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Joern Meissner, Arne K Strauss
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| Abstract |
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One of the latest developments in network revenue management (RM) is the incorporation of customer
purchase behavior via discrete choice models. Many authors presented control policies for the booking process
that are expressed in terms of which combination of products to offer at a given point in time and given
resource inventories. However, in many implemented RM systems—most notably in the hotel industry—bid
price control is being used, and this entails the problem that the recommended combination of products as
identified by these policies might not be representable through bid price control. If demand were independent
from available product alternatives, an optimal choice of bid prices is to use the marginal value of capacity
for each resource in the network. But under dependent demand, this is not necessarily the case. In fact, it
seems that these bid prices are typically not restrictive enough and result in buy-down effects.
We propose (1) a simple and fast heuristic that iteratively improves on an initial guess for the bid price
vector; this first guess could be, for example, dynamic estimates of the marginal value of capacity. Moreover,
(2) we demonstrate that using these dynamic marginal capacity values directly as bid prices can lead to
significant revenue loss as compared to using our heuristic to improve them. Finally, (3) we investigate
numerically how much revenue performance is lost due to the confinement to product combinations that can
be represented by a bid price.
The heuristic is not restricted to a particular choice model and can be combined with any method that
provides us with estimates of the marginal values of capacity. In our numerical experiments, we test the
heuristic on some popular networks examples taken from peer literature. We use a multinomial logit choice
model which allows customers from different segments to have products in common that they consider to
purchase. In most problem instances, our heuristic policy results in significant revenue gains over some
currently available alternatives at low computational cost. |
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| Keywords |
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Revenue Management, Network, Bid Prices, Choice Model
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| Status |
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European Journal of Operational Research, Vol 217, Issue 2 (March 2012) pp 417–427. |
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| Download |
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www.meiss.com/download/RM-Meissner-Strauss-04.pdf
(698 kb) |
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| Reference |
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BibTeX,
Plain Text |
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