PhD Researchers & Doctoral Candidates
A bibliometric review that doubles as a strong standalone paper and an evidence-based justification for your thesis's gap.
Research Methods
Bibliometric & Scientometric Research
Before you can add to a field, you have to see it clearly. We map the structure of a literature—its influential works, its thematic clusters, how it has evolved, and where the real gaps sit—turning thousands of papers into an evidence-based picture that positions your own contribution.
Citation & co-word analysis
Science & thematic mapping
VOSviewer · Bibliometrix · CiteSpace
Reproducible, journal-ready
Sample output
theme A
theme B
Overview
A map of the field, not a reading list
A traditional literature review reflects what one team happened to read. A bibliometric analysis reflects the field itself—its citation structure, its thematic clusters, and its trajectory—derived systematically from thousands of records rather than a curated sample. That objectivity is exactly why editors increasingly value it, and why it is such a strong way to open a research agenda or justify a gap.
The credibility, though, is in the craft. The database choice (Scopus versus Web of Science) changes the results; author names must be disambiguated; keyword variants merged; duplicates removed. Skip that cleaning and the prettiest network map is built on noise. We treat data preparation as the core of the work, documented and reproducible, before any visualization is produced.
From there we build the analysis your question needs—co-citation and bibliographic coupling for intellectual structure, keyword co-occurrence and thematic evolution for how topics shift, collaboration networks for who works with whom—and interpret it, so the deliverable is a genuine argument about the field, not a gallery of clusters.
Who We Work With
For anyone mapping or entering a field
If you need to see the shape of a literature—to publish a review or to position new work—this is the right desk to write to.
Faculty & Academic Researchers
Science-mapping reviews to open a research agenda, frame a special issue, or consolidate a field you work in.
Journal Editors & Special-Issue Leads
Field overviews and trend analyses that set the agenda for a call for papers or an editorial.
Research Institutes & Think Tanks
Landscape and trend analysis to see where a research area is heading before committing a program to it.
Universities & Research Offices
Research-productivity and collaboration mapping to inform strategy and benchmarking.
Review & Synthesis Teams
Groups running systematic reviews who want a bibliometric layer for breadth and objectivity.
Capabilities
The full bibliometric toolkit
Organized by what you want to see in the literature—structure, themes, or collaboration. If your study needs a method not listed here, ask—this is the core, not the boundary.
Who builds on whom
The citation-based methods that reveal a field's foundational works and its intellectual lineages.
- Bibliometric analysis
- Scientometric analysis
- Citation analysis
- Co-citation analysis
- Bibliographic coupling
- Citation networks
What the field is about & where it's going
Co-word and mapping methods that surface themes, track their evolution, and identify emerging topics.
- Keyword co-occurrence
- Thematic mapping
- Thematic evolution
- Science mapping
- Research trend analysis
Who works together, read in depth
Collaboration networks and the systematic-plus-bibliometric review format that pairs breadth with synthesis.
- Co-authorship analysis
- Collaboration networks
- Systematic + bibliometric reviews
- VOSviewer
- Bibliometrix / Biblioshiny
- CiteSpace
- R / Python workflows
How the Analysis Works
Six steps from search to science map
A transparent sequence where the unglamorous middle—data cleaning—is treated as the most important step. Nothing is a black box.
Steps are adapted to your goal: intellectual structure vs. thematic evolution vs. collaboration, and whether the output is a standalone review or a bibliometric layer within a systematic one. We confirm the scope with you before extraction.
-
1
Scope
Define the research question, the field boundary, the database, and the time window that the analysis will rest on.
Inputs: question · field · database · time window
-
2
Search
Build and run a reproducible query in Scopus or Web of Science, and export the full bibliographic records.
Sources: Scopus · Web of Science · documented query
-
3
Clean
Disambiguate authors, merge keyword variants, and remove duplicates—the step that determines whether the map is signal or noise.
Steps: author disambiguation · keyword merge · dedup
-
4
Analyze
Run the citation, co-word, and network analyses your question requires, with appropriate thresholds and clustering.
Methods: co-citation · coupling · co-word · networks
-
5
Map
Produce and refine science maps, thematic and evolution plots, and collaboration networks that are legible, not cluttered.
Tools: VOSviewer · Bibliometrix · CiteSpace
-
6
Interpret
Turn the maps into an argument about the field—its structure, gaps, and trajectory—with reproducible data and scripts.
Output: figures · interpretation · methods · data & scripts
Rigor by default
The checks that keep a map honest
A network diagram can look authoritative and mean nothing. The data discipline behind a credible bibliometric study is standard on every engagement.
Included on every project
- Documented search query and database choice
- Author-name disambiguation and keyword harmonization
- Deduplication and transparent inclusion criteria
- Justified thresholds and clustering choices
- Reproducible dataset and scripts you keep
What You Receive
Every engagement, delivered in full
Not a black-box result and a number, but a complete, documented package you can submit, defend, and reproduce.
- Documented search query and cleaned dataset
- Performance analysis (top authors, sources, papers)
- Co-citation and coupling maps of intellectual structure
- Thematic map and thematic-evolution plots
- Collaboration and co-authorship networks
- Interpretation of clusters, gaps, and trends
- High-resolution, publication-ready figures
- Reproducible Bibliometrix / R or Python scripts
- Journal-ready methodology and results sections
Where this fits
Part of a larger arc
A bibliometric study is strongest at the start of a research program—defining the gap that the rest of the MAS Research Model then sets out to fill.
Research Design & Planning
Identification strategy, power, and specification decided before estimation begins.
Explore methodsStatistical & Methodological Audit
An independent check of assumptions, specification, and reproducibility before submission.
Explore auditPublication & Research Support
Methods and results reporting, journal selection, and reviewer-response support.
Explore support
FAQ
Common questions
Answers to what most researchers and project leads ask before we begin a bibliometric or science-mapping engagement.
A systematic review appraises the content of studies to answer a question; a bibliometric analysis measures the structure of a literature—who cites whom, which themes cluster, how a field has evolved—using citation and co-word data rather than reading every paper. The two are complementary, and a combined systematic-plus-bibliometric review is an increasingly popular and publishable format.
It depends on your field's coverage, and the choice materially affects the results, so we make it deliberately and document it. Scopus and Web of Science index different journals; we select based on coverage of your topic, explain the trade-off, and are transparent about the search date and query so the analysis is reproducible.
The intellectual structure and trajectory of a field: its most influential works and authors, the thematic clusters and how they have shifted over time, emerging and declining topics, collaboration patterns, and—most usefully for your own work—where the genuine gaps are. It turns a vague sense of a literature into an evidence-based map.
VOSviewer and CiteSpace for network visualization, and Bibliometrix / Biblioshiny in R for the full analytic workflow, supplemented with custom R or Python where a bespoke metric or figure is needed. You receive the cleaned dataset and reproducible scripts, not just static images.
Either. Data cleaning is often the most consequential and time-consuming stage—disambiguating author names, merging keyword variants, removing duplicates—and we can run the full pipeline from search string to figures, or take an exported dataset and handle the analysis and mapping.
Yes. Bibliometric and science-mapping reviews are a well-established article type in management, business, and economics journals, and are often used to open a special issue or frame a research agenda. We build them to the reporting standards those journals expect.
Yes—this hybrid is one of our most requested formats. The bibliometric layer maps the structure of the field objectively, while the systematic layer reads and synthesizes the key clusters in depth, giving a review both breadth and interpretive substance.
Yes, and it is the best time. The search query, the database, the time window, and the unit of analysis all shape what a bibliometric study can conclude—settling them up front, with a clear research question, prevents a large dataset that answers nothing in particular.
Related Expertise
Often paired with econometrics
Mapping a research field?
Tell us the topic and roughly its boundaries—we'll tell you the right database, the analyses that fit, and what a bibliometric study can reveal.