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

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

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

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

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

The research aims to develop an assessment framework that evaluates critical success factors (CSFs) for the Quality 4.0 (Q 4.0) transition among Indian firms.

The authors use the fuzzy-Delphi method to validate the results of a systematic literature review (SLR) that explores critical aspects. Further, the fuzzy decision-making trial and laboratory (DEMATEL) method determines the cause-and-effect link. The findings indicate that developing a Q 4.0 framework is essential for the long-term success of manufacturing companies. Utilizing the power of digital technology, data analytics and automation, manufacturing companies can benefit from the Q 4.0 framework. Product quality, operational effectiveness and overall business performance may all be enhanced by implementing the Q 4.0 transition framework.

The study highlights significant awareness of Q 4.0 in the Indian manufacturing sector that is acquired through various means such as training, experience, learning and research. However, most manufacturing industries in India still follow older quality paradigms. On the other hand, Indian manufacturing industries seem well-equipped to adopt Q 4.0, given practitioners' firm grasp of its concepts and anticipated benefits, including improved customer satisfaction, product refinement, continuous process enhancement, waste reduction and informed decision-making. Adoption hurdles involve challenges including reliable electricity access, high-speed Internet, infrastructure, a skilled workforce and financial support. The study also introduces a transition framework facilitating the shift from conventional methods to Q 4.0, aligned with the principles of the Fourth Industrial Revolution (IR).

This research exclusively examines the manufacturing sector, neglecting other fields such as medical, service, mining and construction. Additionally, there needs to be more emphasis on the Q 4.0 implementation frameworks within the scope of the study.

This may be the inaugural framework for transitioning to Q 4.0 in India's manufacturing sectors and, conceivably, other developing nations.

This study aims to validate a model to assess the level of lean maturity of Brazilian hospitals based on the adaptation of the SAE J4000/2021 standard.

The methodology was divided: (1) adaptation of the standard to the health context, (2) application of the questionnaire through a survey, and (3) comparison of the results of the level of maturity in the standard and by the clustering technique, using Minitab.

The research presents two contributions: (1) validation of a model to assess the level of lean maturity based on the SAE J4000/2021; (2) insights into the level of maturity of Brazilian hospitals. It was observed that only 10% of the sample was classified at maturity level 3 and 75% at level 2. Private and large hospitals showed greater maturity compared to the others.

This includes the limited number of hospitals that participated in the survey, given the difficulty of adherence to due constraints of time and staffing from hospitals, during the COVID-19 pandemic.

This article presents a lean maturity assessment proposal, adapting a consolidated standard in the automobile industry to the health context. Insights on the lean maturity of Brazilian hospitals can contribute to the development of policies to encourage the implementation of the lean philosophy directed to each specific environment.

This study serves as a guide for public agents interested in monitoring the quality of hospital indicators through the SAE J4000/2021 standard. From this lean maturity analysis, hospital managers can understand their opportunities for improvement in both human and organizational aspects. This favors the improvement of service delivery to society that depends on health services.

Due to the lack of research that validates lean maturity level assessment models in Brazilian hospitals, this study can be considered a pioneer in this Brazilian research by validating the SAE J4000/2021 standard in its updated version in the health context.

Identifying the criteria that effectively drive innovation in universities is critical to assessing their innovation maturity level, and hence, planning for the improvements required to reach a target level. This paper aims to propose a three-phase approach to develop a multidimensional maturity assessment framework used by university decision-makers to determine their level of innovation readiness.

First, a systematic collection of evaluation criteria from the literature is conducted. The results are mapped into different categories in a hierarchical and multidimensional way, and validated by experts. The second phase aims to identify the critical factors and their priorities, which are determined using analytic network process (ANP). To facilitate that, a panel of thirteen experts is formed and questionnaires are sent to rank the importance of the criteria and their elements. Finally, a maturity assessment tool is developed to complement the framework, allowing decision-makers to determine the level of innovation maturity with respect to each dimension and the overall position.

Results revealed three clusters, eight criteria and 26 subcriteria related to innovation in universities. The findings about the relative importance of the various attributes are reflected in the developed assessment tool and taken into consideration in the maturity indices computation approach.

To the best of the authors’ knowledge, this is the first attempt to develop a comprehensive list of innovation success drivers in universities and to use this list to design an innovation maturity assessment framework

Lean manufacturing (LM) concepts have been widely adopted in diverse industrial sectors. However, no literature review focusing on case studies describing LM implementation is available. Case studies represent the actual implementation and provide secondary data for further analysis. This study aims to review the same to understand the pathways of LM implementation. In addition, it aims to analyse other related review questions, such as how implementing LM impacts manufacturing capabilities and the maturity level of manufacturing organisations that implemented LM, to name a few.

A literature review of case studies that discuss the implementation of LM during the last decade (from 2010 to 2020) is carried out. These studies were synthesised, and content analyses were performed to reveal critical insights.

The implementation pattern of LM significantly varies across manufacturing organisations. The findings show simultaneous improvement in manufacturing capabilities. Towards the end of the last decade, organisations implemented LM with radio frequency identification, e-kanban, simulation, etc.

Reviewing the case studies documenting LM implementation to comprehend the various nuances is a novel attempt. Furthermore, potential future research directions are identified for advancing the research in the domain of LM.

This study aims to analyze how cultural variations impact the relationship between long-term debt use and managerial overconfidence. Investigate into how the relationship between growth prospects and the utilization of long-term debt is moderated by managerial overconfidence. In addition, the research explores the moderating effect of managerial overconfidence on cash flow levels.

The study used long-term debt as the dependent variable and used generalized method of moments–instrumental variables regression analysis to examine data from 356 firms across 11 Middle East and North Africa (MENA) countries and 5 industries between 2013 and 2021.

CEO overconfidence moderately boosts the link between long-term debt maturity and growth potential, particularly for firms with limited internal funding. Cultural factors, such as masculinity and uncertainty avoidance, play a significant role in moderating the relationship between managerial overconfidence and debt maturity choices.

To understand the impact of managerial overconfidence on a company’s debt maturity decision, it is essential for boards and shareholders to consider and monitor the CEO’s behavioral traits, particularly for growing companies. Regulators and policymakers must also be wary of the risk of internal control weakening due to overconfident managers, especially in MENA markets.

The authors’ contribution to the literature lies in exploring how managerial overconfidence moderates the agency conflict between shareholders and debtholders in MENA region firms, which has received minimal attention in previous studies. This study expands the knowledge of the impact of managerial overconfidence on emerging economies and provides evidence that national culture plays a vital role in determining debt financing decisions.

This paper aims to explore and develop knowledge about implementing and applying a quality management system (QMS) in the public sector.

A study was conducted including 16 qualitative in-depth interviews with 18 respondents, all working with QMSs in the Swedish public sector.

The study identified five main themes that are problematic in relation to the implementation of the statutory QMS in the public sector. The identified themes show that there exists a gap between theory and practice regarding how the statutory QMS needs to be implemented and applied.

Based on the analysis of the findings, the authors propose a model of core values and supporting elements for QMS in the public sector to bridge the gap between theory and practice.

The study identified problems when implementing statutory QMSs in the public sector and presents a model of improvement. Further research is needed regarding statutory QMS in the public sector.

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.

Quality 4.0 is being presented as the new stage of quality development. However, its overlying concept and rationale are still hard to define. To better understand what different authors and studies advocate being Quality 4.0, a systematic literature review was undertaken on the topic. This paper presents the results of such review, providing some avenues for further research on quality management.

The documents for the systematic literature review have been searched on the Scopus database, using the search equation: [TITLE-ABS-KEY (“Quality 4.0”) OR TITLE-ABS-KEY (Quality Management” AND (“Industry 4.0” OR “Fourth Industr*” OR i4.0))]. Documents were filtered by language and by type. Of the 367 documents identified, 146 were submitted to exploratory content analysis.

The analyzed documents essentially provide theoretical discussions on what Quality 4.0 is or should be. Five categories have emerged from the content analysis undertaken: Industry 4.0 and the Rise of a New Approach to Quality; Motivations, Readiness Factors and Barriers to a Quality 4.0 Approach; Digital Quality Management Systems; Combination of Quality Tools and Lean Methodologies and Quality 4.0 Professionals.

It was hard to find studies reporting how quality is actually being managed in organizations that already operate in the Industry 4.0 paradigm. Answers could not be found to questions regarding actual practices, methodologies and tools being used in Quality 4.0 approaches. However, the research undertaken allowed to identify in the literature different ways of conceptualizing and analyzing Quality 4.0, opening up avenues for further research on quality management in the Industry 4.0 era.

This paper offers a broad look at how quality management is changing in response to the affirmation of the Industry 4.0 paradigm.

The construction industry has struggled to deliver schemes on time to budget and right-first-time (RFT). There have been many studies into nonconformance and rework through quantitative research over the years to understand why the industry continues to see similar issues of failure. Some scholars have reported rework figures as high as 12.6% of total contract value, highlighting major concerns of the sustainability of construction projects. Separately, however, there have been few studies that explore and detail the views of industry professions who are caught in the middle of quality issues, to understand their perceptions of where the industry is failing. As such, this paper interrogates qualitative data (open-ended questions) on the topic of nonconformance and rework in construction to understand what industry professionals believe are the causes and suggested improvement areas.

A qualitative approach is adopted for this research. An industry survey consisting of seven open-ended questions is presented to two professional working groups within a Tier 1 contractor, and outputs are analysed using statistic software (NVivo 12) to identify prominent themes for discussion. Inductive analysis is undertaken to gain further insight into responses to yield recurrent areas for continuous improvement.

Qualitative analysis of the survey reveals a persistent prioritisation of cost and programme over quality management in construction project. Furthermore, feedback from construction professionals present a number of improvement areas that must be addressed to improve quality. These include increased training and competency investment, overhauling quality behaviours, providing greater quality leadership direction and reshaping the way clients govern schemes.

There are limitations to this paper that require noting. Firstly, the survey was conducted within one principal contractor with varying levels of knowledge across multiple sectors. Secondly, the case study was from one major highways scheme; therefore, the generalisability of the findings is limited. It is suggested that a similar exercise is undertaken in other sectors to uncover similar improvement avenues.

The implications of this study calls for quality to be re-evaluated at project, company, sector and government levels to overhaul how quality is delivered. Furthermore, the paper identifies critical learning outcomes for the construction sector to take forward, including the need to reassess projects to ensure they are appropriately equip with competent personnel under a vetted, progressive training programme, share collaborative behaviours that value quality delivery on an equal standing to safety, programme and cost and tackle the inappropriate resource dilemmas projects finding themselves in through clear tendering and accurate planning. In addition, before making erratic decisions, projects must assess the risk profiling of proceed without approved design details and include the client in the decision-making process. Moreover, the findings call for a greater collaborative environment between the construction team and quality management department, rather than being seen as obstructive (i.e. compliance based policing). All of these must be driven by leadership to overhaul the way quality is managed on schemes. The findings demonstrate the importance and impact from open-ended survey response data studies to enhance quantitative outcomes and help provide strengthened proposals of improvement.

This paper addresses the highly sensitive area of quality failure outcomes and interrogates them via an industry survey within a major UK contractor for feedback. Unique insights are gained into how industry professionals perceive quality in construction. From previous research, this has been largely missing and offers a valuable addition in understanding the “quality status quo” from those delivering schemes.