seaports. The purpose of the organization is to encourage global research on issues related to international trade. Member institutes include The University of Rhode Island (US), Inha University (Korea), LeHarve University (France), Xiamen University (China), Washington University (Seattle, Washington, US), University of Hawaii (US), The Royal Melbourne Institute of Technology (RMIT-Australia), Hull University (GB), Haifa University (Israel), and Meiji University (Japan). While invitations were sent to ten GU8 members, 28 experts and managers, representing eight ports, agreed to participate in the pilot study. They are Busan Port (Korea), the port of Los Angeles/Long Beach (US), port of LeHarve (France), Port of Incheon (Korea), Port of Chennai (India), Port of Mayaguez (Puerto Rico), Port of Melbourne (Australia), Port of New York/New Jersey (US).

5. Pilot Study Results The following tables report the results of the pilot study. Only a few minor revisions were recommended to the instrument during the pilot phase and were not substantial enough to affect the results. Therefore, after adjusting for sample size, AHP analysis was conducted on the data. The results are reported in Tables 5-9. The Continuity Index (CI), which measures the logical consistency of the results, was .80, which is less than the critical value of 1.0. Any CI exceeding 1.0 is considered logically inconsistent (Song and Yeo, 2004). Table 5 reports the general titles and number of respondents in the pilot study. All categories of respondents in the study are represented, while those of academic researcher represent the greatest number. Table 5 - Port Affiliation & Position

Port (Asst.)

Director

Elected Official

Port Senior Manager

Researcher Shipper Carrier

Busan 2 2 1 3 1 LA/LB 1 1 1 2 1 NY/NJ 1 1

Melbourne 1 Chennai 1 Incheon 1 1

Mayaguez 1 2 LeHarve 2

No Specific Port Affiliation 2 Table 6 reports the scores of the results of the pair-wise comparisons. As a result, Port Location is the most important priority to estimating the Volume Competitiveness of global seaports. In general, the southern-most seaports in the northern hemisphere enjoy competitive

advantages over those in the northern-most areas primarily because of the lessening effects of winter on container port operations. The northern-most ports tend to be affected by ice-laden oceans through channels and fog. These inhibit port operations, often shutting down operations for days-on-end. Southern-most ports face little or no icing of the ports or entries, although they are more subject to hurricanes and typhoons. The second priority is Service Level. Port customers want to know that their cargo will be off-loaded and on-loaded within the expected time period, and in good condition else they must carry additional protective inventory at hinterland locations to avoid stock-outs. The third competitive factor is Port Cost. This is not surprising since globalization is founded on the premise that the savings in production of goods and services exceeds the additional cost of logistics to deliver the goods to market. The fourth most important factor is Port Facility, which involves the activities and infrastructure that support the shipping liners when vessels are in port, including vessel crews and maintenance and repair services. The fifth priority is Cargo Volume, which measures the actual amount of cargo a port handles. While important, this variable is lowest priority because the capacity of ports to handle and adapt to cargo is relatively well-known among shippers and liners. Table 6 – Volume Competitiveness - Pair-wise Comparison matrix, weights, & priority Cargo

Volume Port Facility

Port Location

Service Level

Port Cost Weight Priority

Cargo Volume 1 3.33 .445 .95 .885 .087 5 Port Facility 1 .848 2.544 2.14 .171 4 Port Location 1 3.269 2.889 .282 1 Service Level 1 3.056 .276 2 Port Cost 1 .184 3 Table 7 reports the results of Investment Competitiveness. The highest priority to attract new investors is Institutional Structure. This is intuitive since investors want to know that port administrators have the authority to act in the best interest of the port business, free from excessive governmental or regulatory influence. The second priority is Financial Resources. This means that investors want to know that the port has sufficient capital or access to credit to respond to changes to the shipping industry or to the competitive moves of rival ports. The third priority is Port Reputation, which involves the port’s reputation for treating liners and port users fairly and decision-making surrounding good business practices rather than political agendas or preferential treatment. The fourth priority is price, which involves a port’s ability to charge fair-market prices for its services. This differs from Port Cost – measured in Volume Competitiveness – because Price has more to do with matching what competitors charge for similar services rather than any build-on of profit over port cost. This means that some port services are sold at near-cost, such as basic container loading/off-loading fees, while others such as peak-period fees, demurrage, and support facilities may be sold at premium. The fifth priority is Legal Structure, which involves the avenue of dispute resolution for liners and port users. In general, the greater the autonomy of the port administrators to settle disputes/claims by customers, the more attractive the port is to new

investors. While important, it may have ranked last because only a small, less than 5%, of all business transactions result in some form of dispute or claim by a port user. Table 7 – Investment Competitiveness - Pair-wise Comparison matrix, weights, & priority Price Institutional

Structure Legal Structure

Financial Resources

Port Reputation

Weight Priority

Price 1 1.245 1.49 1.43 1.434 .163 4 Institutional Structure

1 2.158 2.178 2.184 .246 1

Legal Structure 1 1.768 1.595 .153 5 Financial Resources

1 2.10 .243 2

Port Reputation 1 .195 3 Table 8 reports the overall values of Volume Competitiveness for each port. These values correspond to scores for the individual competitiveness of each port. As a result, each port is ranked for competitiveness. As expected, Busan ranked highest among the ports in the pilot study. This is expected because Busan, as a transshipment, mega-hub port, handles the fifth-largest volume of all seaports (based on 2005 annual volume reports). This is the largest among the pilot-study ports. Los Angeles/Long Beach ports ranked second, which also corresponds to the 2005 volume estimates among the pilot study ports. This provides external validity for the measurement instrument in that the results tend to match objective data for actual port volume. Table 8 – Overall Values of Volume Competitiveness Cargo

Volume (.087)

Port Facility (.171)

Port Location (.282)

Service Level (.276)

Port Cost (.184)

Overall Values

Ranking

Busan 0.5011 0.3750 0.3099 0.2062 0.1773 0.1570 1 LA/Long Beach 0.1415 0.1610 0.2856 0.2014 0.1930 0.0983 2 LeHarve 0.1313 0.1240 0.1112 0.1488 0.0743 0.0610 5 Incheon 0.0900 0.1508 0.0937 0.1921 0.2075 0.0834 3 NY/NJ 0.0332 0.1467 0.0520 0.1781 0.2130 0.0735 4 Chennai 0.0272 0.0202 0.0307 0.0500 0.1123 0.0281 6 Melbourne 0.0321 0.0104 0.0455 0.0103 0.0125 0.0133 8 Mayaguez 0.0435 0.0120 0.0714 0.0138 0.0104 0.0160 7 Table 9 reports the values for Investment Competitiveness by individual port. In this case the results were somewhat surprising. Incheon ranked as having the highest competitiveness for new investment, followed closely by Los Angeles/Long Beach and Busan. This occurred probably because Incheon is in the midst of a planning program that intends to create 30 new container berths on the Korean west coast. This is important because it is near the

Seoul/Incheon Airport, with the potential of making the Incheon area an important intermodal hub. This may explain why Incheon was ranked highest for investment because it has the highest potential for new volume growth – over that of the older ports of Los Angeles/Long Beach or Busan. However, these ports still have potential for less-risky growth because their overall scores, while statistically different, were not far below Incheon. Ranked lowest is Mayaguez, which is probably due the excess capacity available at the port. While the potential for attracting new passenger cruise business to the port is still viable, most of the commercial fruit business that once existed has moved to San Juan or to other countries, thus creating excess capacity for loading, off-loading, and storing containers. Table 9 – Overall Values of Investment Competitiveness Price

(.163)

Institutional Structure (.246)

Legal Framework (.153)

Financial Resources (.243)

Port Reputation (.195)

Overall Values

Ranking

Busan 0.2002 0.2229 0.1776 0.2430 0.2271 0.1070 3 LA/Long Beach 0.1670 0.1994 0.1742 0.2740 0.2602 0.1075 2 LeHarve 0.1114 0.0542 0.0976 0.0912 0.1017 0.0456 5 Incheon 0.1779 0.2311 0.2710 0.2610 0.1451 0.1089 1 NY/NJ 0.1776 0.1517 0.1235 0.0703 0.0909 0.0614 4 Chennai 0.0622 0.0135 0.0321 0.0122 0.0843 0.0206 8 Melbourne 0.0557 0.0271 0.0638 0.0383 0.0800 0.0269 6 Mayaguez 0.0479 0.1006 0.0604 0.0100 0.0100 0.0228 7

6. Discussion of the Pilot Study Results The weights and overall values reported in Tables 5 to 9 are summarized in Figure 2.

Port Competitiveness

Volume Competitiveness(Customer-facing)

.5014

Investment Competitiveness(Owner-facing/Public Policy)

.4986

PortLocation

.282

PortFacility

.171

CargoVolume

.087

ServiceLevel.276

PortCost.184

InstitutionalStructure

.246

LegalFramework

.153

FinancialResources

.243

PortReputation

.195

Price.163

Busan.2640

LA/LB.2058

Incheon.1923

LeHarve.1066

Melbourne.0402

Chennai.0487

Mayaguez.0388

Figure 2 – Pilot Study - AHP with weights and overall values Volume Competitiveness Based on the results in Table 6, Port Location (.282) is the most important criteria in the competitiveness of global ports. Service Level (.276) is a close second, followed at a distance by Port Cost, Port Facility, and Cargo Volume. This means that 58.5% of a shipper’s, or 3PL carrier’s decision to select a port is based on where the port is located, relative to the destination of the cargo, and whether or not a port can off-load or load the cargo within the promised time period. This finding is important because it suggests that ports are not selected primarily based on port costs, meaning that shippers do not view them as commodities in the supply chain, but as value-added assets. However, since ports can’t be physically relocated to improve the Port Location variable, the finding that it is important does not help administrators at existing ports to make better decisions. It does mean that port directors should focus resources on reducing the time it takes to off-load and load containers in order to improve service levels. This does not mean that port costs can be ignored, accounting for 18.4% of shipper’s decision, because costs must still be in line with other similar ports. This variable increases in importance in areas where viable alternatives exist, such as Korea, China, and Puerto Rico, and less important where viable alternatives do not exist, such as LeHarve, and Melbourne. Using these criteria on the eight selected ports, Busan is the most competitive port in the world for improving volume, followed by LA/LB

and Incheon. This finding is supported historically as Busan has increased annual container volume at a rate that has kept it ranked as one of the top five ports in the world, second only to Chinese ports, which were not represented in this study. Investment Competitiveness Based on the results reported in Table 7, Institutional Structure (.246) is the most important factor for potential investors, followed closely by Financial Resources (.243). Together they explain 48.9% of an investor’s decision. However, the minor differences in weights of .003 suggest both factors are of practically equal importance to an investor. Port Reputation (.195), Price (.163), and Legal Structure (.153), while less important, collectively account for 51% of an investor’s preference of port investment. This suggests that potential investors prefer ports that are strong in all five factors of Investment Competitiveness, rather than a few dominant variables. In relative Investment Competitiveness values, reported in Table 9, Incheon (.1089), LA/LB (.1075), and Busan (.1073) are equally attractive for investors. This is because all three ports have strong weights on all five factors. NY/NJ (.614) and LeHarve (.456) are third and fourth, with Chennai, Mayaguez, and Melbourne practically tied for the least attractive for investors. This suggests that the last three ports must make significant changes in their ability to reinvest funds in port infrastructure, improve practices that increase competition for services to capture new investment funds, and develop legal systems to efficiently and quickly resolve disputes between stakeholders. Investment Competitiveness vs. Volume Competitiveness In evaluating the overall scores for investment versus Volume Competitiveness, Volume Competitiveness was found to be slightly more important representing 50.14% of overall competitiveness. However, the two factors are practically of equal importance, which is logically consistent in that the most competitive ports are attractive to both shippers and investors. This may explain why Busan and LA/LB have demands on their ports that consistently exceed capacity and why Incheon has achieved strong growth in a relatively few years of operation. These results address first research question.

Will the existing actions by ports improve their competitive positions? The results show that the activities of Busan, LA/LB, and Incheon are improving their competitive positions. However, the remaining ports must make substantial improvements in Service Levels and all five factors of Investment Competitiveness to become competitive with the larger ports. Strong Volume Competitiveness suggests that investments in infrastructure have a high probability of attracting new revenue and the associated returns. Increased investment in infrastructure leads to increased port capacity and decreases the probability of disruptions. Increased capacity also leads to higher service levels – resulting in greater volume.

Conclusions will not be drawn from the pilot test since the purpose was to develop and test a new scale and a survey to collect data for the larger-scale study.

7. Full Study – 55 Global Seaports The results of the pilot study provide evidence that the new measurement scales are reliable. The sampling frame for the full study is the 200 world’s largest container ports. In Spring 2009, managers, directors, carriers, shippers, and researchers at these ports were solicited three times by e-mail and/or by telephone phone to participate in a large-scale study of port competitiveness. Graduate students fluent in Chinese, Korean, French, and English made the contacts. The top 100 container ports by volume were solicited multiple times. Out the top 100, 55 ports agreed to participate. Some provided multiple respondents, while others provided only a single respondent. The highest ranking port in the study, Singapore, was # 1 in container volume in 2007, and the lowest ranking port in the study was Ghent, ranked #84 in container volume globally. However, since the pilot study did not include Chinese ports, an effort was made to test the instrument by conducting interviews with port officials and administrators at the Port of Xiamen. As a result of these interviews the survey instrument was slightly revised. Upon completion of the revisions, the instrument was translated into four languages – English, Korean, Chinese, and French. The revised instruments are included in Appendices B-E respectively. A list of the participating ports is included in Table 10 along with the title of the respondent and their association with the port. While many of the respondents had port affiliations, others such as researcher respondents evaluated ports they had sufficient knowledge of, but who may not have a formal relationship such as manager, shipper, or carrier. Since the revisions to the survey items were minor, and affected primarily only the applicability of the instrument to Chinese ports, the responses from the pilot study were retained for inclusion in the sample. Table 10 – Respondent Port Affiliation and Position PORT Port

(Asst.) Director

Elected Official

Port Senior

Manager

Researcher Shipper Carrier

Singapore 2 4 3 1 Shanghai 2 Hong Kong 1 1 3 Busan 2 2 1 3 Rotterdam 1 1 Dubai 1 Hamburg 1 1 LA/LB 1 1 1 2 1 Antwerp 1 Klang 1 NY/NJ 1 1 Bremen 1 Xiamen 2 2 2 Mumbai 1 Tokyo 1

Gioia, ITL 1 Valencia 1 Nagoya 1 Manila 1 LeHarve 2 Savannah 1 Santos 1 Santos 1 Kobe 1 Barcelona 1 Oakland 1 Vancouver 1 Kingston 1 Melbourne 1 Said 1 Bruges-Zeebr 1 Incheon 1 1 Chennai 1 Boston 1 1 Mayaguez 1 4 Hull 1 Charleston 1 Houston 1 Tacoma 1 New Orleans 1 Seattle 1 Gwangyang 1 Ulsan, SK 1 Amsterdam 1 Dampier 1 Haifa 1 Marseilles 1 Osaka 1 Copenhagen 1 Beaumont 1 Instanbul 1 Swansea 1 Genoa 1 Nador 1 Varberg 1 Ghent 1 The first step in the analysis was to impute missing data created by respondents skipping questions. Overall only 2% of the data points were left incomplete by the respondents. The missing data were imputed using the Expectation Maximization (EM) imputation procedure which essentially develops a regression equation to predict the missing data points, and re-values outliers to the next reported value within 3 standard deviations of the mean. This technique has been shown to be more reliable than simple means imputation (Tabachnick and Fidell, 2001). The next step was to analyze the pair-wise comparisons between each variable. The results are shown in Table 11. The results show that Port Location is the factor with the highest priority in estimating the Volume Competitiveness of global seaports. This

was expected and is consistent with all previous research. In general, the southern-most seaports in the northern hemisphere enjoy competitive advantages over those in the northern-most areas primarily because of the lessening effects of winter on container port operations. The northern-most ports tend to be affected by ice-laden oceans through channels and fog. These factors inhibit port operations, often shutting down operations for days-on-end. Southern-most ports face little or no icing of the ports or channels, although they are more subject to disruptions due to hurricanes and typhoons. The second priority in Volume Competitiveness is Service Level. Port customers want to know that their cargo will be off-loaded and loaded within the expected time period, and in good condition, else they must carry additional protective inventory at hinterland locations to avoid stock-outs. The third competitive factor is Port Cost. This is not surprising since globalization is founded on the premise that the savings in production of goods and services exceeds the additional cost of logistics to deliver the goods to market. However, despite what is often reported in studies that promote Cost as the #1 factor for port choice, it was ranked # 3 in this study. The lower ranking of Cost under that of Service Level has empirical support since shippers will often pay as much as $100 per container to ship during peak periods so that their goods arrive on time. If Port Cost was top priority, few shippers would be willing to pay the peak-period premiums. The fourth most important factor is Port Facility, which involves the activities and infrastructure that support the shipping liners and their crews when vessels are in port, including maintenance and repair services. This is important because some crews can’t leave their vessels when in foreign ports because of the need for passports and visas, which are not typically given to vessel crews. However, crews can order food and goods for delivery to their ships. Small ships that operate similar to convenience stores often service these vessels when in a port of call. The fifth priority is Cargo Volume, which measures the actual amount of cargo a port handles. While important, this variable is lowest priority because the capacity of ports to handle and adapt to cargo is relatively well-known among shippers and liners and is less of a differentiator. Some sample bias may also exist and help explain this finding because only ports ranking in the top-85 world-wide were in the sample. This means that handling adequate capacity is assumed among top ports and may be less of a differentiator than other factors. Table 11 – Volume Competitiveness - Pair-wise Comparison matrix, weights, & priority Cargo

Volume Port Facility

Port Location

Service Level

Port Cost Weight Priority

Cargo Volume 1 .3714 .087 .2625 .215 .062 5 Port Facility 1 .0485 .8428 .8352 .166 4 Port Location 1 1.358 4.648 .355 1 Service Level 1 1.255 .233 2 Port Cost 1 .185 3

Table 12 reports the results of Investment Competitiveness. The highest priority to attract new investors is Port Reputation, with a slight lead over the second highest priority, Financial Resources. This is intuitive since investors work from primarily public information, and a port’s reputation for making decisions on sound business principles is important. This differs from the results in the pilot study, but is understandable given the small sample size. Some of these findings are compared to the pilot study since, unlike the Volume Competitiveness factors, no previous academic studies examine these variables in an AHP model. These variables were taken from the World Bank Report (2007) which does not contain a literature review. The second priority is Financial Resources. This means that investors want to know that the port has sufficient capital or access to credit to maintain port assets, and respond to the competitive moves of rival ports. The third priority is Institutional Structure. This differs from the pilot study which rated Institutional Structure first, but this could be due to the small sample size. In the full study, Institutional Structure among the top global ports is well-known among shippers and liners and therefore may be less of a differentiator in choosing investment alternatives. The fourth priority is Price, which involves a port’s ability to charge fair-market prices for its services. This differs from Port Cost – measured in Volume Competitiveness – because Price has more to do with matching what competitors charge for similar services rather than any build-on of profit over Port Cost. The Price variable also involves the autonomy of a port to set prices free from political interference. This means that some port services are sold at near-cost, such as basic container loading/off-loading fees, while others may be sold at premium prices, such as peak-period fees, demurrage, and support facilities. In the pilot study, there was concern that the variables Port Cost and Price would be highly correlated, creating problems with multi-colleniarity. However, no statistically significant correlation was found in the full study. The fifth priority is Legal Structure, which involves the avenue of dispute resolution for port users. In general, the greater the autonomy of the port administrators to settle disputes/claims by customers without involving the local judicial system, the more attractive the port is to new investors. While important, Legal Structure may have ranked last because only a small, less than 4%, of all port business transactions result in some form of dispute or claim. This means that investors are not concerned that few claims represent a substantial threat to their investment. There are also slight differences in weights between Financial Resources and Port Reputation. While there is no formal test for statistical significance between scores, this finding is probably practically insignificant, meaning that the two variables may be considered of equal importance to investors. It is important to note here that four of the weighted values are close – within .0035 of each other. This suggests that investors are concerned that a port with good investment characteristics has a balance of the investment variables instead of dominance in one or two. As discussed previously, even the variable Legal Framework scored relatively high on importance – although clearly less than the other four variables. Table 12 – Investment Competitiveness - Pair-wise Comparison matrix, weights, & priority Price Institutional

Structure Legal Framework

Financial Resources

Port Reputation

Weight Priority

Price 1 1.093 1.197 .888 .832 .1995 4 Institutional Structure

1 .824 1.29 1.295 .2002 3

Legal Framework 1 .233 1.195 .1624 5 Financial Resources

1 .258 .2200 2

Port Reputation 1 .2229 1 Table 13 reports the overall scores for Volume Competitiveness. These values correspond to scores for the individual competitiveness of each port. As a result, each port is ranked for competitiveness in the column eight using the weights in column seven. Column 9 reports the 2007 global rankings based on actual container volume at each port. As expected, Singapore and Shanghai ranked # 1 and # 2 respectively. The rankings are generally consistent with the actual container volumes handled by each port, which provides external validity to the new measurement scale. However, this finding is somewhat obscure in Table 13 because the actual port rankings in Column 9 have gaps – meaning that not all of the top 85 ports participated. Therefore, the actual numbers used as rankings in column 9 are ordered based on their position in the sampling frame. This means that if port 20 and 25 are in the sample, but not ports 21, 22, 23, or 24, the ranking in column 9 is ordered 20, 25, etc. In column 8 the numbers represent simple orders in the sample meaning 20, 21 would be used. If the ports are reordered based on simple ranks and analyzed using Spearman’s rank-order correlation, the r = .74, showing significant agreement between the study results and observed 2007 results. Another factor explaining some of the difference between the actual and predicted rankings is the time lag that took place between the actual 2007 results and the data collection period which extended across 2007 - 2009. The economic downturn experienced during this period caused a shifting of container volume world-wide, whose final results will not be available until next year. A third factor explaining the difference between the actual and predicted rankings is that the scale not only captures existing factors affecting container volume, but also provides insight into future developments by capturing the plans of port officials and administrators. For example in the Volume Competitiveness scale, Busan ranks third in the world behind Singapore and Shanghai, but ahead of Hong Kong and Rotterdam, while in actual volume Busan ranked # 5 behind these two ports. One explanation for this is that Hong Kong and Rotterdam is expected to lose more volume than Busan in the future. This prediction appears to be coming true in 2009 in that Hong Kong is expected to drop to 10th or 12th overall and Rotterdam is expected to drop to 7th or 9th overall in total annual container volume, both behind Busan. This provides further external validity that the scale not only captures exiting factors affecting port container volume but also considers future effects of economic and competitor actions. It is important to understand that while Rotterdam slipped in 2009 rankings, it will likely improve its competitive position as soon as the new and second Maasvlakte terrain expansions are completed in 2011. It is likely that Rotterdam will overtake Shanghai and Singapore in overall annual tonnage, thus utilizing the assets financed by private and public investors. A surprising factor is that Incheon, ranked # 51 in 2007 in actual container volume, was ranked #18 in the new scale ahead of Antwerp, New York/New Jersey, and Tokyo. This

suggests that based on the future plans to expand Incheon to 30 berths and its proximity to Seoul/Incehon airport, port managers expect to experience a marked increase in container volume. However, it is likely that Incheon will cannibalize some of the volume going to Busan – especially those related to airfreight. Much of this anticipated increase in volume is also attributable to the port’s close proximity to Seoul, where half of the nation’s populous lives. Currently goods must be shipped 6-8 hours by truck or rail from Busan to Seoul. Once Incheon is fully on-line the travel time to and from Seoul for import/export cargo will be reduced to 90 minutes. This suggests that Incheon may quickly become a major player in international trade. It also suggests that the port should continue to invest in superstructure and infrastructure to achieve the 30 berths currently planned. However, there is political and popular objection to investing public tax revenue in expanding existing port capacities at both Busan and Incheon because existing capacity is much greater than the anticipated demand for the next decade. Once the Busan old port is renovated the combines capacity at both will exceed 20 Million TEU’s annually. Busan still enjoys an advantage over Incheon in Port Location for transshipment volume, which is the number one factor in Volume Competitiveness. Other surprising findings in the port rankings are the predicted increased competitiveness of the ports of Xiamen, Savannah, Manila, Nagoya, and Santos. These ports, ranked 22, 37, 35, 34, and 39 in actual container volume in 2007, have risen to 8, 11, 12, 13, and 14 respectively in the new scale. This means that the ports plan to overcome some of their disadvantage in Port Location by attracting new business through increased Service Levels and tightly controlling Port Cost, was could succeed in increasing container volume. External validity of their improved competitiveness can be found through the activities conducted at the ports over the last few years. For example, due to the widening of the Panama Canal, many post-panamax class vessels will be able to travel to the US east coast from Asia without transshipping volume through Busan or Los Angeles/Long Beach. To handle the expected increase in volume, Target Inc. has invested millions of dollars in new Distribution Centers in Savannah, and Walmart has invested similar levels in Houston. These major corporations would not likely make these capital-intensive investments unless they were certain the Panama Canal project would yield greater volume through these ports. In regards to Manila, the recent trend for fruit companies to relocate their operations to the Philippines will result in greater container volume for the port. External validity for increased container volume through Nagoya and Santos was not identified during the time of this study, but the Japanese port’s improved competitiveness could be partially explained by an anticipated improvement in the Japanese economy, which has been sluggish for over a decade. The competitiveness ranking of the Korean port Gwangyang at #34 is surprising since it was ranked just #65 worldwide in actual container volume in 2007, and far ahead of Ulsan, ranked just behind it in actual volume at #66. The reason for this improvement is because its rating on the Cargo Volume and Port Location factors were relatively higher than similar-size ports. However, this does not explain why it scored much higher on these factors than Ulsan. A partial explanation may be due to the single respondent for each port, thus it is

possible that methods-bias accounted for the difference in results. Only replication with multiple respondents can definitively explain the variance in the two similar ports. Table 13 – Overall Values of Volume Competitiveness PORT

Cargo Volume (.062)

Port Facility (.166)

Port Location (.355)

Service Level (.233)

Port Cost (.185)

Weight Overall Ranking

Study

2007 Rank Actual

Volume Singapore 0.0465 0.0123 0.0411 0.043 0.0331 0.02865 1 1 Shanghai 0.0541 0.0021 0.0411 0.0108 0.0434 0.02858 2 2 Busan 0.0340 0.0375 0.0196 0.0244 0.0415 0.02768 3 5 Hong Kong 0.0340 0.0375 0.0196 0.0244 0.0415 0.02737 4 3 Rotterdam 0.0439 0.0240 0.0209 0.0336 0.0284 0.02554 5 6 Hamburg 0.0429 0.0269 0.0209 0.0359 0.0284 0.02530 6 9 Dubai 0.0439 0.0266 0.0209 0.0359 0.0284 0.02480 7 7 Xiamen 0.0047 0.0186 0.0208 0.0313 0.0436 0.02472 8 22 LA/LB 0.0493 0.0130 0.0294 0.0176 0.0163 0.02376 9 13 Bremen 0.0333 0.0345 0.0338 0.0023 0.0103 0.02292 10 20 Savannah 0.0049 0.0179 0.0294 0.0249 0.0230 0.02292 11 37 Manila 0.0335 0.0344 0.0338 0.0023 0.0103 0.02291 12 35 Nagoya 0.0049 0.0151 0.0294 0.0249 0.0235 0.02251 13 34 Santos 0.0074 0.0345 0.0191 0.0103 0.0312 0.02105 14 39 Klang 0.0060 0.0249 0.0309 0.0127 0.0153 0.02076 15 16 Gioia, ITL 0.0060 0.0249 0.0309 0.0127 0.0153 0.02076 16 27 Mumbai 0.0074 0.0347 0.0176 0.0103 0.0312 0.02059 17 24 Incheon 0.0350 0.0209 0.0137 0.0229 0.0112 0.02016 18 51 NY/NJ 0.0065 0.0128 0.0110 0.0296 0.0228 0.01971 19 19 Instanbul 0.0070 0.0289 0.0179 0.0227 0.0150 0.01923 20 74 LeHarve 0.0078 0.0183 0.0213 0.0308 0.0099 0.01879 21 36 Antwerp 0.0100 0.0218 0.0235 0.0129 0.0166 0.01841 22 14 Tokyo 0.0100 0.0218 0.0235 0.0129 0.0166 0.01841 23 26 Barcelona 0.0067 0.0123 0.0184 0.0249 0.0215 0.01810 24 42 Kobe 0.0065 0.0123 0.0125 0.0296 0.0228 0.01732 25 41 Valencia 0.0065 0.0128 0.0110 0.0296 0.0228 0.01692 26 33 Oakland 0.0067 0.0125 0.0132 0.0272 0.0201 0.01666 27 43 Charleston 0.0105 0.0103 0.0211 0.0213 0.0112 0.01638 28 62 Kingston 0.0052 0.0150 0.0118 0.0213 0.0242 0.01596 29 46 Copenhagen 0.0105 0.0108 0.0196 0.0213 0.0111 0.01594 30 72 Vancouver 0.0070 0.0127 0.0132 0.0225 0.0201 0.01572 31 44 Beaumont 0.0305 0.0157 0.0122 0.0185 0.0112 0.01567 32 73 Bruges 0.0131 0.0113 0.0167 0.0213 0.0111 0.01529 33 50 Gwangyang 0.0497 0.0113 0.0125 0.0032 0.0195 0.01510 34 65 Mayaguez 0.0131 0.0113 0.0167 0.0213 0.0111 0.01421 35 60 Haifa 0.0061 0.0150 0.0118 0.0166 0.0188 0.01407 36 69 New Orleans 0.0131 0.0202 0.0162 0.0074 0.0121 0.01397 37 64 Houston 0.0174 0.0090 0.0198 0.0118 0.0086 0.01394 38 63 Seattle 0.0174 0.0106 0.0191 0.0089 0.0107 0.01374 39 65 Genoa 0.0157 0.0203 0.0122 0.0110 0.0121 0.01366 40 81 Hull 0.0157 0.0203 0.0125 0.0091 0.0121 0.01335 41 61 Boston 0.0157 0.0204 0.0110 0.0091 0.0121 0.01332 42 59 Tacoma 0.0235 0.0077 0.0169 0.0118 0.0086 0.01331 43 64 Varberg 0.0069 0.0150 0.0118 0.0142 0.0161 0.01316 44 83 Dampier 0.0087 0.0136 0.0088 0.0178 0.0174 0.01308 45 68

Ulsan, SK 0.0183 0.0092 0.0169 0.0118 0.0086 0.01306 46 66 Marseilles 0.0200 0.0113 0.0073 0.0237 0.0089 0.01292 47 70 Chennai 0.0157 0.0204 0.0110 0.0091 0.0120 0.01288 48 54 Said 0.0159 0.0202 0.0111 0.0086 0.0121 0.01278 49 49 Osaka 0.0157 0.0204 0.0110 0.0085 0.0122 0.01277 50 71 Swansea 0.0150 0.0205 0.0112 0.0086 0.0121 0.01278 51 80 Nador 0.0157 0.0204 0.0110 0.0086 0.0121 0.01278 52 82 Melbourne 0.0148 0.0113 0.0081 0.0237 0.0089 0.01267 53 47 Amsterdam 0.0148 0.0108 0.0118 0.0142 0.0107 0.01218 54 67 Ghent 0.0148 0.0108 0.0118 0.0142 0.0107 0.01218 55 84 Table 14 reports the values for Investment Competitiveness by individual port. In this case the results were not surprising. Shanghai and Singapore ranked as having the highest competitiveness for new investment, followed closely by Busan, which was somewhat surprising that it ranked ahead of Hong Kong, Rotterdam, and Dubai. This occurred probably because Busan new port is in the midst of a huge development program involving long-term plans to create premium living and business space for over 250,000 foreigners, self-contained with education, healthcare, and recreational facilities. The Busan new port development also includes plans for new intermodal links to the Trans-Siberian Railway, and express roadway to major highways. These plans will require at least several decades to complete and require huge private and public investments. A time-line for this project is difficult because completing the planned Trans-Siberian linkages will require strong and sustained diplomatic efforts. Creating successful long-term, stable relationships with North Korea and Russia is key to future success but impossible to predict. The lower ranking of Rotterdam could be explained by its current investment in expansion. The port is in the midst of a huge expansion at Massvlakte that consumes all of its current investment Euros. Once the expansion is completed in 2011, the port should increase in Volume Competitiveness – manifested through possibly passing Shanghai and Singapore as the top global port. Incheon was ranked #21 for Investment Competitiveness, much higher than its current #51 ranking for actual volume. The probable reason for Incheon’s relatively strong position, relative to those with lesser scores, is because it is planning to build 30 new berths near the Seoul/Incheon Airport, with the potential of making the Incheon area an important intermodal hub. This may explain why Incheon has a high potential for new volume growth – over that of the older ports of Xiamen and Savannah. After Incheon, subsequent port scores drop marginally. Ranked last is Istanbul, which is probably due to the excess capacity at the port, and poor potential for increased international trade due to its proximity to the war in Iraq.

Table 14 – Overall Values of Investment Competitiveness PORT

Price (.1995)

Institutional Structure (.2002)

Legal Framework (.1624)

Financial Resources (.2200)

Port Reputation (.2229)

Weight Overall Ranking

Shanghai 0.0459 0.0087 0.0027 0.0252 0.0447 0.02694 1 Singapore 0.0017 0.0448 0.0348 0.0346 0.0385 0.02550 2 Busan 0.0186 0.0207 0.0287 0.0346 0.0340 0.02479 3 Hong Kong 0.0186 0.0200 0.0287 0.0340 0.0340 0.02449 4 Rotterdam 0.0287 0.0123 0.0038 0.0250 0.0324 0.02286 5 Dubai 0.0334 0.0099 0.0035 0.0322 0.0302 0.02249 6 Hamburg 0.0332 0.0098 0.0030 0.0320 0.0302 0.02242 7 Valencia 0.0382 0.0233 0.0111 0.0155 0.0214 0.02207 8 LA/LB 0.0020 0.0329 0.0519 0.0232 0.0104 0.02153 9 Kobe 0.0299 0.0259 0.0142 0.0156 0.0192 0.02091 10 LeHarve 0.0142 0.0284 0.0081 0.0184 0.0276 0.02085 11 Antwerp 0.0138 0.0208 0.0346 0.0183 0.0195 0.02047 12 Tokyo 0.0110 0.0210 0.0296 0.0176 0.0251 0.02021 13 NY/NJ 0.0287 0.0234 0.0113 0.0155 0.0216 0.02016 14 Kingston 0.0311 0.0136 0.0112 0.0198 0.0237 0.02004 15 Klang 0.0141 0.0182 0.0282 0.0231 0.0185 0.01976 16 Gioia, ITL 0.0141 0.0182 0.0282 0.0231 0.0185 0.01976 17 Barcelona 0.0287 0.0236 0.0113 0.0155 0.0194 0.01976 18 Oakland 0.0263 0.0234 0.0115 0.0155 0.0216 0.01976 19 Vancouver 0.0263 0.0210 0.0115 0.0156 0.0216 0.01930 20 Incheon 0.0171 0.0222 0.0275 0.0230 0.0064 0.01922 21 Mumbai 0.0244 0.0123 0.0041 0.0275 0.0209 0.01822 22 Nagoya 0.0221 0.0164 0.0123 0.0229 0.0164 0.01799 23 Xiamen 0.0145 0.0205 0.0234 0.0092 0.0212 0.01781 24 Santos 0.0220 0.0123 0.0046 0.0275 0.0209 0.01781 25 Varberg 0.0239 0.0138 0.0115 0.0175 0.0216 0.01774 26 Melbourne 0.0157 0.0255 0.0155 0.0123 0.0185 0.01730 27 Marseilles 0.0157 0.0255 0.0155 0.0123 0.0185 0.01730 28 Savannah 0.0221 0.0140 0.0125 0.0206 0.0164 0.01706 29 Bremen 0.0334 0.0080 0.0214 0.0181 0.0067 0.01701 30 Manila 0.0334 0.0080 0.0214 0.0181 0.0067 0.01701 31 Genoa 0.0028 0.0192 0.0220 0.0218 0.0197 0.01665 32 Boston 0.0093 0.0164 0.0206 0.0243 0.0127 0.01641 33 Chennai 0.0030 0.0164 0.0220 0.0218 0.0209 0.01638 34 Swansea 0.0030 0.0164 0.0220 0.0218 0.0209 0.01638 35 Said 0.0093 0.0163 0.0206 0.0243 0.0127 0.01614 36 Osaka 0.0093 0.0163 0.0206 0.0243 0.0127 0.01614 37 Nador 0.0093 0.0163 0.0206 0.0243 0.0127 0.01614 38 Hull 0.0091 0.0168 0.0209 0.0243 0.0104 0.01575 39 Haifa 0.0239 0.0115 0.0203 0.0061 0.0175 0.01550 40 New Orleans 0.0046 0.0163 0.0206 0.0243 0.0142 0.01549 41 Dampier 0.0167 0.0255 0.0112 0.0109 0.0119 0.01510 42 Mayaguez 0.0127 0.0181 0.0214 0.0079 0.0142 0.01458 43 Houston 0.0147 0.0156 0.0275 0.0078 0.0108 0.01446 44 Bruges-Zee 0.0129 0.0181 0.0214 0.0079 0.0142 0.01432 45 Copenhagen 0.0127 0.0181 0.0214 0.0079 0.0142 0.01432 46 Amsterdam 0.0288 0.0140 0.0066 0.0069 0.0140 0.01420 47 Ghent 0.0287 0.0140 0.0066 0.0069 0.0140 0.01420 48

Tacoma 0.0125 0.0185 0.0275 0.0079 0.0084 0.01408 49 Beaumont 0.0191 0.0148 0.0214 0.0113 0.0067 0.01404 50 Ulsan, SK 0.0127 0.0156 0.0275 0.0079 0.0086 0.01359 51 Gwangyang 0.0109 0.0148 0.0229 0.0093 0.0112 0.01318 52 Charleston 0.0143 0.0197 0.0092 0.0079 0.0142 0.01302 53 Seattle 0.0072 0.0222 0.0153 0.0085 0.0084 0.01188 54 Instanbul 0.0096 0.0099 0.0122 0.0097 0.0089 0.00980 55

Figure 3 below reflects the results of the AHP analysis in graphical format. Due to the large number of ports in the study, they can not be depicted graphically as they were in the pilot study.

Figure 3 – The Full Sample

Port Competitiveness

Investment Competitiveness

(.488)

Volume Competitiveness

(.512)

Port Reputation

(.2229)

PortLocation(.3550)

Port Facility(.1661)

Cargo Volume(.0622)

Service Level

(.2333)

Port Costs

(.1851)

Price

(.1995)

Institutional Structure

(.2002)

Legal Framework

(.1624)

FinancialResources

(.2200)

As seen in Figure 3, Volume Competitiveness is slightly more important to overall Port Competitiveness than Investment Competitiveness because the potential for volume growth is essential to convincing investors that their money will be used to attract new business.

8.0 Discussion The finding that Port Location is the most important factor in Volume Competitiveness is consistent with previous research, e.g. Song and Yeo (2004) that tested similar variables in a Chinese context. However, it differs with some US-based research, e.g. Grigalunas, et al. (2004) that found that Cost was the most important factor. These differences could be contextual since there are container port alternatives in the Northeast US and China that may encourage Cost competition, whereas regions with few alternatives may consider Port Location the most important factor. The finding that Service Level is the second most important variable differs from previous research, e.g. Song and Yeo, that found Port Facility was second, along with other factors, e.g. Grigalunas, et al. Also, the difference between the first and second priorities is less in this study than Song and Yeo, or in Grigalunas, et al. This suggests that a balance in all five factors increases competitiveness greater than dominance of one or two factors. Another reason for these conflicts could be due to the difference in sampling frames, i.e. Song and Yeo suffered from regional bias because they only measured Chinese ports exclusively, as do others focused on a single country or geographical region. In contrast, this study examines port competitiveness on five continents – a more diverse sample. Therefore, the way ports compete within a geographical region could be different than when competing on a global basis. This may explain why a balance among port capabilities is important to improve competitiveness. Another possibility is that the observed differences are due to random chance rather than a true difference in samples. This issue can only be addressed through replication studies. A third possible explanation for the differences is that this study is the first to simultaneously test Investment Competitiveness and Volume Competitiveness together and suggests that Investment Competitiveness now accounts for some of the variance previously accounted for by Volume Competitiveness.

Effects of the Panama Canal on Asian and American shipping practices are evident in many of the results. But less evident is the support for the effects on Asia of liners using the Northwest Passage through Canadian waters to ship containers to the US east cost. This could reduce volume at Los Angeles/Long Beach, through the Panama Canal, and possible transshipment through Singapore, Shanghai, or Busan. But, last year CMA-CGM chose the Port of Boston as its Northeast hub. Prior to this, the company used Jamaica as its exclusive US east coast hub. This suggests that the company is planning for more volume to be shipped through the Northwest route.

9. Study Limitations The major weakness with this study is that most ports provided only a single respondent, which creates issues of response bias. Also, many of the respondents were academics whose knowledge was based primarily on published information or personal knowledge of port activities, which admittedly is affected by time lags between findings and actual publication. Collecting data from multiple respondents in various roles at the ports, as was done at Busan, Singapore, and Xiamen, would have been valuable. Collecting data in a multi-year,

longitudinal manner would theoretically yield results with greater reliability, but these requirements would extend the data collection over a number of years and radically increase costs. Future replication studies should consider these factors and their affects on the results.

10. References Anderson, C. M., J. J. Opaluch, and T.A. Grigalunas, Forthcoming 2009, The Demand for

Import Services at US Container Ports, In Corrected Press, Badri, M. (1999) “Combining the analytic hierarchy process and goal programming for global

facility location-allocation problem”, International Journal of Production Economics, 62, pgs. 237–248.

Beynon, M. (2002) “An analysis of distributions of priority values from alternative comparison

Scales within AHP”, European Journal of Operational Research, 140, pgs. 104–117. Brooks, M. (2000), Sea change in liner shipping: regulation and managerial decision-making in a

global industry. Pergamon, Amsterdam. Chwolka, A and Raith, M. (2001) “Group preference aggregation with the AHP: Implications for

Multiple-issue agendas”, European Journal of Operational Research, 132, pgs. 176–186. Grigalunas, Thomas A., Meifeng Luo, Simona Trandafir, Christopher Anderson and Suk Jae

Kwon. (2004) Issues in Container Transportation in the Northeast: Background, Framework,

Illustrative Results and Future Directions. URI Transportation Center. (URITC Project 536185) 25p. http://www.uritc.uri.edu/media/finalreportspdf/536185.pdf

Haralambides, H. E. and R. Behrens (2000), “Port Restructuring in a Global Economy: An Indian Perspective”, International Journal of Transport Economics, Vol. 27, No. 1, 19-39.

Jacobs, W., Hall, P. (2007), “What Conditions Supply Chain Strategies of Ports?, The Case of Dubai”, Geo Journal, 68, 4, p. 327.

Kerr, W. (2006), “Enjoying a Good Port with a Clear Conscience: Geographic Indicators, Rent Seeking & Development”, The Estey Centre Journal of International Law and Trade Policy, Saskatoon. 7, 1, p. 1

Sang-Hun, Choe (2006), “Asian ports struggle to keep up with Shanghai”, International Herald Tribune, Business/December 20, Available at: http://www.iht.com/articles/2006/12/20/business/transcol21.php, Accessed: June 12, 2007.

Song, D-W, Yeo, K-T, (2004), “A Competitive Analysis of Chinese Container Ports Using the Analytical Hierarchy Process”, Maritime Economics and Logistics, 6, 34-52.

Tabachnick, B., and Fidell, L., 2001, Using Multivariate Analysis, New York: Harper-Collins Publishers, 2001.

Kumar, S. (2002) “A decision support model for the liner shipping competition policy debate,”

Proceedings of the International Association of Maritime Economists, pgs. 12–15. Malchow, M and Kanafani, A. (2001), “A disaggregate analysis of factors influencing port

selection”, Maritime Policy and Management, 28, pgs. 265–277. Murphy, P, Dalenberg, D. and Dabley, J. (1988), “A contemporary perspective on international

port operations,” Transportation Journal, 28, pgs. 23–32. Murphy, P, Daley, J and Dalenberg, D. (1992), “Port selection criteria: an application of a

transportation research framework”, Logistics and Transportation Review, 28, pgs. 237–255.

Ramanathan, R. and Ganesh, L. (1995), “Using AHP for resource allocation problems”, European Journal of Operational Research, 80, pgs. 410–417.

Saaty, T. (1980) Multi-criteria decision making: the analytic hierarchy process, McGraw-Hill,

New York. Slack, B. (1985), “Containerization, inter-port competition and port selection”, Maritime Policy

and Management, 12, pgs. 297–299. Tzeng, G-H, Teng, M-H, Chen, J-J. and Opricovic, S. (2002) “Multicriteria selection for a

restaurant location in Taipei”, International Journal of Hospitality Management, 21, pgs. 171–187.

Vargas, L. (1990) “An overview of the analytic hierarchy process and its applications”, European Journal of Operational Research, 48, pg.2.

Wedley, W, Choo, E and Schoner, B. (2001) “Magnitude adjustment for AHP benefit/cost ratios.

European Journal of Operational Research,” 133, pgs. 342–351. World Bank Report, (2007, Modules 1-8), “Port Reform Toolkit”, available online at,

http://web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTTRANSPORT/EXTPRAL/0,,contentMDK:20517158~menuPK:1221870~pagePK:148956~piPK:216618~theSitePK:338594,00.html

Yap, Wei Yim and Jasmine S. L. Lap (2006), “Competition dynamics between container ports in East Asia”, Transportation research, Part A, Policy and practice, Vol. 40, No. 1, 35-51.

UESCAP-KMI (2000), Comparative Analysis of Port Tariffs in the ESCAP Region, New York: United Nations, Available at: http://http.unescap.org/ttdw/Publications/TFS_pubs/pub_2190/pub_2190.pdf, Accessed: June 12, 2007

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