Essays on Brand Image Effects in Marketing

Kottemann P. Essays on Brand Image Effects in Marketing. Bielefeld; 2017

Measuring Brand Image Perceptions in Co-Branding

Kottemann P, Decker R, Hentschel D. Measuring Brand Image Perceptions in Co-Branding. Social Science Research Network; 2017

Brand Concept Maps in Computer-Aided Interviews – Challenges, Benefits, and Empirical Findings

Kottemann P, Meißner M, Decker R. Brand Concept Maps in Computer-Aided Interviews – Challenges, Benefits, and Empirical Findings. Presented at the 35th ISMS Marketing Science Conference, Istanbul, Türkei

Measuring Brand Concept Maps in Computer-Aided Interviews

Meißner M, Kottemann P, Decker R. Measuring Brand Concept Maps in Computer-Aided Interviews. In: Proceedings of the Australian New Zealand Marketing Conference (ANZMAC) 2012. 2012: CD-ROM.In 2006, John, Loken, Kim, and Monga introduced Brand Concept Maps (BCM) as a new approach for measuring consumers’ brand associations in a standardized way. However, the approach in its original form requires personal interviews to be conducted in controlled lab situations. Due to the fact that the validity of market research studies strongly depends on generating large and representative samples, having to conduct personal interviews is a drawback and might hinder market researchers from fully exploiting BCM’s potential. Against this background, the paper describes challenges of applying the BCM approach in computer-aided interviews and proposes a way to implement BCM in this environment. In an empirical study, we compare BCM data from computer-aided and personal interviews. First results indicate high convergent validity between both data sets. Moreover, applying BCM seems promising because the overall interview length is significantly reduced while evoking a very similar level of associations and connections

Parent Brands´ Influence on Co-Brand´s Perception. A Model-Based Approach

Böger D, Kottemann P, Decker R. Parent Brands´ Influence on Co-Brand´s Perception. A Model-Based Approach. Journal of Product & Brand Management. 2018;27(5):514-522

Investigating feedback effects in the field of brand extension using brand concept maps

Kottemann P, Plumeyer A, Decker R. Investigating feedback effects in the field of brand extension using brand concept maps. Baltic Journal of Management. 2018;13(1):41-64

Measuring brand image: A systematic review, practical guidance, and future research directions

Plumeyer A, Kottemann P, Böger D, Decker R. Measuring brand image: A systematic review, practical guidance, and future research directions. Review of Managerial Science. 2017;13(2):227-265

Using Cluster Analysis for the Identification of Heterogeneous Brand Images

Böger D, Kottemann P, Decker R, Meißner M. Using Cluster Analysis for the Identification of Heterogeneous Brand Images. In: European Conference on Data Analysis 2015, Book of Abstracts. 2015

A mechanism for aggregating association network data: An application to brand concept maps

Böger D, Kottemann P, Meißner M, Decker R. A mechanism for aggregating association network data: An application to brand concept maps. Journal of Business Research. 2017;79(October 2017):90-106.The brand concept maps (BCM) approach is a valuable tool for measuring brand images, that is, an important part of customer-based brand equity. The approach is used to identify brand association networks, which contain information on how the brand and its associations are interconnected in consumers' minds. An essential contribution of the approach is that it provides a set of rules for how to aggregate individual brand association network data into a consensus map. Although BCM's aggregation rules are relatively straightforward and easy to use, the aggregation mechanism still has methodological and practical drawbacks. In this paper, we develop a new aggregation mechanism for individual brand association network data based on a critical assessment of the original aggregation rules. The results of three empirical studies show that the new aggregation mechanism improves the functionality and the aggregation capability, the split-half reliability, and the stability of the aggregation results

The Benefits of Computer-Based Brand Concept Mapping

Meißner M, Kottemann P, Decker R, Scholz S. The Benefits of Computer-Based Brand Concept Mapping. Schmalenbach Business Review. 2015;67(4):430-453