PLS-SEM: INDEED A SILVER BULLET
PLS-SEM: INDEED A SILVER BULLET
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DOI：
10.2753/mtp1069-6679190202
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发表时间：
2011-01-01
影响因子：
3
通讯作者：
Sarstedt, Marko
中科院分区：
文献类型：
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作者：
Hair, Joe F.;Ringle, Christian M.;Sarstedt, Marko
在分析潜在构念之间的因果关系时，结构方程模型（SEM）已经成为市场营销和管理研究的准标准。对于大多数研究人员来说，扫描电镜相当于进行基于协方差的扫描电镜（CB-SEM）。虽然市场研究人员对CB-SEM有基本的了解，但他们中的大多数人对半偏最小二乘SEM （PLS-SEM）的另一种有用的方法几乎不熟悉。本文综述了PLS-SEM及其算法，并概述了何时可以最适当地应用，指出了其未来研究的潜力和局限性。作者得出结论，如果应用得当，PLS-SEM路径建模确实是在许多理论模型和经验数据情况下估计因果模型的“银弹”。
Structural equation modeling (SEM) has become a quasi-standard in marketing and management research when it comes to analyzing the cause-effect relations between latent constructs. For most researchers, SEM is equivalent to carrying out covariance-based SEM (CB-SEM). While marketing researchers have a basic understanding of CB-SEM, most of them are only barely familiar with the other useful approach to SEMpartial least squares SEM (PLS-SEM). The current paper reviews PLS-SEM and its algorithm, and provides an overview of when it can be most appropriately applied, indicating its potential and limitations for future research. The authors conclude that PLS-SEM path modeling, if appropriately applied, is indeed a "silver bullet" for estimating causal models in many theoretical models and empirical data situations.