Bibliometrics

Bibliometric & Citation Analysis Services

A field’s literature is itself data: who cites whom, who works with whom, and which ideas anchor the conversation. Bibliometric and citation analysis maps that structure quantitatively—revealing the intellectual foundations, influential works, and collaboration patterns of a research area. MAS Research delivers rigorous, reproducible bibliometric studies.

Bibliometric and citation analysis uses quantitative methods to study a body of publications—measuring influence through citation analysis, uncovering intellectual structure through co-citation and bibliographic coupling, and mapping research communities through co-authorship and collaboration networks. Built on databases such as Scopus and Web of Science, it reveals the foundations, key works, and social structure of a field.

Citation & co-citation analysis Bibliographic coupling & networks Co-authorship & collaboration VOSviewer, Bibliometrix, CiteSpace

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Citation network community A community B

What bibliometric & citation analysis does

Every research field leaves a quantitative trace: a network of publications linked by citations, authored by people who collaborate in patterns, built on a shared base of foundational works. Bibliometric analysis (and the closely related scientometrics) studies this trace with quantitative methods—turning thousands of publication records into a map of a field’s structure, influence, and development that no amount of manual reading could produce at scale.

Several complementary techniques reveal different facets. Citation analysis measures influence—which works, authors, journals, and institutions are most cited. Co-citation analysis (works cited together by later papers) uncovers the intellectual foundations and schools of thought a field is built on, while bibliographic coupling (works that share references) groups current research by shared foundations, showing the field’s present structure. Citation networks trace how ideas flow and build on one another over time. And on the social side, co-authorship and collaboration networks map who works with whom—across authors, institutions, and countries—revealing the research communities and the connectors that hold a field together.

When to use it, and why it matters

Bibliometric analysis is valuable whenever you need an evidence-based, big-picture view of a research area: to open a literature review or thesis with a rigorous mapping of the field, to identify the seminal works and emerging players, to position a body of work, to understand collaboration structures, or—at the institutional level—to evidence research performance and impact. That last use connects directly to our AACSB and EQUIS accreditation support and institutional research, where faculty-research and citation analytics are central.

It also complements narrative and systematic review: where a meta-analysis synthesises findings, bibliometrics maps the structure of the literature producing them—increasingly combined in hybrid “systematic + bibliometric” reviews. One principle underpins credible work here: a bibliometric study is only as good as the data behind it, so careful database selection and data cleaning are not preliminaries but the foundation.

At a glance

What each technique reveals

Bibliometric techniques and what they show
Technique	Links works by	Reveals
Citation analysis	Who cites whom	Influence — key works, authors, journals
Co-citation analysis	Being cited together	Intellectual foundations & schools of thought
Bibliographic coupling	Shared references	Current research fronts & structure
Citation networks	Directed citation links	How ideas flow and build over time
Co-authorship networks	Writing together	Collaboration communities & connectors

Methodology

Doing bibliometrics rigorously

The credibility of a bibliometric study is decided at the data stage, before any network is drawn. The database matters: Scopus and Web of Science have different coverage, so the choice (or a justified combination) shapes the results, and it must be stated. The search and inclusion strategy—queries, filters, time span, document types—should be transparent and reproducible, ideally documented against review-reporting guidance. And data cleaning is decisive: author-name disambiguation (same author, different spellings), merging institution variants, and reconciling reference formats are laborious but essential, because unclean data produce misleading networks. We treat this groundwork as the core of the work, not an afterthought.

On the analysis side, the techniques are applied with their assumptions in view and the results read judiciously. Network clustering identifies communities, but the number and interpretation of clusters involve judgement—an algorithmically detected cluster is not automatically a meaningful sub-field, so we interpret with domain knowledge rather than at face value. Citation counts reflect visibility and influence, not quality or correctness—they are shaped by field size, age, database coverage, and citation practices—so we use them as indicators to be interpreted, never as verdicts. We report the database, search strategy, cleaning steps, and analytical choices in full, so the study is transparent and reproducible.

Citations measure influence, not quality—and the data decide the result. Citation counts reflect visibility, field size, and age, not correctness, so they are interpreted, not treated as verdicts. And a bibliometric map is only as sound as the database choice and the name/affiliation cleaning behind it.

Software

We deliver bibliometric analysis in the established, reproducible tools of the field—VOSviewer and CiteSpace for science mapping and network visualisation, and bibliometrix/Biblioshiny in R plus Python workflows for data processing and analysis—with documented database selection, cleaning, and analytical choices, and versioned code where code is used.

How we work

How we deliver a bibliometric study

Bibliometric analysis sits within our wider bibliometrics practice and connects to our institutional research—so the data are sound and the maps are interpreted with care.

We start from the research question and scope—a field, a topic, an author set, or an institution—and design a transparent, reproducible search and database strategy. We extract and rigorously clean the data (disambiguating authors, reconciling affiliations and references), then run the appropriate analyses: citation and co-citation, bibliographic coupling, citation and collaboration networks, with clustering to identify communities.

Reporting documents the database, search, and cleaning, the techniques used, and the findings—influential works and authors, intellectual structure, and collaboration patterns—with clear network visualisations and honest interpretation of what the metrics do and do not mean.

You receive the bibliometric results and network maps (citation, co-citation, coupling, co-authorship), the influence and structure findings, the full documentation of database, search, and cleaning for reproducibility, the visualisations, and reproducible analytical files or code (where appropriate and permitted)—ready to anchor a review, thesis chapter, or institutional report.

Where we apply it

Bibliometrics across Management & Allied Studies

Mapping a literature’s structure and influence is valuable across every field and at the institutional level—so bibliometrics applies widely across the disciplines we serve.

Literature Reviews & Theses

Opening a review, dissertation, or research programme with a rigorous, evidence-based map of the field’s structure and foundations.

Research Impact & Accreditation

Evidencing faculty-research influence and institutional research performance—directly supporting AACSB and EQUIS preparation.

Management & Business Research

Mapping sub-fields, foundational works, and emerging themes across management, marketing, and strategy literatures.

Economics & Finance

Tracing intellectual structure and research fronts in economics and finance scholarship.

Social & Interdisciplinary Fields

Mapping emerging and interdisciplinary areas where the literature is fast-moving and hard to survey by hand.

Research Policy & Institutions

Collaboration-network and research-profile analysis for departments, institutions, and funders.

FAQ

Bibliometric analysis: common questions

What is bibliometric analysis?

Bibliometric analysis uses quantitative methods to study a body of publications—measuring influence through citation analysis, uncovering intellectual structure through co-citation and bibliographic coupling, and mapping research communities through co-authorship and collaboration networks. Built on databases such as Scopus and Web of Science, it turns thousands of publication records into a map of a field’s structure, influence, and development. It is closely related to scientometrics.

What is the difference between co-citation and bibliographic coupling?

Both link documents, but in opposite directions in time. Co-citation links two works that are cited together by later papers—it reflects how the field perceives their relationship and reveals intellectual foundations and schools of thought, and it evolves as citing behaviour changes. Bibliographic coupling links two works that share references—it is fixed at publication and groups current research by shared foundations, revealing present-day research fronts. Co-citation looks back to foundations; coupling maps the current structure.

Which database should I use—Scopus or Web of Science?

They have different coverage—of journals, fields, and time spans—so the choice affects the results and should be justified rather than defaulted to. For some studies a single database is appropriate; for others, combining sources (with careful de-duplication) gives better coverage. The right choice depends on the field and question, and we document it transparently because it is part of what makes a bibliometric study reproducible.

Do citation counts measure research quality?

No. Citation counts measure visibility and influence, not quality or correctness. They are shaped by field size, the age of a work, database coverage, and disciplinary citation practices—and even critiques generate citations. We use citation metrics as indicators to be interpreted in context, alongside the network structure and domain knowledge, never as a direct verdict on the merit of a work.

What software do you use?

The established tools of the field: VOSviewer and CiteSpace for science mapping and network visualisation, and bibliometrix (with its Biblioshiny interface) in R, plus Python workflows, for data processing and analysis. The choice depends on the analysis; what matters most is not the tool but the quality of the underlying data—careful database selection and cleaning—and transparent documentation of every step.

How does bibliometrics support accreditation?

Research impact and faculty intellectual contributions are central to business-school accreditation, and bibliometric analysis is a rigorous way to evidence them—citation and publication analytics, research-profile mapping, and benchmarking against peers. This connects directly to our AACSB and EQUIS accreditation support and institutional-research work, where such evidence underpins the self-evaluation. As always, the metrics are presented as interpreted indicators, not as quality verdicts.

Mapping a field or evidencing research impact?

Whether you are opening a review with a rigorous field map or evidencing research influence for accreditation, we deliver bibliometric and citation analysis built on carefully selected, cleaned data—with network maps and honest interpretation of what the metrics mean.

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