The DOI matches its OpenAlex record; 25 of the 25 references it cites were found in a registry or an index.
12 Structural Equation Modeling in Management Research: A Guide for Improved Analysis
Abstract
A large segment of management research in recent years has used structural equation modeling (SEM) as an analytical approach that simultaneously combines factor analysis and linear regression models for theory testing. With this approach, latent variables (factors) represent the concepts of a theory, and data from measures (indicators) are used as input for statistical analyses that provide evidence about the relationships among latent variables. This chapter first provides a brief introduction to SEM and its concepts and terminology. We then discuss four issues related to the measurement component of such models, including how indicators are developed, types of relationships between indicators and latent variables, approaches for multidimensional constructs, and analyses needed when data from multiple time points or multiple groups are examined. In our second major section, we focus on six issues related to the structural component of structural equation models, including how to examine mediation and moderation, dealing with longitudinal and multilevel data, issues related to the use of control variables, and judging the adequacy of models and latent variable relationships. We conclude with a set of recommendations for how future applications of SEM in management research can be improved.
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Cited by
Becker, T. E., Atinc, G., Breaugh, J. A., Carlson, K. D., Edwards, J. R., & Spector, P. E. (2016) · Journal of Organizational Behavior · doi:10.1002/job.2053 · Cited by 989
Self-citationHaar, J. M., Russo, M., Suñe, A., & Ollier-Malaterre, A. (2014) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2014.08.010 · Cited by 965
A comparative study of cb-sem and pls-sem for theory development in family firm research
Astrachan, C. B., Patel, V. K., & Wanzenried, G. (2014) · Journal of Family Business Strategy · doi:10.1016/j.jfbs.2013.12.002 · Cited by 766
Kim, S., Vandenabeele, W., Wright, B. E., Andersen, L. B., Cerase, F. P., Christensen, R. K., Desmarais, C., Koumenta, M., Leisink, P., Liu, B., et al. (2013) · Journal of Public Administration Research and Theory · doi:10.1093/jopart/mus027 · Cited by 587
Ou, A. Y., Tsui, A. S., Kinicki, A. J., Waldman, D. A., Xiao, Z., & Song, L. J. (2014) · Administrative Science Quarterly · doi:10.1177/0001839213520131 · Cited by 561
Metadata
- Authors
- Williams, L. J., Vandenberg, R. J., & Edwards, J. R.
- Venue
- Academy of Management Annals
- Publisher
- Routledge
- Published
- 2009-01-01
- Volume
- 3
- Issue
- 1
- Pages
- 543-604
- ISSN
- 1941-6067 (ISSN-L)
- OpenAlex
- W4256144711
- Cited by
- 900
- References
- 25
- FWCI
- 23.90
- Type
- journal article
- Language
- en
- Open access
- closed
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- Williams, L. J., Vandenberg, R. J., & Edwards, J. R. (2009). 12 Structural Equation Modeling in Management Research: A Guide for Improved Analysis. Academy of Management Annals. https://doi.org/10.1080/19416520903065683
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