Key driver analysis with relative weight analysis: A two-step approach

IF 2.4 4区 管理学 Q3 BUSINESS
Michael S. Garver, Zachary Williams
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引用次数: 0

Abstract

Key driver analysis (statistically inferred importance analysis) is commonly implemented to understand what customer satisfaction attributes are most important in driving overall customer satisfaction. Building on prior research, this article suggests that dominance analysis and relative weight analysis are the most appropriate statistical techniques for conducting key driver analysis, yet relative weight analysis is the more feasible choice. A process is put forth so that research practitioners can conduct key driver analysis with relative weight analysis implementing a two-step approach. The two-step approach should be used when the key driver analysis contains a large number of attributes, which are theoretically redundant and highly correlated.
关键驱动因素分析与相对权重分析:两步法
关键驱动因素分析(统计推断重要性分析)通常用于了解哪些客户满意度属性对提高整体客户满意度最为重要。在先前研究的基础上,本文提出支配分析和相对权重分析是进行关键驱动因素分析最合适的统计技术,但相对权重分析是更可行的选择。本文提出了一个流程,使研究人员可以采用两步法进行关键驱动因素分析和相对权重分析。当关键驱动因素分析包含大量属性时,应采用两步法,因为这些属性在理论上是冗余和高度相关的。
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来源期刊
CiteScore
6.00
自引率
6.70%
发文量
38
期刊介绍: The International Journal of Market Research is the essential professional aid for users and providers of market research. IJMR will help you to: KEEP abreast of cutting-edge developments APPLY new research approaches to your business UNDERSTAND new tools and techniques LEARN from the world’s leading research thinkers STAY at the forefront of your profession
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