Advanced Issues in Market Segmentation Research

Overview

The general aim is to investigate unresolved questions in market segmentation research. Specific tasks include

developing a conceptual framework of segmentation approaches,
developing a methodological toolbox that can be used to classify specific data situations into the proposed classification for segmentation studies,
evaluating the usefulness of random trees for empirical data-driven market segmentation,
gaining insight into the characteristics of various hierarchical partitioning techniques through Monte-Carlo simulations based on artificial data,
improving visualization for market segmentation research results, and
generalising the perceptions based market segmentation framework.

Sara Dolnicar and Friedrich Leisch. Winter tourist segments in Austria: Identifying stable vacation styles using bagged clustering techniques. Journal of Travel Research, 41(3):281-292, 2003.
Sara Dolnicar, Bettina Grün, and Friedrich Leisch. Time efficient brand image measurement - is binary format sufficient to gain the market insight required? In Jose L. Munuera, editor, Proceedings of the 33rd European Marketing Academy Conference, 2004.
Sara Dolnicar and Friedrich Leisch. Testing for structural change over time of brand attribute perceptions in market segments. In Hamparsum Bozdogan, editor, Statistical Data Mining and Knowledge Discovery, chapter 17, pages 297-307. Chapman & Hall/CRC, Boca Raton, Florida, 2004.
Sara Dolnicar and Friedrich Leisch. Segmenting markets by bagged clustering. Australasian Marketing Journal, 12(1):51-65, 2004.
Sara Dolnicar and Friedrich Leisch. Delivering the Right Tourist Service to the Right People - A Comparison of Segmentation Approaches The Journal of Quality Assurance in Hospitality and Tourism, 5(2/3/4):189-207, 2004.