说明PLS-SEM 是否是适当的分析方法时？

答： 中文请参考：

PLS-SEM 的主要优点包括放宽用于使用CB-SEM估计模型的最大概似法所需的常态分布假设，

以及PLS-SEM能够估计具有较小样本量和较复杂模型的能力(Hair et al. 2019; Shiau et al. 2019; Khan et al. 2019; Shiau and Chau 2016)。与CB-SEM相比，PLS-SEM更适用于：当研究目标是对理论发展的探索性研究时；当分析是针对预测的角度时；

当结构模型复杂时；当结构模型包括一个或多个形成性模式时；当样本量较小时；当分布不是常态时；

以及当研究需要潜在变量分数以进行后续分析时(Gefen et al. 2011; Hair et al. 2019; Shiau et al. 2019; Khan et al. 2019; Shiau and Chau 2016; Shiau et al. 2020)。上述原因支持考虑 PLS-SEM是适合研究的SEM方法。

英文请参考：

The primary advantages of PLS-SEM include the relaxation of normal distributional assumptions required by the maximum likelihood method used to estimate models using CB-SEM, and PLS-SEM’s ability to easily estimate much more complex models with smaller sample sizes (Hair et al. 2019; Shiau et al. 2019; Khan et al. 2019; Shiau and Chau 2016).Compared with CB-SEM, PLS-SEM is more suitable for this study including when the research objective is exploratory research for theory development; when the analysis is for a prediction perspective; when the structural model is complex; when the structural model includes one or more formative constructs; when the sample size is smaller due to a small population; when distribution is lack of normality; and when research requires latent variable scores for consequent analyses (Gefen et al. 2011; Hair et al. 2019; Shiau et al. 2019; Khan et al. 2019; Shiau and Chau 2016; Shiau et al. 2020). The above reasons provide supports to consider the PLS is an appropriate SEM method for a study.

Reference:

• Gefen, D., Straub, D.W., and Rigdon, E.E. 2011. "An Update and Extension to SEM Guidelines for Admnistrative and Social Science Research," MIS Quarterly (35: 2) pp.iii-xiv.

• Khan G.F., Sarstedt M., Shiau W,-L., Hair J.F., Ringle C.M., and Fritze M.P., 2019. “Methodological research on partial least squares structural equation modeling (PLS-SEM): An analysis based on social network approaches,” Internet Research (29:3), pp. 407-429

• Shiau, W.-L., Sarstedt, M., and Hair, J.F. 2019. “Internet research using partial least squares structural equation modeling (PLS-SEM),” Internet Research (29:3), pp. 398-406. (SSCI)

• Hair J. F., Risher J. J., Sarstedt M., and Ringle C. M., 2019. "When to use and how to report the results of PLS-SEM," European Business Review (31:1), pp. 2-24.

• Shiau, W.-L., and Chau, Y.K. 2016. “Understanding behavioral intention to use a cloud computing classroom: A multiple model-comparison approach,” Information & Management (53:3), pp. 355-365. (Web of Science 80 times cited, ESI 1% highcited article)

• Shiau, W.-L., Yuan, Y., Pu, X., Ray, S. and Chen, C.C. 2020. "Understanding Fintech continuance: perspectives from self-efficacy and ECT-IS theories," Industrial Management & Data Systems (120:9), pp. 1659-1689.