The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Everything you always wanted to know about SEM (structural equations modeling) but were afraid to ask
Open accessAbstract
This article is intended to serve as a primer for structural equations models for the behavioral researcher. The technique is not mysterious—it is a natural extension of factor analysis and regression. The measurement part of a structural equations model is essentially a confirmatory factor analysis, and the structural part of the model is like a regression but vastly more flexible in the types of theoretical models that may be tested. The models and notation are introduced and the syntax is provided to replicate the analyses in the paper. Part II of this article will appear in the next issue of the Journal of Consumer Psychology, and it covers advanced issues, including fit indices, sample size, moderators, longitudinal data, mediation, and so forth.
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Cites
A Beginner's Guide to Structural Equation Modeling: Fourth Edition
Schumacker, R. E., & Lomax, R. G. (2015) · doi:10.4324/9781315749105 · Cited by 6,604
An updated paradigm for scale development incorporating unidimensionality and its assessment
Gerbing, D. W., & Anderson, J. C. (1988) · Journal of Marketing Research · doi:10.1177/002224378802500207 · Cited by 6,293
A Beginner's Guide to Structural Equation Modeling
Schumacker, R. E., & Lomax, R. G. (2004) · doi:10.4324/9781410610904 · Cited by 6,235
Statistics and Causal Inference
Holland, P. W. (1986) · Journal of the American Statistical Association · doi:10.1080/01621459.1986.10478354 · Cited by 5,293
Corporate Social Responsibility, Customer Satisfaction, and Market Value
Luo, X., & Bhattacharya, C. B. (2006) · Journal of Marketing · doi:10.1509/jmkg.70.4.001 · Cited by 3,439
Causal Inference Using Potential Outcomes: Design, Modeling, Decisions
Rubin, D. B. (2005) · Journal of the American Statistical Association · doi:10.1198/016214504000001880 · Cited by 2,173
Cited by
Specification, evaluation, and interpretation of structural equation models
Bagozzi, R. P., & Yi, Y. (2012) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-011-0278-x · Cited by 3,735
How to improve firm performance using big data analytics capability and business strategy alignment?
Akter, S., Wamba, S. F., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016) · International Journal of Production Economics · doi:10.1016/j.ijpe.2016.08.018 · Cited by 1,624
Patil, P., Tamilmani, K., Rana, N. P., & Raghavan, V. (2020) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2020.102144 · Cited by 820
Akter, S., Fosso Wamba, S., & Dewan, S. (2017) · Production Planning & Control · doi:10.1080/09537287.2016.1267411 · Cited by 478
van der Linden, S. (2014) · European Journal of Social Psychology · doi:10.1002/ejsp.2008 · Cited by 316
Metadata
- Authors
- Iacobucci, D.
- Venue
- Journal of Consumer Psychology
- Publisher
- Wiley
- Published
- 2009-10
- Volume
- 19
- Issue
- 4
- Pages
- 673-680
- ISSN
- 1057-7408 (ISSN-L)
- 1532-7663
- OpenAlex
- W2160917214
- Cited by
- 280
- References
- 6
- FWCI
- 8.12
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
