An assessment of the use of partial least squares structural equation modeling in marketing research
An assessment of the use of partial least squares structural equation modeling in marketing research
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DOI：
10.1007/s11747-011-0261-6
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发表时间：
2012-05-01
影响因子：
18.2
通讯作者：
Mena, Jeannette A.
中科院分区：
文献类型：
--
作者：
Hair, Joe F.;Sarstedt, Marko;Mena, Jeannette A.
大多数方法论领域定期进行批判性反思，以确保严格的研究和出版实践，从而在其领域内获得认可。有趣的是，相对较少的注意力已经支付给评估偏最小二乘结构方程模型（PLS-SEM）在营销研究中的使用，尽管它在近年来越来越受欢迎。为了填补这一空白，我们在30个排名靠前的营销期刊中进行了广泛的搜索，使我们能够识别出30年（1981年至2010年）内发表的204个PLS-SEM应用。这些文章的关键分析地址，除其他外，以下关键方法问题：使用偏最小二乘-SEM，数据和模型的特点，外部和内部模型的评价，和报告的原因。我们还概述了研究人员的选择之间的相互依赖关系，确定潜在的问题领域，并讨论其影响。在我们的研究结果的基础上，我们提供了全面的指导方针，以帮助研究人员避免在PLS-SEM的使用常见的陷阱。这项研究对研究人员和从业人员很重要，因为PLS-SEM需要几个关键的选择，如果不正确，可能会导致不正确的发现，解释和结论。
Most methodological fields undertake regular critical reflections to ensure rigorous research and publication practices, and, consequently, acceptance in their domain. Interestingly, relatively little attention has been paid to assessing the use of partial least squares structural equation modeling (PLS-SEM) in marketing research-despite its increasing popularity in recent years. To fill this gap, we conducted an extensive search in the 30 top ranked marketing journals that allowed us to identify 204 PLS-SEM applications published in a 30-year period (1981 to 2010). A critical analysis of these articles addresses, amongst others, the following key methodological issues: reasons for using PLS-SEM, data and model characteristics, outer and inner model evaluations, and reporting. We also give an overview of the interdependencies between researchers' choices, identify potential problem areas, and discuss their implications. On the basis of our findings, we provide comprehensive guidelines to aid researchers in avoiding common pitfalls in PLS-SEM use. This study is important for researchers and practitioners, as PLS-SEM requires several critical choices that, if not made correctly, can lead to improper findings, interpretations, and conclusions.