Impact of classification granularity on interdisciplinary performance assessment of research institutes and organizations

Purpose: Interdisciplinary research has become a critical approach to addressing complex societal, economic, technological, and environmental challenges, driving innovation and integrating scientific knowledge. While interdisciplinarity indicators are widely used to evaluate research performance, the impact of classification granularity on these assessments remains underexplored.
Design/methodology/approach: This study investigates how different levels of classification granularity - macro, meso, and micro - affect the evaluation of interdisciplinarity in research institutes. Using a dataset of 262 institutes from four major German non-university organizations (FHG, HGF, MPG, WGL) from 2018 to 2022, we examine inconsistencies in interdisciplinarity across levels, analyze ranking changes, and explore the influence of institutional fields and research focus (applied vs. basic).
Findings: Our findings reveal significant inconsistencies in interdisciplinarity across classification levels, with rankings varying substantially. Notably, the Fraunhofer Society (FHG), which performs well at the macro level, experiences significant ranking declines at meso and micro levels. Normalizing interdisciplinarity by research field confirmed that these declines persist. The research focus of institutes, whether applied, basic, or mixed, does not significantly explain the observed ranking dynamics.
Research limitations: This study has only considered the publication-based dimension of institutional interdisciplinarity and has not explored other aspects. Practical implications: The findings provide insights for policymakers, research managers, and scholars to better interpret interdisciplinarity metrics and support interdisciplinary research effectively.
Originality/value: This study underscores the critical role of classification granularity in interdisciplinarity assessment and emphasizes the need for standardized approaches to ensure robust and fair evaluations.