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Using meta‐analytic structural equation modeling to advance strategic management research: Guidelines and an empirical illustration via the strategic leadership‐performance relationship
Author(s) -
Bergh Donald D.,
Aguinis Herman,
Heavey Ciaran,
Ketchen David J.,
Boyd Brian K.,
Su Peiran,
Lau Cubie L. L.,
Joo Harry
Publication year - 2016
Publication title -
strategic management journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 11.035
H-Index - 286
eISSN - 1097-0266
pISSN - 0143-2095
DOI - 10.1002/smj.2338
Subject(s) - structural equation modeling , strategic leadership , strategic management , bivariate analysis , strategic control , strategic thinking , empirical research , knowledge management , strategic planning , strategic alignment , strategic financial management , business , management , process management , management science , computer science , marketing , economics , mathematics , statistics , machine learning
This paper demonstrates how meta‐analysis can be combined with structural equation modeling ( MASEM ) to address new questions in strategic management research. We review this integration, describe its implementation, and compare findings from bivariate meta‐analyses, a direct‐effect structural equations model, and two mediating frameworks using data on the strategic leadership and performance relationship. Results drawn from 208 articles that collectively included data on 495,638 observations demonstrate the new insights available from MASEM while also suggesting a revision to conventional thinking on strategic leadership. Whereas some theories posit that boards of directors influence firm performance through monitoring and disciplining the top management team, MASEM provides more support for the view that boards mediate the top management teams' decisions. Implications for applying MASEM in strategic management are offered . Copyright © 2014 John Wiley & Sons, Ltd.