Ten Basic Questions About Structural Equations Modeling You Should Know the Answers To - But Perhaps You Don't

Davvetas, Vasileios; Diamantopoulos, Adamantios; Zaefarian, Ghasem; Sichtmann, Christina (2020). Ten Basic Questions About Structural Equations Modeling You Should Know the Answers To - But Perhaps You Don't Industrial Marketing Management, 90, pp. 252-263. Elsevier 10.1016/j.indmarman.2020.07.016

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Structural Equations Modeling (SEM) has enjoyed increased popularity as an analytical method among Industrial Marketing Management (IMM) authors over the last years. Despite such popularity, many authors fail to understand the basic principles of the method and reviewers are frequently confronted with manuscripts suffering from erroneous applications, insufficient reporting and questionable interpretation of SEM-based findings. Addressing this issue, the present article presents – in non-technical language – the most basic concepts related to SEM, resolves common misconceptions about the method's application and provides hands-on advice to IMM authors and reviewers dealing with SEM-based manuscripts. Structured along ten fundamental questions, the article covers issues related to (1) latent variables and their scaling, (2) types of parameters in SEM, (3) unstandardized and standardized estimates, (4) model identification, (5) model constraints, (6) model fit, (7) independence and saturated models, (8) modification indices, (9) nested models, and (10) equivalent models. After illustrating these concepts with the use of examples, the article concludes with a list of guidelines addressed both to IMM authors crafting manuscripts using SEM and the peers reviewing them.

Item Type:	Journal Article (Original Article)
Division/Institute:	Business School > Institute for Applied Data Science & Finance > Applied Data Science Business School
Name:	Davvetas, Vasileios; Diamantopoulos, Adamantios; Zaefarian, Ghasem and Sichtmann, Christina0000-0001-6101-9467
Subjects:	H Social Sciences > HF Commerce
ISSN:	00198501
Publisher:	Elsevier
Language:	English
Submitter:	Christina Sichtmann
Date Deposited:	11 Jul 2023 09:23
Last Modified:	11 Jul 2023 09:23
Publisher DOI:	10.1016/j.indmarman.2020.07.016
Uncontrolled Keywords:	Structural equations modeling, Confirmatory factor analysis, Survey research
ARBOR DOI:	10.24451/arbor.18170
URI:	https://arbor.bfh.ch/id/eprint/18170