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Purpose

The aim of this study is to gain a deeper understanding of the samples used in published studies on knowledge management (KM) in small- and medium-sized enterprises (SMEs), particularly with regard to the company sizes, geographic origin and sectors studied. Careful sample selection and the disclosure of this information are crucial for scientific work and progress. Errors or omissions can lead to incorrect conclusions, as certain companies may be under-represented, over-represented or even completely excluded. A focus on sample diversity is especially relevant for KM in SMEs research due to the heterogeneity of these companies.

Design/methodology/approach

To identify relevant studies on sample diversity in existing research on KM in SMEs, the authors consulted papers from a recently published systematic literature review on this topic and supplemented them with current empirical studies. For this, the authors used a systematic literature search and the criteria used at that time. In total, this study includes 163 peer-reviewed papers published between 2001 and 2025 in reputable journals and retrieved from the Web of Science database.

Findings

The findings show that the examined research is limited not only in terms of the diversity of the companies studied but also in terms of the accuracy of the companies examined. There is a strong bias towards studies from Europe, with micro enterprises being under-represented and medium-sized enterprises over-represented. Many studies are unspecific regarding the nature of the firms studied or the industry. A conceptual framework is presented that encompasses the three contexts of company size, geographical origin and industry and highlights the necessity of a rigorous approach to firm selection and reporting in KM in SMEs research.

Originality/value

The authors are unaware of any comparable studies that explicitly highlight the importance of sample diversity and the associated disclosure for research on KM in SMEs. Therefore, they consider their study foundational work intended to enable more robust scientific research in this important field of study.

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