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首页> 外文期刊>Journal of Brand Management >Key determinants of internal brand management success: An exploratory empirical analysis
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Key determinants of internal brand management success: An exploratory empirical analysis

机译：内部品牌管理成功的关键因素：探索性的经验分析

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摘要

This paper presents explorative, empirical data as a first step towards testing the holistic model of internal brand management previously developed by the authors. Based on the premise of identityoriented branding, the authors statistically examine the factors behind the three key concepts of their internal brand management model: brand commitment, brand citizenship behaviour and the brand-customer relationship. The empirical analysis builds on three data sets examining six industry sectors. The three samples were generated by means of surveys of customers, employees and marketing professionals responsible for internal brand management. The results of the statistical analysis reveal the extent to which the hypothesised determinants and causal links between brand commitment, brand citizenship behaviour and brand strength (defined as the degree of behavioural relevance of the brand) hold: The hypothesised causal link between brand commitment and brand citizenship behaviour was empirically validated, whereas the purported relationship between brand citizenship behaviour and brand strength could be shown in tendency. Its causal link could not conclusively be proven as the size of the sample proved to be too small. The hypothesised constituents of brand commitment and brand citizenship behaviour, however, required substantial modification on the basis of the empirical evidence and hence require further empirical testing with a new data set.
机译：本文介绍了探索性的经验数据，作为测试作者先前开发的内部品牌管理整体模型的第一步。在以身份为导向的品牌的前提下，作者从统计学角度考察了其内部品牌管理模型的三个关键概念背后的因素：品牌承诺，品牌公民行为和品牌与客户关系。实证分析建立在检查六个行业部门的三个数据集的基础上。这三个样本是通过对负责内部品牌管理的客户，员工和市场营销专业人员进行调查而得出的。统计分析的结果揭示了品牌承诺，品牌公民行为和品牌强度（定义为品牌的行为相关程度）之间的假设决定因素和因果关系的保持程度：品牌承诺和品牌之间的假设因果关系公民行为得到了经验验证，而品牌公民行为与品牌实力之间的所谓关系则有趋势。由于样本大小过小，无法最终证明其因果关系。但是，假设的品牌承诺和品牌公民行为的构成要素需要根据经验证据进行大量修改，因此需要使用新的数据集进行进一步的经验检验。

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