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

机译:聚合关联网络数据的机制:品牌概念图的应用

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摘要

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.
机译:品牌概念图(BCM)方法是衡量品牌形象的宝贵工具,也就是基于客户的品牌资产的重要组成部分。该方法用于识别品牌关联网络,其中包含有关品牌及其关联如何在消费者心中相互联系的信息。该方法的重要贡献在于,它为如何将单个品牌关联网络数据汇总到共识地图中提供了一组规则。尽管BCM的汇总规则相对简单易用,但汇总机制仍存在方法和实践上的缺陷。在本文中,我们基于对原始聚合规则的严格评估,为个体品牌关联网络数据开发了一种新的聚合机制。三个实证研究的结果表明,新的聚集机制提高了聚集功能和聚集能力,半分裂可靠性以及聚集结果的稳定性。

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