Market Segmentation

Biclustering: Overcoming Data Dimensionality Problems in Market Segmentation” by Sara Dolnicar, Katie Lazarevski, both of the University of Wollongong, New South Wales, Australia, Sebastian Kaiser, and Friedrich Leisch, both of Ludwig-Maximilans-Universität, Munich, Germany, was recently published in the Journal of Travel Research OnlineFirst.  Sara Dolnicar gives us some background on the article below:

• Who is the target audience for this article?

Data analysts in industry and academia who conduct market segmentation.

• What inspired you to be interested in this topic?

I have been interested in market segmentation since my PhD in which I investigated the usefulness of neural networks as data analytic technique for market segmentation.

• Were there findings that were surprising to you?

It’s a new method, so there are no surprising insights as such. Instead we are offering a novel method to tackle methodological problems related to market segmentation.

• How do you see this study influencing future research and/or practice?

Hopefully it will improve the methodological quality of research in this area.

• How does this study fit into your body of work/line of research?

Market segmentation methodology is the focus of my research and has been for about 15 years now. Although it is not a new problem that consumers need to be grouped and although methods for market segmentation have been available for a long time, there are still many gaps in the methodological toolbox for market segmentation. I am passionate about trying to fill this gaps bit by bit. This article is another piece of the puzzle.

Bookmark and Share

0 0 votes
Article Rating

Business & Management INK

Business and Management INK puts the spotlight on research published in our more than 100 management and business journals. We feature an inside view of the research that’s being published in top-tier SAGE journals by the authors themselves.

Subscribe
Notify of
guest

This site uses Akismet to reduce spam. Learn how your comment data is processed.

0 Comments
Inline Feedbacks
View all comments
0
Would love your thoughts, please comment.x
()
x