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Project Highlights
Revenue management is often described as the practice of “selling
the right product to the right customer at the right time and the right
price”.
One of the central aspects of revenue management is pricing, i.e.
finding the
price of a product which maximizes a company’s revenue in a competitive
setting.
Until recently, because of theoretical and technical limitations,
pricing was
mostly ignored by revenue managers. Current revenue management systems
consider
that price is fixed and use dynamic capacity management in order to
increase
revenue.
There is however growing interest
in the practice of optimal pricing. This project is concerned with the
development, implementation and validation of bilevel pricing model in
network
industries.
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Airlines
The birthplace of revenue
management in the seventies, the airline industry faces today new
challenges
that profoundly impact its traditional business model. The rise of
low-cost
carriers, the apparition of new distribution channels such as the
Internet and the
rapidly evolving purchase behaviour of the passengers are all factors
that threaten
the profitability of established carriers.
Our research aims at developing optimization
tools based on bilevel programming that help pricing analysts at an
airline in
setting the best prices for the fare products they manage, given the
current
schedule, the attributes of the products offered by the competition and
the
purchasing habits of the customers. Such a tool can be used in two
contexts. On
the tactical front, where thousands of fare changes are published three
or four
times a day, analysts must react quickly and adjust continuously their
prices. Since
modern airline networks are highly meshed and critically depend on
interconnectedness, it is impossible for a human analyst to estimate
the impact
such fare changes can have on the overall network and to decide whether
the
capacity on a given leg is used in the most profitable way, whence the
need for
computerized decision-aid tools. On the
strategic front, when designing new fare products or establishing new
routes,
airline marketers wish to conduct scenario analyses and perform what is
often
called “what-if” pricing, that is simulating the impact of new products
and
prices on the market. By allowing us to explicitly model customer
behaviour at
the second level, bilevel programming can provide the basis for such a
longer-term, strategic tool.
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Rail
Although unpopular in North
America, rail travel is part of everyday life in many European
countries. Over
the last decades, the development of high-speed links between major
centres has
turned rail into a competitive alternative to air travel for trips less
than
1000km, which are very common in densely populated European countries
such as
France and Germany. Rail operators, most of them partially privatized
monopolies,
exploit these high-yield lines in a way that is very similar to
airlines. Capacity
is divided into control classes analogous to airline booking classes
and a
single train services numerous markets (i.e. origin-destination pairs).
We are currently adapting our
model for solving the passenger rail pricing problem and investigating
the
benefits of its use in this context. This work involves modelling
refinements
as well as the development of new metrics for measuring performance.
One of the
challenges we face is the integration of intermodality into the model,
that is
the possibility for passengers of choosing from more than one means of
transportation. For instance, in the case of European high-speed rail
links,
one must consider car and low-cost airlines as competitors to rail.
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Telecoms
Instead of human passengers,
telecommunication companies transport packets of electronic
information. In spite
of this fundamental difference, telecoms share many common
characteristics with
the airline and rail industries. Networks are highly meshed and
connectivity is
crucial. Capacity is limited and must be allocated wisely but, as with
airlines, unused capacity can be produced at a very low marginal cost.
In many
countries, telecoms have been (or are in the process of being)
deregulated and
competition is fierce.
Our research in the telecoms
domain aims at adapting and refining the bilevel model and validating
its use
in various contexts, for instance in designing new packages and
evaluating
their impact on the network and ultimately on the profitability of the
firm. On
the technical side, certain constraints have to be modified or added to
satisfy
physical network integrity and electrical stability, aspects that are
absent
when it comes to passenger transportation.
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