MAS Research is a curated network of researchers, econometricians, and methodologists—each an active specialist in their field. Your project is matched to someone with relevant expertise in your literature, methods, and publication landscape—not assigned to whoever happens to be available.
Two layers, one accountable structure. The specialist network supports the core—it never replaces it, and work is never simply handed off.
Experienced, senior methodologists who scope each engagement, communicate directly with you, coordinate any specialist contributions, and own the final quality. They stay with your project from the first conversation through to publication, so there is always one person accountable for the whole of it—never a committee to manage or a handoff to chase.
A curated network of active researchers who bring deep expertise in a specific method or domain when a project requires it. Their contributions are always selected, coordinated, and reviewed by the core—so you get specialist depth without fragmentation, and the intellectual credit for your work always stays with you.
The network spans the full toolkit of management and allied-studies research—organized around the intersection of method and domain, so the person on your project knows both.
Cross-sectional, time-series, and advanced panel specialists—from ARDL and VAR to System GMM and CS-ARDL—focused on defensible identification and diagnostics.
Quasi-experimental design and policy evaluation—difference-in-differences, regression discontinuity, IV, and synthetic control—with assumptions tested, not assumed.
Volatility, risk, and asset-pricing specialists across the GARCH family, spillover and connectedness models, and event studies.
Time-series and predictive-modelling specialists who validate honestly out-of-sample, from ARIMA and MIDAS to hybrid econometric-ML approaches.
Predictive, explainable, and causal machine learning, and text-as-data—built for interpretation and reproducibility, not just accuracy.
CB-SEM and PLS-SEM, factor analysis, IRT and Rasch, measurement invariance, and scale development—measurement established before structure.
Multilevel, growth, and cross-lagged models—including RI-CLPM and continuous-time methods—for data observed over time and nested in groups.
Spatial econometrics, geographically weighted regression, and regional convergence and inequality analysis.
Grounded theory, thematic and content analysis, case study, and configurational methods (QCA, fsQCA)—held to the same rigour as quantitative work.
RCTs, lab, field, and survey experiments, conjoint analysis, power analysis, and behavioural economics and finance, designed for clean identification.
Systematic reviews, meta-analysis, and evidence synthesis to PRISMA standards, including network and diagnostic meta-analysis.
Science mapping, citation and co-word analysis, and research-intelligence analysts working in VOSviewer, Bibliometrix, and CiteSpace.
Optimization, multi-criteria decision analysis (AHP, TOPSIS, DEMATEL), data envelopment analysis, and network analysis specialists.
CGE, DSGE, input-output, microsimulation, and agent-based modelling for policy, impact, and scenario analysis.
AACSB and EQUIS readiness, research-productivity analytics, and institutional benchmarking specialists.
Journal-selection, methodology-review, and reviewer-response experts who take sound research through to acceptance.
Method and domain change from project to project; these qualifications do not.
Not people who once learned a technique, but specialists who use their methods on real problems and follow their field's evolving literature—so your analysis meets current standards, not those of a decade ago.
Doctoral-level training and a substantive record in their discipline. We match the depth of the specialist to the demands of the problem, not to whoever happens to be available.
We select for the ability to teach, not just to execute. A result you cannot understand is a result you cannot own, so clear explanation is a core requirement, not a bonus.
Willing to tell you a result does not hold, that a simpler method fits better, or that the data cannot answer the question. That honesty is the foundation of trustworthy research support.
They know the debates, conventions, and journals of your discipline—so the work reads as that of someone who belongs in the conversation, which is half the battle in review.
Every member of the network is bound by the same strict confidentiality. Your unpublished data and ideas are shared only with the specific people working on your project.
A clear, accountable structure—whether the work is handled entirely by the core or with specialist-network support. You are told who will work on your project, and their relevant expertise, before any work begins.
Your research question, data, subject domain, and analytical requirements are reviewed in detail before anything is scoped—so the match is based on what the work actually needs.
A named research strategist takes ownership of the project and becomes your single point of contact, accountable for the whole engagement.
Where the project needs deeper method or domain knowledge, the core selects the right specialist from the network—matched to your field, not on rotation.
Before anything reaches you, a second methodologist independently checks the analysis—the objections a referee would raise, caught in-house first.
Specialist contributions are always coordinated and reviewed by the core. Accountability stays in one place, from first contact to final delivery.
A named lead owns your project end to end.
The right expertise, selected per project.
A second methodologist checks every delivery.
Agreements in place before any data is shared.
Only the people working on your project see it.
The same lead stays with you throughout.
Documented, re-runnable work you keep.
The credit for your research stays with you.
Tell us your research question and the method it needs—we'll match you with someone who genuinely knows the field, and tell you who they are before any work begins.