Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- List of contributors to application chapters
- Preface
- Acknowledgments
- Theory and Methods
- Applications: Case 1
- 7 BWS object case application: attitudes towards end-of-life care
- 8 How consumers choose wine: using best-worst scaling across countries
- 9 Best-worst scaling: an alternative to ratings data
- Applications: Case 2
- Applications: Case 3
- References
- Subject index
- Author index
8 - How consumers choose wine: using best-worst scaling across countries
from Applications: Case 1
Published online by Cambridge University Press: 05 October 2015
- Frontmatter
- Contents
- List of figures
- List of tables
- List of contributors to application chapters
- Preface
- Acknowledgments
- Theory and Methods
- Applications: Case 1
- 7 BWS object case application: attitudes towards end-of-life care
- 8 How consumers choose wine: using best-worst scaling across countries
- 9 Best-worst scaling: an alternative to ratings data
- Applications: Case 2
- Applications: Case 3
- References
- Subject index
- Author index
Summary
8.1 Introduction
This chapter presents an example of the application of BWS to an issue in wine marketing, and by doing so illustrates the steps in using the BW attribute model across multiple countries. At the same time the chapter demonstrates some of the strengths of the BW attribute model in allowing the easy comparison of consumer behavior across a number of countries, whereas traditional Likert scaling often provides little discrimination between the attributes. The approach taken in this chapter is categorized as Case 1 (object case), and follows the topics as discussed below.
First, the issue of marketing wine to multiple countries is explored as a basis for the research. The formulation of the attributes and the issues involved in choosing both the number of attributes to compare and their composition is discussed next. Then the survey instrument is described, including the demographic and other variables collected, which help interpret the results. The formulation of the data for analysis and the actual analysis come next, showcasing the ease of comparing the attributes across the whole sample. Comparing the countries and illustrating the graphical approach for finding differences between how consumers choose wine across countries follow this. Another positive of the BW approach is that it tends to reduce method and respondent variability, which makes the use of multivariate methods, such as clustering, easier to interpret. This is illustrated by using latent class analysis to derive clusters across the countries. These clusters show that there are three overall schemes that wine buyers use to decide on their purchases in each country, but the number of buyers in each segment differs greatly by country. These final results are discussed, and the example concludes with some recommendations for further application of BWS to cross-national research.
8.2 The problem
Wine provides an instructive area in which to use BWS, because it is a complex category that has developed quite differently around the world. There are countries, such as France, Italy and Spain, that have been growing grapes and making wine for well over 1,000 years. Wine for them has been a local drink, usually made and consumed within 50 kilometers. At the same time these countries have exported some of their production to neighboring countries, especially the United Kingdom, where grapes cannot be grown easily.
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- Best-Worst ScalingTheory, Methods and Applications, pp. 159 - 176Publisher: Cambridge University PressPrint publication year: 2015
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