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This study aims to develop a modular and prescriptive digital transformation maturity model whose constituent elements have conceptual integrity as well as reveal the priority weights of maturity model components.

A literature review with a concept-centric analysis enlightens the characteristics of constituent parts and reveals the gaps for each component. Therefore, the interdependency network among model dimensions and priority weights are identified using decision-making trial and evaluation laboratory (DEMATEL)-based analytic network process (ANP) method, including 19 industrial experts, and the results are robustly validated with three different analyses. Finally, the applicability of the developed maturity model and the constituent elements are validated in the context of the manufacturing industry with two case applications through a strict protocol.

Results obtained from DEMATEL-based ANP suggest that smart processes with a priority weight of 17.91% are the most important subdimension for reaching higher digital maturity. Customer integration and value, with a priority weight of 17.30%, is the second most important subdimension and talented employee, with 16.24%, is the third most important subdimension.

The developed maturity model enables companies to make factual assessments with specially designed measurement instrument including incrementally evolved questions, prioritize action fields and investment strategies according to maturity index calculations and adapt to the dynamic change in the environment with spiral maturity level identification.

A novel spiral maturity level identification is proposed with conceptual consistency for evolutionary progress to adapt to dynamic change. A measurement instrument that is incrementally structured with 234 statements and a measurement method that is based on the priority weights and leads to calculating the maturity index are designed to assess digital maturity, create an improvement roadmap to reach higher maturity levels and prioritize actions and investments without any external support and assistance.

This study aims to analyze and synthesize the design features of existing digital transformation maturity models with a developed classification scheme and propose a generic maturity model development wireframe based on design science research.

A systematic literature review is conducted on digital transformation maturity models in peer-reviewed journals, including the Emerald Insight, Science Direct, Scopus, Taylor & Francis and Web of Science databases, which resulted in 21 studies. A concept-centric tabular approach is used to analyze the studies, and intersectional demonstrations are used to synthesize the findings regarding the design features.

The classification scheme derived from the tabular concept-centric approach and iteratively evolved results in three main and 25 subcategories related to the design features. Analysis and synthesis of the studies reveal the granularity of the existing digital transformation maturity models concerning the design features. Furthermore, considering the design features in the classification scheme, a generic maturity model development wireframe is proposed to guide the researchers.

The generic maturity model development wireframe and the classification scheme that represents the design features of existing maturity models guide the researchers for the maturity model development roadmap.

The existing literature review studies do not focus on the design feature of digital transformation maturity models within a systematic literature review perspective. A unique classification scheme derived from the tabular concept-centric approach aims to analyze the granularity level of the existing models. Furthermore, the generic maturity model development wireframe includes the guidelines and recommendations of design science studies and presents a roadmap for maturity model researchers.

The purpose of this paper is to review existing smart manufacturing (SM) maturity models' dimensions and maturity levels to assess their applicability and drawbacks. There are many maturity models available but many of them have not been validated or do not provide a useful guide or tool for applications. This gap creates the need for a review of the existing maturity model's applicability.

Nineteen peer-reviewed maturity models related to “Digital Transformation,” “Industry 4.0” or “Smart Manufacturing” were selected based on a systematic literature review and five consulting firm models were selected based on the author's industry knowledge. The chosen models were analyzed to determine 10 categories of dimensions. Then they are assessed on a 1–5 scale for how applicable they are in the 10 categories of dimensions.

The five “consulting firm” models have a first-mover advantage, are more widely used in industry and are more applicable, but some require payment, and they lack published details and validation. The 19 “peer reviewed” models are not as widely used, lack awareness in the industry and are not as easy to apply because of no web tool for self-assessment, but they are improving. The categories defined to characterize the models and facilitate comparisons for users include “Information Technology (IT) and Cyber-Physical System (CPS) and Data,” “Strategy and Organization,” “Supply Chain and Logistics,” “Products and Services,” “Culture and Employees,” “Technology and Capabilities,” “Customer and Market,” “Cybersecurity and Risk,” “Leadership and Management” and “Governance and Compliance.” The analyzed maturity models were particularly weak in the areas of cybersecurity, leadership and governance.

Researchers and practitioners can use this review with consideration of their specific needs to determine if a maturity model is applicable or if a new model needs to be developed. The review can also aid in the development of maturity models through the discussion of each of the dimension categories.

Compared to existing reviews of SM maturity models, this research determines comprehensive dimension categories and focuses on applicability and drawbacks.

Industry 4.0 is characterised by the exponential pace of technological innovations compelling organisations to transform or be displaced. Industry 4.0 transformation of construction enterprises lacks systematic guidance and notable earlier studies have utilised maturity models to map transformation of enterprises. This paper proposes a conceptual maturity model for construction enterprises for business scenarios leading to Industry 4.0.

The requirements for designing maturity models, including comparison with existing models and scientifically documenting the design process, make Systematic Literature Reviews (SLR) appropriate. Two systematic literature reviews (SLRs) are conducted to shortlist a total of 95 papers, which are subjected to subsequent content analysis.

The first SLR identifies the following process categories as critical levers of industry 4.0 maturity; data management, people and culture, leadership and strategy, collaboration and communication, automation, innovation and change management. The second SLR ascertains that the existing maturity models in construction literature do not adequately correspond to Industry 4.0 business scenarios with limited emphasis on data management, automation, change management and innovation. The findings are assimilated to propose a conceptual Smart Modern Construction Enterprise Maturity Model (SMCeMM).

The paper systematises the transformation of construction enterprises in Industry 4.0 and leads to state-of-the-art development of Industry 4.0 and maturity model research in construction. The proposed conceptual model addressed both the demands of the construction industry as well as what is required to navigate Industry 4.0 better.

Digital transformation is crucial for achieving high-quality development in the construction industry. Assessing the industry's digital maturity is an urgent necessity. The Digital Transformation Maturity Model is a potential tool to systematically evaluate the digital maturity levels of various industries. However, most existing models predominantly focus on sectors such as the Internet and manufacturing, leaving the construction industry comparatively underrepresented. This study aims to address this gap by developing a maturity model tailored specifically for digital transformation within the construction industry.

This study leverages the Capability Maturity Theory and integrates the unique characteristics of the construction industry to construct a comprehensive maturity model for digital transformation. The model comprises five critical dimensions: industry environment, strategy and organization, digital infrastructure, business process and management digitization, and digital performance. These dimensions encompass a total of 25 assessment indexes. To validate the model's feasibility and effectiveness, a digital transformation maturity assessment was conducted within China's construction industry.

The results of the maturity assessment within the Chinese construction industry reveal that it currently operates at the third level of digital maturity (defined level). The industry's maturity score stands at 2.329 out of 5. This outcome indicates that the developed model is accurate and reliable in assessing the level of digital transformation maturity within the construction industry.

This paper contributes both practical and theoretical insights to the field of digital transformation within the construction industry. By creating a tailored maturity model, it addresses a significant gap in existing research and offers a valuable tool for assessing and advancing digital maturity levels within this industry.

This paper aims to provide a maturity model for information security awareness (MMISA), based on the literature, expert interviews and feedback. In addition to developing the MMISA, the authors investigate the role of the three decisive factors that affect ISA maturity level: risk management mechanism, organizational structure and ISA.

The research methodology is a combined one; qualitative and quantitative methods were applied, including surveying the literature, interviews and developing a survey to collect quantitative data about decisive factors that affect ISA maturity level. The authors perform a variance-based partial least squares-structural equation modeling (PLS-SEM) investigation of the relationships between these factors.

The investigation of decisive factors of ISA maturity levels revealed that if the authors identify a strong risk assessment mechanism (through a documented methodology and reliable results), the authors can expect a high level of ISA. If there is a well-defined organizational structure with clear responsibilities, this supports the linking of a risk management mechanism with the level of ISA. The connection between organizational structure and ISA maturity level is supported by ISA activities: an increased level of awareness actions strengthens an organizational structure via the best practices learned by the staff.

The main contribution of the proposed MMISA model is that the model offers controls and audit evidence for maturity levels. Beyond that, the authors distinguish in the MMISA model controls supporting knowledge and controls supporting attitude, emphasizing that this is not enough to know what to do, but the proper attitude is required too. The authors didn't find any other ISA maturity model which has a similar feature. The contribution of the authors' work is that the authors provide a method for solving this complex measurement problem via the MMISA, which also offers direct guidance for the daily practices of organizations.

The aim of the article is to determine research areas and to recognize the current direction in the development of maturity models, to indicate the key areas of organizational maturity models (OMMs) development and their classification as well as to pinpoint research gaps and areas of potential development of OMMs in the context of scientific research and the needs of management practitioners.

The research was conducted using the literature review method, bibliometric analysis and visual mappings.

The empirical classification developed in this paper identified 12 categories based on management areas, constituting the criteria for classifying OMMs models, where OMMs are being developed: Information Technology, Project Management, Business Management and Strategy, Human Resource, Ergonomics, Health and Safety Management, Industry 4.0 concept, Knowledge Management, Process Management, Performance Management, Quality Management, Supply Chain Management, Risk Management and Innovation Management.

The main limitation is the analysis in the scope of topic OMMs including solely the Scopus and Thompson Reuters Web of Science database. Another shortcoming is conducting data analysis and classification based on the abstracts of the selected articles.

This work is a starting point to prospect trends for future revolving around the OMMs crossing different databases.

Despite the multitude of publications concerning the process maturity assessment models applied in the private sector, the matter of the choice of a process maturity assessment model is not so unambiguous in the public sector. The goal of this article is to identify process maturity assessment models applicable to the public sector.

Literature review, enabling identification of process maturity assessment models applicable to the public sector. Comparative analysis, making it possible to identify the advantages and disadvantages of the selected maturity assessment models.

Models enabling assessment of process maturity and e-government maturity applicable to the public sector have been identified. Potential benefits and limitations specific to the analysed models have been established.

The publication indicates which process maturity assessment models can be successfully applied in the public sector. As such, it provides important support for the public sector in the decision-making process concerning the choice and implementation of a specific process maturity assessment model.

This is one of the few study which refers to a comprehensive review and analysis of process maturity assessment models applicable to the public sector. As the relevant contribution, it clarifies the relationships and differences between process and e-government maturity assessment models. This study provides important aid to both practitioners and theorists in terms of the selection of a process maturity assessment model against specific research needs.

Insufficient productivity development in the global and Finnish infrastructure sectors indicates that there are challenges in genuinely achieving the goals of resource efficiency and digitalization. This study adapts the approach of capability maturity model integration (CMMI) for examining the capabilities for productivity development that reveal the enablers of improving productivity in the infrastructure sector.

Civil engineering in Finland was selected as the study area, and a qualitative research approach was adopted. A novel maturity model was constructed deductively through a three-step analytical process. Previous research literature was adapted to form a framework with maturity levels and key process areas (KPAs). KPA attributes and their maturity criteria were formed through a thematic analysis of interview data from 12 semi-structured group interviews. Finally, validation and refinement of the model were performed with an expert panel.

This paper provides a novel maturity model for examining and enhancing the infrastructure sector’s maturity in productivity development. The model brings into discussion the current business logics, relevance of lifecycle-thinking, binding targets and outcomes of limited activities in the surrounding infrastructure system.

This paper provides a new approach for pursuing productivity development in the infrastructure sector by constructing a maturity model that adapts the concepts of CMMI and change management. The model and findings benefit all actors in the sector and provide an understanding of the required elements and means to achieve a more sustainable built environment and effective operations.

This paper presents a maturity model for digital transformation effectiveness in laboratories (labs) with education and research purposes.

The model was developed using design science research methodology, expert interviews and case studies.

The model fulfills three practical goals: (1) to establish comparability of the effectiveness of the digital transformation of labs, (2) to provide lab operators from academia and industry with a guide for (further) transformation and (3) to build initial trust among lab users. In addition, the maturity model contributes to the literature on digital lab transformation by capturing, describing, structuring and evaluating relevant dimensions, items and levels. Model strengths and weaknesses, areas for improvement, international applicability and practical and reusable recommendations are presented as well as the added value in assessing lab functionalities and lab sustainability.

Although originally developed as a maturity model driven by lab education, the model is also suitable for the transformation of research labs in manufacturing technology management. Digital labs can efficiently support industry training and research and development activities as well as simulate the development of new processes prior to their implementation.

Especially for these use cases, the authors see application potentials for the use of online labs from an organizational perspective and from the perspective of stakeholders such as industry users and operators with a manufacturing background, who use and develop transformed labs for teaching and research.