Abstract
The use of Structural Equation Modeling (SEM) in behavioral science and particularly in Information Systems (IS) research is growing rapidly. By using SEM, researchers can theoretically represent and empirically test models that contain latent variables. Despite the great interest in the use of SEM in IS research, sufficient guidelines have not been established for addressing the criteria for selecting either Covariance Based SEM (CB-SEM) or Partial Least Square SEM (PLS-SEM). Our study fills this gap by proposing a framework to use when selecting the appropriate form of SEM to use. We also highlight the various psychometrics properties and the statistical tests required to be reported in various stages of SEM Analysis. Our framework is then applied to a sample of top tier IS publications which utilized SEM. Findings indicate that many of these studies did not clearly justify and explain their type of research as exploratory or confirmatory in nature, nor did they use the proper SEM method. Moreover, most of the articles failed to accurately report the psychometric properties of their measurement model and the required statistical tests. The framework proposed in this paper has the potential to significantly enhance the rigor and quality of future IS research which utilizes SEM.
Recommended Citation
Aghakhani, Navid; Asllani, Beni; and Allen, Richard S.
(2019)
"A Framework for Using Structural Equations Modeling in Information Systems Research,"
Journal of Business, Industry, and Economics: Vol. 24, Article 6.
Available at:
https://roar.una.edu/jobie/vol24/iss1/6