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Evaluating the Use of Covariance‐Based Structural Equation Modelling with Reflective Measurement in Organizational and Management Research: A Review and Recommendations for Best Practice
Author(s) -
Zhang Mary F.,
Dawson Jeremy F.,
Kline Rex B.
Publication year - 2021
Publication title -
british journal of management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.407
H-Index - 108
eISSN - 1467-8551
pISSN - 1045-3172
DOI - 10.1111/1467-8551.12415
Subject(s) - structural equation modeling , covariance , work (physics) , management science , computer science , psychology , knowledge management , mathematics , statistics , engineering , machine learning , mechanical engineering
Covariance‐based structural equation modelling (CB‐SEM) with reflective measurement has been a popular data analysis tool in organizational and management research. Extensive studies and guidelines have been published on what constitutes its best practice. What is much less known is the extent to which CB‐SEM users in organizational and management research comprehend and adhere to the standards and principles behind this advanced analytical technique. In this study, we first devised an evaluation scheme to assess the quality of CB‐SEM performed in a study, and then utilized this scheme to examine 144 CB‐SEM studies published in 12 top organizational and management journals between 2011 and 2016. The evaluation of the published studies revealed a pressing need for more systematic and standardized approaches to planning, conducting and reporting CB‐SEM studies. We discussed the implication of the findings for future work.