The rapid expansion of bibliometric research has generated a large volume of descriptive “snapshot” studies that map publication trends but offer limited strategic or policy-relevant insight. Although improved database access and visualization tools have broadened participation in bibliometric analysis, methodological variability, limited reproducibility, and insufficient evaluative framing constrain its utility for research governance. We argue that bibliometric studies should not be conducted as ends in themselves, but as methods for addressing clearly defined, decision-relevant questions. We define evaluative bibliometrics as decision-oriented analysis grounded in explicit research questions, theoretically aligned indicator selection, temporal sensitivity, robustness assessment, and contextual interpretation. Key methodological considerations are examined, including database selection, search strategy design, attribution bias, normalization approaches, and science mapping parameters. We further synthesize emerging reporting frameworks and propose an evaluative extension framework that integrates decision-context specification with structured transparency requirements. By reframing bibliometrics as a decision-support discipline rather than a descriptive genre, this paper provides a methodological roadmap for researchers, editors, and institutions seeking to enhance the rigor, interpretability, and strategic relevance of bibliometric evidence.
Malcolm Koo (Thu,) studied this question.