Does customer satisfaction lead to improved brand equity? An empirical examination of two categories of retail brands

Purpose – The objective of the present research is to examine the relationship between consumers' satisfaction with a retailer and the equity they associate with the retail brand. Design/methodology/approach – Retail brand equity is conceptualized as a four-dimensional construct comprising: retailer awareness, retailer associations, retailer perceived quality, and retailer loyalty. Then the associative network memory model is applied from cognitive psychology to the specific context of the relationships between customer satisfaction and consumer-based retailer equity. A survey was undertaken using a convenience sample of shopping mall consumers in an Australian state capital city. The questionnaire used to collect data included an experimental design such that two categories of retailers were included in the study: department stores and specialty stores, with three retailers representing each category. The relationship between consumer-based retailer equity and customer satisfaction was examined using multivariate analysis of variance. Findings – Results indicate that retail brand equity varies with customer satisfaction. For department stores, each consumer-based retailer equity dimension varied according to customer satisfaction with the retailer. However, for specialty stores, only three of the consumer-based retailer equity dimensions, namely retailer awareness, retailer associations and retailer perceived quality, varied according to customer satisfaction level with the retailer. Originality/value – The principal contribution of the present research is that it demonstrates empirically a positive relationship between customer satisfaction and an intangible asset such as retailer equity.

Optimal Paths and Costs of Adjustment in Dynamic DEA Models: With Application to Chilean Department Stores

In this paper we propose a range of dynamic data envelopment analysis (DEA) models which allow information on costs of adjustment to be incorporated into the DEA framework. We first specify a basic dynamic DEA model predicated on a number or simplifying assumptions. We then outline a number of extensions to this model to accommodate asymmetric adjustment costs, non-static output quantities, non-static input prices, and non-static costs of adjustment, technological change, quasi-fixed inputs and investment budget constraints. The new dynamic DEA models provide valuable extra information relative to the standard static DEA models-they identify an optimal path of adjustment for the input quantities, and provide a measure of the potential cost savings that result from recognising the costs of adjusting input quantities towards the optimal point. The new models are illustrated using data relating to a chain of 35 retail department stores in Chile. The empirical results illustrate the wealth of information that can be derived from these models, and clearly show that static models overstate potential cost savings when adjustment costs are non-zero.