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15 - Using alternative-specific DCE designs and best and worst choices to model choices

from Applications: Case 3

Published online by Cambridge University Press:  05 October 2015

Jordan J. Louviere
Affiliation:
University of South Australia
Terry N. Flynn
Affiliation:
University of Western Sydney
A. A. J. Marley
Affiliation:
University of Victoria, British Columbia
Jordan J. Louviere
Affiliation:
University of South Australia
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Summary

15.1 Introduction

The purpose of this chapter is to show how to combine an alternative-specific DCE design with a BW choice task. Secondary aims are (1) to show how to add informative choice sets to DCE tasks to gain insights and information about individual differences and (2) to show how to analyze and report choice totals from this type of DCE task to gain additional insights.

Most private sector organizations need to understand pricing and the likely impacts of differences in and/or changes to prices of their own product/service prices and/or the likely impacts of competitor price changes. Similarly, many public sector organizations need to understand and anticipate the consequences of various pricing policies, such as offering incentives to uptake solar appliances, tolls on bridges and highways, usage fees for parks, and so on. As a result, there are numerous potential choice model pricing applications in both sectors. This chapter illustrates one such application, namely modeling the choices of a relevant sample of individuals faced with different airlines and fares for a holiday trip.

I study the flight choices of a sample of 214 individuals randomly sampled from the Pureprofile online panel in Australia who (1) reside in the Sydney metropolitan area, (2) have flown to northern New South Wales (NSW) for a weekend or longer holiday in the past three years or (3) anticipate doing so in the next three years. At the time of the study there were five potential airline choices for such flights within NSW: Jetstar, Qantas, Rex, Tiger and Virgin. Fares for such flights ranged approximately between A$89 and A$239 at various times during the three years prior to the study. Differences between flights within NSW are not large, as most flights are no more than an hour. Airlines flying within NSW try to claim significant differences in services, and, to the extent that such differences exist, I would expect to see them manifest in differential choices of particular airlines.

Thus, one can model and quantify preferences for airlines and fares by designing an alternative-specific discrete choice experiment (ASDCE). Typically, an ASDCE is appropriate when individuals in the market of interest will choose specific offers, such as brands, transport modes, holiday destinations, etc.

Type
Chapter
Information
Best-Worst Scaling
Theory, Methods and Applications
, pp. 297 - 315
Publisher: Cambridge University Press
Print publication year: 2015

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