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Industry 4.0 has offered significant potential for manufacturing firms to alter and rethink their business models, production processes, strategies and objectives. Manufacturing organizations have recently undergone substantial transformation due to Industry 4.0 technologies. Hence, to successfully deploy and embed Industry 4.0 technologies in their organizational operations and practices, businesses must assess their adoption readiness. For this purpose, a multi-dimensional analytical indicator methodology has been developed to measure Industry 4.0 maturity and preparedness.

A weighted average method was adopted to assess the Industry 4.0 readiness using a case study from a steel manufacturing organization.

The result revealed that the firm ranks between Industry 2.0 and Industry 3.0, with an overall score of 2.32. This means that the organization is yet to achieve Industry 4.0 mature and ready organization.

The multi-dimensional indicator framework proposed can be used by managers, policymakers, practitioners and researchers to assess the current status of organizations in terms of Industry 4.0 maturity and readiness as well as undertake a practical diagnosis and prognosis of systems and processes for its future adoption.

Although research on Industry 4.0 maturity models has grown exponentially in recent years, this study is the first to develop a multi-dimensional analytical indicator to measure Industry 4.0 maturity and readiness.

Earned value management systems (EVMS), also called integrated project and program management systems, have been greatly examined in the literature, which has typically focused on their technical aspects rather than social. This study aims to hypothesize that improving both the technical maturity of EVMS and the social environment elements of EVMS applications together will significantly impact project performance outcomes. For the first time, empirical evidence supports a strong relationship between EVMS maturity and environment.

Data was collected from 35 projects through four workshops, attended by 31 industry practitioners with an average of 19 years of EVMS experience. These experts, representing 23 organizations, provided over 2,800 data points on sociotechnical integration and performance outcomes, covering projects totaling $21.8 billion. Statistical analyses were performed to derive findings on the impact of technical maturity and social environment on project success.

The results show statistically significant differences in cost growth, compliance, meeting project objectives and business drivers and customer satisfaction, between projects with high EVMS maturity and environment and projects with poor EVMS maturity and environment. Moreover, the technical and social dimensions were found to be significantly correlated.

Key contributions include a novel and tested performance-driven framework to support integrated project management using EVMS. The adoption of this detailed assessment framework by government and industry is driving a paradigm shift in project management of some of the largest and most complex projects in the U.S.; specifically transitioning from a project assessment based upon a binary approach for EVMS technical maturity (i.e. compliant/noncompliant to standards) to a wide-ranging scale (i.e. 0–1,000) across two dimensions.

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 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.

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.

The factors for higher education institutions’ (HEIs) project management failure have been studied for several years. One of the issues is a lack of tools to combine their knowledge infrastructure capabilities (KIC) with project management (PM) to examine these infrastructures and monitor maturity. There are several project management maturity (PMM) models available. However, there are just a few empirical studies that support the three knowledge infrastructure capabilities and PMM integrations. As a result, the current research aims to suggest a new conceptual model, KIC-knowledge management (KM), and assess a research model that includes the three knowledge infrastructure capabilities as a prerequisite to elevate the PMM.

Partial least squares structural equation modeling (PLS-SEM) is used to evaluate the proposed research model. The study’s hypotheses were also examined using a sample of 352 respondents from PM departments at ten Yemeni public universities.

The study found that if the three key knowledge infrastructure capabilities integrate into the PMs, then it will help HEIs to perform project tasks more effectively and efficiently. Also, it will improve the PM maturity level if all the three capabilities positively effect PMM.

The study findings cannot be generalized to other industries because the collected date were with the Yemeni public universities’ context. Also, the new proposed model can be assessed in various sectors to increase the validity of the model. One more thing, future academics can conduct qualitative research study to validate again the proposed model.

Project managers can develop and improve their organization’s effectiveness and performance by focusing on these findings and using the developed model. Also, the findings of this study can be used as a benchmark for evaluating initiatives and knowledge-based governmental entities.

It is an opportunity for knowledge-based governmental entities particularly and other organizations to elevate most of projects to achieve a supreme level of maturity. Also, this study will assist employees to understand the relationship between KICs and projects within HEIs in Yemen.

This paper is among the first to empirically study the impact of the three knowledge infrastructure capabilities toward PMM. It links between two important domains: KM and PM.

This paper reports the developments of a project cost control system (PCCS) for construction projects to (1) measure its current level of cost control maturity, (2) examine the relationships between elements within PCCS processes and (3) identify improvement areas.

This study adopts a mixed approach of descriptive analysis and partial least squares structural equation modelling (PLS-SEM) to measure the current maturity level of PCCS and evaluate the relationships between elements within PCSS to identify improvement areas. Further importance-performance matrix analysis (IPMA) of priority constructs was conducted to improve a target construct and identify the most important areas of specific actions at indicator levels. The results of IPMA revealed the contrast that has the greatest importance on the performance of others so that the recommendations can be made accordingly. Data collected in New Zealand were used to develop the research model.

This study develops structural and measurement models with the constructs including pre-control, in-control and post-control processes, enablers and their proposed interrelationships. Then, data from survey of 184 experienced project cost control team members reveal that post-control has the lowest maturity or weakest areas in the PCCS. Data analysis facilitated by PLS-SEM confirmed that all the constructs in the structural model have positive and significant relationships with each other and suggested that systematic cost analysis reports, communication, skills and experience, defining roles and responsibilities, and top management's support should be the highest priority for improving the PCCS in a more effective manner.

This study presents one of the earliest attempts to develop and test an integrated model that links sub-processes in PCCS and their enablers. Secondly, this research adds to the construction project management literature by empirically verifying the roles of enablers in enhancing maturity level of PCCS.

The human factor is the most important defense asset against cyberattacks. To ensure that the human factor stays strong, a cybersecurity culture must be established and cultivated in a company to guide the attitudes and behaviors of employees. Many cybersecurity culture frameworks exist; however, their practical application is difficult. This paper aims to demonstrate how an established framework can be applied to determine and improve the cybersecurity culture of a company.

Two surveys were conducted within eight months in the internal IT department of a global software company to analyze the cybersecurity culture and the applied improvement measures. Both surveys comprised the same 23 questions to measure cybersecurity culture according to six dimensions: cybersecurity accountability, cybersecurity commitment, cybersecurity necessity and importance, cybersecurity policy effectiveness, information usage perception and management buy-in.

Results demonstrate that cybersecurity culture maturity can be determined and improved if accurate measures are derived from the results of the survey. The first survey showed potential for improving the dimensions of cybersecurity accountability, cybersecurity commitment and cybersecurity policy effectiveness, while the second survey proved that these dimensions have been improved.

This paper proves that practical application of cybersecurity culture frameworks is possible if they are appropriately tailored to a given organization. In this regard, scientific research and practical application combine to offer real value to researchers and cybersecurity executives.

This study aims to develop and implement an initial framework for assessing progress in lean implementation within an higher education institution (HEI). It includes developing preliminary findings regarding the impacts of lean implementation in the HEI case organization and comparing outcomes from this assessment to outcomes from other published sources.

Existing literature on lean, particularly in an HEI context, was used to develop a preliminary lean assessment framework for HEIs. Quality and continuous improvement literature were also compared to the proposed assessment framework to further validate the approach. This assessment framework was then utilized to evaluate lean implementation at a large public university (LPU) in the U.S.

The paper presents the framework as well as the major findings from the Large Public University (LPU)’s assessment. The assessment findings are further compared to other HEI quality measures and lean assessments done in other industries. Overall, the findings suggest that the assessment framework provides valuable insight to HEI organizations implementing lean.

The research intends to support lean assessment standardization efforts by proposing a preliminary lean assessment framework for the HEI, grounded in research trends, research findings, identified gaps in the research, and case study outcomes. To the research team's knowledge, this is the first lean assessment framework proposed for HEIs and also contributes to research gaps related to service industry frameworks and those containing both practices and outcomes. The framework can be used by other researchers as a foundation for additional conceptual and empirical developments on the topic and by researchers and practitioners seeking to understand and assess lean implementation progress in the HEI.

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.