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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.

The purpose of this paper is to determine if companies in the modular and offsite construction (MOC) industry are agile or not and its level of application for agility principles, which allows for quick responses to the increasingly dynamic nature of industry environments.

This paper proposes an agility assessment framework for MOC that uses 48 assessment attributes organized into four categories: metrics, drivers, enablers and capabilities. A questionnaire approach was used to disseminate the framework globally in 19 countries and synthesize its relevance to the MOC industry. The questionnaire had 55 complete responses, majority of respondents work in managerial positions for MOC manufacturing facilities and onsite general contractors.

It was found that the lowest metric score for adapting to change was for cost since controlling cost would be difficult for any changes required after the design freeze stage. The top agility driver was found to be the need to respond to the wide variety of customer expectations, while the lowest driver was the existence of competing priorities. The top agility enabler was vendor partnership, which can be related to current postpandemic supply chain disruptions. Regarding technological capabilities, Europe and the USA acquired better scores compared to Asia, Latin America and Africa.

This study contributes to the MOC body of knowledge by creating an agility assessment tool for MOC firms to analyze their agile approach and environment, identifying the preliminary importance of agility assessment attributes and determining significant agile differences between the main MOC industry groups.

The lack of knowledge has hindered the successful implementation of lean in the construction industry. This has alarmed the need for lean learning practices. Out of numerous models, the learning-to-learn sand cone model received a wider acknowledgment for learning practices. Thus, this study aims to propose a learning-to-learn sand cone model integrated lean learning framework for the construction industry.

The research adopted an interpretivism stance. A qualitative research approach was adopted for the study. Consequently, fifteen (15) semi-structured interviews and document reviews were carried out to collect data in three (3) cases selected through purposive sampling. Code-based content analysis was used to analyse the data.

Fifty-two (52) sub-activities pertaining to nine lean learners at each stage of the lean learning procedure were identified. The most significant practices in the lean learning procedure to continuously improve lean learning in the organisation were maintaining records, providing a performance update to senior management and preparing and distributing several hierarchical manuals for all levels of staff to aid in the implementation of lean approaches.

The findings of the research can be aided to successfully implement lean by following the identified sub-activities via various parties within the organisation. The proposed lean learning framework opens several research areas on lean learning in the construction industry. This is the first research to uncover a lean learning framework in the construction industry rather than at the educational institute level.

In response to mounting global concerns about climate change and scarcity of natural resources, manufacturers have been pressured to develop strategies and enhance their sustainability performance. The integration of sustainable lean manufacturing (SLM) during value chain processes could balance environmental, social and economic concerns into their decision-making, which not only ensures responsible practices but also drives efficiency and success. This paper aims to identify, measure and prioritize metrics to develop a performance measurement system that assesses the multi-dimensional performance of SLM.

Strategic decision-making has some conflicting criteria and objectives to be considered simultaneously. The Multi-Criteria Decision Making provides a foundation for selecting, sorting and prioritizing these strategies with the determination of drivers and indicator weight.

The performance model enables the decision-makers to consistently evaluate the level of sustainability through a multidimensional framework, which could support the assessment of the existing sustainability of a manufacturing process and analyze opportunities for improvement. This study divided the performance into five drivers: Quality, Operational, Finance, Environment, Safety and People and selected 17 KPIs for assessing the multi-dimensional performance of SLM organizations. The research results revealed an organization's perspective transition from strategies focused on operational and economic performance to a more sustainable ideal with greater importance for social and environmental directions.

This framework will be facilitated by the selection of the most significant drivers and the development of strategic plans for the successful adoption of sustainable manufacturing. The practices support implementation, pursue competitive advantages and sustain manufacturing, meeting strategic requirements of suitable and lean performance. With the limited resources of the organizations, the framework proposed will guide the priorities and actions to be taken toward the SLM.

The purpose of this study is to carry out a comprehensive systematic review of lean implementation frameworks and roadmaps developed over the past decade and report the key findings along with the limitations and the way forward.

A systematic review methodology proposed by Tranfield (2003), was followed to identify the relevant works on the research topic. Articles were searched using a set of inclusion criteria in various databases including Google Scholar, Web of Science and Science Direct over a period of 30 years.

The high failure rate of lean system implementation, reaching a range between 70 and 90% in almost all industries, is a matter of concern. This failure rate is still high even though numerous frameworks and roadmap models exist to streamline lean implementation. There is no standard framework or roadmap identified in the literature and many organisations are implementing lean in their unique ways. However, it would be desirable to develop a practical and systematic roadmap on lean-looking into the cultural and leadership dimensions rather than focusing on a set of tools. Moreover, most frameworks and roadmaps lack the sustenance aspects of lean implementation.

This research only identifies the fundamental gaps with the existing frameworks and roadmaps on lean implementation. The next phase of the research is to develop a roadmap and validate it with a number of organisations in different cultural contexts and leadership styles.

The authors argue that this is one of the most comprehensive systematic review on lean frameworks and roadmaps, ever produced in the literature to date.

Previous research has managed to clearly define lean technical competencies. However, the behavioral competencies remain underestimated, and the roles of lean experts are not clearly stated: are they teachers, facilitators or technical experts? The present paper investigates lean behavioral competencies and their relationship to lean experts' roles.

This article serves as an exploratory study built on interviews, observations and focus groups conducted during a three-year longitudinal study accompanied by a three-year follow-up. The case takes place in an international automotive company in partnership with Toyota in which lean adoption was part of a consistent strategy over a period of 20 years.

The study clarifies lean behavioral competencies related to organizational efficiency (nominal management, improvement management and respect for people) and relational efficiency (problem resolution, competencies development and systemic interactions). The study helped create a typology of lean experts' roles related to the maturity level of the environment in which they intervened. Moreover, Lean experts' roles in congruence with the environment seem to positively influence the creation of emerging human relationships that are beneficial to process improvement and competencies development.

This paper is the first to clarify behavioral competencies with respect to lean experts' roles and to study the temporality of the introduction of lean practices. The findings recommend that researchers better acknowledge the influence of lean behavioral competencies during lean adoption and their relationship to contextual factors and organizational performance. A practical methodology is proposed to measure the necessary behavioral adjustments of lean experts or employees.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

The purpose of this paper is to explore the moderating role of Lean Six Sigma (LSS) practices in explaining the relationship between quality management practices (QMPs) and quality performance.

Partial least square-based structural equation modeling (PLS-SEM) was used to empirically examine the moderating effect of LSS practices on QMPs and quality performance in Malaysian medical device manufacturing companies.

Findings revealed that both QMPs and LSS practices have a significant and positive effect on quality performance. Furthermore, LSS practices served as a substitute for moderating the positive relationship between QMPs and quality performance in such a way that the relationship becomes weaker as LSS practices increase.

LSS is acknowledged as the most well-known hybrid methodology; however, due to its relative newness, it has not been studied in great detail. Unlike previous studies, this paper argued that Lean and Six Sigma practices are distinct from its predecessor TQM practices; moreover, both Lean and Six Sigma practices do not need to substitute QM/TQM practices instead of complimenting the QMPs. In addition, this study adds to the growing body of QM literature by empirically examine the effect of LSS practices in moderating the relationship between QMPs and quality performance.

Lean construction (LC) consists of very effective techniques; however, its implementation varies considerably from one industry to another. Although numerous lean initiatives do exist in the construction industry, the research topic related to LC implementation is still unexplored due to the scarcity of validated assessment frameworks. This study aims to provide the first attempt in developing a structural model for successful LC implementation.

This study developed a Lean construction model (LCM) by critically reviewing seven previous LC frameworks from different countries, defining 18 subprinciples grouped into 6 major principles and formulating testable hypotheses. The questionnaire was pre-tested with 12 construction management experts and revised by 4 specialized academics. A pilot study with 20 construction units enhanced content reliability. Data from 307 Moroccan construction companies were collected to develop a measurement model. SPSS V. 26 was used for Exploratory Factor Analysis, followed by confirmatory factor analysis using AMOS version 23. Finally, a structural equation model statistically assessed each construct's contribution to the success of LC implementation.

This work led to the development of an original LCM based on valid and reliable LC constructs, consisting of 18 measurement items grouped into 6 LC principles: Process Transparency, People involvement, Waste elimination, Planning and Continuous improvement, Client Focus and Material/information flow and pull. According to the structural model, LC implementation success is positively influenced by Planning and Scheduling/continuous improvement (β = 0.930), followed by Elimination of waste (β = 0.896). Process transparency ranks third (β = 0.858). The study demonstrates that all these factors are mutually complementary, highlighting a positive relationship between LC implementation success and the holistic application of all LC principles.

To the best of the authors’ knowledge, this study is the first attempt to develop a statistically proven model of LC based on structural equation modelling analysis, which is promising for stimulating construction practitioners and researchers for more empirical studies in different countries to obtain a more accurate reflection of LC implementation. Moreover, the paper proposes recommendations to help policymakers, academics and practitioners anticipate the key success drivers for more successful LC implementation.

This study aims to investigate the implementation of lean human resource management (HRM) practices in manufacturing small- and medium-sized enterprises (SMEs) and explore how various factors interact to influence their successful adoption. By exploring the interplay among these factors, the research seeks to identify key drivers affecting the adoption of lean HRM in manufacturing SMEs. Ultimately, the research intends to provide insights that can guide organisations, practitioners and policymakers in effectively implementing lean HRM practices to enhance operational efficiency, workforce engagement and competitiveness within the manufacturing SME sector.

The study combined total interpretive structural modelling (TISM) and Matrice d'Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis. TISM helped in understanding the hierarchical relationship among different factors influencing lean HRM implementation, whereas MICMAC analysis provided insights into the level of influence and dependence of each factor on others.

The research revealed that “top management support” emerged as the most independent factor, indicating that strong support from top management is crucial for initiating and sustaining lean HRM practices in manufacturing SMEs. On the other hand, “employee involvement and empowerment” was identified as the most dependent factor, suggesting that fostering a culture of employee engagement and empowerment greatly relies on the successful implementation of lean HRM practices.

While the study provided valuable insights, it has certain limitations. The research was conducted within the specific context of manufacturing SMEs, which might limit the generalizability of the findings to other industries. Expert opinions introduce subjectivity in data collection. Additionally, the study may not cover all critical factors, allowing room for further exploration in future research.

The findings have practical implications for manufacturing SMEs aiming to implement lean HRM practices. Recognising the pivotal role of top management support, organisations should invest in cultivating a strong leadership commitment to lean HRM initiatives. Furthermore, enhancing employee involvement and empowerment can lead to better adoption of lean HRM practices, resulting in improved operational efficiency and overall competitiveness.

This research contributes to the field by offering a comprehensive exploration of the interplay among factors influencing lean HRM implementation. The use of TISM and MICMAC analysis provides a unique perspective on the relationship dynamics between these factors, allowing for a nuanced understanding of their roles in the adoption of lean HRM practices in manufacturing SMEs. The identification of “top management support” as the most independent and “employee involvement and empowerment” as the most dependent factors adds original insights to the existing literature.