Use of structural equation modeling in operations management research: Looking back and forward ☆

By Rachna Shah, Susan Meyer Goldstein. 2006

1,043 citations recorded by the source corpus.

Subfields: Management Information Systems, Organizational Behavior and Human Resource Management

View Paper: https://www.semanticscholar.org/paper/8bfd00303821bd1f7bdf086dc3d0765f30b4dc1f

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In Management Information Systems

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Citations in the corpus

How to Write Up and Report PLS Analyses (2010, background): “As an example, Shah and Goldstein (2006), in their review of 93 SEM-based articles in operations management, found an average of 4.4 latent variables per model with a range of 1–12 latent variables, and between 3 and 80 manifest variables with a mean of 14.”
Celebrity endorsement, self-brand connection and consumer-based brand equity (2015, methodology): “Further, our chosen estimation method of maximum-likelihood is purportedly unbiased to moderate violations of normality (Shah and Goldstein, 2006).”
Performance evaluation and a flow allocation decision model for a sustainable supply chain of an apparel industry (2015, methodology): “The weights estimated by SEM are therefore considered more valid than weights obtained through any other approach (Shah and Goldstein, 2006).”
Editor's comments: a critical look at the use of PLS-SEM in MIS quarterly (2012, result): “By comparison, in their review of CB-SEM studies, Shah and Goldstein (2006) report an average of 4.7 latent variables and 16.3 indicators per model.”
Defining and developing measures of lean production (2007, background): “Because many fit indices are affected by sample size (e.g. GFI, NFI and AGFI) and others by the ratio of manifest variables per latent variable (e.g. NNFI and CFI), Shah and Goldstein (2006) suggest reporting a broad set of fit indices.”
Dynamic Capability Building in Service Value Networks for Achieving Service Innovation (2009, methodology): “In SEM, there is no single test of significance that can absolutely identify a correct model based on the sample data (Schumacker & Lomax, 1996; Holmes-Smith et al., 2005; Shah & Goldstein, 2006).”
A new criterion for assessing discriminant validity in variance-based structural equation modeling (2015, methodology): “Specifically, the Fornell-Larcker criterion is a standard approach to assess discriminant validity in covariance-based SEM (Shah and Goldstein 2006; Shook et al. 2004).”
Lean Manufacturing, Non-Financial Performance Measures, and Financial Performance (2009, neutral): “indices for small sample sizes (Shah and Goldstein, 2006).”
Impact of environmental regulations on innovation and performance in the UK industrial sector (2010, methodology): “While SEM has been used by researchers for a long time, it has started to receive the attention of empirical Operations Management researchers only recently ( Shah and Goldstein, 2006”
Covariance-Based Structural Equation Modeling in the Journal of Advertising: Review and Recommendations (2017, background): “We do not intend to detail how to do SEM, as other reviews or texts provide adequate, although sometimes overlooked, descriptions of the procedure (see Bagozzi and Yi 2012; Byrne 2016; Iacobucci 2010; Shah and Goldstein 2006).”
Toward a subjective measurement model for firm performance (2012, neutral): “Close to normal distributions and a sample size of 111 observations allowed the use of maximum likelihood estimation, recommended for samples between 100 and 150 cases (Hair, Anderson, Tatham, & Black, 2005), and small deviations from normality (Shah & Goldstein, 2006).”
Non-normality of Data in Structural Equation Models (2008, methodology): “Following the principles suggested by Bollen and Long (20), Hoyle and Panter (21), and Shah and Goldstein (22), we report the model fit indices from several different index families.”
Impact of Information Technology Integration and Lean/Just-In-Time Practices on Lead-Time Performance (2006, methodology): “Other fit indices include normed fit index (NFI), nonnormed fit index (NNFI), and comparative fit index (CFI) (Shah & Goldstein, 2006).”