Maturity models : Taking stock and moving forward

Padmaka Mirihagalla, G. Vastag
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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.
成熟度模型:进行评估并向前推进
成熟度模型(mm)是基于这样一个前提:组织能力成熟度的提高会导致预期结果度量的改进。这种有希望的潜力解释了mm越来越受欢迎,以及在各种学术和专业期刊上发表了大量关于该主题的出版物。本研究基于对1973年至2017年期间在193个期刊上发表的339篇论文的分析。在简要概述了mm的理论基础之后,作者着重从潜在作者的角度回答了“在哪里发表才能获得最大的影响”的问题。一篇出版物的影响力,通过其生命周期内收集的引用次数来衡量,受期刊质量(通过Clarivate Analytics的期刊文章影响力评分、Scimago期刊排名和Scimago Q类别来衡量)和出版物的公开可用性长度的影响。各种划分模型(决策树、自举森林和提升树)的结果表明,在高质量、公认的期刊上发表论文往往会获得更多的引用。换句话说,在一个期刊网络中,并不是所有的引用都是平等的,因为有选择性的、排名靠前的期刊的引用比其他期刊的引用更平等。同样重要的是要强调,Scimago的Q分类与论文发表后的成功无关;Q分类是衡量期刊质量的一种嘈杂而糟糕的方法,并没有在全球范围内使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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