A test of the stability of retail store image mapping based on multientity scaling data

Abstract

Multientity scaling is a multiattribute measurement procedure that obtains ratings of two or more entities from a single respondent at the same time. The purpose of this research is to examine experimentally the stability of perceptual maps of retail stores based upon two types of multientity scaling data — data produced by attribute and entity-based scaling procedures. The findings indicate both procedures may produce mapping instability when the comparative retail store context of the ratings is changed, with attribute-based scaling being characterized by more instability than entity-based scaling. Based upon the findings, potential methods of increasing retail store image mapping stability are explored.