基于协方差的结构方程模型(CB-SEM):作为营销研究工具的应用指南

J. Hair, M. Gabriel, V. Patel
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引用次数: 503

摘要

结构方程建模(SEM)越来越成为社会科学,特别是市场营销学科中概念和理论发展的首选方法。在市场营销研究中,越来越需要评估复杂的多重潜在结构和关系。二阶结构可以建模,提供对关系的改进的理论理解以及简化。SEM特别适合于研究多个结构之间的复杂关系。两种最流行的基于扫描电镜的分析方法是基于协方差的扫描电镜(CB-SEM)和基于方差的扫描电镜(PLS-SEM)。虽然每种技术都有其优点和局限性,但在本文中,我们将重点介绍使用AMOS的CB-SEM,以说明其在检查客户导向、员工导向和公司绩效之间关系方面的应用。我们还演示了高阶结构在为客户导向和员工导向的响应性和主动性组件建模时是如何有用的。
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AMOS Covariance-Based Structural Equation Modeling (CB-SEM): Guidelines on Its Application as a Marketing Research Tool
Structural equation modeling (SEM) is increasingly a method of choice for concept and theory development in the social sciences, particularly the marketing discipline. In marketing research there increasingly is a need to assess complex multiple latent constructs and relationships. Second-order constructs can be modeled providing an improved theoretical understanding of relationships as well as parsimony. SEM in particular is well suited to investigating complex relationships among multiple constructs. The two most prevalent SEM based analytical methods are covariance-based SEM (CB-SEM) and variance-based SEM (PLS-SEM). While each technique has advantages and limitations, in this article we focus on CB-SEM with AMOS to illustrate its application in examining the relationships between customer orientation, employee orientation, and firm performance. We also demonstrate how higher-order constructs are useful in modeling both responsive and proactive components of customer and employee orientation.
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