choice-based demand forecasting in airline revenue management systems

261 Pages·2017·3.74 MB·English

CHOICE-BASED DEMAND FORECASTING IN
AIRLINE REVENUE MANAGEMENT SYSTEMS

Jue Wang

This thesis is presented for the degree of
Doctor of Philosophy of
The University of Western Australia

UWA Business School

Management & Organisations

2015

To my parents Wei Wang and Guanshu Wang
and my Husband Pan Zhang

ABSTRACT
Over the last decade, airline markets around the world have been reshaped dramatically
by the rapidly growing low-cost carriers and new forms of distribution channel.
Significant reduction in searching cost brought by the web-based distribution has made
fare product comparison and purchasing an easier task. As a result, traditional demand
models based on independent (fare class) demand assumption has been violated. A
better understanding of passenger choice behaviour is now needed since the
development of new generation revenue management (RM) system requires inputs of
demand based on dependent fare classes.
Early studies on dependent demand mainly focused on the buy-up and buy-down
behaviour for single-leg flights. With the introduction of discrete choice modelling,
more recent studies are beginning to incorporate competitions between flights and
carriers into the model. In a discrete choice model, a customer is assumed to weigh up
service levels of a fare product against its price. The fare option with the highest
satisfaction is the one being chosen. As all the components taken into consideration by a
traveller may not be readily at hand for the analyst, the satisfaction or utility of a fare
product is measured by way of a systematic component – the observed utility – and a
random component – the unobserved utility. As such, the choice decision is modelled
up to a probability. Discrete choice models are theoretically sound for fare product
demand forecasting, as they directly work on the decision making process of air
travellers.
Currently, the most widely applied discrete choice model in revenue management is the
multinomial logit model (MNL), within which the unobserved utility of each alternative
is independently and identically distributed (IID). Such a structure leads to the
independence from irrelevant alternatives or IIA property. That is, the ratio of
probabilities for two alternatives is independent from the existence of any other
i
alternative in the choice set. However, the biggest limitation of IIA is the resulting
proportional substitution pattern, which suggests that an improvement in the attributes
of one alternative reduces the probabilities for all other alternatives by the same
percentage. This highly restricted structure is unlikely to hold in the context of real
airline markets. This is because the behaviour of compensatory travellers is likely to
vary among the population, and to capture these variations advanced DCMs should be
applied.
In addition to preference heterogeneity, the decision making process of air travellers are
also varying. For example, in RM literature the new priceable/yieldable segmentation
was derived on the behavioural difference between the price-oriented (priceable)
travellers and the service-oriented (yieldable) travellers. The former would persistently
choose the available fare product with the lowest price, while the latter is only interested
in a single type of fare product. Although none of the two types of traveller strictly
follows the utility maximisation behaviour, they have not been differentiated from the
compensatory travellers during choice model estimation.
In order to address the above issues, a new stated choice design method was proposed.
The use of stated preference (SP) data over the revealed preference (RP) data is because
repeated choices from individual travellers that are necessary to identify the decision
rule heterogeneity are relatively easy to be obtained under the SP environment. To
generate the stated choice experiments, availability design methods were used. Different
from traditional labelled experimental designs with fixed choice set composition,
availability designs vary the alternatives in a choice set through a ‘master design’, under
which the presence and absence of each alternative can be controlled systematically.
Such a practice mimics fare product stock-outs caused by the capacity limitation of
aircrafts and RM controls utilised by the airlines, but more importantly, it allows the
natural correlations between price and service levels to be maintained – a condition
ii
seldom can be met under fixed-composition design due to attribute trade-offs required
by the efficient design criteria.
In this thesis, the proposed design has been tested under both simulated and empirical
environments. The simulation studies demonstrate the benefit of using availability
designs in identifying preference heterogeneity and decision rule heterogeneity in a
population. The empirical results show that both preference heterogeneity and decision
rule heterogeneity are likely to exist in the real airline market, and they can affect the
result of fare class demand in a dramatic way.
The thesis provides a proof-of-concept of using RP-SP calibrated choice models for fare
product demand forecasting, and proves the importance of air travel choice studies in
the development of the new generation choice-based RM system.

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