Two-Mode Classification in Advertising Research

Schwaiger, Manfred (1997): Two-Mode Classification in Advertising Research. 20th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Freiburg, March 6–8, 1996. Klar, Rüdiger und Opitz, Otto (eds.) : In: Classification and Knowledge Organization. Proceedings of the 20th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Freiburg, March 6–8, 1996, Berlin; Heidelberg: Springer. pp. 596-603

Abstract

In the past years two-mode clustering methods were applied to marketing subjects in order to represent relevant marketing information. The clustering methods just mentioned can be roughly divided into methods using grand matrices and other methods, such as the centroid-effect-method or the GENNCLUS-algorithm. This paper focusses another way of constructing a grand matrix from recall and recognition data. Using the grand matrix the well-known one-dimensional clustering methods can be applied to gain more detailed information about cognitive communication effects in advertising research.

• Item Type: Conference or Workshop Item (Paper)
• Form of publication: Publisher's Version
• Keywords: Customer Segment; Recognition Data; Advertising Research; Heterogeneity Measure; Complete Linkage Algorithm
• Faculties: Munich School of Management > Institute for Market-based Management
• Subjects: 300 Social sciences > 330 Economics
• Place of Publication: Berlin; Heidelberg
• Language: English