“Making Theoretical Contributions with Meta‑Analysis”
DETAILS
Call for Papers – Special Issue: “Making Theoretical Contributions with Meta‑Analysis”
Journal: Human Resource Management Review
Publisher: Elsevier
Impact Factor: 13.0 | CiteScore: 24.7
Submission deadline: 01 June 2026
Overview
This special issue explores how meta‑analysis can advance, refine, and generate theory in human resource management (HRM). While meta‑analyses are often seen as tools for summarising existing knowledge, this collection aims to elevate them as engines for theoretical innovation, extension, and critique in the HRM field.
The journal explicitly requires meta‑analytic submissions to make a clear conceptual or theoretical contribution rather than merely providing effect‑size estimates. The issue welcomes both exemplar empirical meta‑analyses and conceptual/methodological papers that guide future researchers on how to use meta‑analysis for theory building.
Core Themes
1. Meta‑analyses that advance HRM theory
Studies that develop, test, challenge, or extend theory in HRM subdomains (e.g., selection, performance management, leadership, HR systems, well‑being, diversity, and inclusion).
Use of meta‑analysis, MASEM (meta‑analytic structural equation modelling), meta‑regression, and other advanced techniques to uncover boundary conditions, mediators, and moderators implied by theory.
Work that moves beyond “what is the effect size” to “what does this tell us about the underlying mechanisms, assumptions, and scope of the theory?”
2. When and why to use meta‑analysis
Conceptual and methodological papers that clarify:
What distinguishes a meta‑analysis with theoretical impact from one that mainly summarises.
When meta‑analysis is preferable to other forms of systematic review or empirical analysis (e.g., for large literatures, heterogeneous samples, or complex constructs).
Guidance on designing meta‑analyses explicitly for theory building, including choices about constructs, samples, effect‑size transformation, and model specification.
3. Methodological improvements for theory‑oriented meta‑analysis
Critical reflections on limitations of current meta‑analytic practice (e.g., publication‑bias sensitivity, measurement heterogeneity, overlooked contingencies) and how to overcome them to strengthen theoretical inference.
Proposals for protocols, reporting standards, and best practices tailored to theory‑driven meta‑analysis in HRM and organisational behaviour.
Reflections on the balance between “testing” versus “developing/generating” theory with meta‑analytic evidence.
4. Meta‑analysis as a tool for cumulative science
Reviews that assess how past meta‑analyses have shaped HRM knowledge, and where they have missed opportunities to influence theory.
Discussions on how to link meta‑analysis with primary research to create a cumulative, theory‑driven HRM science.
Submission Track Options
Exemplar theoretical meta‑analyses
Meta‑analytic HRM studies that explicitly:
Develop, test, or extend theory (rather than simply updating prior reviews).
Use mediators, moderators, or MASEM to reveal contingent or mechanistic patterns.
Propose new frameworks, boundary conditions, or conceptual re‑interpretations based on the aggregated evidence.
Papers on advancing theory through meta‑analysis
Conceptual reviews or methodological frameworks explaining how to design meta‑analyses for theoretical impact.
Critical reflections on journal expectations, common pitfalls, and best practices for theoretical‑oriented meta‑analysis in HRM.
Proposals for checklists, templates, or decision‑paths that guide researchers through the meta‑analytic process with theory‑building as the goal.
Submission Details
Submission window: 1 May – 31 May 2026.
Submission platform: Human Resource Management Review Editorial Manager:
https://www.editorialmanager.com/HUMRES/default.aspxWhen submitting, select article type: “VSI: Theoretical Contributions in Meta‑Analysis”.
All manuscripts must follow the journal’s Guide for Authors:
https://www.sciencedirect.com/journal/human-resource-management-review/publish/guide-for-authorsSubmissions will undergo double‑blind peer review under the journal’s standard procedures.
For questions, contact the Guest Editors (contact details are provided in the call).
Guest Editors
Patrick E. Downes, University of Kansas, USA
Lindsey M. Greco, Oklahoma State University, USA
Why This Issue Matters
Meta‑analysis is central to HRM’s evidence‑based identity, but its theoretical potential is still under‑leveraged.
By clarifying how to use meta‑analysis for theory development, testing, and extension, this special issue aims to help the field move beyond simple “summary” work and toward systematic, cumulative, and conceptually rich knowledge about the HRM phenomena that matter most.
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