This study aims to discuss the taxonomic accuracy of organizational categories for small businesses and new ventures through an analysis of the cohesion of the constituent entities in relation to the age and size dimensions.
To analyze the information, the content analysis technique was applied to a text corpus of 285 articles published from 2019 to 2022 in the main journals that are specialized in small businesses and new ventures. For the data analysis, the chi-square test, the one-proportion Z-test and binary logistic regression were performed.
The accuracy of the organizational categories in the articles of the sample was considered “reasonable to poor” and thus biased due to the wide range of values identified for the size and age dimensions of the entities that they combine. The analysis of the causes led to the creation of a taxonomy with four types of errors in the categorization process, three of which were recurrent among the articles in the sample.
Irrespective of the term employed, whether compound or otherwise, articles on small businesses and new ventures require critical thinking on the part of readers to question to what extent biased categorization may have impacted the analyses, that is, the potential for the interference of the liabilities of smallness (size) and newness (age) constructs in the findings and discussions of research.
Those responsible for funding agencies, editors, reviewers, researchers and other stakeholders of small businesses and new ventures must be attentive to the correct collection and recording of the “date of foundation” attribute and the “number of employees” variable, as well as their use for selecting samples and cases used in research.
This study is innovative in that it provides evidence that not only ontological difficulties are involved regarding the use of compound terms such as “small and medium-sized enterprise,” but also that epistemological difficulties are involved, due to the combination of disparate organizational instances (in terms of age and/or size) in the same analytical category.
