This dashboard provides a comprehensive overview of family business research published in peer-reviewed journals ranked by the Academic Journal Guide 2024 (AJG/CABS). Publications are collected from OpenAlex. Journal quality ratings come from the AJG 2024 list.

Platform

The Family Business Research Dashboard is an open research intelligence tool developed by CeFEO — the Centre for Family Entrepreneurship and Ownership at Jönköping International Business School (JIBS) for the WIFU Foundation. The dashboard provides a comprehensive, continuously updated view of the family business research field, covering publication trends, scholarly index, research themes, and methodological patterns.

The dashboard was built using Claude Code, Anthropic’s AI-powered development environment. All data infrastructure, analytical pipelines, and front-end components were developed through iterative collaboration between the research team and Claude. The platform is supported by a relational database powered by Supabase (PostgreSQL), which stores and serves all publication records, classification taxonomies, and pre-computed dashboard views.

The Ask tab (currently in beta) provides a natural-language search engine over the dashboard’s publication database. Questions are interpreted by Claude Haiku 4.5, which translates them into calls to a small set of dedicated SQL functions running against the classified paper corpus, the scholar, institution and journal aggregates, and the L1–L3 taxonomy. The model then synthesises a concise answer with inline citations that link back to the relevant paper, scholar or journal pages on the dashboard. Results are derived from titles, abstracts and keywords processed during classification, not from full article texts. The search engine is designed to give a rapid overview of a question and surface core references; it is not a substitute for a systematic literature review.

To keep capacity fair across users, Ask is rate-limited per IP address. Questions are spaced over the course of a session, with longer pauses after every ten; the limit is thirty questions per 24-hour rolling window. For larger or systematic searches, please use the contact form.

The database is kept current through an automated pipeline that periodically queries the OpenAlex API — an open bibliographic index of over 250 million scholarly works — to detect and incorporate newly published articles. These automated updates are orchestrated by Claude Code and run on a weekly schedule, ensuring that the dashboard reflects the latest state of the field without manual intervention.

Data Collection

The collection follows a systematic, journal-by-journal approach across 1,814 AJG-ranked journals matched to OpenAlex source identifiers. Journals are processed in order of AJG rating (4★ → 4 → 3 → 2 → 1), with core family business journals processed first.

Keyword search: For each journal, the title and abstract fields are searched in OpenAlex for the keyword combinations listed below. Core journals (Family Business Review, Journal of Family Business Strategy, and Journal of Family Business Management) additionally have all papers collected regardless of keyword matches.

Deduplication: Papers are deduplicated across all journals and search terms using the unique OpenAlex work identifier.

Search keywords

Each keyword pair is searched in both the title and abstract fields. Plurals and hyphenated variants are included explicitly to account for limitations in OpenAlex's stemming.

Wildcard pattern	Expanded search terms
famil* AND own*	family ownership, family own, family-owned
famil* AND firm*	family firm, family firms
famil* AND ent*	family enterprise(s), family entrepreneur(s), family entrepreneurship, family entrepreneurial
famil* AND control*	family control, family-controlled
famil* AND leader*	family leader(s), family leadership
famil* AND manag*	family management, family manager(s), family managerial
famil* AND business*	family business, family businesses
famil* AND offic*	family office(s), family officer(s)
famil* AND CEO*	family CEO, family CEOs
famil* AND influen*	family influence, family influences
famil* AND wealth	family wealth

Journal matching

Each AJG journal was matched to its OpenAlex source identifier using ISSN codes (print and electronic). Of 1,823 AJG journals, 1,814 were successfully matched (99.5%), with 100% coverage for all journals rated 3, 4, and 4★.

Coverage

Period: 1988 – 2025.
Source: OpenAlex (openalex.org).
Journal scope: All journals listed in the Academic Journal Guide 2024 (CABS).

Relevance Filtering

Because keyword-based collection inevitably retrieves papers where terms like “family” appear in non-business contexts (e.g., family medicine, protein families, family-wise error rates, or family planning), the full dataset undergoes a thorough AI-assisted review to identify and remove false positives.

Each paper’s title, abstract, and topic metadata are evaluated against a structured set of relevance criteria. Papers with unambiguous family business signals — such as core journal provenance, explicit family firm terminology, or recognised family business topic labels — are retained automatically. Papers with clear non-business uses of the word “family” and no countervailing evidence of business context are removed. The remaining ambiguous cases are individually examined by AI, which reads each abstract and assesses whether the paper genuinely investigates family firms, family entrepreneurship, family ownership, or closely related phenomena.

Research Classification

Every paper in the database is classified along five dimensions: research design (quantitative, qualitative, mixed methods, conceptual, review, or meta-analysis), theories invoked, topics addressed, countries studied, and analytical methods employed.

AI-based extraction

The primary classification method uses Claude Haiku (Anthropic) to interpret each paper’s abstract. The model identifies the research design, extracts explicitly named theories, infers the empirical country context, and recognises the analytical techniques described. This approach captures meaning beyond surface keywords — for example, it can infer that a study of “listed firms on the Borsa Italiana” is set in Italy, or that a paper describing “structural equation modelling with partial least squares” uses PLS-SEM, even when these labels are not stated verbatim.

Pattern-based extraction

For papers that have not yet undergone AI classification, a complementary extraction pipeline uses score-based pattern matching. This system applies over 600 regex patterns per dimension, incorporating known synonyms, abbreviations, institutional markers, and contextual cues. Each potential match is scored, and only classifications exceeding a confidence threshold are retained.

Abstract recovery

A small fraction of records in OpenAlex lack abstracts, which limits classification accuracy. To address this, a dedicated script retrieves missing abstracts directly from publisher websites, extracting abstract text from article metadata and writing it back into the database.

Classification coverage

Taxonomy structure

Raw classifications are organised into a three-level hierarchy (L1 → L2 → L3) for each dimension. Level 1 provides broad macro categories, Level 2 provides intermediate groupings, and Level 3 captures the specific labels as extracted from abstracts. The dashboard allows switching between levels to explore the data at different granularities.

Index Methodology

The index measures scholarly contribution to the family business research field based on publications over a rolling 3-year window. It is published annually on January 31.

Journal quality weights

Each paper is assigned a quality weight based on its journal's AJG 2024 rating:

Papers published in unranked journals receive a weight of zero and do not contribute to author or institution scores.

Eligibility

To be included in the index, a researcher must have published at least 3 relevant papers within the 3-year window. This threshold ensures that ranked scholars demonstrate sustained engagement with the family business research field rather than occasional contributions.

Author index

Authors are scored using fractional counting. For a paper with k co-authors published in a journal with AJG weight w:

An author's total score is the sum of their fractional scores across all papers published within the 3-year window. For example, a sole-authored paper in a 4★ journal contributes 5.00 points, while a paper with 4 co-authors in a 3-rated journal contributes 0.75 points per author.

Institution index

Institutions are scored on the same fractional basis as authors, with a discount for secondary affiliations. For each paper in the window, an institution earns one credit, weighted by the strongest connection any of its authors declared on that paper:

The affiliation-type weight t equals 1.0 if any author at the institution lists it as their primary affiliation on the paper, or 0.5 if every author at the institution lists it only as a secondary affiliation. The maximum over authors means that a single primary author is enough to give the institution full weight; only purely secondary appointments are discounted.

The institution's total score is the sum of credits across all papers in the rolling window. Multiple co-authors at the same institution on the same paper do not produce additional credits — each paper contributes at most one credit per institution.

Institutions are resolved to their parent university where applicable, so business schools, research centres, and departments aggregate under the host university (for example, a paper by an author at the Centre for Family Entrepreneurship and Ownership counts toward Jönköping University). Where no parent mapping is available, the raw affiliation string is used.

Journal index

Journals are ranked by the number of family business papers published in the 3-year window. No weighting is applied.

Index example

Paper	Journal	AJG	Weight	Co-authors	Author score
Paper 1	Strategic Management Journal	4★	5	2	5 ÷ 2 = 2.50
Paper 2	Family Business Review	3	3	1	3 ÷ 1 = 3.00
Paper 3	Small Business Economics	3	3	4	3 ÷ 4 = 0.75
Total score					6.25

Name normalisation

Author names are deduplicated to account for variant spellings, particularly for prefixed surnames (e.g., “De Massis, Alfredo” and “Massis, Alfredo De”). A systematic matching process identifies and merges equivalent name records before scores are computed.

Data Sources & References

OpenAlex — Priem, J., Piwowar, H., & Orr, R. (2022). OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and concepts. arXiv preprint arXiv:2205.01833.

Academic Journal Guide 2024 — Chartered Association of Business Schools (CABS). Academic Journal Guide 2024. London: CABS.

Fractional counting — Adapted from the UT Dallas Top 100 Business School Research Rankings methodology.