Tastlé-Nestlé, Toogle-Google: The effects of similarity to familiar brand names in brand name innovation
Ann Kronrod and
Tina M. Lowrey
Journal of Business Research, 2016, vol. 69, issue 3, 1182-1189
Abstract:
When developing new brand names, marketers face the dilemma of how similar their new brand name is or should be to familiar brand names in the market. The current research tests the complete range of conditions exploring how the degree of similarity of a new brand name to an existing one may affect attitudes toward the new brand name. The authors first replicate an inverted-U pattern suggested by congruency theories. However, this result holds only in the case of positive pre-existing attitudes toward familiar brand names. Additional tests demonstrate a U-shaped pattern in the case of negative attitudes toward familiar brand names, and a linear relation between similarity and attitudes in the case of no pre-existing attitudes toward familiar brand names. A field study replicates these findings, testing actual choice of products that bear different levels of resemblance to real positive and negative brand names (Oreo and Spam).
Keywords: Brand name; Branding; Brand attitudes; Similarity; Familiarity; Innovation (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S014829631500421X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:69:y:2016:i:3:p:1182-1189
DOI: 10.1016/j.jbusres.2015.09.015
Access Statistics for this article
Journal of Business Research is currently edited by A. G. Woodside
More articles in Journal of Business Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().