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Abstract Background The benefits of lean adoption in healthcare include improved process efficiency and quality of patient care. However, research indicates that lean implementation in healthcare, and specifically hospitals, is often not sustained. Furthermore, there is a need for maturity models that guide lean implementation, specifically in hospitals. This study develops a prescriptive maturity model named the Sustaining of Lean Adoption in Hospitals Roadmap (SOLAR) that acts as a practical guideline for the sustainable adoption of lean in hospitals. Methods The SOLAR has three theoretical foundations, namely lean implementation success factors in hospitals, implementation science, and change management theory. A systematic literature review was conducted to determine the lean implementation success factors in hospitals as the first building block. Secondly, practices from implementation science were used to create the action items in the SOLAR. Ten change steps were elicited from change management theory as the third theoretical building block of the roadmap. We refined the roadmap through three Delphi rounds that verified its useability in hospitals. Results The final SOLAR consists of four maturity phases (prepare, plan, experiment and learn, and sustain) and includes action items for each phase related to the hospital’s strategy, resources, engaging of people, and culture. The action items and change management steps shown in the SOLAR are not intended as an exhaustive list but provide guidelines on aspects hospitals must consider when they aim to adopt lean sustainably. Conclusions The strong theoretical base of the SOLAR enables hospitals to safely experiment and learn which implementation methods are best suited to their unique environment. The SOLAR is, therefore, an actionable guideline that informs both academics and practitioners involved in lean adoption in hospitals. This roadmap can guide future retrospective longitudinal or action research.

Maturity models are valuable tools when assessing the readiness and progress of technology incorporation in organizations, providing information for decision-making, resource allocation, and competitive advantage. The Internet of Things is a technology paradigm of global importance, especially for organizations, as it supports productivity improvements, real-time analysis, and customer satisfaction. Therefore, adopting and implementing this technology in enterprises brings several challenges, such as technological, organizational, security, and maturity issues. However, secondary studies that systematically compile the existing literature on these specific mechanisms for the enterprise domain are still being determined. This article aims to address this knowledge gap by conducting a review to deepen and synthesize the existing knowledge. This research followed established methodologies and protocols to synthesize and analyze the state of the art in the area; 489 documents were retrieved from seven bibliographic databases, and, applying inclusion and exclusion criteria, 36 primary studies were selected. The results indicate that the typical structures of maturity models incorporate technological, organizational, human, performance, and security dimensions through graded levels that denote the sophistication of the Internet of Things. Measurement techniques and metrics vary from model to model. There are few empirical validations or standardized improvement frameworks. The main conclusion is that there is a diversity of models, dimensions, indicators, and methods and a need for more comprehensive, adaptable, and user-friendly tools to help companies assess their Internet of Things maturity and inform future development strategies. [ABSTRACT FROM AUTHOR]

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Nowadays, disruptive events pose significant threats to organizations, making resilience a critical focus. Evaluating supply chain resilience is essential to avoid escalating disruptions. However, the literature on this topic is fragmented, and the assessment of resilience remains an open gap due to the lack of a clear definition of the dimensions and elements for its evaluation. To fill this gap, this study integrates a systematic literature review (SLR) and a systematic literature network analysis (SLNA) to propose a MAturity MOdel for REsilient Supply Chains (MaMoReS). Through content analysis and stringent selection of 15 resilience maturity models (ResMMs) via SLR, along with an SLNA on 6,474 sources, this method defines dimensions and sub-dimensions. The proposed MaMoReS is framed around five levels and five dimensions: risk management, agility, flexibility and adaptability, redundancy and robustness, transparency and visibility, and collaboration and relationships. The MaMoReS is applied to two case studies, pinpointing the practicality of the MaMoReS for measuring the resilience maturity level of the two companies along with their dimensions and sub-dimensions scoring. Thus, the MaMoReS can be used as an assessment tool by supply chain managers and researchers to evaluate the resilience of a supply chain. [ABSTRACT FROM AUTHOR]

Background: The benefits of lean adoption in healthcare include improved process efficiency and quality of patient care. However, research indicates that lean implementation in healthcare, and specifically hospitals, is often not sustained. Furthermore, there is a need for maturity models that guide lean implementation, specifically in hospitals. This study develops a prescriptive maturity model named the Sustaining of Lean Adoption in Hospitals Roadmap (SOLAR) that acts as a practical guideline for the sustainable adoption of lean in hospitals. Methods: The SOLAR has three theoretical foundations, namely lean implementation success factors in hospitals, implementation science, and change management theory. A systematic literature review was conducted to determine the lean implementation success factors in hospitals as the first building block. Secondly, practices from implementation science were used to create the action items in the SOLAR. Ten change steps were elicited from change management theory as the third theoretical building block of the roadmap. We refined the roadmap through three Delphi rounds that verified its useability in hospitals. Results: The final SOLAR consists of four maturity phases (prepare, plan, experiment and learn, and sustain) and includes action items for each phase related to the hospital's strategy, resources, engaging of people, and culture. The action items and change management steps shown in the SOLAR are not intended as an exhaustive list but provide guidelines on aspects hospitals must consider when they aim to adopt lean sustainably. Conclusions: The strong theoretical base of the SOLAR enables hospitals to safely experiment and learn which implementation methods are best suited to their unique environment. The SOLAR is, therefore, an actionable guideline that informs both academics and practitioners involved in lean adoption in hospitals. This roadmap can guide future retrospective longitudinal or action research. [ABSTRACT FROM AUTHOR]

Abstract Introduction: Managing clinical trials is a complex process requiring careful integration of human, technology, compliance, and operations for success. We collaborated with experts to develop a multi-axial Clinical Trials Management Ecosystem (CTME) maturity model (MM) to help institutions identify best practices for CTME capabilities. Methods: A working group of research informaticists was established. An online session on maturity models was hosted, followed by a review of the candidate domain axes and finalization of the axes. Next, maturity level attributes were defined for min/max levels (level 1 and level 5) for each axis of the CTME MM, followed by the intermediate levels. A REDCap survey comprising the model’s statements was then created, and a subset of working group members tested the model by completing it at their respective institutions. The finalized survey was distributed to all working group members. Results: We developed a CTME MM comprising five maturity levels across 11 axes: study management, regulatory and audit management, financial management, investigational product management, subject identification and recruitment, subject management, data, reporting analytics & dashboard, system integration and interfaces, staff training & personnel management, and organizational maturity and culture. Informaticists at 22 Clinical and Translational Science Award hubs and one other organization self-assessed their institutional CTME maturity. Respondents reported relatively high maturity for study management and investigational product management. The reporting analytics & dashboard axis was the least mature. Conclusion: The CTME MM provides a framework to research organizations to evaluate their current clinical trials management maturity across 11 axes and identify areas for future growth.

Copyright of Journal of Economic Research & Business Administration is the property of Al-Farabi Kazakh National University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In an effort to improve the security, dependability, and quality of infrastructure systems, the implementation of complex transportation construction and maintenance projects is essential. Building upon a previous study that identified six crucial factors for effectively implementing new and emerging technologies in the State Department of Transportations (DOTs), this research aims to comprehensively explore six critical factors using a maturity model perspective. DOTs have shown increasing interest in adopting emerging and wireless technologies, as evident in various Federal Highway Administration Every Day Counts initiative. This study employs a mixed-methods approach, using survey responses from DOT personnel to evaluate the relative significance of technology implementation factors and subfactors. The six factors for successful technology implementation explored in this study are Organization Structure, Information Technology Infrastructure, Data Security, Information Workflow, Personnel Training, and Stakeholder Engagement. The study also evaluates the relative importance of People, Process, and Technology for each of these six factors. The paper focuses on providing detailed insights into the different criteria of each technology implementation factor and subfactor to guide agencies in successful technology deployment. Understanding these factors is critical to deploying emerging technologies successfully, which, in turn, leads to much-needed efficiency and productivity in highway construction and asset management. The findings of this study can help DOTs prioritize their technology investments and ultimately contribute to the development of a more advanced and sustainable transportation infrastructure system. [ABSTRACT FROM AUTHOR]

Featured Application: A robust Systematic Literature Review (SLR) of assessment instruments (maturity models, roadmaps, frameworks, and readiness assessments) to assess the level at which Industry 4.0 is deployed in an organization. The research provides a comprehensive perspective of readiness assessment instruments for Industry 4.0 digital transformation and sets the foundations for future action plans and projects. Nowadays, different Industry 4.0 technologies have been implemented into diverse industries. However, these implementations are not standardized across similar industries and countries. Consequently, companies are actively looking for assessment instruments—maturity models, roadmaps, frameworks, readiness assessments—to assist in their digital transformation, to determine their Industry 4.0 level, and to identify technologies and strategies that should be implemented in specific areas, thus developing a feasible implementation plan. A review is conducted following the PRISMA (Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses) methodology to analyze the different research works on assessment instruments focused on Industry 4.0. A total of 538 articles, book chapters, conference proceedings, editorial material, reviews, and reports written in the English language were retrieved. Of these, 132 research papers were examined using a mixed analysis format to generate bibliometrics, and 36 articles were then deeply studied for a complete meta-analysis. The findings and insights of this meta-analysis led to a compilation and summary of dimensions, outcomes, enablers, and key components typically involved in Industry 4.0, which are comprehensively integrated to present the best practices for assessing Industry 4.0 and deploying a digital transformation that can impact productivity, flexibility, sustainability, quality, costs, and time. [ABSTRACT FROM AUTHOR]

Nowadays, disruptive events pose significant threats to organizations, making resilience a critical focus. Evaluating supply chain resilience is essential to avoid escalating disruptions. However, the literature on this topic is fragmented, and the assessment of resilience remains an open gap due to the lack of a clear definition of the dimensions and elements for its evaluation. To fill this gap, this study integrates a systematic literature review (SLR) and a systematic literature network analysis (SLNA) to propose a MAturity MOdel for REsilient Supply Chains (MaMoReS). Through content analysis and stringent selection of 15 resilience maturity models (ResMMs) via SLR, along with an SLNA on 6,474 sources, this method defines dimensions and sub-dimensions. The proposed MaMoReS is framed around five levels and five dimensions: risk management, agility, flexibility and adaptability, redundancy and robustness, transparency and visibility, and collaboration and relationships. The MaMoReS is applied to two case studies, pinpointing the practicality of the MaMoReS for measuring the resilience maturity level of the two companies along with their dimensions and sub-dimensions scoring. Thus, the MaMoReS can be used as an assessment tool by supply chain managers and researchers to evaluate the resilience of a supply chain.

Maturity models are valuable tools when assessing the readiness and progress of technology incorporation in organizations, providing information for decision-making, resource allocation, and competitive advantage. The Internet of Things is a technology paradigm of global importance, especially for organizations, as it supports productivity improvements, real-time analysis, and customer satisfaction. Therefore, adopting and implementing this technology in enterprises brings several challenges, such as technological, organizational, security, and maturity issues. However, secondary studies that systematically compile the existing literature on these specific mechanisms for the enterprise domain are still being determined. This article aims to address this knowledge gap by conducting a review to deepen and synthesize the existing knowledge. This research followed established methodologies and protocols to synthesize and analyze the state of the art in the area; 489 documents were retrieved from seven bibliographic databases, and, applying inclusion and exclusion criteria, 36 primary studies were selected. The results indicate that the typical structures of maturity models incorporate technological, organizational, human, performance, and security dimensions through graded levels that denote the sophistication of the Internet of Things. Measurement techniques and metrics vary from model to model. There are few empirical validations or standardized improvement frameworks. The main conclusion is that there is a diversity of models, dimensions, indicators, and methods and a need for more comprehensive, adaptable, and user-friendly tools to help companies assess their Internet of Things maturity and inform future development strategies.

In an effort to improve the security, dependability, and quality of infrastructure systems, the implementation of complex transportation construction and maintenance projects is essential. Building upon a previous study that identified six crucial factors for effectively implementing new and emerging technologies in the State Department of Transportations (DOTs), this research aims to comprehensively explore six critical factors using a maturity model perspective. DOTs have shown increasing interest in adopting emerging and wireless technologies, as evident in various Federal Highway Administration Every Day Counts initiative. This study employs a mixed-methods approach, using survey responses from DOT personnel to evaluate the relative significance of technology implementation factors and subfactors. The six factors for successful technology implementation explored in this study are Organization Structure, Information Technology Infrastructure, Data Security, Information Workflow, Personnel Training, and Stakeholder Engagement. The study also evaluates the relative importance of People, Process, and Technology for each of these six factors. The paper focuses on providing detailed insights into the different criteria of each technology implementation factor and subfactor to guide agencies in successful technology deployment. Understanding these factors is critical to deploying emerging technologies successfully, which, in turn, leads to much-needed efficiency and productivity in highway construction and asset management. The findings of this study can help DOTs prioritize their technology investments and ultimately contribute to the development of a more advanced and sustainable transportation infrastructure system.

This article explores the current state and challenges of precision oncology, specifically focusing on the maturity of the field as a learning health system. The study conducted interviews with professionals involved in Molecular Tumor Boards to gather insights on the practice, tools, and barriers of precision oncology. The findings suggest that while the field is evolving, there are still obstacles such as resource-intensive infrastructure and knowledge gaps. The article also discusses the role of academic medical centers and industry in precision oncology, as well as the need for education, accessibility, and privacy considerations. Overall, the study emphasizes the importance of learning from patient experiences and developing maturity models to advance precision oncology. [Extracted from the article]

Abstract Introduction: This study aimed to map the maturity of precision oncology as an example of a Learning Health System by understanding the current state of practice, tools and informatics, and barriers and facilitators of maturity. Methods: We conducted semi-structured interviews with 34 professionals (e.g., clinicians, pathologists, and program managers) involved in Molecular Tumor Boards (MTBs). Interviewees were recruited through outreach at 3 large academic medical centers (AMCs) (n = 16) and a Next Generation Sequencing (NGS) company (n = 18). Interviewees were asked about their roles and relationships with MTBs, processes and tools used, and institutional practices. The interviews were then coded and analyzed to understand the variation in maturity across the evolving field of precision oncology. Results: The findings provide insight into the present level of maturity in the precision oncology field, including the state of tooling and informatics within the same domain, the effects of the critical environment on overall maturity, and prospective approaches to enhance maturity of the field. We found that maturity is relatively low, but continuing to evolve, across these dimensions due to the resource-intensive and complex sociotechnical infrastructure required to advance maturity of the field and to fully close learning loops. Conclusion: Our findings advance the field by defining and contextualizing the current state of maturity and potential future strategies for advancing precision oncology, providing a framework to examine how learning health systems mature, and furthering the development of maturity models with new evidence.

This article is the second in a two-part series of articles presenting the methodology and main findings of the Digimeter research series on SME digitalisation (the first part presented the theoretical foundations). The Digimeter research series aims to systematically measure SME digitalisation in Hungary in six dimensions: digital presence; digital life; business management; sales and marketing; finance; IT security. Results show there was no significant development between 2020 and 2022. SMEs in Hungary are using IT tools below their potential. Digimeter data are available using the same methodology and the questions asked are not based on subjective judgements of readiness. The limitation of the research series is that it does not measure individual differences in digitalisation between economic sectors due to the consistent methodology. The long-term goal of Digimeter is to identify what could make the digitalisation of Hungarian SMEs more efficient. [ABSTRACT FROM AUTHOR]

The article is based on the results of a literature review on enterprise digitalisation, small and medium-size enterprise (SME) digitalisation and their measurement. It is the first in a two-part series of articles, the broad theoretical framework of the Digimeter research series on SME digitalisation. One of the most frequently studied topics in relation to SMEs is digitalisation and measuring digital maturity. However, research on SME digitalisation faces a number of challenges. Digitalisation affects companies as a whole and SMEs are more likely to experience this process as a challenge than larger firms. This article illustrates the diversity of the field of enterprise digitalisation, which means that there is no universally accepted definition. For this reason, the measurement of SME digitalisation is not clear either from the literature or from practice. There are more differences than similarities between the measurements identified, and there is no established methodology for measuring SME maturity or development. [ABSTRACT FROM AUTHOR]

Maturity models (MMs) are strategic tools used to assess and improve the current state of processes, objects, or people, with the goal of achieving continuous performance enhancement. While MMs are applied in various fields, their scope, design, and application criteria within Supply Chain Management and Logistics (SCML) lack comprehensive studies. This article aims to address this gap through a systematic literature review. The review analyzes 137 relevant articles using both bibliometric and content analysis techniques. The bibliometric analysis identifies major contributions, popular journals, and the classification and evolution of key keywords. The content analysis focuses on critical criteria related to the scope, design, and application of MMs. The findings reveal a growing emphasis on models assessing Industry 4.0 readiness and sustainability principles. However, several gaps are identified, including limited attention to optimizing and integrating logistic processes, underutilized and unvalidated MMs, and the absence of comprehensive improvement guidelines. Based on these trends and research gaps, this study proposes five recommendations for future developments that benefit both academics and practitioners. These recommendations aim to address the identified limitations and provide guidance for comprehensive and effective improvement strategies. [ABSTRACT FROM AUTHOR]

Digital transformation impacts longstanding business models and enables enterprises to create new ones. This transformation leads to increased competition that forces enterprises to compete, not only between companies but also between the entire supply chain and business networks. The emerging concept of digital business ecosystems (DBE) allows enterprises to concentrate on network co-creation and co-evolution of bundled services and products across enterprise boundaries. This exploratory study introduces a maturity model derived from existing DBEs. Based on employing a design science methodology, we reviewed 22 scientific publications, interviewed 28 senior experts from practice and derived a maturity model from the results. We applied the maturity model through an online survey to 29 DBEs from different industry sectors and compared it with 22 maturity assessment approaches from other domains. The maturity model enables researchers to compare and assess existing DBEs and helps practitioners to identify areas for improvement in the collaboration within DBEs.

Lean construction (LC) is becoming prevalent, and assessment of the level of LC implementation is vital for organizations to realize their full potential. In meeting that need, lean construction maturity models (LCMMs) play a key role. However, there is less evidence of critical reviews in spite of the significant number of LCMMs available. Therefore, this study was initiated with the aim of systematically reviewing the literature on existing lean-construction-related maturity models (MMs) through a critical review. The study adopted the PRISMA method to review 24 such models using manual content analysis. The study revealed the most common attributes among the models, along with their key strengths and weaknesses. The findings of this study can be directly used to develop more robust LCMMs and enhance the knowledge base on theoretical underpinnings. From an industry perspective, the findings assist organizations to more effectively assess LC maturity. The study invites further research on the area of LC maturity and advocates for developing new MMs addressing these areas identified for improvement. [ABSTRACT FROM AUTHOR]

The presented article focuses on the acute topics of process management in educational institutions. A maturity model is here proposed in order to develop an effective marketing mix for educational facilities. It is used to assess the current state of each element of the marketing mix and identify areas for improvement. The main contribution is the detailed description of why it is necessary to create a maturity model when creating a marketing mix in the school sector. To achieve this, individual process information programs are analyzed and specifics for the educational sector are given. The article focuses on educational facilities, such as schools, universities, and training centers. By utilizing a maturity model, educational facilities can identify gaps in their marketing strategies and develop a more effective marketing mix to attract and retain students. Furthermore, up-to-date maturity models were analyzed and, as a result of the research, a new, separate model was created with detailed description. Part of the new model is also an analysis of practical use by employees in selected school establishments. The results of this study can provide insights for educational institutions to enhance their marketing strategies and better meet the needs of their target audience. [ABSTRACT FROM AUTHOR]

Due to the increasing demand for batteries, fueled by the transition to sustainable energy sources and electric vehicles, battery factories are currently being built all around the world. To meet the resulting challenges, digital technologies are a key component in the context of competitive battery cell manufacturing. For a requirements-oriented implementation of an appropriate Industry 4.0 environment, three Digital Twins are implemented to meet the digital needs in the battery cell manufacturing environment: The Product Twin, the Plant Twin, and the Building Twin. Addressing the challenges of battery cell manufacturing requires holistic Digital Twins that encompass the entire lifecycle. Existing Maturity Models do not provide a sufficient basis for a systematic assessment and holistic development of the Product-, the Plant-, and the Building Twin in battery cell manufacturing. Therefore, a novel Maturity Model considering the specific requirements has been developed. The Maturity Model is developed using an action model based on the Design Science Research methodology. The content components are carried out with qualitative empiricism - literature review, expert workshops, expert interviews - within five iterations. This is followed by expert evaluation of the model using a case study. The result of the empiricism is a holistic Maturity Assessment Model for Digital Twins in Battery Cell Industry. The Maturity Model includes five maturity levels, twelve maturity dimensions, 50 maturity sub-dimensions and 250 maturity indicators. Fuzzy Logic is used to perform the quantitative maturity assessments of the Digital Twins by means of the maturity indicators. The evaluation results show that the model can offer consistent and reproducible maturity assessments. Once the model has been tested and verified with further case studies it is plausible that the Maturity Model can be applied to a wide range of Digital Twins in the manufacturing industry. [ABSTRACT FROM AUTHOR]

Nowadays, we live in the era of Big Data. Companies have realized by now that transitioning to a datadriven business is strategic for their growth and competitiveness. To achieve that, companies should get the most value out of their data through Big Data technologies. In the previous work, we showed how maturity models are essential to assess the ability of companies to start Big Data projects and prevent eventual failures. We also explored literature and editors' offerings in this field and proposed an exhaustive maturity model that includes Methodology, a maturity domain of high importance and impact. In the present work, we aim to provide a detailed picture of the proposed global Maturity Model design by exploring the temporal domains and explaining how they evolve through time. In addition, we aim to introduce the assessment framework, a tool we made available for North African companies to be able to evaluate their Big Data maturity. Unlike the currently available models, which are usually detailed and complex, the global assessment tool is quick and easy. We enriched the assessment questionnaire with best practices, and more importantly, the assessment tool suggests a list of shortcomings that companies should avoid in order to succeed in their Big Data adoption journey. Moreover, we present the technologies used to implement the global assessment tool. We also show an example of a company's assessment results via visualizations. Furthermore, we demonstrate the importance of the methodology domain through assessment results; and we analyze which sector has mature companies and which maturity domains are more mature by industry sector. Finally, we conclude with an opening on using Multiple Criteria Decision-Making techniques to calculate companies' maturity accurate scores. [ABSTRACT FROM AUTHOR]

Nowadays, different Industry 4.0 technologies have been implemented into diverse industries. However, these implementations are not standardized across similar industries and countries. Consequently, companies are actively looking for assessment instruments—maturity models, roadmaps, frameworks, readiness assessments—to assist in their digital transformation, to determine their Industry 4.0 level, and to identify technologies and strategies that should be implemented in specific areas, thus developing a feasible implementation plan. A review is conducted following the PRISMA (Preferred Reporting Items for Systematic Literature Reviews and Meta-Analyses) methodology to analyze the different research works on assessment instruments focused on Industry 4.0. A total of 538 articles, book chapters, conference proceedings, editorial material, reviews, and reports written in the English language were retrieved. Of these, 132 research papers were examined using a mixed analysis format to generate bibliometrics, and 36 articles were then deeply studied for a complete meta-analysis. The findings and insights of this meta-analysis led to a compilation and summary of dimensions, outcomes, enablers, and key components typically involved in Industry 4.0, which are comprehensively integrated to present the best practices for assessing Industry 4.0 and deploying a digital transformation that can impact productivity, flexibility, sustainability, quality, costs, and time.

Maturity models (MMs) have witnessed exponential increase due to their successful application in several domains. However, there is an absence of review that guides researchers in developing, applying and validating Public-Private Partnership maturity models (PPPMMs). This study examines PPPMMs, provides guidance on the topic and highlights gaps in the literature. A literature search on selected electronic databases was conducted, and the study adopted the widely accepted Preferred Reporting Items for Systematic Review and Meta-analysis statement (PRISMA). The study identified a total of four thousand six hundred and eighteen (4,618) studies, and twenty-one studies (21Nr) were rigorously selected. The results revealed PPPMMs as an emerging area of research with a low number – 21 publications since its deployment for about two (2) decades. Similarly, the findings unveiled a lack of uniformity in conceptualising the terms, dimensions used, and methodology adopted. This finding is attributed mainly to the limited use of the theoretical lens, which considerably weakens the model’s theoretical foundation and limits its potential to guide improvement. Additionally, there are more efforts in developing MMs than applying and validating them. Furthermore, there is an unbalanced focus on descriptive models over prescriptive and comparative models, which inhibit the model’s potential to guide improvement. Future work should provide a solid ground to the field using a theoretical lens and focus on prescriptive models with a strong emphasis on application and validation. This research is the first of its kind that synthesises and brings together available PPPMMs literature into one place. It also contributes to the body of knowledge by highlighting areas of research that require immediate attention to enhance the much-needed success of PPP in the post-COVID-19 era.

This paper proposes the creation and application of maturity models to guide institutional strategic investment in research informatics and information technology (research IT) and to provide the ability to measure readiness for clinical and research infrastructure as well as sustainability of expertise. Conducting effective and efficient research in health science increasingly relies upon robust research IT systems and capabilities. Academic health centers are increasing investments in health IT systems to address operational pressures, including rapidly growing data, technological advances, and increasing security and regulatory challenges associated with data access requirements. Current approaches for planning and investment in research IT infrastructure vary across institutions and lack comparable guidance for evaluating investments, resulting in inconsistent approaches to research IT implementation across peer academic health centers as well as uncertainty in linking research IT investments to institutional goals. Maturity models address these issues through coupling the assessment of current organizational state with readiness for deployment of potential research IT investment, which can inform leadership strategy. Pilot work in maturity model development has ranged from using them as a catalyst for engaging medical school IT leaders in planning at a single institution to developing initial maturity indices that have been applied and refined across peer medical schools.

With the evolutions of projects, it is necessary that companies understand the importance of project management, since this idea allows them to plan and monitor a project properly, through a set of knowledge, techniques, and tools. However, the implementation of project management alone is not enough. It is necessary that there is a continuous improvement in project management and an increase in maturity that accompanies the changes and needs of companies. These improvements and increases in maturity level are possible with the application of maturity models in project management. When well used, they allow companies to understand where they fail and where they need to improve. And if the measures taken from the models are applied, companies benefit positively in the delivery of the intended results, on time and on budget. As well as, in standing out compared to other companies in the market. Therefore, this study proposed a framework to compare project management maturity models. It allows the consideration of a set of variables when choosing a model. The results show that the Prado PMMM is typically the most suitable model for evaluation. [ABSTRACT FROM AUTHOR]

Maturity models have always been applied, but in the last decade, it has been used in the use of electronic government. Talking about the quality of care and its quality differs in the tools available and the one that is most competent in the market. The implementation of (information technology) IT in a company goes hand in hand with its level of maturity, therefore, it is important to answer the following questions: What are the effects of applying the maturity model for electronic government? Difficulties of applying maturity models to apply electronic government? That is why the searches focused on difficulties were made for the presentation of the articles that we use. It is concluded that although the implementation of electronic government in organizations is of the utmost importance, it is useless if we do not have a maturity model applied so that the IT part is effective. [ABSTRACT FROM AUTHOR]

Knowledge, being recognized as a primary resource, established Knowledge Management as a strategic factor in organizations. However, many of these organizations face difficulties in understanding how knowledge loss occurs, as well as implementing Knowledge Management and evaluating its performance, making maturity models stand out. In this sense, this research aims to analyze the level of CG maturity of a Public Institution, specifically in the Municipality of the city of Contagem, Minas Gerais, Brazil. As methodological procedures, a quantitative approach was adopted, with data collection through a survey, being a questionnaire with 39 questions on a five-point Likert-type interval scale and analysis through statistical procedures to identify dimensionality, reliability and validity of indicators for achieving maturity analysis. The research results showed that the Municipality of Contagem is at level three of maturity in Knowledge Management, being incipient (initial, embryonic), as it seeks to manage knowledge and its critical areas for its success. To raise this stage, 38 actions are proposed. As a limitation, there is the impossibility of reaching a value closer to the total number of respondents in the observation unit, despite the support of senior management. For future studies, it is suggested to apply this research in other Public Institutions. [ABSTRACT FROM AUTHOR]

Digital transformation impacts longstanding business models and enables enterprises to create new ones. This transformation leads to increased competition that forces enterprises to compete, not only between companies but also between the entire supply chain and business networks. The emerging concept of digital business ecosystems (DBE) allows enterprises to concentrate on network co-creation and co-evolution of bundled services and products across enterprise boundaries. This exploratory study introduces a maturity model derived from existing DBEs. Based on employing a design science methodology, we reviewed 22 scientific publications, interviewed 28 senior experts from practice and derived a maturity model from the results. We applied the maturity model through an online survey to 29 DBEs from different industry sectors and compared it with 22 maturity assessment approaches from other domains. The maturity model enables researchers to compare and assess existing DBEs and helps practitioners to identify areas for improvement in the collaboration within DBEs. [ABSTRACT FROM AUTHOR]

Background: Industry 4.0 is a burgeoning research area that has been addressed by many research entities. However, the literature shows that the industrial sector lacks the awareness and knowledge needed to comply with Industry 4.0 implications, particularly in developing countries. Methods: This study evaluates the status of small and medium enterprises (SMEs) in Jordan concerning Industry 4.0. Four criteria are assessed, including Industry 4.0 readiness, maturity, drivers, and barriers. Samples of SME respondents and Industry 4.0 experts are surveyed using an online questionnaire. Results: The results show that SMEs in Jordan are not mature enough nor ready to apply Industry 4.0. For the readiness dimension, SME respondents and experts agreed that the Jordanian SMEs' status is between having initiatives in the pilot phase or implementing concepts to low degrees, except for autonomous workpiece and smart product aspects, in which Jordanian SMEs are behind due to financial and technological reasons. It was found that none of the Industry 4.0 investigated technologies have reached maturity levels. Customer requirements, cost reduction, competitors' practice, productivity improvement, and quality improvement are found to be the major influencing drivers for Industry 4.0, while a lack of awareness and knowledge is found to be the crucial barrier hampering Industry 4.0 implementation. Conclusions: Jordan needs country-scale initiatives for the implementation of groundbreaking Industry 4.0 development, incorporating government agencies, industrial parties, and experts, relying on Industry 4.0's readiness and practice status as a starting point, and considering the influential drivers and barriers to steer the development process. [ABSTRACT FROM AUTHOR]

Context. The electronic government has become a trend for transforming public management to comply with the performance of an efficient, modern state. The processes for public procurement and personnel recruitment represent an essential fraction of a country’s public spending. Objective. Maturity models are tools for assessing different management dimensions resulting in some level of organizational maturity on an ordinal scale which can show null, partial, or total progress towards the desired state. This paper presents an e-government maturity model for public procurement and personnel recruitment processes, based on a literature review to determine the current state of research in the field. Methodology. We have used a known procedural model from Becker to support the design of the proposed model. Later on, we have tested it with government buyers and personnel recruiters. Findings. These initial results show that users understand the questionnaires designed for the study, and their answers allow us to obtain deep validation. A tool with these characteristics can be handy for measuring the degree of transparency in public entities, thus reducing corruption levels in their processes. Conclusion. This proposal describes the complexity of variables that influence the transparency of a socio-technical process in public tenders. We describe five levels of transparency for software procurement through development projects. These classifications enable the maturity levels of the transparency of electronic procedures used by government agencies to be measured in different dimensions. Implications. One of the crucial challenges to increasing a government’s transparency is defining a regulatory or legal framework that regulates its processes and allows the levels of transparency or corruption to be measured in its different departments. Thus instruments and metrics play a crucial role in monitoring the expected change. With direct application in the industry, a model is an essential step for fundamental transparency in electronic governments.

Enterprise data warehouses for research (EDW4R) is a critical component of National Institutes of Health Clinical and Translational Science Award (CTSA) hubs. EDW4R operations have unique needs that require specialized skills and collaborations across multiple domains which limit the ability to apply existing models of information technology (IT) performance. Because of this uniqueness, we developed a new EDW4R maturity model based on prior qualitative study of operational practices for supporting EDW4Rs at CTSA hubs. In a pilot study, respondents from fifteen CTSA hubs completed the novel EDW4R maturity index survey by rating 33 maturity statements across 6 categories using a 5-point Likert scale. Of the six categories, respondents rated workforce as most mature (4.17 [3.67–4.42]) and relationship with enterprise IT as the least mature (3.00 [2.80–3.80]). Our pilot of a novel maturity index shows a baseline quantitative measure of EDW4R functions across fifteen CTSA hubs. The maturity index may be useful to faculty and staff currently leading an EDW4R by creating opportunities to explore the index in local context and comparison to other institutions.

Abstract Introduction: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps. Methods: We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration’s Informatics Enterprise Committee, and a publicly available online self-assessment tool. Results: We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels. Conclusion: The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities.

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Background: Due to the high potential to gain competitive advantage in today's global market, supply chains play a critical role in the current industry. Understanding maturity and its features in the context of the supply chain can help companies achieve higher levels of performance. To assess and measure supply chains, a wide variety of supply chain maturity models have been developed to help companies analyze the existing state in the supply chain, allowing for the achievement of higher levels of maturity and providing guidance in the development of an improvement roadmap. Methods: The review spans from the early 1990s to 2021 and examines research carried out and published in the literature, including papers on conference proceedings, articles in journals, and technical reports. The previous models, stages, dimensions (areas/elements), and methods are included in this review. Research gaps are also noted, analyzed, and discussed. Results: The purpose of this study is to perform a comparative analysis of supply chain maturity models to explore the special characteristics of the studied models, which help to identify the differences and similarities between each other, and also to present the various focus areas related to the supply chain. The results show the existence of a large variety of models with a trend to the customs of models for specific area of supply chain. We also identified that most of the models have similar maturity level names and number since they are developed based on previously existing maturity models. The results of this paper are meant to serve as a reference guide for a detailed understanding of documented supply chain maturity models and help practitioners to seek better alignment in regards to supply chain maturity models characteristics. Conclusions: Supply chains play an important role in the market rivalry nowadays. Understanding maturity and its components in the context of supply chain management can help companies perform at higher levels. Despite the high number of maturity models developed in the field of supply chain, the result of this review shows that there is a need for new studies to fill the gaps in the existing work and to take into consideration the complexity faced in the management of supply chain networks. [ABSTRACT FROM AUTHOR]

Despite their undisputed potential, the uptake of collaborative robots remains below expectations. Collaborative robots (cobots) are used differently from conventional industrial robots. The current safety focus of collaborative workspaces is predominantly on the technological design; additional factors also need to be considered to cope with the emerging risks associated with complex systems. Cobot technologies are characterized by an inherent tradeoff between safety and efficiency. They introduce new, emergent risks to organizations and can create psychosocial impacts on workers. This leads to a confusing body of information and an apparent contradiction about cobot safety. Combined with a lack of safety knowledge, this impedes the introduction of cobots. A multi-step methodology was used, including a literature review and conceptual modeling. This article argues for the need for a system-wide safety awareness readiness assessment in the consideration phase of cobot implementation to alleviate the knowledge deficit and confusion. This work will benefit both researchers and practitioners. In addition, it defends the appropriateness of a maturity grid model for a readiness assessment tool. The building blocks for an easy-to-use and practically applicable tool are proposed, as well as an agenda for the next steps. [ABSTRACT FROM AUTHOR]

Maturity models (MMs) are strategic tools used to assess and improve the current state of processes, objects, or people, with the goal of achieving continuous performance enhancement. While MMs are applied in various fields, their scope, design, and application criteria within Supply Chain Management and Logistics (SCML) lack comprehensive studies. This article aims to address this gap through a systematic literature review. The review analyzes 137 relevant articles using both bibliometric and content analysis techniques. The bibliometric analysis identifies major contributions, popular journals, and the classification and evolution of key keywords. The content analysis focuses on critical criteria related to the scope, design, and application of MMs. The findings reveal a growing emphasis on models assessing Industry 4.0 readiness and sustainability principles. However, several gaps are identified, including limited attention to optimizing and integrating logistic processes, underutilized and unvalidated MMs, and the absence of comprehensive improvement guidelines. Based on these trends and research gaps, this study proposes five recommendations for future developments that benefit both academics and practitioners. These recommendations aim to address the identified limitations and provide guidance for comprehensive and effective improvement strategies.

Lean construction (LC) is becoming prevalent, and assessment of the level of LC implementation is vital for organizations to realize their full potential. In meeting that need, lean construction maturity models (LCMMs) play a key role. However, there is less evidence of critical reviews in spite of the significant number of LCMMs available. Therefore, this study was initiated with the aim of systematically reviewing the literature on existing lean-construction-related maturity models (MMs) through a critical review. The study adopted the PRISMA method to review 24 such models using manual content analysis. The study revealed the most common attributes among the models, along with their key strengths and weaknesses. The findings of this study can be directly used to develop more robust LCMMs and enhance the knowledge base on theoretical underpinnings. From an industry perspective, the findings assist organizations to more effectively assess LC maturity. The study invites further research on the area of LC maturity and advocates for developing new MMs addressing these areas identified for improvement.

Industry 4.0 brings technologies of automation, the use of collaborative robots, and modern advanced warehousing interconnected with digitization of all steps of the production process, not excluding logistics. Internal logistics vary in different product types. Due to the specification of the Industry 4.0. concept, irregularities can be improved into fully autonomous processes. This trend also raises SMEs' flexibility in terms of business processes and production organization. The transformation to Industry 4.0 is different from many perspectives (technological, organizational, financial). Therefore, companies need to know their processes' state and determine their readiness for automation and digitization. After this, a consecutive strategy needs to be adjusted. This article presents the evaluation results of a comparison within individual business sectors (automotive, engineering, and electrical engineering fields). Several scientific methods were used for the successful realization of the objectives of the work (basic logical methods and empirical methods). The proposed methodology was verified in the form of an experiment in selected industrial enterprises. Internal logistics processes were observed inside real enterprises as a form of suitable preliminary research. Further potential cooperation between the companies and a team of experts specializing in Industry 4.0 is planned. [ABSTRACT FROM AUTHOR]

Purpose: This paper seeks to establish an Industry 4.0 maturity model for manufacturing SMEs. This research presents the characteristics of the proposed model, which takes the elements and the scope of the fourth industrial revolution, as well as the dimensions and assessment scales of some maturity models already applied. Likewise, this document shows the modeling process and the model's validation in SMEs in the city of Bogotá-Colombia. Design/methodology/approach: To determine the criteria of the maturity model, 6 major stages have been established: Literature Review, Development of the model; Validation of the model; Application of the model; Data analysis; and Conclusion and Recommendations. Findings: Considering the validation of some maturity models shown in the literature review, and aligned with the purpose of this article, 8 dimensions have been established to measure the maturity level of SMEs: Service; Operations; Quality; Products; Documented information-Big Data; Leadership and strategy; Communication; and Culture and people. A model has been generated that allows evaluating the degree of compliance in each dimension for manufacturing SMEs. The model can be applied to companies in any industry. Also, it can determine the degree of implementation compliance of companies in the same sector. Research limitations/implications: According to the literature reviewed, SMEs, especially those in Latin America, still do not have a culture of applying the elements of Industry 4.0. Therefore, in the research, it was not easy to understand the intrinsic variables of Industry 4.0 that SMEs have applied in different areas, which does not allow us to have the current context of SMEs and from that perspective to have a better simulation of the business model maturity. Practical implications: The model presented in this document serves as a basis for SMEs in Latin America to establish a baseline measurement in relation to the application of Industry 4.0 elements in companies. Social implications: What is intended with this work is to frame a baseline so that companies can understand their current maturity level in terms that industry 4.0 could cover. Likewise, they can generate actions for the appropriation of new technologies that allow them to be more competitive. This document can be taken and applied by those entrepreneurs companies who wish to measure their operations. Originality/value: The essential point for the generation of the maturity level measurement model is focused on determining the necessary dimensions on which the evaluation is based. In the literature found, most models focus their dimensions on measuring the digital in their processes and tangentially evaluate the organizational structure and the relationship between them. Additionally, the authors who address the organization as a whole do not reveal the details for SMEs to self-evaluate. The models found have only been implemented to evaluate one company alone or individually. This model presents the core dimensions holistically and explicitly, taking important criteria such as quality, service, communication, and the culture of all employees. Additionally, it shows in detail the model that allows SMEs of the manufacturing sector to self-assess themselves in each dimension and in turn the degree of the business sector in which they are or belong. [ABSTRACT FROM AUTHOR]

The article develops an institutional maturity perspective for foresight capacity building in knowledgeintensive organizations (KIO), as typically embedded in highly demanding dynamics of generation and use of knowledge, which is necessary for constructing comprehensive visions and studying the future. A foresight maturity grid is proposed as structured in five dimensions: people; sophistication of methods, platforms, and infrastructures; the complexity of application areas; organizational structure; and impact on the environment. Described in five maturity levels gradually progressing in organizational capabilities, they constitute an evolutionary logic operatively articulated in processes, projects, and foresight cycles. The resulting grid, conceptually constructed in consideration of other proposals, guides the design and stabilization of foresight systems, forming a basis for the accumulation of organizational learning curves. An application case in a Colombian public KIO provides evidence of its usefulness and applicability in building foresight capabilities. [ABSTRACT FROM AUTHOR]

Digital transformation signifies changes in all components and systems of the supply chain. It is also a strategic decision of the organization which, in the long run, can result in the creation of competitive advantage in the market. Digital transformation is affecting all organizations, regardless of their activity. Digital transformation of the supply chain involves the use of industry 4.0 based technologies as well as the replacement of traditional practices with new ones based on digital solutions. The implementation of digital solutions, such as artificial intelligence, IoT, cloud computing, etc., therefore, improve communication between stakeholders in the supply chain, as well as improve efficiency and effectiveness. When conducted, digital transformation must be measured by different levels of maturity. In this paper, authors research current models of measuring digital transformation maturity in supply chain and propose a new model based on identified theories and needs.

Over the last two decades, governments have increased their investment in information technology to improve the use of public resources, using public electronic procurement systems to obtain better prices, better solutions and to show transparency in the procurement process. Public procurement of software development projects is specific acquisitions having specific technical, methodological, and management constraints that make transparency an elusive target. This article proposes a maturity model as a tool to measure tendering transparency when government agencies procure software development. We have used a procedural model to support the design of maturity models along four dimensions: Institutionalization, Software procurement process, Communication, and Accountability. We have defined a five-step model, and we have tested it with real government buyers. The model is supported by an appraisal tool that helps to guide the next steps in the transparency of software acquisitions.

This study conducted a systematic literature review in order to describe the standards, audit models, maturity, and strategic planning principles for digital preservation. This work has a qualitative research approach, is documentary, descriptive and systematic. It uses the protocol for a systematic literature review. The results indicate a total of 309 candidate studies, 42 selected papers, and 24 primary studies. Ten standards, eight audit models and three digital preservation maturity models are presented. In addition, several studies in the field of strategic planning are analyzed, in aspects such as risks, regulations, administrative management, archival, technological, organizational, levels, strategy policy, structure for digital preservation, among others. [ABSTRACT FROM AUTHOR]

Industry 4.0 requires companies to go through a complex transformation. Numerous maturity models offer to measure the readiness of an enterprise for the transition to a new operation mode. However, there is a lack of research efforts in developing an advisory tool for digital readiness improvement recommendations. This study aims to create a systematic approach for building an advisory decision support system based on Industry 4.0 Maturity Models. The development of the proposed system has gone through three stages, including analysis of the existing maturity models, reviewing the development methods of decision-support systems, and industrial interactions with manufacturing companies via the project online recommendation tool. The developed advisory system provides I4.0 readiness recommendations based on industry best practices, integration of recommendation databases with a maturity model, information filtration algorithm, and weight-based prioritisation of suggestions. Moreover, an interactive and user-friendly interface was developed to enable the user to utilise the system easily and efficiently. [ABSTRACT FROM AUTHOR]