The anatomy of an award-winning meta-analysis: Recommendations for authors, reviewers, and readers of meta-analytic reviews

verifiedmedium profile · Journal of International Business Studies · 2021

Steel, Piers; Beugelsdijk, Sjoerd; Aguinis, Herman

10.1057/s41267-020-00385-z · CrossRef: verified

How this was studied

paradigm: positivistpurpose: explanatory causaldesign: meta analytic synthesisidentification: nonetime: cross sectionaldata: quantitative survey

A meta-analytic synthesis — it pools many primary studies rather than running a single design, so there is no single-study diagram.

analysis: meta analysis · validity (validity): internal unclear · external addressed · construct addressed · statistical addressed · classifier confidence 0.8

What this article reports

The findings we extracted from this work, normalized into Principia’s relationship form (X → Y). Each feeds the synthesized models below.

cultural diversitycreativity

r = 0.18 · grade A · unverified

Models this article informs

The meta-analytic priors this article contributes evidence to — its place in the broader synthesis.

In the authors’ words

The article’s own abstract.

Abstract Meta-analyses summarize a field’s research base and are therefore highly influential. Despite their value, the standards for an excellent meta-analysis, one that is potentially award-winning, have changed in the last decade. Each step of a meta-analysis is now more formalized, from the identification of relevant articles to coding, moderator analysis, and reporting of results. What was exemplary a decade ago can be somewhat dated today. Using the award-winning meta-analysis by Stahl et al. (Unraveling the effects of cultural diversity in teams: A meta-analysis of research on multicultural work groups. Journal of International Business Studies, 41(4):690–709, 2010) as an exemplar, we adopted a multi-disciplinary approach (e.g., management, psychology, health sciences) to summarize the anatomy (i.e., fundamental components) of a modern meta-analysis, focusing on: (1) data collection (i.e., literature search and screening, coding), (2) data preparation (i.e., treatment of multiple effect sizes, outlier identification and management, publication bias), (3) data analysis (i.e., average effect sizes, heterogeneity of effect sizes, moderator search), and (4) reporting (i.e., transparency and reproducibility, future research directions). In addition, we provide guidelines and a decision-making tree for when even foundational and highly cited meta-analyses should be updated. Based on the latest evidence, we summarize what journal editors and reviewers should expect, authors should provide, and readers (i.e., other researchers, practitioners, and policymakers) should consider about meta-analytic reviews.

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