From raw data to defensible evidence.
We convert research questions, field data and institutional evidence into coherent analytical outputs that withstand academic, policy and stakeholder scrutiny.
Four stages, documented at every step
Question & design
Clear framing, testable propositions, appropriate design and a written analysis plan before data is touched.
Evidence
Field instruments, sampling, data collection protocols and quality checks — primary or secondary.
Analysis
SEM, fsQCA, econometric modelling or mixed methods, chosen for the question rather than the fashion.
Decision
Policy- and institution-facing outputs with limitations, assumptions and methodological choices made explicit.
Method families we work in
SEM / CFA / PLS-SEM
Measurement models, structural paths, reliability, validity, invariance testing and substantive interpretation — applied in our own published work on fintech adoption and capability expansion.
fsQCA / NCA
Configurational analysis, necessary-condition analysis and complex causal pathways, for questions where net effects hide the real story.
Econometric modelling
ARDL bounds testing, EGARCH/TGARCH volatility modelling, time-series and macro-financial applications, benchmarked across countries in ICSSR-sponsored research.
Evidence synthesis
PRISMA-style systematic reviews, bibliometric mapping, thematic synthesis and policy summaries that make literatures usable.
Mixed methods
Survey design, qualitative coding, triangulation and integrated interpretation — including large-scale primary fieldwork (500+ respondents).
Reproducible research
Open-data replication, Zenodo records, versioned analysis files, clean tables, dashboards and figures. See our open science statement.
Quality standards
Three commitments run through every analysis. First, fit between question and method: we select techniques because the research question demands them, and we say so in writing. Second, transparency of assumptions: estimation choices, robustness checks, exclusions and limitations are documented in the deliverable itself, not hidden in an appendix. Third, reproducibility: wherever data-sharing agreements permit, outputs are delivered with the files needed to reproduce them.
These are the same standards applied in the team's peer-reviewed publications — which is the point. The discipline that survives journal review is the discipline we bring to client work.