When Can Bibliometric Evidence Be Trusted? Developing a Conditional Robustness Theory for Research Evaluation in Business Research

Quand peut-on faire confiance aux données bibliométriques ? Développement d’une théorie de la robustesse contingente pour l'évaluation de la recherche en sciences de gestion

Kaïs Ferjani ()
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Kaïs Ferjani: UMA - Université de la Manouba [Tunisie]

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Abstract: Bibliometrics has become one of the most widely used tools in management and accounting research, yet the method that measures scholarly impact is rarely asked to justify its own statistical footing. This paper turns the bibliometric lens on bibliometrics itself. Drawing on a Scopus and Web of Science corpus assembled through a PRISMA-guided identification and screening process (6,144 unique records, 763 retained at the eligibility stage), we combine science mapping (co-word analysis, thematic mapping and thematic evolution, co-citation analysis and a historiographic map) with a systematic reading of the 57 most influential works in the field to ask a single question: is bibliometrics a statistically robust and econometrically reliable research method, and why do some journals and researchers accept it while others do not? We find that the field's own most-cited literature is dominated by critical and nuanced positions (33 of 57 works) rather than unconditional endorsement (8 of 57), converging instead on a small set of recurring validity threats spanning data coverage, indicator construction, citer behaviour and research governance. From this evidence we develop the Contingent Theory of Bibliometric Robustness, which reframes bibliometric robustness not as an inherent property of citation counts but as an achievement that depends on triangulation with peer judgement, field normalisation, transparent construction rules and adequate sample scale. We discuss the implications of this model for research evaluation in accounting, finance and management, where journal-ranking lists such as the ABS Academic Journal Guide, the ABDC list and the Financial Times 50 sit at the exact intersection of indicator construction and institutional governance, and we close with a nine-point research agenda derived directly from the threats identified.

Keywords: systematic literature review; accounting and management research; journal ranking; statistical robustness; research evaluation; scientometrics; bibliometrics; bibliometrics scientometrics research evaluation statistical robustness systematic literature review journal ranking accounting and management research (search for similar items in EconPapers)
Date: 2026-07-01
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