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Quality 4.0 is an emerging research topic concerned with rethinking how quality management needs to be adopted in the digital era. The purpose of this research is to conduct a systematic review on the state of the research in the field of Industry 4.0 impact on improving quality management aspects and how technology can be leveraged to enhance its practices.

A systematic review of the literature published in the last 5 years is conducted. 52 papers were selected, mapped based on the technology they focused on and categorized based on the addressed quality aspects.

The review revealed various areas where quality management can benefit from Industry 4.0 technologies, identified several research gaps and suggested new directions for future research. Firstly, the literature provided some insights about industry 4.0 potential contributions but lacks further detail on the exact applications and solutions through use cases and case studies. Secondly, there has been a focus on the potential benefits provided for quality control while there is a clear scarcity in terms of the other quality management tools and methodologies. Thirdly, there is a lack of studies on economic analysis or detailed impacts on quality costs that justifies the substantial investments needed. Finally, there is a need for including more studies about the mapping and integration of ISO 9001 requirements and Industry 4.0 features.

This is the first attempt to conduct a comprehensive review on the ways industry 4.0 technologies can be leveraged for the field of quality management. Based on this review, several directions for further research in this area are identified.

This study aims to investigate the adoption of Quality 4.0 (Q4.0) and assess the critical failure factors (CFFs) for its implementation and how its failure is measured.

A qualitative study based on in-depth interviews with quality managers and executives was conducted to establish the CFFs for Q4.0.

The significant CFFs highlighted were resistance to change and a lack of understanding of the concept of Q4.0. There was also a complete lack of access to or availability of training around Q4.0.

The study enhances the body of literature on Q4.0 and is one of the first research studies to provide insight into the CFFs of Q4.0.

Based on the discussions with experts in the area of quality in various large and small organizations, one can understand the types of Q4.0 initiatives and the CFFs of Q4.0. By identifying the CFFs, one can establish the steps for improvements for organizations worldwide if they want to implement Q4.0 in the future on the competitive global stage.

The concept of Q4.0 is at the very nascent stage, and thus, the CFFs have not been found in the extant literature. As a result, the article aids businesses in understanding possible problems that might derail their Q4.0 activities.

Recent research outputs can be difficult to implement into ongoing safety critical processes. Hence, research is well beyond current practices in railway asset management. This paper demonstrates the process of creating tangible change within a railway asset management organization by introducing a framework for advancing track geometry deterioration analyses (TGDA) in practice.

The research was conducted in three parts: (1) maturity models were reviewed and adapted as the basis for the framework, (2) the initial maturity level was investigated by conducting semi-structured expert interviews, and (3) a framework for development was created in cooperation with stakeholders during three workshops. The methodology and findings were tested and applied in the Finnish state rail network asset management.

The main output of this study is the framework for advancing TGDA in railway asset management. The novel framework provides structure for controlled incremental development, which is essential when altering a safety critical process.

The research process was successfully applied in Finland. Following the steps presented in this article, any organization can apply the framework to plan their development schemes for railway asset management.

Full-scale implementation of novel models and methods is often overlooked, which prevents practical asset management from obtaining tangible benefits from research. This research provides an innovative approach in narrowing the overlooked research gap and brings research results within the reach of practitioners.

Today, companies are struggling to develop their human resources analytics (HRA) capability, although interest in the subject is rapidly increasing. Furthermore, the academic literature on the subject is immature with limited practical guidance or comprehensive models that could support organisations in the development of their HRA capability. To address this issue, the aim of this paper is to provide a maturity model – i.e. HRAMM – and an interdependency matrix through which an organisation can (1) operationalise its HRA capability and assess its organisational maturity; (2) generate harmonious development roadmaps to improve its HRA capability; and (3) enable benchmarking and continuous improvement.

The research described in this paper is based on the popular methodology proposed by Becker et al. (2009) and the procedure for maturity evaluation developed by Gastaldi et al. (2018). This method combines academic rigour and field experience in analytics, in a process spanning eight main phases that involves literature reviews and knowledge creation techniques.

We define HRA maturity through four areas and 14 dimensions, providing a comprehensive model to operationalise HRA capability. Additionally, we argue that HRA maturity develops through an evolutionary path described in four discrete stages of maturity that go beyond traditional analytics sophistication. Lastly, the interdependency matrix reveals specific enablers for the development of HRA.

This paper provides practitioners with useful tools to monitor, evaluate and plan their HRA development path. Additionally, our research helps practitioners to prioritise their work and investment, generating an effective roadmap for developing and improving their HRA capability.

To the best of the authors’ knowledge, this study is the first to provide a model for evaluating the maturity of HRA capability plus an interdependency matrix to evaluate systematically the prerequisites and synergies among its constituting dimensions.

The purpose of this paper is twofold: first, to describe Lean maturity in primary care using a questionnaire based on Liker’s description of Lean, complemented with observations; and second, to determine the extent to which Lean maturity is associated with quality of care measured as staff-rated satisfaction with care and adherence to national guidelines (NG). High Lean maturity indicates adoption of all Lean principles throughout the organization and by all staff.

Data were collected using a survey based on Liker’s four principles, divided into 16 items (n=298 staff in 45 units). Complementary observations (n=28 staff) were carried out at four units.

Lean maturity varied both between and within units. The highest Lean maturity was found for “adhering to routines” and the lowest for “having a change agent at the unit.” Lean maturity was positively associated with satisfaction with care and with adherence to NG to improve healthcare quality.

Quality of primary care may benefit from increasing Lean maturity. When implementing Lean, managers could benefit from measuring and adopting Lean maturity repeatedly, addressing all Liker’s principles and using the results as guidance for further development.

This is one of the first studies to evaluate Lean maturity in primary care, addressing all Liker’s principles from the perspective of quality of care. The results suggest that repeated actions based on evaluations of Lean maturity may help to improve quality of care.

A globalized world demands proactive tactics from organizational supply chains. Companies should be capable of mitigating the impacts of natural and manmade disasters, which requires that they understand their stages of maturity and resilience. This study develops a theoretical model of the relationship between maturity and resilience, seeking to guide decision-making about aligning these two concepts.

A systematic literature review was conducted to identify the constructs that form the basis for our proposed maturity and resilience model.

The authors identified the key constructs related to maturity and resilience by analyzing the existing literature and selected 13 constructs and 3 maturity stages to construct our maturity and resilience model.

This research contributes to the supply chain management literature, especially that involving the themes of maturity and resilience. It can encourage research to develop future empirical research in the field to validate and overcome the limitations of the initial model the authors propose.

The authors’ proposed model supports supply chain managers in establishing strategies to increase resilience based on the maturity of the chains they manage, enabling them to face crises such as the coronavirus disease 2019 (COVID-19) pandemic.

The model presents a holistic view of maturity and resilience in supply chains contributing to supply chain theory by examining the alignment between the two themes.

This study aims to determine if the quality of national institutions and banking development condition the maturity of debt depending on the horizon of short or long term.

Analysis is performed on a sample of 116 nonfinancial companies from Peru and Brazil. The measures of quality of national institutions and banking development were obtained from World Bank data and included factorial analysis for dynamic considerations.

The findings, through the treatment of pointed indicators, the factor analysis and the subsequent estimation of a dynamic econometric model, called GMM-SYS, show that institutional quality fosters the maturity of long-term debt and banking development boots short-term financial relations.

Evaluating different measures of the quality of national institutions and banking development is necessary to demonstrate the robustness of the results beyond the sample evaluated in Latin America.

The research allows to understand the interaction between national institutions and system banking through debt maturity, and this is useful for establishing common target between both groups.

It is important for corporate finance to understand the mechanisms of the interaction between national institutions and system banking, because this affects internal decisions of firms regarding financial implications.

The treatment of measures of national institutions and banking development include dynamic considerations, and the application of this study in Latin America provides new findings regarding these kind of indexes and their interaction with firms´ features such as debt maturity.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.