A decade of digital maturity models: much ado about nothing?

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2023-10-24 DOI:10.1007/s10257-023-00656-w
Tristan Thordsen, Markus Bick
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Abstract

Abstract The topic of digital maturity has evolved into a full-grown hype in the last decade. It is widely assumed that the level of an organization’s digital maturity is directly linked to its performance. Digital Maturity Models (DMMs) have been designed specifically to assess an organization’s digital status quo and to provide concrete measures to increase its level of digital maturity. Given this relevance, a multitude of these models have emerged. Still, the development and application of DMMs is controversially discussed within the academic community leading to great uncertainty regarding their value for both theory and practice. In this systematic literature review, we seek to paint a comprehensive picture of the research field by identifying and contrasting the main contentious opinions among IS scholars. An analysis of detailed information regarding the research area – encompassing extensive DMM literature, academic discussion, and feedback – shows that various critical voices question the actual practical and theoretical value of DMMs, underlining the absence of objective evaluation criteria of these models and pointing out the lack of empirical data to prove the suggested relationship between maturity and performance. Based on our experience in this field, we provide a first synthesis of eleven years of DMMs and derive a research agenda.
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十年的数字成熟度模型:无事生非?
在过去的十年里,数字成熟度的话题已经发展成为一个成熟的炒作。人们普遍认为,组织的数字成熟度水平与其绩效直接相关。数字成熟度模型(dmm)是专门为评估组织的数字现状而设计的,并提供具体措施来提高其数字成熟度水平。鉴于这种相关性,出现了许多这样的模型。尽管如此,dmm的发展和应用在学术界仍存在争议,导致其理论和实践价值存在很大的不确定性。在这篇系统的文献综述中,我们试图通过识别和对比IS学者之间的主要争议观点来描绘研究领域的全面图景。对该研究领域详细信息的分析——包括广泛的DMM文献、学术讨论和反馈——表明,各种批评声音质疑DMM的实际实践和理论价值,强调缺乏这些模型的客观评价标准,并指出缺乏实证数据来证明成熟度和绩效之间的关系。根据我们在这一领域的经验,我们提供了11年来DMMs的第一次合成,并得出了一个研究议程。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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