Jean-Paul Rodrigue (2017), New York:
Routledge, 440 pages.
Maritime Routing Patterns
Authors: Dr. Alexander Kuznetsov and Dr. Jean-Paul Rodrigue
NOTE: This page is no longer updated.
The main prevalent feature of contemporary global transportation
systems is containerization. Intermodalism, being a logical consequence
of containerization, also added to the substantial changes in the landscape
of the transport industry, namely by favoring integration between different
transport systems. New and ever developing transportation routes appear
to be randomly structured. Still, there is a rationale behind this complex
The main objective of this section is to provide an overview to the
interplaying factors shaping the transportation networks and affecting
the logistical decision taken when designing a supply chain consisting
of different modes. An Excel spreadsheet which contains the data used
in this application is available. It contains the different port location
patterns, ratios of constant and variable costs, distances and service
patterns, vehicle’s capacity utilization.
These are certain operational costs
connected to every vehicle used for cargo transportation. Vehicles have
also different cargo capacity, so the
unit transportation cost is different
for every transportation mode.
Economies of scale are expressed in the alternation of the vehicles’
economy: for short distances the truck is the most cost effective. For
medium and long distances rail, then the feeder ship and eventually
the ocean ship become more cost effective. All these considerations
remain only for fully loaded vehicles. A
partially loaded vehicle can substantially change the relative cost
effectiveness of transportation modes.
Not only the concrete values, but even the relative levels of costs,
capacities and distances can differ greatly. Fluctuations in fuel prices,
wages, or financial policies (e.g. a company can increase the mobilization
price over real cost), define real operation costs and, eventually,
set the effective service range of a mode. Still, these general relationships
remain in the real world and are taken into consideration when a transport
mode is selected.
It should also be noted that the distance between an origin and a
destination is not Euclidian, not even geographical: it is the
transport or logistical distance
needed to be taken into consideration.
With all these reservations, propensity to use larger vehicles triggers
the rationalization of transportation routes selection. A
simplified example helps illustrate
how this process works which considers 10 ports of similar size that
are located along two maritime facades, evenly spaced along the coastline.
A different pattern of services
can be suggested, consolidating all cargo from the façade of departure
at one port (hub), delivering it to the opposite hub and distributing
to the feeders. This hub-and-spoke routing rationalization gives a better
result as the port-to-port pattern.
Transportation costs by land (at the distances of 100 and 200) are
lower than by water (see operational costs).
This implies that consolidation to the hub port would be more cost effective
if performed by trucks or rail. Indeed, this logic serves as a driving
force for rationalization of inland transportation. As cargo flows merge
into larger ones, the distance between these consolidation centers is
set by the threshold of different transport modes. Obviously, the reality
deviates from this theoretical framework, since the cargo usually is
not evenly distributed, the distances are different, and vessel capacity
In addition, there are alternatives to the hub-to-hub solution. Indeed,
with a simple pendulum pattern an
ocean ship can call every port of one façade, picking cargo in each
port and dropping it in every port of destination facade. At the beginning
and ending parts of the voyage (along coastlines) the ocean vessel would
not be fully loaded, but these legs are only a small fraction of the
whole distance. Using the same cost calculation framework, the costs
for this case are almost half of the initial configuration which seems
to be more cost effective than the previous solution.
Still, this solution is not correct, since it falls out from the
limited reality of our sample. The error in this reasoning is quite
clear; the additional costs for calling extra ports on the route as
not been taken into account. In the calculation of operational costs
it was assumed that the fixed costs components included costs only at
two calling ports at each side of the route. Every additional port of
call involves additional costs such as towage, pilotage, and dues, which
should be taken into consideration. The
consideration of additional costs
for port calls significantly changes the outcome, but the total
costs are still lower than the hub-and-spoke pattern.
Yet another solution can be found by
combining pendulum and hub patterns. The loads, distances and coefficients
in the examples used in this section were selected to provide that all
solutions are equal. Those who wish to explore routing problems in more
depth can use the attached
Excel spreadsheet to
develop different scenarios and their optimal solutions.