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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.

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.

The various quality improvement (QI) frameworks and maturity models described in the health services literature consider some aspects of QI while excluding others. This paper aims to present a concerted attempt to create a quality improvement maturity model (QIMM) derived from holistic principles underlying the successful implementation of system-wide QI programmes.

A hybrid methodology involving a systematic review (Phase 1) of over 270 empirical research articles and books developed the basis for the proposed QIMM. It was followed by expert interviews to refine the core constructs and ground the proposed QIMM in contemporary QI practice (Phase 2). The experts included academics in two academic conferences and 59 QI managers from the New Zealand health-care system. In-depth interviews were conducted with QI managers to ascertain their views on the QIMM and its applicability in their respective health organisations (HOs).

The QIMM consists of four dimensions of organisational maturity, namely, strategic, process, supply chain and philosophical maturity. These dimensions progress through six stages, namely, identification, ad-hoc, formal, process-driven, optimised enterprise and finally a way of life. The application of the QIMM by the QI managers revealed that the scope of QI and the breadth of the principles adopted by the QI managers and their HOs in New Zealand is limited.

The importance of QI in health systems cannot be overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality overstated. The proposed QIMM can help HOs diagnose their current state and provide a guide to action achieving a desirable state of quality improvement maturity. This QIMM avoids reliance on any single QI methodology. HOs – using the QIMM – should retain full control over the process of selecting any QI methodology or may even cherry-pick principles to suit their needs as long as they understand and appreciate the true nature and scope of quality.

This paper contributes new knowledge by presenting a maturity model with an integrated set of quality principles for HOs and their extended supply networks.

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.

The purpose of this study is to propose a framework for the convergence of maturity model and education and evaluation in accounting.

The present research was conducted in two phases. In the first phase, to determine the indicators of convergence of the maturity model and education and evaluation in accounting, a Meta-Synthesis method was used. The conceptual model includes two dimensions of “Teaching and learning processes” and “Evaluation methods"; five levels of initial, repeatable, defined, managed and optimized; and a total number of 35 indicators. In the second phase, a questionnaire was developed, and academics as accounting faculty members in Iranian public universities were employed to fill out the questionnaire electronically and present a final framework. Having received the questionnaires, 66 questionnaires were analyzed statistically.

The results showed that the two dimensions of “Teaching and learning processes” and “Evaluation methods” considering initial, repeatable, defined, managed and optimized levels include 35 indicators, which form a framework for the convergence of maturity model and education and evaluation in accounting. The results show that both dimensions have positive and significant regression path coefficients in the convergence model. Moreover, the dimension of teaching and learning processes has the highest regression path coefficient indicating a greater impact on the convergence model. Besides, all five levels have positive and significant regression path coefficients with dimensions. Finally, in this study, all indicators were prioritized according to five levels.

Due to the success of maturity models and the urgent developments that require transformative improvements in accounting education, maturity models can respond to the challenges associated with education and learning in accounting. Thus, conceiving an image of the convergence of maturity model, education and evaluation in accounting seems imperative which has been scarcely investigated previously.

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.

This study’s main objective is to explore the ISO 9001 implementation model and identify a future research agenda. This is important because not all organizations find it easy to implement ISO 9001, and not all organizations get positive benefits after implementing it.

The paper presents a comprehensive review of the literature on ISO 9001 implementation models using the preferred reporting items for systematic reviews (PRISMA) methodology to systematically review the existing literature on ISO 9001 implementation models. Relevant studies published from 2003 to early 2023 are explored to reveal the research landscape, gaps and trends.

Many ISO 9001 implementation methods have been developed for actual implementation in organizations, including models, frameworks, special variable considerations, application uses and integration. These methods were developed and applied to cover gaps regarding constraints, unbeneficial, special conditions, implementation objectives and organization types in ISO 9001 implementation. Current issues and future research on ISO 9001 implementation models were found, namely ISO 9001 implementation models specific to SMEs, ISO 9001 implementation levels, ISO 9001 implementation models that are agile to change, and affordable certification models.

Only a few researchers have systematically reviewed the literature or taken a bibliometric approach in their analyses to provide an overview of the current trends and links to ISO 9001 implementation models. The ISO 9001 standard is a general standard and can be applied by all organizations with the implementation method left to the implementer. Many implementation methods have been developed, but several implementation obstacles and disadvantages are still found. It is important to know the extent of current research and discover future research gaps regarding methods of implementing the ISO 9001 standard.

Construction industry (CI) has great prominence for the world economy, and it is expected that, with the use of the innovative technologies and approaches of Industry 4.0 (I4.0), the new industrial paradigm, construction can reach higher levels of productivity. This study aims to develop a model (readiness model) to assess the level of use of I4.0 technologies by the construction sector in Brazil and its most relevant applications.

The methodology used was bibliographic research, design-science research and a survey to validate the model, carried out with 162 companies, considered among the main ones in the sector in Brazil. The literature review revealed 13 technologies of I4.0 applied to construction; hence, the views of industry experts were based on these technologies.

The Digital Advancement Within CoNstruction (DAWN) readiness model was proposed, showing that among the 13 evaluated technologies of I4.0 and their applications, the Brazilian construction companies had a low level of utilization; both high and middle-income companies presented this low level of use; some technologies with a greater number of scientific publications were less used in practice in the Brazilian construction.

The originality and theoretical contribution are to present a readiness model to assess the level of use of I4.0 technologies and their most relevant applications in the CI in countries with an economy similar to Brazil’s, making it possible to measure the level of adoption of these technologies.

Digitalisation, which involves the use of digital technologies in transforming an organisation’s activities, transcends just the acquiring of emerging digital tools. Having the right people to drive the implementation of these technologies and attaining strategic organisational goals is essential. While most studies have focused on the use of emerging technologies in the construction industry, less attention has been given to the ‘people’ dimension. Therefore, this study aims to assess the people-related features needed for construction digitalisation.

The study adopted pragmatic thinking using a mixed-method approach. A Delphi was used to achieve the qualitative aspect of the research, while a questionnaire survey conducted among 222 construction professionals was used to achieve the quantitative aspect. The data gathered were analysed using frequency, percentage, mean item score, Kruskal–Wallis H test, exploratory factor analysis and confirmatory factor analysis.

Based on acceptable reliability, validity and model fit indices, the study found that the people-related factors needed for construction digitalisation can be grouped into technical capability of personnel, attracting and retaining digital talent and organisation’s digital culture.

The findings offer valuable benefits to construction organisations as understanding these identified people features can help lead to better deployment of digital tools and the attainment of the digital transformation.

This study attempts to fill the gap in the shortage of literature exploring the people dimension of construction digitalisation. The study offers an excellent theoretical backdrop for future works on digital talent for construction digitalisation, which has gained less attention in the current construction digitalisation discourse.

The purpose of this paper is to analyse and classify the literature that contributed to three questions, namely, what are the benefits of big data analytics (BDA) in the field of supply chain management (SCM) and logistics, what are the challenges in BDA applications in the field of SCM and logistics and what are the determinants of successful applications of BDA in the field of SCM and logistics.

This paper conducts a systematic literature review (SLR) to analyse the findings of 44 selected papers published in the period from 2016 to 2020, in the area of BDA and its impact on SCM. The designed protocol is composed of 14 steps in total, following Tranfeld (2003). The selected research papers are categorized into four themes.

This paper identifies sets of benefits to be gained from the use of BDA in SCM, including benefits in data analytics capabilities, operational efficiency of logistical operations and supply chain/logistics sustainability and agility. It also documents challenges to be addressed in this application, and determinants of successful implementation.

The scope of the paper is limited to the related literature published until the beginning of Corona Virus (COVID) pandemic. Therefore, it does not cover the literature published since the COVID pandemic.

This paper contributes to the academic research by providing a roadmap for future empirical work into this field of study by summarising the findings of the recent work conducted to investigate the uses of BDA in SCM and logistics. Specifically, this paper culminates in a summary of the most relevant benefits, challenges and determinants discussed in recent research. As the field of BDA remains a newly established field with little practical application in SCM and logistics, this paper contributes by highlighting the most important developments in contemporary literature practical applications.