Hair, Joseph F.Joseph F.HairRingle, Christian M.Christian M.RingleSarstedt, MarkoMarkoSarstedt2019-12-122019-12-122011-04-01Journal of Marketing Theory and Practice 19 (2): 139-151 (2011-04-01)http://hdl.handle.net/11420/4049Structural 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 SEM-partial 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.en1069-667920112139151Allgemeines, WissenschaftJournal Article10.2753/MTP1069-6679190202Other