Maturity models : Taking stock and moving forward

Mirihagalla, Padmaka and Vastag, Gyula (2022) Maturity models : Taking stock and moving forward. HUNGARIAN STATISTICAL REVIEW: JOURNAL OF THE HUNGARIAN CENTRAL STATISTICAL OFFICE, 5 (1). pp. 3-28. ISSN 2630-9130

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Abstract

Maturity models (MMs) are based on the premise that improved maturity in organisational capabilities leads to improvements in the desired outcome measures. This promising potential explains the growing popularity of MMs and the large number of publications on the subject in various academic and professional journals. The present study is based on an analysis of 339 MM papers published in 193 journals between 1973 and 2017. After giving a brief overview of the theoretical underpinnings of MMs, the authors focus on answering the question of ‘where to publish to achieve maximum impact’ from the perspective of potential authors. The impact of a publication, measured by the number of citations collected over its lifetime, is influenced by the quality of the journal (measured by the journal’s article influence score by Clarivate Analytics, Scimago Journal Ranking by Scimago, and Scimago Q category) and the length of public availability of the publication. Results from a variety of partitioning models (decision tree, bootstrap forest, and boosted tree) show that publishing in high-quality, recognised journals tends to result in more citations. In other words, in a network of journals, not all citations are equal as citations in selective, highly ranked journals are more equal than others. It is also important to emphasise that Scimago’s Q classification has no bearing on a paper’s post-publication success; Q classification is a noisy and poor measure of a journal’s quality that is not used globally.

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