Project code: Revenue Management
Research group: Multi-agent and Adaptive Computation (SEN4)
Project coordinator: Han La Poutré

The goal of Revenue Management (RM) is to exploit the structure of the
demand for goods or services in order to optimize revenue. The
classical example of RM is varying prices of essentially similar
airline seats, exploiting the fact that the number of seats is limited
and customers are willing to pay different amounts of money.
Fundamental questions that arise within RM are how can a pricing
strategy be developed such that revenues are as high as possible? How
should the market be segmented? Are there seasonal influences? Should
prices vary over time? How do you set prices for combinations of goods
or services?

In strongly competing markets (such as the airline industry) in which
profit margins have become very small, RM has become crucial in order
for companies to survive. RM is emerging now in many application areas
such as hotel reservations, car rental, airport parking services,
energy markets, tour operators, casino's, cruise ships, entertainment,
public transportation and sporting events to name but a few.

This project focuses on how adaptive pricing mechanisms can be
developed that optimize revenue. Important aspects are how goods can
be automatically combined, how preferences of customers and general
market analysis can be performed to support pricing on the basis of
transaction data, what are good adaptive strategies for pricing in a
dynamic market, what does it mean for an adaptive strategy to be good
in a duopoly or oligopoly where competitors are also using adaptive RM
methods?

Members
Sara Ramezani, Peter Bosman, Han La Poutré