JOINT TRANSPORT RESEARCH CENTRE

Discussion Paper No. 2008-8
February 2008

The Impact of Hinterland
Access Conditions on
Rivalry between Ports
Anming ZHANG
Sauder School of Business
University of British Columbia
Vancouver, Canada

The views expressed in this paper are those of the author and do not necessarily represent
positions of the Sauder School of Business, the OECD or the International Transport
Forum.

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A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

Abstract: This paper examines the interaction between hinterland access conditions and port
competition. Competition between ports is treated as competition between alternate intermodaltransportation chains, while the hinterland access conditions are represented by both the corridor
facilities and the inland roads. We find that when ports compete in quantities, an increase incorridor capacity will increase own port’s output, reduce the rival port’s output, and increase own
port’s profit. On the other hand, an increase in inland road capacity may or may not increase own
port’s output and profit, owing to various offsetting effects. Essentially, while more road capacity
reduces local delays and moderates the negative impact of own output expansion, it induces greater
local commuter traffic and may moderate the reduction by local commuter traffic in response to arise in cargo traffic, both of which reduces own output and profit. Similarly, inland road pricing
may or may not increase own port’s output and profit. Finally, case examples for selected ports andregions are discussed.

Keywords: Seaports; Corridor; Hinterland; Intermodal transport chain; Competition; Capacity
investment; Road pricing

Acknowledgement: I would like to thank Sarah Wan for very helpful discussion on some of thedata used in this paper.

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

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TABLE OF CONTENTS

1.

INTRODUCTION ...............................................................................................................52.

BACKGROUND .................................................................................................................83.

AN ANALYTICAL MODEL ............................................................................................11
3.1
3.2
3.3

4.

CASE EXAMPLES ...........................................................................................................19
4.1
4.2
4.3.

5.

A basic framework ................................................................................................11
Quantity competition .............................................................................................15
Price competition and related issues......................................................................17

The Le-Havre-Hamburg port range .......................................................................19
Canada ...................................................................................................................21
Shanghai ................................................................................................................22

CONCLUSION AND FUTURE RESEARCH..................................................................24
5.1.
5.2.

Port/hinterland interactions and organizational correspondence ...........................24
Overlapping and captive hinterlands .....................................................................25

REFERENCES ...............................................................................................................................26

Vancouver, February 2008

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A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

1. INTRODUCTIONPort competition has been driven by two separate but related developments in the shipping
industry. First, containerization has helped lower transport costs, shorten transport times andimprove schedule reliability and security, and hence has made large-scale global sourcing andproduction possible, stimulating the demand for sea shipping (e.g. Notteboom, 2006; Levinson,2006). Furthermore, as described by, among others, Luo and Grigalunas (2003) and Cullinane andSong (2006), containerization has dramatically increased competition among ports. The intermodal
movement of freight by containers through ports has reduced port-handling costs and increased thereach of markets served from a given port. Whereas a port used to be able to count on an exclusive“hinterland” for freight movements, these hinterlands may now be reached by freight movements
through competing ports. As a result, ports have lost their monopolies over their hinterlands, withport hinterlands increasingly overlapping with one another. As argued by van Klink and van den
Berg (1998), gateway ports are in a unique position to, on the one hand, stimulate intermodaltransport and, on the other hand, use the intermodal systems to enlarge their hinterlands. In thecommercially famous Le Havre-Hamburg range, for instance, major ports vigorously vie with one
another for interior hinterland shipments that have alternative routing possibilities. The second
development has been the devolution of public responsibility in ports through privatization andcommercialization of activities (e.g., Cullinane and Song, 2002; Brooks, 2004). Fleming and Baird(1999) argue that private ports lead more naturally to port competition than public ports.
While both containerization and port commercialization intensify port competition, thedramatically increased cargo movements are certainly stressing ports and their hinterlands’
transportation systems. It has been widely recognized that congestion is acute at many ports aroundthe world, and tremendous efforts have been extended to the resolution of the problem at both thepolicy and research levels (see, e.g., Heaver, 2006; De Borger, et al., 2008; Yuen, et al., 2008). In
comparison, relatively little attention – especially in academic research – has been paid on thehinterland access conditions and their impact on the port and port competition. In a port “transport
supply chain,” users incur delay costs not only at ports, but also at other parts of the chain, andhence overall congestion is dictated by the weakest link (or node). A survey conducted by Maloni
and Jackson (2005) suggests that U.S. port managers’ greatest concern in port capacity expansion
planning is the capacity constraint imposed by local roads. Heaver (2006) further describes how the
shipping developments, including containerization, change the bottleneck of this intermodal system,
which has over time shifted from stevedoring on the ship to the ship/port interface (e.g.,terminal/berth investment, crane and yard productivity) and, more recently, to the port/inlandinterface (e.g., hinterland connection, inland transportation).1
In this paper, we investigate the impact of hinterland access conditions on the port and port
competition. There have been many empirical studies on the productivity and efficiency of port
operations (see, e.g., Turner, et al., 2004, and Cullinane and Song, 2006, for references). For
example, Turner, et al. (2004) collected fourteen years of data on twenty-six container ports inNorth America, used data envelopment analysis to compute the relative productivity measures of
1

See also the earlier work by Jansson and Shneerson (1982).

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the ports, and then regressed the productivities on a number of explanatory factors in an attempt todetermine which factors differentiated the more productive container ports from the less productive
ports. They find that higher measures of port productivity were associated with greater numbers ofClass 1 railroads serving the port, and conclude: “This is clear support for the importance of rail
service quality, perhaps including frequency of service, and rail service competition, to the successof container ports.”2 Several authors further argue that hinterland access is one of the importantfactors that influence the competitiveness of a seaport when it competes with other seaports(Notteboom, 1997; Kreukels and Wever, 1998; Fleming and Baird, 1999). Distinct from thesestudies, this paper attempts to identify the channels through which hinterland access conditions may
affect a port’s competitiveness in an environment of competing ports. This is done largely throughanalysis of a theoretical model.
Our second objective in this paper is to link urban mobility with port competition. Congestion atlarge urban areas has become a major policy issue, and freight movements are a major contributor
to urban congestion (they also create other social costs such as pollution, safety hazards and roaddamage). According to US GAO (2003), from 1993 through 2001 truck traffic on urban highways
in the United States increased more than twice as much as passenger traffic. Given existing urban
highway congestion, this implies that freight traffic was contributing to worsening congestion at afaster rate than passenger traffic. Berechman (2007) further finds that the additional highway traffic
due to a (modest) 6.4% container throughput increase at the Port of New York would induce annual“social costs” that range from $0.66 billion to $1.62 billion – over 60% of which is from congestion
costs (the time-loss due to traffic conditions and drivers’ discomfort, both of which are a function ofincreasing road volume-to-capacity ratios). On the other hand, congested roads could also hinder the
port development. For instance, as to be shown later, the growth at the Ports of Los Angeles andLong Beach has been hindered by road congestion in the greater Los Angeles area. To tackle theurban mobility problem, options such as the investment in road capacity and road pricing have been
actively discussed (debated) at both the policy and research levels.3 Will these options adopted in
the hinterland improve the port’s traffic? and how do they interact with the port’s competitiveness?
These questions have yet been addressed in the literature, but will be investigated in the present
paper.
More specifically, we develop an analytical model in which we treat competition between ports
as competition between alternate intermodal transportation chains: To the extent that a port can be apart of the cheapest, most reliable intermodal transportation chain, it will then out-compete otherports for a customer’s business. In addition to the port, the hinterland access conditions form theother components of the chain. Here, the hinterland access conditions are represented separately bycorridor facilities that are specific for seaport cargo – e.g., the designated rail lines connecting toports such as the Alameda Corridor – and by inland roads that used by both the freight trucks andlocal commuter cars. Basically, a capacity or pricing policy may change the congestion levels at
corridor and inland road facilities, which in turn may affect ports’ output/price decisions and profits.
2

Dresner (2007) has documented the dramatic shift of container traffic from the Port of Baltimore to the Portof Norfolk over the past twenty years. This shift is attributed to a number of factors, including railroad
preference for Norfolk over Baltimore. It was claimed that the railroads prefer to concentrate their business at
ports other than Baltimore for economic reasons. Norfolk Southern, one of the two Class 1 railroads serving
Baltimore, prefers to concentrate its business at its homeport in Norfolk. The other Class 1 railroad, CSX,
prefers to concentrate much of its business in New York. Since most of the container traffic is not destined to
local markets at either Norfolk or Baltimore, the availability of high quality rail services at Norfolk is
conducive to its competitiveness.
3
There is an extensive literature on urban road pricing (see Small and Verhoef, 2007, for a literature survey,
and recent studies by Lindsey, 2007a, 2008, on related issues).
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We shall also discuss, in both the theoretical analysis and case studies, how the presence of
hinterland facility congestion and of port competition affects regions’ strategic policies concerning
hinterland transport facilities.
We find that when ports compete in quantities, an increase in corridor capacity will increaseown port’s output, reduce the rival port’s output, and increase own port’s profit. Our analysis
suggests that the rivalry between ports may, owing to the strategic effect, result in a higher level ofcorridor capacity investment than would be had in the absence of rivalry, such as in an isolated,single port case. This over-investment result might be weakened if the mode of port competition isin prices. Regarding inland road capacity, we find that under quantity competition, an increase inroad capacity in general may or may not increase own port’s output and profit, owing to various
offsetting effects. Essentially, while more road capacity reduces local delays and moderates thenegative impact of own output expansion, it induces greater local commuter traffic and may
moderate the reduction by local commuter traffic in response to a rise in cargo traffic, both of which
reduces own output and profit. We further investigate the impact of inland road pricing on port
competition and find that it may or may not increase own port’s output and profit. Finally, caseexamples for selected ports and regions are discussed to supplement the analytical study.
This paper is related to several studies in the literature. By taking into account the hinterlandtransportation network and assuming shippers minimize the total cost of moving containers fromsources to markets, Luo and Grigalunas (2003) empirically estimate demand for major container
ports. The intermodal transportation network in their model contains rail, highway and international
shipping line sub-networks. They point out that because of the increasing importance of intermodaltransportation, the traditional method for port demand estimation using hinterland delimitation is nolonger valid for container port demand estimation. Ports will serve not only markets in theirvicinity, but also compete for markets in areas far from the port, through the use of high-speed, lowcost rail connections. Their numerical results reveal that vast geographic market areas are serviced
by major ports on both coasts, and hence demonstrate the potential for national competition between
ports. Parola and Sciomachen (2005) present a discrete event simulation modeling approach related
to the logistics chain as a whole in the northwestern Italian port system. They analyze thepotentiality of the system by giving particular attention to the land transport and the modal split reequilibrium with the aim of evaluating a possible future growth of the container flows.4 Lirn, et al.
(2004) use, in part, a survey to explore the importance of various service attributes fortransshipment port selection by global carriers. Lindsey (2007b) discusses various policy
considerations concerning transportation Infrastructure investments, pricing and gateway
competition.
Our analytical model is perhaps most closely related to De Borger, et al. (2008) who study atwo-stage game where each government first decides on the capacities of the port and the hinterland
network – both of which are congestible – so as to maximize its regional welfare, and then theprivate ports engage in a duopolistic pricing subgame. In comparison, the present paper considers
non-congestible ports, which allows us to abstract away the issue of port investment while focusing
on the impact of hinterland access conditions on port competition. An innovation of the paper torepresent the hinterland access conditions by both the corridor facilities and the inland roads. The
separation of inland roads from corridors allows us not only to be more realistic and to delineate theimpacts of different hinterland access conditions, but also to investigate the interaction between
urban road congestion, port-related freight traffic and the ports’ pricing and output behavior. The
4

A similar study is done by Kim, et al. (2007) who consider a multimodal transportation problem ofdetermining the transportation flow quantity (i.e., volume of container cargos) and the transportation mode ineach trade route, with the objective of minimizing the sum of shipping and inland transportation costs. The
modal is then fitted, as a case study, using the container cargo data in Korea.

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 20087

latter investigation is important because a growing large number of urban areas in the world are
suffering road congestion, and solutions such as capacity investment and road pricing have been
actively debated. Moreover, unlike De Borger, et al., we consider both the quantity competition andprice competition and compare the results from the two modes of port competition.5
The paper is organized as follows. Section 2 provides background information for our analyticalmodeling. Section 3 develops analytical model to examine the interaction between urban roadcongestion and port development, as well as to illustrate how hinterland access conditions impact
rivalry between ports. Section 4 discusses three case examples, namely, the Le Havre-Hamburg port
range, gateway ports in Canada, and the Port of Shanghai, and describes the recent policy initiatives
in these regions regarding hinterland/corridor infrastructure expansion and pricing. Finally, Section
5 contains a brief summary and discusses future research.

2. BACKGROUND

Cullinane and Talley (2006) define a port as “a place that provides for the vessel transfer ofcargo and passengers to and from waterways and shores.” They note that a port is a “node” in atransportation system, connected to other ports and inland destinations by spokes or transportationroutes or corridors. As indicated earlier in the introduction, containerization has greatly facilitatedthe just-in-time production and door-to-door transport services; as a consequence, a port becomes apart of the “network.” On the part of inland connections, a seaport and its inland forms anintermodal transportation system in which the port serves both its local and interior (hinterland)
regions. Consider the cargo flow to the hinterland (the reverse flow can be similarly analyzed).
Goods from the rest of the world (imports) are first shipped to a seaport, and then are transported tothe hinterland region by trucking, rail, inland waterway, or a combination of these modes. The
modal split differs greatly between seaports depending on the geographical situation and existing
infrastructure. For example, international cargos shipped to the Port of New York/New Jersey are
distributed in 2005 to the U.S. hinterland by truck (73% of total freight), waterway (36%) or rail
(1%) (Berechman, 2007), whereas the corresponding modal splits for Rotterdam in 2005 are 60%,
30.5% and 9.5% respectively. Similarly, other major gateways,6 such as Antwerp, Hamburg, Los
Angeles, Long Beach, Vancouver, Busan, Shanghai, Hong Kong and Singapore, serve theirrespective hinterlands by intermodal transportation systems.
An obvious consequence of this intermodal system is the network nature of multi-stage
activities and the application of a total distribution cost approach. These imply that all members of
the transport supply chain, including the port, would contribute to the “cost” of cargo shipments.
This cost includes the transit time and its reliability. Hummels (2001) finds that controlling for the
distance, each additional day spent in transport from/to a country reduces the probability that the
U.S. will source from that country by 1.0%-1.5%, while time cost in travel is on average equivalent

5

As to be seen below, there are a few other modelling differences as well, including the linear demand anddelay functions used in De Borger, et al. (2008), as opposed to the more general demand and delay functionsin the present paper.
6
A “gateway” may be defined as a coastal metropolis with port access to both its hinterland and the rest of theworld, which captures a substantial share of total regional and international trade volumes (Berechman, 2007).
8

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to a 16% ad-valorem tariff.7 In addition, firms (shippers or consignees) are required to increase theirinventories so as to prevent the shortage of inputs in production and goods to sell if delivery times
are uncertain due to congestion delays.8
Both the gateway port and its hinterland’s transport system are prone to congestion. Whilst
congestion at major ports has been widely recognized, congestion at connected facilities in thehinterland, such as road, highway, rail and waterway, is less discussed. As discussed earlier, thelatter problem not only exists but also is getting serious. Here are two further road examples. First,
road congestion in Vancouver is a major concern with rising container trucking as a significant
contributor (Lindsey, 2007a, 2008). Truck traffic in the grater Vancouver area is anticipated toincrease by 50% between now and 2021, generated primarily by the port related activities(www.th.gov.bc.ca/gateway/). Second, 80% of containers generated in the direct hinterland of
Shanghai (Shanghai and neighboring cities in Jiangsu and Zhejiang provinces) are transported byland to the Port of Shanghai, which has seriously strained road system around Shanghai (Y. Zhang,2007).
Indeed, hinterland accessibility plays an important role in port growth and competitiveness. We
use the Ports of Los Angeles (LA) and Long Beach (LB) to illustrate this point. Table 1 (first row)reports the correlations between the annual percentage change of the combined LA/LB container
throughput and the annual percentage change in various urban mobility indicators. The Texas
Transportation Institute’s annual Urban Mobility Reports reveal how congestion delays arechanging in U.S. urban areas. To measure travel delays they adopt free-flow conditions at the speed
limit as a baseline, below which congestion is considered “unacceptable.” Since these urban
mobility data take Los Angeles and Long Beach (along with Santa Ana) as a single region, thecontainer throughputs of LA and LB, taken from their respective websites for 1995-2006, are added
together.

Table 1. Correlation of annual container throughput growth (market share, respectively)
and changes in urban area mobility – Los Angeles/Long Beach, 1995-2006
Total delay(personhrs)
LA+LB container
throughput growth
LA+LB container
market share-0.683*(0.029)-0.414(0.235)

Delay perpeak
traveler(personhrs)-0.649*(0.024)-0.353(0.318)Travel time
index

Total
congestion
cost ($)

Congestion
cost perpeak traveler($)-0.716*(0.020)-0.301(0.398)-0.684*(0.029)-0.405(0.246)-0.642*(0.045)-0.367(0.297)

Note: * Significant at the 0.01 level (2-tailed). Standard errors in parentheses.
Table 1 shows that the growth of container throughput at these two ports is negatively, andhighly statistically significant, correlated with all the road congestion/delay measurements –namely, total delay, delay per peak traveler, travel time index, total congestion cost, and congestion
cost per peak traveler – for the Los Angeles/Long Beach/Santa Ana area. This indicates that thegrowth at LA and LB was hindered by urban road congestion. Alternatively, any improvements inurban area mobility also significantly raised container throughput going through the two ports.
7

The average ocean travel time is suggested to be 20 days.
Gausch and Kogan (2001) find that halving inventories could reduce unit production costs by
20%.
8

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To see how hinterland accessibility affects port competitiveness, we further examine thecorrelations between the annual percentage change in market share of LA/LB and the annual
percentage change in urban mobility indicators. For this purpose, the most relevant market may be
the U.S. west-coast port range which consists of six major seaports, namely, Seattle, Tacoma,
Portland, Oakland, Los Angeles, and Long Beach.9 LA and LB are clearly the No. 1 and No. 2
container ports in the range, owing in large part to their having more corridor linkages to U.S.
inland markets than other west-coast ports (Rodrigue, 2007). These six ports accept about 85% of
the U.S.-bound containers from Asia.10
As can be seen from Table 1 (second row), the changes in urban road congestion are found, likethe effect on throughput growth, to be negatively correlated with the changes in LA/LB’s market
share. That is, when the congestion level rises, the combined market share of LA/LB in the westcoast port range falls; similarly, when the congestion level falls, their market share rises.11 For
instance, in 2004-2005 the two ports had to divert a large number of ships to other ports because oftruck and rail congestion (Journal of Commerce, August 8, 2005). These observations suggest thaturban area mobility conditions can affect the competitiveness of a port vis-à-vis other ports. If a port
has good transportation connections and minimum inland congestion, freight may be moved
through this port to destinations previously served exclusively through the less efficient ports.
It is noted that, while the Los Angeles/Long Beach/Santa Ana area has been among the mostcongested urban areas in the U.S., the combined market share of LA/LB in the west-coast port range
has been maintained at around 70% over the years, amid the continuing growth of container traffic
from Asia, especially China as it emerges as a world manufacturing power house. This stability is
due in part to the ability of the region and ports to control any further increase in congestion. For
instance, a “traffic mitigation fee” – $50 per twenty-foot equivalent unit (TEU) or $100 for allcontainers larger than a TEU – is imposed on containers entering or exiting port terminals during
peak hours by PierPASS, a program (a non-profit corporation) developed by the Ports of Long
Beach and Los Angeles to mitigate the problem of congestion on the highways serving the ports. In
addition, containers entering or exiting the ports can use the local highway system or the Alameda
Corridor, a new rail link developed in recent years that eliminates all level crossings between theports and the major rail terminals in central Los Angeles. The fee for the use of the Alameda
Corridor is $18 per TEU. Thus, while congestion in the region remains at a high level, it may not begetting worse relatively to that of competing ports.12

9These ports might also compete with the Canadian west-coast ports, namely, Vancouver and in the future,
Prince Rupert.
10
Due to the strong growth of imports from Asia, congestion has become a major problem for these ports andrespective inland facilities. The ensuing delays have imposed substantial costs on carriers and shippers (see,e.g., Bloomberg News, December 4, 2005).
11
Unlike the effect on throughput growth, however, none of the correlation coefficients are statisticallysignificantly different from zero.
12
As long as the change in congestion level is marginal, shippers and forwarders are reasonably certain about
the congestion they are going to encounter: i.e., the delays will be “expected.” Thus they are able toincorporate the waiting time caused by congestion into their shipping schedules (e.g., assign more time to thatleg of movement during peak hours). Even though the level of congestion is high, shippers and forwarders
may still be willing to use LA/LB, because they are able to follow their schedules by planning ahead of time.
In this case, shippers and forwarders may still achieve a given level of delivery reliability.
10

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3. AN ANALYTICAL MODEL

The above discussion suggests that urban road congestion inhibits the port development but thatat the same, port-related freight contributes to urban road congestion. In this section we develop ananalytical model to examine this interaction, as well as to investigate how hinterland accessconditions influence port competition. A central point is that competition between ports haschanged from competition between individual ports in terms of port charge and service tocompetition between alternate intermodal systems, among which ports form an importantcomponent. Shipping lines, forwarders and shippers would seek the best system: To the extent that aport can be a part of the cheapest, most reliable intermodal transportation chain, it will then outcompete other ports for a customer’s business. This point has been made by Notteboom (2007) who
states, “Port choice has become more a function of network costs and port selection criteria are
related to the entire network, in which the port is just one node.” Further, the issue of improving theintermodal connections in a transportation chain has also been recognized in the policy arena,
including, in the context of port-inland transportation, the adequacy of landside connections to ports(e.g., Australian Government, 2005). This section will further illustrate how such competition
impacts rival ports’ outputs, prices and profits.
3.1.

Basic framework

We consider likely the simplest model structure in which our question – what would be theeffects of hinterland access conditions on the rivalry between ports – can be addressed. There are
two seaports, labeled 1 and 2, that share the same overseas customers and have each a downstream,
congestible transport network to a common hinterland. This set-up follows the one in De Borger, etal. (2008). Located in two separate regions, the two ports are competing with each other in the sensethat their services are substitutes to users. They may be in the same port range – e.g., the ranges ofnorthwest Europe or of the North American west coast – and so regions 1 and 2 could be twocountries (e.g., Antwerp and Rotterdam, or Vancouver and Seattle) or two regions within the same
country (e.g., Rotterdam and Amsterdam, or Bremen and Hamburg). Users of the ports and relatedtransport networks include shipping lines, shippers, consignees, transport companies (e.g., railroads,
trucking companies), third party logistics operators, freight forwarders, or some combination ofthese groups. For simplicity we shall just use “shipping lines” to represent the users.
Each port charges shipping lines pi per cargo unit (e.g., TEU) for port use, and faces demand

X i ( ρ1 , ρ 2 ) , where ρ i represents the generalized (total) user cost if shipping lines use port i for
cargo shipment, i = 1,2 . This “full price” faced by shipping lines is given by:ρ i = pi + DCi ( K Ci ) + DLi (Vi , K Li ) + t i ,i = 1,2(1)

where DCi and DLi denote the delay costs occurred at the corridor and local road delivery
respectively, and t i the road toll.
Four important features about the above specification are worth noting. First, unlike the set-up
in De Borger, et al. (2008), we consider non-congestible ports. This simplification allows us toabstract away the issue of port investment while focusing on the impact of hinterland access

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conditions on port competition. Second, port charge pi is an important element of the full price. For
instance, in analyzing waterborne containerized imports from Asia to the North American westcoast ports, Leachman (2008) finds that imposition of container fees without compensating
improvements in container transit times would result in significant traffic diversion: Even a modest$30 per TEU fee assessed on imports at the San Pedro Bay Ports would result in approximately a
6% in loss in both total and trans-loaded import traffic.13
Third, in formulation (1) the hinterland access conditions are represented by: (a) transportfacilities that are specific for the seaport cargo; and (b) those facilities that are subject to joint use
with traffic other than the seaport cargo. These, then, are further operationalized with corridor androad conditions respectively. In practice, cargo passing through a port may be shipped out by rail,
inland waterway, road, or a combination of these modes. The modal split differs greatly between
seaports depending on the geographical situation and existing infrastructure. For example, in 2006
about 60% of Rotterdam’s containers were shipped out by truck, while this percentage was 75% for
the Port of New York/New Jersey. In general, rail and inland waterway are used for long-haulfreight transport (e.g., greater than 500km in the North American context) whereas trucks for final
delivery. Thus if a shipment is for local port market, it would use road transport. On the other hand,
if the shipment is for the hinterland, it would use a combination of modes: first with rail or inland
waterway for the corridor leg and then by trucks for the final delivery. In either case, shipping lines
may, in their inland transportation, encounter potential congestion, and hence delays, at both thecorridors (rail, inland waterway) and local roads. Corridors may also be considered as inland
terminals serviced by designated trains – The Alameda Corridor in Los Angeles mentioned above
and the new rail corridor in The Netherlands are such examples.
Furthermore, compared to major rail/inland waterway corridors, the road would have much
more local traffic – i.e., traffic other than the seaport cargo – such as local commuters. To capture
these distinct features, we have in (1) considered that the corridor congestion is affected only bycorridor capacity, denoted K Ci , whilst the road congestion is affected by both road capacity,
denoted K Li , and total road traffic volume Vi . In the context of Alameda Corridor mentioned in
Section 2, therefore, investment in this new rail link represents an increase in corridor capacity K Ci .
While the Alameda Corridor diverts many containers to designated rail, there remains a significant
portion that leaves the Ports of Los Angeles and Long Beach by truck, especially freight destinedfor the local market. Such traffic (as well as the traffic of final delivery in hinterland) may
encounter road delays which will, as specified in (1), depend on both road capacity K Li and totalroad traffic Vi .
Fourth, we further specify that the corridor delay cost falls as the corridor capacity ( K Ci )'increases, i.e., DCi(⋅) < 0 . Since the road is used by both cargo shipments X i and local

commuters, we have Vi = X i + Yi , with Yi denoting local traffic volume. The road delay costsatisfies:

∂DLi
> 0,
∂Vi

∂DLi
< 0,
∂K Li

∂ 2 DLi
∂Vi

2

≥ 0,

∂ 2 DLi≤ 0.
∂Vi ∂K Li(2)

13

See also Luo and Grigalunas (2003) who provide an estimate of the impact on port demand and inter-port
competition due to hypothetical changes in port use fees at selected ports.

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Thus, increasing traffic volume ( Vi ) will increase road congestion while adding capacity ( K Li ) will
reduce road congestion, and the effects are more pronounced when there is more congestion.
Assumption (2) is quite general and holds for the two widely used delay functions: a “linear” delay
function in that D Li is a linear function of the volume-capacity ratio (e.g., De Borger and Van
Dender, 2006; De Borger, et al., 2005, 2007, 2008) or D (V , K ) = aV /( K ( K − V )) with a being a
positive parameter, which is estimated from steady-state queuing theory (see, e.g., Lave and
DeSalvo, 1968).14
We now turn attention to local road traffic, Yi : It depends on a “full price” ρ Li , with theinverse demand function being ρ Li (Yi ) . Here, the full price is the sum of the road toll andcongestion cost:ρ Li (Yi ) = t i + DLi ( X i + Yi , K Li ) ,i = 1,2(3)Note that in the above full-price formulations (1) and (3), it has been implicitly assumed that a
uniform toll has imposed on trucks and local vehicles. Further, equation (3) implicitly determines
Yi as a function of ( t i , X i , K Li ): Yi = Yi* (t i , X i , K Li ) . It is straightforward, using (2) andρ ' (⋅) < 0 (downward-sloping demand), to show:
∂Yi*
1
= '
< 0,
∂t i
ρ Li − (∂DLi / ∂Vi )∂Yi*∂DLi / ∂Vi= '<0∂X i ρ Li − (∂DLi / ∂Vi )

∂Vi
∂Y *
ρ Li'
= 1+ i = '
> 0,
∂X i
∂X i ρ Li − (∂DLi / ∂Vi )∂Yi*∂DLi / ∂K Li= '>0∂K Li ρ Li − (∂DLi / ∂Vi )(4)
for i = 1,2 . Inequalities (4) show that (a) an increase in road toll will reduce the local traffic; (b) an
increase in cargo traffic will decrease the local traffic; (c) an increase in road capacity will increase
the local traffic; and (d) an increase in cargo traffic will, while reducing the local traffic, increase
overall road traffic. While effects (a)-(c) are as expected, effect (d) is somewhat less obvious.
As indicated above, each port’s demand depends on both its full price ρ i and the rival port’s
full price ρ j :X 1 = X 1 ( ρ1 , ρ 2 ) ,X 2 = X 2 ( ρ1 , ρ 2 ) .

(5)

Solving the two equations in (5) for ρ1 and ρ 2 yields:

ρ1 = ρ1 ( X 1 , X 2 ) ,ρ2 = ρ2 (X1, X 2 ) .

(6)

Using (1) and Yi = Yi * (t i , X i , K Li ) , equations (6) can be written as, for i = 1,2 :pi = ρ i ( X 1 , X 2 ) − DCi ( K Ci ) − DLi (Vi , K Li ) − t i ≡ pi ( X 1 , X 2 ; K Ci , K Li , t i ) .
14(7)

Queuing at junctions is the dominant source of delay in many urban areas (Santos, 2004).

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 200813

Consequently, each port’s profit may be expressed as:

π i = pi ( X 1 , X 2 ; K Ci , K Li , t i ) ⋅ X i = π i ( X 1 , X 2 ; K Ci , K Li , t i ) ,i = 1,2(8)

where the port operating costs are, for simplicity, assumed to be zero.15 This assumption allows us
to focus on potential channels linking hinterland accessibility with port competition through thedemand side rather than the cost side. In effect, there has been an extensive empirical literature on
the cost efficiency of port operations, some of which associated inland transport connections withthe port operating costs. For example, Turner, et al. (2004) find that the best way to become a lowcost port operation appears to maximize rail service into ports. To the extent that improvement inhinterland access conditions reduces per-unit port operating costs which in turn enhances the port’s
competitiveness vis-à-vis its rival, the demand-side linkage is less obvious. As is to be seen below,
however, some of the mechanisms operating through the costs also appear through the demand-side
interactions. Thus the zero-cost assumption is for simplicity of modeling and won’t really affect thebasic insights of our analysis.
We consider situations where the ports make their strategic decisions taking both the corridor
capacity ( K Ci ) and the road capacity and toll ( K Li , t i ) as given. Infrastructure investments incorridors and roads are long lasting and typically irreversible. Similarly, whether to impose roadpricing, and if so, by which scheme, take a long time to decide for political and implementation
reasons, and once determined, it is hard to reverse. That is, investments in inland capacity and roadpricing are usually longer term decisions as compared to the ports’ decisions on their charges orquantities. In other words, the ports compete with each other in price or quantity taking K Ci , K Li
and t i as given.
Furthermore, as reflected in the above full-price approach, the two ports compete as parts ofintermodal transport chains. The success of each chain is recognized to be dependent on each of theparts working to provide an efficient, reliable system, which in turn depends on each region’s
policies on inland infrastructure pricing and investment and on the charge of its port.16 In what
follows, we shall consider that the port and its hinterland belong to a single region which ensures
their coordination in their decisions. One motivation for this is that to maintain theircompetitiveness and provide better service to their consumers, various forms of collaboration havebecome more popular between ports and inland transportation. For example, many ports use rail
connections as a strategic tool to penetrate new markets and retain dominance over existing
hinterlands (Debrie, 2004). Major European port operators, such as Eurogate and Hamburger Hafen,
have been participating in rail services, whereas major stevedores in Australia, namely, P&O Portsand Patrick Co., have been involved in significant restructuring to control landside chains (Debrieand Gouvernal, 2006). We shall discuss the issue of port and hinterland being separate regions in
Section 5.

15

Since there is no congestion at the port, port capital cost is not relevant in this case. Further, note that our
results will continue to hold for constant (but non-zero) operating costs.
16
More generally, Carbone and De Martino (2003) place such an environment in the context of supply chain
management. The contribution of a port to a supply chain (to which it belongs) depends on its infrastructure,connectivity, and ability to add value; for example by providing punctual and frequent service for shippers, bydisseminating important information (e.g., product location) to other members of the supply chain, and byproviding a secure environment for the cargo. Rivalry between intermodal transport chains has also been
examined in Zhang, et al. (2007) in the context of the air cargo market.
14

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

3.2.

Quantity competition

Consider first that the two ports compete with each other by choosing quantities to maximize
profits. In this case, the Cournot-Nash equilibrium is characterized by the first-order conditions:

π 11 ( X 1 , X 2 ; K C1 , K L1 , t1 ) = 0 ,π 22 ( X 1 , X 2 ; K C 2 , K L 2 , t 2 ) = 0(9)where the subscripts denote partial derivatives ( π 11 ≡ ∂π 1 / ∂X 1 , etc.). Following standard practicein models of quantity competition, we assume the quantities are “strategic substitutes” (e.g., Bulow,
et al., 1985; Tirole, 1988). In addition, regularity conditions are imposed so that the equilibrium
exists, is unique and stable; consequently, comparative static exercises conducted below aremeaningful.
We begin with the first comparative-static result concerning the effects of corridor capacity
K Ci (all the proofs are omitted to save space, but are available upon request from the author):
Proposition 1: Under quantity competition, an increase in corridor capacity will: (a) increase own
port’s output, (b) reduce the rival port’s output, and (c) increase own port’s profit.
The rationale for Proposition 1 may be explained as follows. Note that the condition ofquantities being “strategic substitutes” ensures a downward-sloping output “reaction function” foreach port, which is defined by each equation in (9). An increase in the corridor capacity by (say)region 1 will increase its port’s marginal profit ( ∂π 11 / ∂K C1 = − DC' 1 > 0 ). With the rising marginal
profit port 1’s reaction function shifts outward, i.e., it behaves more aggressively and produces
more output for each output choice of its rival; whilst port 2’s reaction function stays unchanged.
This moves the equilibrium outputs ( X 1* , X 2* ) along port 2’s reaction function, thereby increasing

X 1* and decreasing X 2* .
Furthermore, the impact on port 1’s (equilibrium) profit can be split into two parts:

∂X 2*
∂π 1
∂π 1*
.
= π 21+∂K C1∂K C1 ∂K C1(10)The second term on the right-hand side (RHS) of (11) represents a “direct effect” of the shift in port
1’s profit function, whereas the first term an “indirect effect” of the shift in its marginal profit,
which in turn will change the equilibrium. Whilst the term ∂π 1 / ∂K C1 = − X 1 DC' 1 > 0 captures a
direct advantage of corridor capacity investment by reducing corridor delay, the indirect effect is
unique to competing ports. Since this effect works by indirectly influencing the behavior of the rival
port – port 2 becomes less aggressive by committing to a smaller quantity, which in turn improves
own profit as the outputs are substitutes – it is often referred to as the “strategic effect.” Observethat this indirect, strategic effect augments the direct effect. Our analysis therefore suggests that therivalry between multiple ports may, owing to the strategic effect, result in a higher level of corridor
capacity investment than would be had in the absence of rivalry, such as in an isolated, single portcase.
We now turn to examination of the comparative-static effects of road capacity and toll.
A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

15

Proposition 2: Under quantity competition, an increase in inland road capacity may or may notincrease own port’s output and profit, owing to various offsetting effects. Similarly, inland roadpricing may or may not increase own port’s output and profit.
The intuition behind Proposition 2 is as follows. As indicated above, the output effect depends
critically on the impact of an increase in capacity on own marginal profit. In the present roadcapacity case and for port 1, this impact is, by (8) and (7),∂D L1 ∂ 2V1∂V1 ∂ 2 DL1∂DL1 ∂DL1 ∂Y1*
∂π 11
− X1
− X1
−
=−
∂V1 ∂X 1∂K L1∂X 1 ∂V1∂K L1∂K L1 ∂V1 ∂K L1
∂K L1

(11)

The first term on the RHS of (11) is positive by (2) – more road capacity reduces local delays – but
the second term is negative by (2) and (4), as more capacity induces greater local traffic. The third
term is non-negative given by (4) that ∂V1 / ∂X 1 > 0 and ∂ 2 DL1 / ∂V1∂K L1 ≤ 0 , indicating that anincrease in capacity would moderate the negative impact of own output expansion. The fourth (andfinal) term in (11) has the same sign as ∂ 2V1 / ∂X 1∂K L1 , which can be either positive or negative
for the general functional forms we are considering here, but is nevertheless strictly positive forlinear local demand ρ L1 (Y1 ) and delay cost D L1 (⋅) . In the linear case, essentially more capacity
will moderate the reduction by local traffic in response to a rise in cargo traffic. Taken together, theabove discussion shows that the sign of ∂π 11 / ∂K L1 is generally undetermined. As a consequence,
port 1’s reaction function can shift outward or inward, leading, respectively, to an expansion or
reduction of its (equilibrium) output.
A related consequence of the undetermined marginal-profit effect is that the output of port 2
may contract or expand following an increase in region 1’s road capacity. Thus, the strategic effectof road capacity investment can be positive or negative on port 1’s profit. As for the “direct” effect,
it is given by:∂DL1 ∂Y1*
∂DL1
∂π 1
− X1
= −X1
∂V1 ∂K L1
∂K L1
∂K L1

(12)

As discussed in connection with (11), the first-term on the RHS of (12) is positive but the second
term is negative. In words, the benefit from more road capacity and hence less congestion is diluted
by induced local traffic. As a result, the direct effect on own profit can, similar to the strategic
effect, be positive or negative.
Finally, the impact of road toll on output and profit can be similarly discussed. For instance, thedirect effect of tolls on own profit is given by:∂DL1 ∂Y1*∂π 1.
= −X1 − X1
∂V1 ∂t1∂t1(13)

The first term on the RHS of (13) shows the obvious negative effect of tolls on the generalized
cost of shipments going through port 1. On the other hand, an increase in road toll reduces local
vehicle traffic which in turn will create more road space for freight traffic, leading to higher runningspeeds and reliability for trucks. Captured by the second term which is, by (2) and (4), positive, thislatter effect benefits shippers and improves port 1’s profit. The net impact on own profit is, at thisgeneral level, undetermined. Thus, road pricing at a region’s roads may or may not benefit the16

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

region’s port. On the other hand, if trucks have a much higher value of travel time than local
commuting cars (US DOT, 2003), it might be possible that trucks overall benefit from a congestion
toll, thus benefiting the port.17
3.3.

Price competition and related issues

The previous subsection considers quantity competition. What if the mode of port competition
is in prices (rather than quantities)? In this case the profit function for each port is specified as:Π i = pi X i ( ρ1 , ρ 2 ) = Π i ( p1 , p 2 ; K C1 , K L1 , t1 , K C 2 , K L 2 , t 2 ) ,i = 1,2 (14)where the second equality follows from the use of (1) and Yi = Yi * (t i , X i , K Li ) , and the profit is
written as a function of prices (rather than quantities). Treating capacities and tolls as parameters,
each port chooses its price to maximize profit, and the resulting Bertrand-Nash equilibrium ischaracterized by the first-order conditions:

Π ii ( p1 , p 2 ; K C1 , K L1 , t1 , K C 2 , K L 2 , t 2 )(≡ ∂Π i / ∂pi ) = 0 ,i = 1,2(15)

Following standard practice in models of price competition, strategy variables p1 , p 2 are assumed
to be “strategic complements” (e.g., Bulow, et al., 1985; Tirole, 1988) and regularity conditions are
imposed for the existence, uniqueness and stability of the equilibrium.
To highlight the main implications of price competition, we shall below focus just on thecorridor transport part so that (15) become Π ii ( p1 , p 2 ; K C1 , K C 2 ) = 0 (i.e., road transport is
suppressed). The impact of an increase in corridor capacity on the equilibrium prices, output andprofit is summarized in the following result:
Proposition 3: Under price competition, an increase in corridor capacity will increase own port’s
price and reduce the rival port’s price. Furthermore, it has an undetermined impact on own port’s
output, the rival port’s output and own port’s profit, owing to various offsetting effects.
Proposition 3 indicates that an increase in the corridor capacity of region 1 will raise port 1’s
price while inducing port 2 to cut its price. These price effects can be explained as follows. Notethat the prices being “strategic complements” ensures two upward-sloping reaction functions,defined by (15), in the p1 - p 2 dimension. An increase in the corridor capacity by region 1 will shift
its port’s reaction function outward, i.e., it enables port 1 to charge a higher price for each pricechosen by the competing port. Unlike the case of quantity competition (where port 2’s reaction
function stays unchanged) however, in this case port 2’s reaction function shifts as well, and it shifts
downward. As a result, at the new equilibrium, the price of port 1 rises whilst the price of port 2
falls.

17

Here we have considered a flat toll, as opposed to a variable (peak-off peak) toll which is more effective incombating road congestion. Recent research in the U.S. has shown that truckers have little scope foradaptation to variable tolls because of rigid delivery schedules imposed by shippers and consignees (HolguinVeras, 2006). Thus consideration of a variable toll might lead to a similar result, that is, congestion toll at aregion’s roads may or may not benefit the region’s port.

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 200817

Thus, an increase in corridor capacity yields two offsetting effects on own profit: it reduces port
1’s profit owing to the price drop at port 2 and the ensuing demand shift away from port 1 (recall
the two ports produce substitutes) – a negative strategic effect. Caring for its port’s profit, region 1
therefore has a strategic motive to invest in less road capacity. On the other hand, capacity
investment improves port 1’s profit via a reduction in its hinterland’s road delays – a positive direct
effect. The net impact on own profit is general undetermined. Finally, The impact on port 1’s(equilibrium) output is given as follows:∂X 1 ∂p 2*∂X 1 '∂X 1* ∂X 1 ( ρ1* , ρ 2* ) ∂X 1 ∂p1*
DC1 +
+
=
=
∂ρ 2 ∂K C1∂ρ1 ∂K C1 ∂ρ1
∂K C1
∂K C1

(16)

While the first and third terms on the RHS of (16) are negative – an increase in corridor capacity
reduces own port’s output via the price effects discussed above – the second term represents the
positive impact of capacity via a reduction in region 1’s corridor delay. As a result, the over impact
on own output is undetermined. The impact on the rival port’s output can be similarly seen,∂X 2 ∂p 2*∂X 2 '∂X 2* ∂X 2 ∂p1*
DC1 +
+
=
∂ρ 2 ∂K C1∂K C1 ∂ρ1 ∂K C1 ∂ρ1(17)with the first and third terms on the RHS of (17) being positive but the second term being negative.
The above analysis suggests that the motive for investing corridor capacity so as to improving
own port’s competitiveness (in terms of port throughput and profit) may be weakened if the natureof port competition is in prices rather than quantities. Which model of competition is “correct” forports? In general, this depends in large part on production technology of an industry underconsideration (here, the port industry). In Cournot competition, firms (here, ports) commit toquantities, and prices then adjust to clear the market implying the industry is flexible in priceadjustments, even in the short run. On the other hand, in Bertrand competition, capacity is unlimited
or easily adjusted in the short run. In reality, some industries behave like Bertrand and others
Cournot. Thus, which model of oligopoly is applicable to a particular industry might be of anempirical question. While there is an extensive literature on the empirical evidence of the relevanceof certain oligopoly models to a particular industry (see, e.g., Bresnahan, 1989; Brander and Zhang,1990), no such study has been conducted for ports. Such study would be helpful in assessing theimpact of hinterland access conditions in the context of port competition.
In the above analysis of price competition, there are no capacity constraints at the ports. This isconsistent with our formulation of the ports being non-congestible (which allows us to abstract
away from considering port investment and focus on hinterland access conditions). With capacity
constraints, a reasonable formulation of port competition, given in De Borger, et al. (2008), is a
two-stage game where ports first invest in port capacity and then compete over prices. Note that thetiming recognizes that investment in port capacity takes time and cannot be changed quickly
relative to the ease and rapidity with which prices can be adjusted. In the second stage, the Bertrand
equilibrium, given port capacity, has the ports pricing such that they produce to capacity (or nearcapacity if the port delay-cost function is convex). Taking the pricing behavior into account, theequilibrium of the two-stage game involves, under certain rationing and other conditions, each port
investing in capacity equal to its Cournot quantity. This is the Kreps and Scheinkrman (1983) resultthat “quantity precommitment and Bertrand competition yield Cournot competition.” Oneinterpretation, then, of our quantity-competition model is that is a reduced form of the more
complicated two-stage (capacity; price) game in which hinterland access conditions (corridor androad capacities, road congestion tolls) are treated as exogenous factors.
18

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

4. CASE EXAMPLESIn this section we discuss three case examples, namely, the Le Havre-Hamburg port range,
major gateway ports in Canada, and the Port of Shanghai, and describe the recent policy initiatives
in these regions regarding hinterland/corridor infrastructure expansion and pricing.
4.1.

The Le Havre-Hamburg port range

The Le Havre-Hamburg (LHH) port range constitutes a number of ports in France, Belgium,
The Netherlands, and Germany. Among these ports, Rotterdam, Hamburg, Antwerp, Bremen, Le
Havre and Zeebrugge are ranked No. 1 to No. 6 container ports, all of which handled more than 1
million TEUs in 2006 (Table 2). The other three major ports in this range, namely, Amsterdam,
Dunkirk and Ghent, are relatively minor in container business, handling container throughput
306,000, 205,000 and 39,000 TEUs, respectively, in 2006. Like the west-coast port range in North
America, the LHH range has seen a rapid growth in container traffic due in large part to the Asia
economic booms (and also to the large increase of imports from the new Central Europe membersof the EU). As can be seen from Table 2, the container throughput for the top six ports as a wholehas an 89% growth between 1985 and 1995, and a 159% growth between 1995 and 2006.
Table 2. Container throughput for Le Havre-Hamburg port range, selected years(1,000 TEU)

Rotterdam
Hamburg
Antwerp
BremenLe Havre
Zeebrugge
Total

1985

1995

2006

2,715
1,159
1,243
998
566
218
6,899

4,787
2,890
2,329
1,524
970
528
13,028

9,690
8,862
7,018
4,450
2,121
1,653
33,794GrowthGrowth(1995-85) (2006-95)
76%
102%
149%
207%
87%
201%
53%
192%
71%
119%
142%
213%
89%
159%

Source: Calculation based on the Port of Rotterdam – Le Havre-Hamburg range container
throughput time series data.
Within the Le Havre-Hamburg range there is strong competition among the ports. The
competitive dynamics may be approximated by the changes in market share of each port over time.
With a comparatively low tidal range, quick and easy access both to the North Sea and to the
productive Rhine hinterland, Rotterdam has been the leading container port in Europe.18 However,this position has gradually been eroded over time, especially during the past decade (Table 2):18

Its two main rivals, Antwerp and Hamburg, are inland ports. In order to reach the ports from sea, vessels
have to sail up the river before arriving at the upstream ports, incurring higher operating and time costs thanreaching Rotterdam which sits right on the coastal line. The 2003 data shows that the deepsea call efficiency
ratios (TEUs handled as a percentage of two-way capacity of vessel called at port) of Antwerp and Hamburg
were 27.7 and 22.7 respectively, while this ratio was about 18.5 for Rotterdam (Notteboom, 2006) suggestingthat both Antwerp and Hamburg have to be more capable of handling sudden arrival of large container
volumes.

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

19

Whilst Rotterdam grew 102% between 1995 and 2006, this rate is below the regional average of
159%, and only half of the rates enjoyed by its two main rivals, Hamburg and Antwerp. As a result,both Hamburg and Antwerp (and lately, Bremen) have gained market share at the expense ofRotterdam, and Rotterdam has lost its dominant position in container market share.19 Also note that
Hamburg has become the second largest container port in this range since 1987 (used to be No. 3
behind Antwerp) and that Zeebrugges has, like Hamburg, enjoyed a very rapid growth, albeit
starting from a low level of container traffic.
Fleming and Baird (1999) note that there is a long history in port rivalries on the LHH port
range. According to the authors (p. 387):“The 19th century heavy industrialization of north-western Europe brought economic andcommercial linkages that were stronger than the political divisions, so that, from 1870 to theoutbreak of World War I, French, Belgian, Dutch and German ports were vying for the hugely
productive industrial hinterlands of Ruhr and Rhine valleys, Lorraine, Luxembourg, the Saar,
The Sambre-Meuse valley of Belgium and the coal mining districts of northeastern France, allpart of what geographers labeled the heavy industrial triangle with apexes in the French Nord,the German Ruhr and the French (but German from 1871 to 1918) Lorraine. Rivalries for thecommerce of this region were fierce and governments were very much involved, using various
strategies to support their ports. The Dutch, for over a century, blocked Antwerp’s easy accessto the Rhine. The Belgians retaliated by building the ‘iron Rhine,’ a very early rail connection
from Antwerp to the Rhine and Ruhr. In the era of economic nationalism between World Wars I
and II the Germans favored Bremen and Hamburg, setting artificially low rail freight rates tointerior industrial regions. The French, after World War II, used the same rail rate strategy tofavor Dunkerque on shipments to and from the Lorraine metallurgical district.”
Fleming and Baird (1999) further describe more recent policy developments (pp. 387-388):“Governments are still involved and each container port tends to complain about their rivals’‘unfair’ state subsidies. Actually, unlike UK ports, all the main continental container ports regard
provision and maintenance of access channels as essential infrastructure to be funded by the state.
… Although the port authorities both in Antwerp and Rotterdam take pride in their ‘autonomies’ inport management, there is no doubt that Belgian national interests and Dutch national interests arevery much entwined in the fortunes of these two huge ports. This is inescapable and it explains, inlarge part, the determination of each port to hold on to ‘market share’ and to re-equip for new
business. … German ports may have lost the national subsidies and preferential treatment of the late1980’s but the Lander-level governments still have a strong interest and influence in Bremen’s andHamburg’s port activities.” As a result, “Throughout the entire Le Havre-Hamburg range there ismuch complaining recently about ‘distortions of competition,’ each port suggesting that its rivals inadjoining states are using the public sector to give unfair competitive advantage.” (p. 388).
Like the North American west-coast ports, the LHH ports recently encountered high pressure ofport and inland congestion. Facing the dramatic container traffic growth of the last two decades, thedense and intricate network of river, canal, rail and highway developed post World War II began tochoke. Antwerp, Rotterdam and Hamburg have expanded, or will expand, their port capacities, in
response to the port congestion problem (Quinn, 2002). On the hinterland accessibility, we first notethat the modal splits among road, waterway/barge and rail for the three main competitors –Rotterdam, Antwerp, and Hamburg – are, in 2005, 60% / 30.5% / 9.5% respectively for Rotterdam,
60% / 32.4% / 7.6% for Antwerp, and 66.1% / 13.6% / 20.3% for Hamburg. Thus, for the three19

It is notable that Rotterdam has increased its transhipment function in recent years: Its relative shares ofcontainers accessing hinterland and transhipped are, respectively, 83.4% and 16.6% in 2002, but 76.1% and23.9% in 2006.

20

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

ports, road is the dominant mode of transport to access hinterland. Both Antwerp and Hamburg
have been trying to promote hinterland access modes other than road. Antwerp completed theAntwerp Intermodal Network project at the end of 2006. This project aims to shift transport fromroad to rail and barge over distances less than 250 km, so that the pressure on road traffic can berelieved. The increase in barge volume attributed to this project is around 249,761 TEUs in 2006.
At a wider level, as a measure to smooth the intermodal connectivity the European Community
recently proposed a standardization and harmonization program concerning intermodal loading
units: While the standardized characteristics of containers (e.g., TEU) were usually used for sea
mode, swap bodies were usually used for land modes. This program is estimated to provide
European industry and transporters with efficiency gains, and a reduction of up to 2% in logistics
costs (European Commission, 2004). Another example is the Trans-Europe Networks (TENs)
project, which aims to promote competitiveness of and cohesion within Europe by improving
transportation infrastructure of different regions to a desired level and enhancing urban accessibility(Vickerman, 2007). These initiatives may help enhance the competitiveness of LHH ports vis-à-vis,
for example, Mediterranean ports.20
4.2.

CanadaVancouver and Montreal are Canada’s two major maritime freight gateways, ranked No. 1 andNo. 2 in container throughput in the country. Both cities have heavy truck volumes, including
freight traffic to and from the U.S.; and nationwide, freight shipments are concentrated along a few
widely separated corridors so that substitution possibilities are limited. As discussed in Lindsey(2007a, 2008), both urban areas (and also Toronto) have serious and growing congestion, and as
gateway cities, both have a strong incentive to facilitate freight transport. The master plan of thecity of Montreal sets out several priorities for transportation including: facilitating freight
movements to maintain the city’s competitive position as a freight hub while limiting theenvironmental impact of road freight transport, upgrading selected highways and building new ones
(Lindsey, 2008).
Now consider Vancouver, British Columbia. As Canada’s largest container port, its container
throughput has grown at an annual rate of 12% since 1980 – the corresponding figure for Montreal
is 6% – which is also faster than the growth rate of other U.S. west-coast ports. Asian countries areagain the driving force for Vancouver’s container growth, with China accounting for 62% of the
Asian share in 2006. Despite several major expansions, congestion is still a major concern, both at
the port and at the local roads. The latter is caused by trucks moving freight between terminals andaround the region. It is also caused by local consumption of these containers: about 20% of
container volumes moving through the Port of Vancouver is local traffic and thus relies on trucks
for final delivery. The rapidly growing truck traffic contributes to congestion delays that not only
impede passenger transport but also disrupt freight supply chains. The British Columbia Trucking
Association has estimated the cost of congestion to freight movements in the grater Vancouver
regional district (GVRD) as C$500 million a year (Lindsey, 2008).
Container traffic in Vancouver is expected to triple by 2020 despite the opening of the newcontainer facilities at the port of Prince Rupert north of Vancouver. The current Vancouver’s shareof the North American west-coast ports – Vancouver, Seattle, Tacoma, Portland, Oakland, Los
20

Heaver (2006) notes that the advent of same-day of the week liner services has sharpened the competition
among ports on a route. For example, a line may substitute a port on one coast for a port on another if the
profit contribution to a vessels’ route is enhanced by substituting one for the other within the cycle time
available under the constraint of same-day service.

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 200821

Angeles, and Long Beach – is 8.5% but the goal is to reach 12% share by 2020. Congested port
terminals and roads could hinder such development. For instance, while a passenger could choose
between various means of transport (and different times of the day) for his/her travel, goods
sometimes could only be delivered by roads based on a tight schedule. Since Vancouver is the main
gateway to Canada, it needs to develop and maintain an efficient road network.
As a result of increasing port and road congestion, governments and port operators have been
looking for solutions, which include capacity expansion and congestion pricing. In early 2006 theprovince of British Columbia embarked on an ambitious Gateway Program administered by the
Ministry of Transportation in consultation with TransLink (the Greater Vancouver Transportation
Authority, which has authority for roads and public transportation in the GVRD, as well as
responsibility for long-range transportation and land use planning) and local municipalities. The
Gateway Program includes a set of major transport infrastructure projects primarily for expanding
capacity at the port and related rail and road facilities in the province. The centerpiece is the Port
Mann/Highway 1 Project to twin the Port Mann Bridge crossing the Fraser River, and toll the Port
Mann Bridge. The tolling is intended to facilitate freight traffic by reducing non-commercial vehicle
traffic, and it is hoped that it will become a part of a comprehensive regional approach to roadpricing. The Program treads a fine line between the goals of accommodating freight transport andimproving competitiveness of Vancouver vis-à-vis other gateway ports, and reducing congestionand emissions. The federal government’s Asia-Pacific Gateway and Corridor Initiative, launched in
October 2006, is providing additional funds.21.
4.3.

Shanghai22

The Port of Shanghai has enjoyed a 30-40% annual growth rate in containers handled for over a
decade, rising to No. 2 container port in the world. Its container volume is largely driven byinternational trade as the export/import contributes nearly 90% to the total container throughput inShanghai. About 87% of containers handled are generated in the hinterland of Shanghai, with therest 13% being transshipment.
An important hinterland for Shanghai is the west-to-east Yangtze River, the so-called golden
waterway. The Yangtze River is a natural corridor that links the interior regions of China to the
Pacific coast, and Shanghai is used as the gateway for these interior regions to trade with the rest of
the world. Apart from a strong direct hinterland in the Yangtze River Delta, there is a vast indirect
hinterland in the middle and upper reaches of the Yangtze River that will drive future growth inShanghai. The feeder fleet used in the Yangtze River has largely been outdated, however. In 2003,
there were around 2,000 shipping companies operating more than 68,000 vessels in the trunk of the
Yangtze River. These vessels are built by different shipyards without a unified standard. In fact,
there are more than 300 types of different vessels operating in the river and most of these vessels
have small tonnage, low speed and poor operating efficiency. The outdated fleet caused inefficiency
in the operation of port facilities, as much newer facilities built to handle modern container ships are
ill equipped to operate with ships of old and different types. The passing capacity of the ship lock in
the Three Gorges had also been severely limited as the ship lock had to deal with many vessels ofdifferent sizes.
In the national strategy of developing mid- and western China, the development of the watertransportation system along the Yangtze River received a high priority. To improve the efficiency of21
22

For more information about the two programs, see www.th.gov.bc.ca/gateway/ and www.apgci.gc.ca.
This subsection is based largely on Y. Zhang (2007).

22

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

the water transportation along the golden waterway, China Ministry of Communication has
developed plans for standardization of river vessels. At the end of 2003, the new standard oncontainer ship and truck ro/ro ship was announced. The new standards on other types of rivervessels were announced in 2004. It is planned that standardization of river vessels will be carriedout in two stages (in two five-year plans) and by 2020 the standardization rate should reach 90% forriver vessels navigating in the trunk of Yangtze River.
Another plan to improve gateway operations in the Port of Shanghai is to establish river-coast
direct shipping route from inland ports in the Yangtze River to the Yangshan deepwater port in East
China Sea – which is the newest container terminal of the Port of Shanghai – to avoid “doubletransshipping.”23 Indeed, in May 2006, the first express route from Wuhan, a major city east of
Shanghai, to Yangshan was open so that it now takes two days for the containers generated around
Wuhan to arrive at the Yangshan port for further transshipping to Europe. Without the river-coast
direct shipping, it would take 5 days. As the number of containers handled in Wuhan in recent years
has grown at 30% annually, establishment of this express route would significantly enhance theeffectiveness of Shanghai as the gateway for the regions in the middle reaches of the Yangtze River.
In 2006, construction of the first special river-coast direct shipping vessel, the so-called Yangshanclass container ship, started in Shanghai. The Yangshan-class ship has a capacity of 400 TEU, andis suitable for navigation between Wuhan and Yangshan.
Both the standardization and river-coast direct shipping initiatives would improve efficiency of
the gateway operations for the Yangtze River’s middle reaches. On the other hand, it is also underplan that seagoing vessels should be able to sail into the Yangtze River in its lower reaches. This
necessitates the upgrading of waterway conditions, especially the water depth. There is a three-stage
plan for deepening the waterway in the lower Yangtze River. The first-stage work started in 1998
and completed in 2002, which provided an 8.15-meter water depth at the entrance to Yangtze River
course. The second-stage work started in 2002 and finished in 2005. In November 2005, Ministry ofCommunication announced that the Yangtze River 10-meter deepwater course had reached Nanjing,which indicated that the 430km waterway from Shanghai to Nanjing now was accessible to the 3rd
and 4th generation container ships. The third-stage work started in 2006 and, upon its completion,
would deepen the water depth further to 12.5 meters.
These initiatives would significantly improve the hinterland access conditions for the Port of
Shanghai, which will enhance its further development into a premier container port in Asia.

23

As most vessels in the Yangtze River cannot sail in the sea, containers generated in different
regions along the Yangtze River that are carried by river vessels to Shanghai for transhipping tointernational destinations cannot directly dock on the Yangshan deepwater port. These
containers must be unloaded in the Waigaoqiao port (another major terminal at the Port of
Shanghai), which is located along the bank of Yangtze River, and then transshipped by coastal
barges for about 70 nautical miles to the Yangshan port for further transhipping. This doubletranshipping not only extends overall shipping time for customers, but also puts great stress on
already strained capacity at the Waigaoqiao port.
A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 200823

5. CONCLUSION AND FUTURE RESEARCH

In this paper we have examined the interaction between hinterland access conditions and port
competition. Competition between ports is treated as competition between alternate intermodaltransportation chains, while the hinterland access conditions are represented, separately, by the
corridor facilities and by the inland roads. We found that when ports compete in quantities, anincrease in corridor capacity will increase own port’s output, reduce the rival port’s output, andincrease own port’s profit. On the other hand, an increase in inland road capacity may or may notincrease own port’s output and profit, owing to various offsetting effects. Essentially, while moreroad capacity reduces local delays and moderates the negative impact of own output expansion, it
induces greater local commuter traffic and may moderate the reduction by local commuter traffic inresponse to a rise in cargo traffic, both of which reduces own output and profit. Similarly, inland
road pricing may or may not increase own port’s output and profit. Finally, case examples forselected ports and regions are discussed to supplement the analytical study.
The paper has also raised a number of other issues and avenues for future research. Below we
discuss two such issues.
5.1.

Port / hinterland interactions and organizational coordination

In our analysis we have considered that the port and its hinterland belong to a single region,
which ensures their coordination in their decisions. For a given intermodal transportation chain,
however, the port, the corridor and the inland road may belong to different, separate parties(regions, or organizations). Each party tries to maximize its own interest, which may not be thesame as the interest for the entire chain. An example of break-down coordination between the port
and hinterland is given in Y. Zhang (2007), who notes: “There has been a lack of coordination
between water transport and land transport along the Yangtze River. With the development of the
new highway system in China, there have been an increasing number of bridges built to cross the
Yangtze River. On the trunk of the waterway some 2800km in length, there is one bridge every
30km on average. Such a high density of the bridges provided convenience for the north-south land
traffic, but has serious impacts on the west-east water traffic. Since the 1980s, there have been
dozens of new docks capable of handling vessels of 5,000 tonnage built along the Yangtze River.
The bridges on the river, however, have only allowed vessels of 3,000 tonnage to sail beneath.”
This perhaps more realistic structure naturally raises the questions about the nature ofinteractions among the parties, and their coordination, in congestion pricing and capacity
investment, and about their impact on rivalry between ports. Assuming a single, isolated intermodaltransportation chain, Yuen, et al. (2008) investigates the effects of congestion pricing implemented
at a gateway port on its hinterland’s optimal road pricing, road congestion and social welfare. A.
Zhang (2007) is similar to Yuen, et al. (2008) in that he addresses the interaction and coordination
issue in facility pricing in a gateway-hinterland intermodal system. Unlike Yuen, et al. however, heinvestigates the impact of the hinterland’s highway congestion pricing on the gateway, andconsiders both pricing and capacity investment. Both papers demonstrate the important need for
coordination among the multiple parties in order to achieve the efficiency for the entire chain.
Extending this line of research to the setting of competing ports – such as the one analyzed in thispaper – is an important future research.

24

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

5.2.

Overlapping and captive hinterlands

In our analysis we have followed the set-up in De Borger, et al. (2008) that the two seaports
compete for a common hinterland. This set-up of (completely) overlapping hinterlands may bejustified, as discussed earlier, by the emergence of container trade; it also allows us to focus on theissue of port competition. In many markets, however, both overlapping and captive hinterlands may
exist. For example, in their observation about ports in the Le Havre-Hamburg range, Fleming and
Baird (1999) note: “While these ports vie with one another for interior hinterland shipments itshould be noted that each has a competitive advantage in its local hinterland to which it has best
access. It is the ‘discretionary’ shipments which have alternative routing possibilities that stir thecompetitive fires. … Le Havre’s hinterland is primarily French.” Another example is the Port of
Shanghai: Both the (direct) Yangtze River Delta and the indirect hinterland in the middle and upper
reaches of the Yangtze River are captive hinterlands for Shanghai, whilst transshipping markets
along the north-south coastline (about 13% of Shanghai’s container throughput) are subject tocompetition with other Chinese or East Asian seaports.
Although the captive hinterlands do not subject to immediate competition, they play animportant role in the competition between ports. A larger captive hinterland for a port would: (a)allow for (other things, such as load factor and ship size, being equal) more frequent services byshipping lines; (b) allow shipping lines to use larger ships, deriving economies of scale (Cullinane,2005); (c) yield a higher load factor for shipping lines so the port is more likely to be chosen as a“load center” or in their scheduled stop on a route (Heaver, 2006); (d) facilitate the growth of thirdparty LSPs (logistics services providers) and forwarders at/near the port, which would in turnfacilitate the port’s role in the logistics supply chain; and (e) allow more value-added “clusters”(transport product, logistics product and port-related manufacturing product) to be developed,
further attracting more liners, LSPs and forwarders (De Langen, 2002, 2004). All of these would
make the port more competitive in competing for the overlapping market. For instance, a larger
captive hinterland for a port results in higher traffic density which in turn will, among things, lower
freight rates.24
If both the overlapping and captive markets are considered, then important interactions between
the two markets and their impact on port competition need to be analyzed. An earlier paper by
Basso and Zhang (2007) has analyzed a somewhat similar problem in the context of airports. They
did not consider either the hinterland markets, or the intermodal nature of transportation chains.
Nevertheless, their model might be adapted, after incorporating features of the model developed in
the present paper, to an analysis of seaport port competition with both the overlapping and captive
hinterlands.

24

In effect, Y. Zhang (2007) concludes: “Based on the examination of the regional development along theYangtze River, it is concluded that, with direct and indirect hinterlands of such grand scale and foreseeable
development on the hinterland, Shanghai should aim for efficient gateway operations, strengthening its
connections to its hinterlands and providing best service to its clients along the golden waterway fordomestic/international transhipping, rather than competing with other international shipping centers in Asia
Pacific for international/international transhipping.”

A. Zhang — Discussion Paper 2008-8 — © OECD/ITF, 2008

25

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