Facing the burden of chronic diseases has become a priority for health-care systems’ economic and social sustainability. To this end, this paper aims to focus on adopting Health Lean Management (HLM), a widely used managerial approach, to improve the performance and quality of care provided in chronic care pathways. HLM addresses not only efficiency and timeliness issues but also care effectiveness and integration. Indeed, the lack of continuity and co-ordination of care constitutes a major challenge for chronic pathways. This research provides an innovative contribution, by extending the implementation of HLM to chronic pathways developed across hospital and territorial care. Indeed, HLM scope typically regards hospital units and departments; hence, analysing the interaction between different levels of care represents a novelty from an academic and practical perspective.

With the aim of understanding how to extend the adoption of HLM towards the territory, an action research project has been developed. In particular, an improvement project focused on breast cancer care pathways has been launched in a Spanish hospital. The research investigates which HLM activities, tools and practices need to be accomplished in this kind of project, grasping insights into emerging wastes. To this end, the HLM project followed the Define, Measure, Analyse, Improve and Control (DMAIC) cycle, supporting the project team in effectively conducting a preliminary context analysis, qualitative and quantitative data collection, the current state analysis and the countermeasure proposals.

The analysis conducted on the breast cancer care pathway highlighted major criticalities in managing the diagnosis of new patients. In particular, waiting times to obtain diagnostic imaging and breast specialist consultations highly impacted the care pathway effectiveness and efficiency. Specific wastes that caused these delays have been investigated, leading to the definition of specific countermeasures that could minimise the inefficiencies: an 85% reduction of the staging process lead time was estimated.

The achieved results contribute to enhancing the quality of care delivered to breast cancer patients. This paper enriches the theoretical knowledge about HLM, extending its typical field of application; provides practical support to health-care providers, managers and leaders with a case demonstrating how to develop HLM projects adopting the DMAIC cycle; and finally, it has valuable social implications, addressing the global threat of chronic disease.

The purpose of this study is to examine mediating effect of employee’s ability, motivation and opportunity to participate (AMO) between the investment in lean six sigma training and service recovery performance of an IT service support organization. Moreover, this research examines which among the AMO model components significantly and positively influence service recovery performance. This study also intends to analyze the moderating role of manager support and peer support, leading to improved service recovery performance in the organization.

The research design explored the relationship among the variables as illustrated by the operational framework of the study. This study used a quantitative approach to analyzing data through descriptive and inferential statistics. The descriptive part focused on demographic information such as age, gender, education, role in the company and tenure. A graphical summary is used to describe and summarize the demographic data and highlight the measures of central tendency, such as the calculation of mean, median and mode, and the measures of dispersion, such as standard deviation and variation. A correlational design enables the research to determine the relationship among the variables, identify the effect through variability, and the coefficient of determination in identifying patterns in providing empirical evidence for the research objectives.

The findings of the study revealed that investment in lean six sigma training would significantly and positively influence service recovery performance. The result confirmed the previous empirical research on the correlation between lean six sigma initiatives and the economic benefits achieved by the business, with high-cost recovery rates (Swink and Jacobs (2012) and Shafer and Moeller (2012). It supported the research conducted by Al-Ababneh et al. (2021) and Samer et al. (2017) on the impact of the quality program on service recovery performance improvement. The organization may consider investing in human capital and considers the employees as human assets. Investing in human capital is one of the significant investments an organization can make and the organization can also see a bottom-line benefit from strategically designed training activities according to Mello (2019).

This paper fulfills an identified need to study how AMO model affects the relationship between investment in lean six sigma training and service recovery performance.

This study aims to bridge the gap between traditional continuous improvement methodologies and emerging digital technologies by systematically analyzing how hybrid innovation models – integrating Lean Manufacturing, Six Sigma and Industry 4.0 tools – drive productivity gains across industries.

A systematic literature review of 96 empirical studies was conducted, synthesizing evidence from diverse sectors (e.g. manufacturing, construction, services), geographical regions and temporal contexts. The analysis focused on operationalizing incremental innovation through the lens of Lean, Six Sigma and Industry 4.0 integration.

Lean principles (e.g. Kaizen, 5S) and Six Sigma methodologies (e.g. DMAIC, defect reduction) remain critical for process optimization, particularly in resource-constrained settings. Industry 4.0 tools (e.g. IoT, automation) amplify these gains through real-time data analytics and workflow automation. Sectoral analysis reveals significant productivity improvements in manufacturing (15%–25% waste reduction) and construction (20% efficiency gains), while health care and finance exhibit implementation gaps because of rapid technological evolution.

Practitioners can adopt a phased integration strategy, prioritize Lean/Six Sigma for foundational process stability and layer Industry 4.0 tools for advanced analytics and automation; sector-specific roadmaps are provided to address challenges like workforce readiness and legacy system compatibility.

This study contributes to the literature by synthesizing 96 empirical studies to offer a comprehensive view of how traditional continuous improvement methods (Lean, Six Sigma) are increasingly integrated with digital tools (Industry 4.0) to drive incremental innovation. Unlike prior research that treats these mechanisms separately, this review maps out hybrid models, highlights sectoral and geographical variations and provides a temporal analysis of incremental innovation’s evolution.

This study aims to integrate Industry 4.0 (I-4.0) technologies with Lean principles, proposing a framework called “Lean 4.0” to improve production efficiency and quality.

This study was conducted in several steps. First, the objectives of this study were defined. Second, a systematic literature review was conducted to identify research gaps in integrating I-4.0 into lean production (LP). Third, the “Lean 4.0” framework was designed based on general systems theory (GST). Fourth, a pilot study was carried out in a controlled environment to validate the proposed framework empirically. Finally, an overall summary of this study was produced, highlighting the limitations and contributions of the proposed “Lean 4.0” framework.

An improved integration framework, “Lean 4.0,” was designed and proposed to the scientific community. In addition, the demonstration of the proposed framework in a controlled lab environment shows that merging Lean and I-4.0 can significantly improve the production floor’s overall equipment effectiveness, emphasizing the potential for digital transformation of the LP system.

This study was conducted in a controlled educational laboratory, which may not reflect the complexities of real-world manufacturing environments. Thus, additional research is needed to validate the “Lean 4.0” framework across different industries to assess its effectiveness and adaptability.

The proposed framework was validated through a pilot study, which provided the first empirical evidence for the scientific community. In addition, the framework is grounded in GST, ensuring a structured and holistic approach. Its content was also validated through expert opinions, making this framework a pioneering effort in its field.

The aim of this study is to explore the concept of operational excellence (OPEX) in the context of African businesses. It seeks to identify the main themes, topics and trends within the OPEX discourse and to uncover emerging areas and potential directions for future research. By emphasizing the unique challenges and opportunities in African markets, this study aims to broaden the understanding of OPEX and its applicability in diverse business environments.

This study adopts a mixed-methods approach, combining qualitative and quantitative analyses. Using topic modeling and text analytics, the study examines a range of scholarly literature and social media content. The methodology involves a meticulous extraction and analysis of data from peer-reviewed journals, alongside an exploration of themes emerging from social media, blogs and forums. This approach allows for a comprehensive understanding of OPEX trends in both academic and practical contexts.

The study reveals that OPEX in African businesses is intricately linked with innovation, strategic leadership, cultural dynamics, global market integration and data analytics. Key findings include the importance of integrating cultural understanding into operational strategies, the role of adaptive leadership in navigating the African market and the necessity of aligning operational processes with global trends, innovations and data-driven insights. The research also highlights the unique challenges African firms face, such as balancing local and global business practices, leveraging cultural diversity for competitive advantage and harnessing the power of data analytics for OPEX.

This research contributes original insights into the understanding of OPEX in African business contexts, an area that has been relatively under-explored in existing literature. It offers a novel perspective by integrating academic and practical viewpoints, thereby providing a more holistic understanding of OPEX. The findings have significant implications for both business leaders and researchers, offering strategic directions for firms operating in or with African markets and suggesting new avenues for academic inquiry in the field of OPEX.

Lean implementations have a low success rate due to various reasons, like misunderstanding Lean and cultural differences in implementing Lean outside of Japan. Researchers suggested created cultural adaptation of Lean for improve buy-in of employees and high success rates during Lean implementations. Thus, this study aims to delve into the similarities between Lean leadership and Ubuntu leadership to propose a South African Lean–Ubuntu leadership framework.

A systematic literature review was used to collect data on Ubuntu leadership. Thereafter, the Lean leadership style was compared to the Ubuntu leadership style to find similarities and differences.

Thereafter, the correlations and variations between Lean and Ubuntu leadership principles were amalgamated in the design of a South African Lean–Ubuntu leadership framework.

This study focused on the development of a literature-based framework; however, it is recommended that future studies validate the model by practical implementation in South African organisations. Additionally, this framework is limited to a South African cultural adaptation of Lean leadership; it is suggested that future studies explore other cultural adaptations in other countries.

Both Ubuntu and Lean philosophies teach the importance of people and team members; by using this framework organisations have a better opportunity to engage with employees and help them better understand Lean during the implementation stages, thereby increasing the chances of employee buy-in and bridging the gap to a brighter South Africa.

To the best of the authors’ knowledge, this is the first study to propose a South African Lean–Ubuntu leadership framework.

This paper aims to investigate how implementing lean six sigma and Industry 4.0 (LSSI4.0) can influence a company’s financial performance and discusses the current trend involving LSSI4.0 in China.

For statistical analysis, financial data was sourced from the China Stock Market and Accounting Research database. Keywords used to assess the implementation status of LSSI4.0 were extracted from the 2007 to 2020 annual reports of A-share manufacturing companies. Regression analysis was applied to the quantitative analyses of 5,041 observational data points from 945A-share manufacturing companies in China.

LSSI4.0 implementation in the manufacturing industry boosts the firms’ financial performance. However, the former outperforms the latter in terms of long-term advantages. Meanwhile, incorporating lean six sigma (LSS) into Industry 4.0 (I4.0) can lead to long-term improved financial performance compared to solely implementing the I4.0.

The findings possess limited international representativeness because all empirical data were derived from Chinese large manufacturing companies. In addition to return on assets and return on equity, financial performance can also be measured using other financial metrics, such as return on investment. In this study, only listed manufacturing companies were considered as research samples.

Top management must acknowledge the positive impact of LSSI4.0 on financial performance and prioritize implementing I4.0 based on LSS implementation.

Empirical results concerning the effectiveness of LSS implementation in enhancing financial performance are inconclusive, particularly in China. In addition, most studies collected data through surveys and interviews, so the representativeness of their outcomes is limited. Overall, this study evaluated the impact of LSSI4.0 implementation with large sample size.

Achieving operational excellence in supply chain management (SCM) is essential for enhancing customer satisfaction, improving efficiency, and sustaining industrial competitiveness. This paper aims to develop an integrated Lean Six Sigma (LSS) framework to optimize SCM by minimizing waste, enhancing process reliability and improving responsiveness. The framework’s effectiveness is validated through a case study in a spare parts manufacturing company in Egypt, demonstrating its practical application and impact.

The study identifies critical success factors (CSFs) for effective LSS implementation in SCM. A structured DMAIC (Define-Measure-Analyze-Improve-Control) approach is applied, offering a data-driven methodology for optimizing supply chain performance and ensuring sustainable improvements.

The proposed framework significantly enhances SCM efficiency, operational effectiveness and customer satisfaction. Key performance improvements include product quality (85%–89%), sigma level (2.5–2.7) and processing time reduction (645–370 h/ton), Overall Equipment Effectiveness (OEE) increases (75% to 81%), value-added activity enhancement (50% to 54%), and customer satisfaction growth (87% to 89%). These improvements, achieved through LSS methodologies, drive defect reduction, workflow optimization, enhanced equipment utilization and a culture of continuous improvement, ensuring long-term operational excellence.

This study’s scope was limited to a single product in a specific industrial context. Future research should explore the broader applicability of the LSS-SCM framework across various sectors, including services, to assess its versatility and generalizability. Expanding the research scope will provide valuable insights into the framework’s adaptability and potential impact across different industries.

This research provides a structured and replicable methodology for managers and engineers to enhance SCM performance, streamline production processes, and strengthen operational resilience. It offers practical, data-driven strategies for integrating LSS into SCM, enabling organizations to optimize processes, reduce waste and achieve long-term competitive advantage.

This study presents a comprehensive, empirically validated LSS framework for SCM optimization. By demonstrating the structured application of LSS tools, provides a novel, systematic approach to enhancing efficiency, effectiveness and resilience in modern supply chains, fostering sustainable continuous improvement and industrial competitiveness.

The purpose of this paper is to provide a guiding framework for the implementation of a plant-wide lean pull system (LPS) and to demonstrate its applicability and practical relevance in an automotive supplier company in Tunisia.

Action research is used to develop the framework in a collaborative context. The effectiveness of the framework in addressing the original research problem and achieving the desired outcomes is evaluated. Relevant lessons are drawn for future implementations, and opportunities for adapting the framework to other contexts are explored.

The paper highlights the usefulness of the framework not only in guiding the LPS implementation process but also in organising managers’ thinking and deepening their understanding so that success in terms of performance outcomes can be achieved. The paper improves understanding of the integrated approach to LPS, promotes the key idea that pull is not a black and white concept but rather a matter of degree and highlights the critical role of developing stability to successfully manage the transition from one level of pull to the next. This role also extends to sustaining, improving and extending the LPS at the plant level, which are too important implementation steps to be ignored in the literature.

Previous studies have often taken a narrow approach to LPS implementation, reducing it to the pull phase and limiting its scope to a single segment of the value stream. However, the proposed framework unfolds further phases, pre- and post-pull and synergistic interactions between phases and underlying lean tools to support a holistic and integrated approach to LPS implementation at the plant level.

This research aims to enhance digital marketing processes by using design of experiments in safelist mailers and traffic exchange websites.

The research applies design of experiments to improve an online digital marketing website.

The findings show that design of experiments can help improve digital marketing quality by generating more interactions with safelist mailers and traffic exchange websites, reducing time spent in the marketing process, allocating the appropriate amount of credits to significant websites and avoiding product price increases.

This research aims to increase awareness of the impact and applicability of design of experiments to digital marketing and demonstrates the application of design of experiments in any digital marketing process, including safelist mailers and traffic exchange websites.

To the best of the authors’ knowledge, this is the first study applying design of experiments within online marketing. This study can be leveraged by academics and marketing functions to demonstrate the benefits of design of experiments to the marketing function to improve process efficiency and resource utilisation.

This study aims to explore how instructors and trainees perceive value generation within companies through Lean learning conducted in an industrial context. It specifically examines the influence of this learning on decision-making, issue resolution, opportunities for continuous improvement, waste reduction and alignment with corporate goals.

This research adopts a survey method, using two online questionnaires targeted at Lean instructors and trainees from companies in Northern Portugal. It included sample selection and questionnaire development based on literature and objectives. The data analysis techniques encompass descriptive statistics and coding for open-ended responses.

Instructors and trainees emphasize the effectiveness of experiential learning techniques, such as games and simulations, in facilitating the understanding and application of Lean principles. This transformative approach enhances corporate efficiency, decision-making and problem-solving capabilities. However, the study reveals that despite the widespread adoption of Lean learning in the analyzed companies, a structured framework to measure its added value is lacking. The findings underscore the need for metrics that capture Lean’s true impact: individuals who challenge the status quo and actively drive transformative solutions, positioning Lean as both a technical methodology and a human-centered driver of growth.

The primary limitations of this study are the small sample size and its geographical focus on Northern Portugal. While the sample size is relatively limited, the selected companies’ extensive experience with Lean practices ensures that the data collected remains valuable and insightful. In addition, the regional scope may limit the generalizability of the findings to other contexts or regions. Future research should aim to address these limitations by expanding both the sample size and geographical coverage, which would provide a broader understanding of Lean learning’s impact and improve the applicability of the results to different industrial settings.

This study distinguishes itself through its human-centered approach to Lean learning, shifting the focus from traditional tools and techniques to the experiences of individuals. Addressing a critical gap in Portuguese research – where operational outcomes often take precedence over human factors like motivation and development – underscores Lean’s broader potential to cultivate systems thinking, sustainability and ethics.

This paper aims to conduct an inclusive bibliometric review of the International Journal of Lean Six Sigma (IJLSS) to elucidate the scholarly landscape, growth trends, impact, mappings, couplings, networking and thematic evolution within the field of Lean Six Sigma (LSS) research.

Using advanced bibliometric techniques, including network analysis and clustering, this study examines the publication output of IJLSS since its inception in 2010. The analysis focuses on identifying key contributors, mapping collaborative networks, tracing thematic evolution and exploring emerging research trends. The study is executed as per the proposed easy-to-understand methodology, containing well-structured nine segments hitting various critical-bibliometrics of IJLSS along with their respective implications.

The review reveals substantial growth in the publication output of IJLSS, with India emerging as a prominent contributor. Keywords such as “Lean”, “Six Sigma”, “Quality Management”, “Operational Excellence”, “Supply Chain Management”, “Industry 4.0” and “Sustainability” emerge as central themes, reflecting the journal’s focus on process improvement methodologies along with corresponding case studies. Collaborative networks among authors and countries are robust, indicating the global reach of LSS scholarship. Emerging research trends highlight areas of potential future exploration within the field.

Limitations of this study include the reliance on bibliometric data and the exclusion of nonindexed sources. However, the findings offer valuable insights into the scholarly landscape of IJLSS, providing researchers and practitioners with a comprehensive overview of LSS research inclinations and developments.

This paper contributes to the literature by providing a detailed analysis of LSS research published in IJLSS through a unique approach and future directions. The study adds to existing knowledge by mapping collaborative networks, tracing thematic couplings and identifying emerging research clusters within the ever evolving domain of LSS.

The 5Whys methodology is a problem-solving technique used across diverse fields to unearth the root causes of issues. Despite its widespread use, challenges persist with adequately using the tool and effectively eliminating the root cause. The purpose of this study is to assess the effectiveness of using the 5Whys technique and employees’ proficiency in problem-solving.

The research methodology uses a 91 completed 5Why case studies data set. It involves systematically retrieving 5Whys worksheets and pertinent documents, extracting data and relevant details and meticulously organizing this information within MS Excel. Subsequently, the data undergoes cleaning and transformation to achieve a structured format suitable for analysis. Finally, the data is analyzed and discussed and recommendations are provided.

Despite 96.7% of cases having a clear problem statement, only 57.1% quantified problem impact. Problems varied in complexity, with 53.8% classified as moderate difficulty and 25.3% having multiple root causes. However, 48.4% lacked a proper cause-and-effect sequence and 22.0% failed to identify root causes. Only 39.6% of cases eliminated root causes, with 34.1% featuring a clear problem statement, identifying root causes, implementing corrective and preventive actions and verifying their effectiveness. Employee skills were a concern, with 63.2% categorized as “Novice” and 63% completed only one 5Why problem-solving. Resolutions averaged 5.6 days, indicating the need for streamlined processes and highlighting areas for improvement in organizational capabilities.

The study’s reliance on 91 production cases limits its generalizability to other environments like offices or warehouses. Practically, the findings highlight the need for improved training in the 5Whys technique, standardized root cause validation and integrating preventive actions with corrective measures. Expanding the 5Whys beyond production and complementing it with tools like fishbone diagrams can further enhance problem-solving capabilities.

This study examines the effectiveness of the 5Whys methodology and employee problem-solving skills, using a data set of 91 cases to provide new insights for enhancing problem-solving processes.

This study aims to address the challenges faced by healthcare manufacturing SMEs in high-mix, high-volume environments, particularly in light of the COVID-19 pandemic.The authors propose the implementation of the Production Wheel framework as a solution to optimize operational efficiency and cost-effectiveness. Using real-world anonymized data from a high-mix, high-volume manufacturing project, the authors evaluate the feasibility and impact of this framework. The findings indicate significant reductions in changeover and inventory costs, with notable improvements in production efficiency. The study highlights the potential of the Production Wheel in healthcare manufacturing while providing insights based on authentic industry data.

The Production Wheel framework is introduced as an 8-step method that encompasses analyzing historical volumes, identifying key product families, developing current and future state value stream maps, assessing capacity utilization and implementing Kanban-based pull systems with supermarkets between processes. This approach is grounded in Lean manufacturing principles and is tailored to the specific needs of the healthcare manufacturing industry.

The adoption of the Production Wheel framework enables healthcare manufacturers to align their production more closely with actual demand, minimizing waste and reducing overheads. This agile approach facilitates the adaptation to a high mix of products without compromising efficiency, ensuring a resilient and responsive supply chain that can effectively meet the evolving needs of the market.

While this conceptual paper introduces the Production Wheel framework in the context of healthcare manufacturing, future research should focus on the practical implementation and empirical validation of the proposed approach. Case studies and quantitative analyses of the framework’s impact on operational efficiency, inventory management and cost-effectiveness would provide valuable insights for academics and practitioners.

The Production Wheel framework offers a practical approach for healthcare manufacturers to navigate the challenges posed by the COVID-19 pandemic and the increasing demand for customized products. By integrating this methodology alongside flexible manufacturing systems, manufacturers can enhance their ability to adapt to market disruptions while maintaining optimal operational performance.

This paper contributes to the Lean Manufacturing literature by introducing the Production Wheel concept as a novel framework for healthcare manufacturing. The proposed approach addresses the unique challenges faced by the healthcare manufacturing sector in the wake of the COVID-19 pandemic and provides a strategic roadmap for optimizing operational efficiency and cost-effectiveness.

This study aims to analyse the application of lean thinking in warehousing operations’ picking and packing processes.

The research design used is a conceptual framework based on the literature for lean practitioners’ guidance.

The results of the empirical study reveal an increase in efficiency of 30% in picking and packing operations when analysing and decreasing the non-value-added processes in this case study

The proposed framework has not been implemented in a wide range of operations. The findings are limited due to the focused feature of the case study. Additional cost–benefit analysis can be investigated.

This study can guide warehousing logistics practitioners towards achieving excellence in manual picking and packing operations through lean thinking implementation.

This study overcomes the lack of a structured framework for lean manual order picking and packing and evaluates the potential of a set of lean and process analysis tools to increase the efficiency of order picking and packing.

This study aims to assess the effect of the implementation of the Six Sigma approach to improve the quality of post-operative pain management in patients attending Alexandria University Student Hospital.

A pre-post interventional study involving patients over the age of 16 years old who were proposed and planned for any surgical operation at Alexandria University Student Hospital. We used Six Sigma’s define, measure, analyze, improve and control (DMAIC) improvement process. Data were gathered from samples evaluated six months before the Six Sigma project’s implementation and seven months after the project’s implementation. The areas selected for improvement were using postoperative pain assessment and reducing postoperative pain management POPM defects.

There was a significant decrease in the overall mean (SD) of the worst pain score between the pre-intervention 7.5 (±2.4) and post-intervention 2.7 (±1.9) phases (p < 0.001). A significant decrease (p < 0.001) in the DPMO between pre-and post-intervention phases (580773.4, 78678.2 respectively). That decrease was followed by an improvement in the sigma level of the POPM process (from 1.375 to 3 sigma level).

This research underscores the efficacy of ongoing quality improvement initiatives, particularly through the Six Sigma DMAIC methodology, in enhancing surgical care by optimizing postoperative pain management. Implementing Six Sigma can significantly increase patient satisfaction by reducing discomfort and improve recovery outcomes by minimizing complications like blood clots, infections and chronic pain. Additionally, it promotes optimal resource utilization and cost efficiency in health-care systems by streamlining pain management procedures. Overall, the study confirms that Six Sigma effectively improves postoperative outcomes and reduces process defects in pain management. However, the research contains a few pitfalls which may be the exclusion of cancer patients, children under 16 years old and intensive care patients. These excluded groups might have different pain management needs and responses and different pain assessment tools, so the results may not apply to these populations. Besides, the research considered mainly general surgery and orthopedic operations for improvement. As they were the most prevalent types of surgeries in the research setting.

Health-care organizations can improve postoperative pain treatment by implementing the Six Sigma strategy, which incorporates technical integration, patient-centric measurements, customized programs and ongoing improvement. To the best of our knowledge, this is the first study in Egypt and worldwide to investigate the implementation of the Six Sigma strategy in post-operative pain management.

This study aims to explore the challenges and opportunities of adopting Industry 4.0 technologies in Africa, specifically focusing on the automotive industries in Morocco and Nigeria. By comparing these two leading African countries in Industry 4.0 adoption, the research seeks to identify key factors influencing the implementation of smart manufacturing technologies and to provide insights into the potential benefits and challenges faced.

The research uses a multiple case study design with a quantitative approach, collecting data through structured questionnaires from 167 participants across five automotive companies in Morocco and Nigeria. Regression analysis assessed the impact of opportunities and challenges. Statistical analysis identified significant differences between the two countries.

The study reveals significant differences in the perceived challenges and benefits of Industry 4.0 adoption between Morocco and Nigeria. In Morocco, key challenges include high implementation costs and resistance to change, whereas, in Nigeria, lack of skilled workforce and high implementation costs are predominant barriers. Both countries recognize the benefits of improved productivity, better product quality and enhanced supply chain agility.

While focused on two countries and the automotive industry, the study provides valuable insights into Industry 4.0 adoption in Africa, with potential for expanded future research.

The insights provided by this study can guide policymakers in developing tailored strategies to support Industry 4.0 adoption in Africa. For organizations, understanding the specific challenges and benefits can aid in designing effective Industry 4.0 implementation plans, enhancing competitiveness and achieving sustainable growth.

By providing a comparative analysis of Morocco and Nigeria, the study offers unique insights into the specific factors influencing Industry 4.0 implementation in different African contexts with differences between North and West of Africa.

Current studies show that the Lean Six Sigma (LSS) methodology is used all over the world, by different types of companies in different countries. However, this is not yet the case for certain developing countries such as Morocco, where this methodology is still being discovered and applied and where also the relationship between the adoption of this methodology and sustainable performance is not yet clear. Thus, the aim of this study is to investigate the impact of LSS tools, used by industrial companies in Morocco, on the three dimensions of performance: economic, social and environmental.

This study used partial least squares-based structural equation modeling (PLS-SEM) to conduct an empirical examination of the impact of LSS tools used by Moroccan manufacturing industries on their sustainable performance. Data were collected using a semistructured questionnaire, with a total of 121 valid responses collected for this study.

The results showed that the adoption of LSS tools has a positive effect on the sustainable performance of these industries. The analysis of the collected data also revealed that this effect is most significant when it comes to social performance, followed by environmental and finally economic performance. It was also found that Lean Management tools have a greater impact than Six Sigma tools.

The results of this study may encourage Moroccan industries that are new to LSS to adopt it, as it proves to have positive results not only on the economic aspects of the firm but also on the improvement of employee well-being and the protection of our planet’s environment. In addition, this study gives them an idea of the tools that are most widely used in their Moroccan context, thus facilitating the choice of tools with which they can begin to embed a continuous improvement mindset.

Although several studies have already analyzed the relationship between the LSS approach and sustainable performance, these studies have generally focused on developed countries that are well advanced in the use of these tools. Hence, the originality of this study is its relevance to the Moroccan context, which still needs more studies in the fields of continuous improvement and sustainability.

Operationnal excellence has emerged as a critical factor for organisations competitiveness. Companies in developing countries are striving to elevate their operational performance to new heights. This study aims to explore the effective best practices, drivers and challenges to operational excellence in North African business.

To address the objectives of this study, a qualitative approach is adopted. A total of 13 experienced professionals holding leads initiatives within North African enterprises are surveyed. Following, content analysis method is employed to extract, categorise and analyse the knowledge from the interviews.

The findings indicate that the implemented best practices include process optimisation, performance measurement, standardisation, customer-centric approach, lean manufacturing and total quality management. For a successful adoption, the results shed light on the importance of leadership commitment, upskilling, digitalisation and employee’s empowerment. However, the implementation faces several challenges incorporating unsustainable engagement, resistance to change, disconnected practices, insufficient investment, deficient improvement assessment and limited access to digitalisation.

This study contributes to exploring the best practices, enablers and barriers to successful implementation of operational excellence in emerging economies. Its findings can be used by scholars and decision-makers to advance knowledge around operational excellence, broaden the existing strategies to tailor specific contexts and promote operational performance.

By incorporating I4.0 technologies, the agri-food supply chain (AFSC) can become leaner, faster, more robust and greener. However, many challenges must be overcome to fully realise I4.0 in this context. Therefore, this paper aims to identify the challenges that hinder the adoption of I4.0 technologies on the development of the Lean, Agile, Resilient and Green (LARG) AFSC.

The approach adopted was to identify challenges addressed in the literature with expert opinion and Total Interpretive Structural Modelling (TISM) for adaptation. In addition, a Weighted Influence Non-linear Gauge Systems (WINGS) methodology has been developed that uses expert opinion to generate a power and influence matrix.

The results show that lack of commitment and understanding of top management (X12), lack of long term vision (X17) and lack of incentives and government support (15) are the most important challenges.

This study does not explore the effectiveness of the concluded challenges of I4.0 and their strategy to overcome them. Also, the authors relied on a limited sample size for this study, which might not cover the detailed challenges within LARG AFSC. Finally, this study lacks in future advancement of I4.0, which may further affect the challenges.

By mentioning the key challenges, this study empowers LARG AFSC organisations to build a targeted strategy for smoother I4.0 implementation.

Industry 4.0 challenges remain unexplored in LARG AFSC. This improved awareness equips managers to navigate better the potential issues and complexity that may arise when adopting I4.0 in the LARG AFSC.

This study aims to investigate the alignment between Industry 4.0 and Lean Six Sigma (LSS) in the context of sustainable development, focusing on the reasons for the growing attention to this integration and its implications for sustainability.

This research is designed based on literature overview using a review of bibliometric analysis and structural topic modeling of existing literature to provide evidence on the relationship among Industry 4.0 technologies, LSS practices and sustainable organizational performance.

It is evident from the study that incorporating Industry 4.0 technology with LSS can lead to a great sustainable manufacturing. With the use of digital tools such as Internet of Things sensors, advanced analytics and artificial intelligence, organizations significantly improve real-time monitoring, improve resource allocation and apply predictive maintenance, thus minimizing waste and the environmental effect. This approach also propels innovation and agility and fosters a culture of continuous improvement while evolving around higher-level topics around quality control and strategic management. Findings reveal that these integrations ensure operational excellence and sustainable development.

The study provides guidelines for researchers and practitioners working on integration of Industry 4.0 technologies and LSS for enhancing the environmental and resource performance in manufacturing.

The novelty of the research is the integration of the knowledge existing on Industry 4.0 and LSS and its contribution in sustainable development perspectives. Moreover, this study may also be useful for other researchers because it provides a general overview of the trends and theoretical contribution that are practically confirmed in the empirical level.

This study aims to explore the implementation of operational excellence (OpEx) within the Moroccan automotive industry, focusing on its perception, adoption and integration into organizational structures.

This research uses a qualitative, exploratory design, using semi-structured interviews with eight key experts from various ecosystems within the Moroccan automotive industry. A purposive expert sampling method was used to select participants with significant experience in OpEx, ensuring a deep, context-specific understanding of its implementation.

This study reveals that Moroccan automotive firms adopt OpEx practices in a phased, structured manner, beginning with foundational methodologies such as Lean manufacturing, 5S and Kaizen, before progressing to advanced tools like Six Sigma. The integration of these practices is typically supported by dedicated teams within engineering and production departments, with some firms establishing specialized OpEx departments reporting directly to plant directors. While notable progress has been made in the adoption of OpEx, significant challenges remain, particularly regarding the technical expertise required for advanced methodologies like Six Sigma. Nevertheless, strong support from international parent companies and Morocco’s highly integrated automotive ecosystem has been identified as key enablers in accelerating the adoption of OpEx best practices.

The generalizability of this study is constrained by its focus on a specific industry and region. While the qualitative findings provide valuable insights into the Moroccan automotive sector, further research is needed to broaden the scope across different industries and geographical contexts. Future studies could explore the application of OpEx practices in other developing economies or investigate the role of Industry 4.0 technologies in enhancing OpEx outcomes.

This study contributes to the limited body of research on OpEx implementation in developing economies, offering empirical insights from the Moroccan automotive industry. The findings provide practical insights for industry practitioners and theoretical contributions toward understanding how OpEx practices can be adapted and scaled within the unique context of emerging economies.

Maintenance activities directly impact equipment availability, operational costs and product quality. Moreover, the application of lean tools in this context has demonstrated significant potential for enhancing process efficiency. Therefore, this paper aims to explore the degree of integration of lean tools in the optimization of maintenance processes within Brazilian companies.

Initially, 11 critical factors (CF) for the effective integration of lean tools in maintenance management were identified in the literature. Based on these CFs, the authors carried out a survey with 64 experts to evaluate how effective is the application of lean tools in the Brazilian industrial context. Furthermore, the data collected from the experts was analyzed using a multicriteria decision analysis approach, the Fuzzy TOPSIS Class and a scenario-based sensitivity analysis. This methodology categorized each CF into one of three levels of application: excellent, moderate or unacceptable.

The survey was applied to professionals from different sectors, including general manufacturing, services, logistics, agroindustry and others. The study shows that 4 of the 11 CFs were classified as “excellent,” reflecting the high application intensity of traditional maintenance practices in Brazilian industries. On the other hand, most lean-related CFs were rated “unacceptable,” including Kansei Engineering, Heijunka, Andon and Jidoka. Sensitivity analysis confirmed these findings’ robustness, as classifications remained consistent despite varying respondent experiences.

The key contribution of this study lies in identifying specific lean tools that are underused, providing a clear direction for future research and industry improvement. This research integrates expert opinion and fuzzy methods to extract key information about the integration of lean tools in maintenance process optimization in Brazilian industries.

The purpose of this study is to introduce a framework aimed at helping manufacturing companies in developing countries start their digital transformation journey, focusing on small and medium manufacturers.

This study proposes a CAP-Do cycle framework to facilitate digital transformation at the shop floor level. This study emphasises effective data collection using affordable Internet of Things tools and sensor statuses to differentiate between machine and human losses in semi-automated production lines. This paper also compares unit- and time-based overall equipment effectiveness indicators for measurement and offers a step-by-step analysis guide.

Sensor data’s active and inactive statuses help identify whether losses stem from machine or human issues, crucial for semi-automated production lines in developing countries. Accurate loss data guide improvements in machinery and operator activities. Additionally, time-based calculations of performance and quality rates provide a detailed loss breakdown, unlike unit-based methods that overlook process time variations.

The framework’s implementation is tested on a prototype testbed, suggesting its real-world application may require adjustments to address the diverse factors of loss encountered in actual production environments.

This study outlines methods for data collection and detailed analysis using external sensors to classify machine and human issues. This study advocates for applying time-based overall equipment effectiveness calculations within the CAP-Do cycle for continuous improvement.

This study aims to develop a smart quality control framework integrating Six Sigma methodology, real-time sensing technologies and machine learning algorithms to enhance manufacturing defect prediction and process optimization. By leveraging predictive capabilities and real-time data analysis, the framework seeks to reduce costs associated with poor quality and improve overall process capability.

The proposed framework uses the Define-Measure-Analyze-Improve-Control methodology to identify and address critical process parameters. A robust Internet of Things (IoT) sensing network is incorporated for continuous process monitoring. At the same time, multiple machines learning models, including decision trees, random forests, boosted decision trees, linear regression and k-star algorithms, are evaluated for predictive defect detection. Implementation was conducted at an electrical conductor manufacturing facility, enabling real-time analysis and intervention to prevent defects.

The implementation of the framework demonstrated significant improvements in quality and efficiency. The cost of poor quality was reduced from 5% to 1.7%, a 66% improvement. Process capability was enhanced, with sigma levels increasing from 3.14 to 4.3. These results validate the effectiveness of combining traditional quality control techniques with advanced Artificial Intelligence and IoT technologies, delivering predictive capabilities and enabling real-time process optimization.

This study highlights the innovative integration of Six Sigma, machine learning and IoT sensing technologies to transform manufacturing quality control. The smart quality control framework represents a significant advancement in manufacturing intelligence, offering a scalable, data-driven solution that improves efficiency, competitiveness and sustainability across diverse industrial applications.

The efficiency-enhancing and performance-boosting benefits of lean six sigma (LSS) practices have been advocated in both academia and industry. However, their mediating and moderating effects remain unclear and the impact of LSS practices is underdeveloped in the Chinese context. Therefore, by focusing on publicly listed companies in China, this study aims to investigate whether, how and when LSS practices link to organizations’ innovation and financial performance.

Data from 66 Chinese publically listed companies spanning a period of 25 years (2000–2024) was analyzed using the difference-in-difference method which compared the changes in outcomes over time between a treatment group and a control group.

This research found that LSS practices are positively related to firm-level outcomes including innovation and financial performance. The authors also confirm the mediating effect of operational capability on these relationships. Moreover, the empirical evidence suggests that implementing the quality management systems (QMS) standard, ISO 9001, moderates the relationships between LSS practices and innovation and financial performance such that these relationships are stronger for firms in organizations with higher maturity levels in implementing the standard.

This study sheds light on LSS theory and offers valuable recommendations for lean managers on how to leverage LSS practices to improve their innovation and performance capabilities.

This research provides novel insights into the influence of LSS practices on firm-level outcomes such as the level of innovation and financial performance. To the best of the authors’ knowledge, this study is the first to theoretically propose and empirically validate how and when LSS practices influence firm outcomes by introducing the mediating mechanism of operational capability and the boundary condition of QMS standards.

This study aims to review and synthesize existing research in the field. Additionally, this study identifies emerging themes and future research opportunities based on the discussions within these studies. This research also develops a model to integrate artificial intelligence with agile human resource (AHR) practices and strives to outline potential directions for future researchers.

This study adopted a systematic literature review (SLR) and bibliometric analysis followed by content analysis through bibliographic coupling to analyze the identified literature. The SCOPUS database was used in this study, using a search string of keywords to identify the relevant research literature. The initial extraction resulted in 151 articles after adopting a series of inclusion–exclusion criteria, which led to the final attainment of 73 articles to be included for further analysis and discussion.

This study through the extant literature identified five themes and foundations of artificial intelligence in AHR practices research and developed a model for future investigation by future researchers.

To the best of the authors’ knowledge, this study is one of a kind that explores artificial intelligence within AHR practices for improved employee and organizational well-being. Thus, developing a synthesized work provides a comprehensive picture of the research domain.

This study aims to develop a people-centred model for lean implementation in the South African context that simultaneously focuses on continuous improvement and Respect for People (RFP).

The elaborated action design research (eADR) method was used within the design science research (DSR) paradigm. The research continuum was entered at the problem-diagnosing stage, after which four iterative concept design stages were completed: a systematic literature review revealed the meaning of Respect for People; an applied thematic analysis summarised the RFP principles in the South African context; the design requirements were developed; the Respect for People model was developed and evaluated using the Delphi technique.

The RFP model consists of two value streams – the traditional product value stream and the people value stream. A specific problem-solving process connects these two value streams to bring problems to the surface and help develop individuals who can solve these problems. It was concluded that an effective and sustainable lean implementation could occur only by valuing employees’ knowledge, experience and insight and developing their skills. An improved people value stream would naturally lead to an improved product value stream.

To the best of the authors’ knowledge, this is the first study that incorporates the true meaning of RFP into a practical lean implementation framework for the South African context. The RFP model contributes towards organisational success by providing a practical means to include people during the lean implementation process, thereby contributing to improved lean implementation.

The purpose of this study is to examine how a focal firm’s supply relationships influence lean supply chain management (LSCM) implementation and its impact on operational performance.

An empirical study of 285 Spanish focal firms has explored the relationships between supply uncertainty, strategic supplier performance, LSCM implementation and operational performance. A structural equation model was used to test four hypotheses.

The results indicate that supply uncertainty and strategic supplier performance significantly impact the decision to implement LSCM. The findings highlight the importance of strategic supplier performance for driving LSCM adoption. However, this study also suggests that LSCM implementation should be carefully considered in situations characterized by high supply uncertainty.

This study suggests that enhancing LSCM implementation and improving performance from key suppliers are crucial factors in achieving favorable operational performance in focal firms. Practitioners receive guidance on aligning their supply relationships, considering contextual factors and leveraging strategic supplier performance to drive effective LSCM implementation.

This study offers novel insights by examining the antecedents to LSCM implementation from a contingency and relational perspective specifically focused on the context of supply relationships. This research contributes to the existing body of knowledge on supply chain management by shedding light on the interplay between supply uncertainty, strategic supplier performance, LSCM implementation and operational performance.

The purpose of this study is to explore the contextualized use of Lean and Six Sigma (LSS) practices in the state governments in the USA. This study analyzes LSS’s capacity to innovate public service administration to improve efficiency, effectiveness and equity in government.

This study used the Grounded Theory Method to analyze 2,048 LSS project reports from 32 state governments between 2003 and 2024, aiming to identify systematic patterns in the adjustment and application of LSS within state service administration and its outcomes.

The 32 states applied LSS across 24 service areas, adapting it in five ways: strategic programming, production efficiency, customer focus, internal accountability and equity and service expansion. LSS projects primarily reported financial and managerial improvements, with some citing equity and service expansion as project success.

The use of self-reported results likely underrepresented LSS failures, making empirical validation essential for confirming inductively generated propositions in future research.

The findings of this study imply that managerial motivations and project goals affect how LSS’s methods and principles can be adjusted to address competing values in the public sector. This study offers insights into effectively applying LSS to optimize public service administration and achieve better outcomes for citizens.

The findings expand the literature on LSS for public service mission, offering implications for its strategic application in the public sector. The large-scale multiple case study enhances the credibility of these findings beyond what single case studies or literature reviews can provide.

Lean Six Sigma (LSS) improves the efficiency of organizations by systematically reducing variability, optimizing processes and eliminating waste to promote quality, productivity and customer satisfaction. The purpose of this paper is to investigate the impacts of LSS on promoting continuous improvement practices and enhancing organizational efficiency.

The method of this study involves a comprehensive systematic literature review and bibliometric analysis, which encompasses the time period between 2001 and April 2024 and collecting 1,992 articles from the Scopus database. The study uses several advanced tools such as RStudio for data processing, Biblioshiny for interactive analysis of bibliography and VOSviewer for illustrating scientific landscapes and research clusters detection.

The findings of the study point out that efficiency, quality improvement and cost minimization are significantly affected through the application of LSS tools and techniques, which is consequently leads to promoting organizational excellence through continuous improvement across a variety of industrial sectors. Furthermore, the study focuses on the recent trends in the LSS’s application including the integration of digital tools with LSS to grow the significance on sustainability. These trends are following to find out directions for further research by fostering continuous development in the business processes.

The study is distinct in terms of its originality as systematic literature review and bibliometric analysis are coordinately demonstrated to provide a robust understanding about the impacts of LSS implementation in promoting organizational efficiency. The findings of the study generate new opportunities for the LSS sphere in the coming years. Using of modern technologies including Biblioshiny, VOSviewer and RStudio to analyze nearly two decades’ scientific literature. Thus, valuable insights offered by this research into the practical implications of LSS tools from the economic and social context to boost organizational performance through continuous improvement.

This paper aims to propose and test a comprehensive multidimensional lean implementation model and investigates how external lean practices influence internal practices during a manufacturing firm’s lean transformation.

A survey was conducted on 197 managers at multiple manufacturing firms in the Midwestern region of the USA. Data were analyzed using partial least squares-based structural equation modeling.

The findings attest to diffusion and adoption intensity of internal lean practices to be significantly higher for the process and equipment operational impact area among Midwest manufacturers; significant positive influence of external lean practices in customer relationships on internal lean practices related to four operational impact areas: process and equipment, production control, new product development and human resource management; significant positive impact of external lean practices in supplier management on internal ones related to three (except work force management) operational impact areas.

In contrast to unidimensional lean implementation models in literature, the proposed multidimensional lean model recognizes the multifaceted nature of internal and external lean practices and classifies them into six higher order impact areas. To the best of the authors’ knowledge, this is the first study to examine the influence of external lean practices on internal ones based on their operational impact areas individually and not as a single construct.

This study aims to explore an empirical investigation for developing a digital control system for identifying steel sheet thickness deviation to improve productivity and coating quality on a galvanizing process line in the context of Lean Six Sigma 4.0.

This paper used a Lean Six Sigma 4.0 empirical application approach to promote a digital control system in zinc thickness measurement. The approach covered equipment specification, network configuration, control and monitoring software, security routine, thickness calculation, deviation routine and supervisory system. Performance tests show that this approach has produced good results, making it a viable application.

The main contribution of this study is to demonstrate that Lean Six Sigma 4.0 concepts can promote the measurement of steel sheet thickness deviations with accuracy, sensitivity and reliability, as demanded by the global market. The results of this study showed errors of 0.1% of the actual thickness, making it technically feasible to implement this system for steel sheet thickness readings ranging from 0.01 mm to 4 mm.

This research demonstrates an interdimensional linkage between Lean Six Sigma 4.0 concepts to explore an empirical investigation for implementing a digital control system using data acquisition modules and control software to guarantee the coating quality applied to steel products under the standard organization.

The purpose of this paper is to present a case study in the plywood industry, aiming to demonstrate the successful integration of green lean six sigma (GLSS) and theory of inventive problem solving (TRIZ).

As a result of the integration of lean manufacturing, green production and six sigma, GLSS was developed. An innovative solution method such as TRIZ is needed to complement the performance of GLSS. A perfect combination of TRIZ and GLSS is looking forward to providing significant contributions in producing less waste, as a substantial factor to commit in green manufacturing for sustainability.

The industrial waste recycling rate was measured before and after the implementation of GLSS-TRIZ, that is 92%−93% and more than 95%, respectively. This proves that the GLSS-TRIZ has been evidently recognized as a powerful framework to achieve a green and sustainable manufacturing.

Sustainability has been a hot topic in the global manufacturing space for several years now. This focus on environmentally conscious practices is becoming increasingly prominent across various industries. With environmental concerns on the rise, green manufacturing is becoming increasingly important as manufacturers strive for more efficient and sustainable manufacturing processes. The past few decades have seen the emergence of innovative methodologies such as lean, green, six sigma, but addressing the entire sustainable development problem alone is not feasible. An organized and systematic method of problem-solving with analysis and forecasting techniques is performed to complement and realize a powerful methodology.

This study aims to investigate the challenges to the implementation of value stream mapping (VSM) to enhance sustainable construction practices and determines its underlying factorial structure.

This study used a quantitative research approach, using a questionnaire survey to gather data. The collected data was analysed using statistical methods, including mean item score, relative importance index (RII), Gini’s mean and exploratory factor analysis.

This study revealed that language barrier is the topmost ranked challenge to the implementation of VSM in achieving sustainable construction projects. However, resistant to change with an RII of 0.700, when compared with the geometric mean of 0.6966 calculated from the stationary analysis was identified as the most consistent challenge. The research also identified two clusters of challenges: implementation and integration challenges and capacity building and process management challenges.

The research was conducted in Nigeria, specifically in the Federal Capital Territory. Thus, the results may not reflect regional disparities in construction methodologies, obstacles and the implementation rates of VSM in other areas of the country.

The finding of this study underscores the importance of fostering a culture that values innovation and continuous improvement within the construction sector.

This study adopted a robust analytical technique by introducing stationary analysis through the use of Gini’s mean to determine the most consistent challenge of VSM. Furthermore, this research is pioneering as it constitutes the inaugural effort within the Nigerian construction sector to methodically tackle these challenges, providing novel perspectives on the obstacles hindering VSM implementation.

The construction industry has benefited from adopting Industry 4.0 (I4.0) technologies and Lean construction (LC) practices. To better understand the effects of adopting I4.0 technologies on sustainable performance in construction projects, a model is developed to pursue this relationship and deliberate the mediating role of LC ambidexterity, which is based on paradox thinking and organizational ambidexterity theory.

This study adopts a survey design, collects data on construction projects in China and tests the hypothesized model through the partial least squares structural equation modeling method. A purposive and snowball sampling strategy was applied for recruiting research participants. Between January and February 2023, 102 construction professionals from Chinese construction companies using I4.0 technologies participated in the survey. Measures of LC ambidextrous capabilities, I4.0 technologies and sustainable performance are rated on a five-point Likert scale.

The results confirm that the use of I4.0 technologies has a positive effect on LC ambidexterity capability and sustainable performance. The LC exploitative capability has positive effects on sustainable performance. Even if the impact of exploration capability on sustainable performance is not well reflected in the current study, it is still worthwhile for organizations to develop LC ambidexterity of exploration and exploitation in the context of projects, as exploration’s impact on performance will probably only be realized over longer terms.

This study contributes to the body of knowledge of I4.0, LC and project sustainable performance in the construction industry and provides managerial implications on how to achieve sustainable performance from an ambidexterity perspective.

Emergency departments (EDs) are essential to hospital operations, involving complex processes and interactions with several hospital departments. As the entry point for many patients, EDs often face challenges such as overcrowding, staffing shortages and disruptions to patient flow, all of which negatively impact patient satisfaction. This paper aims to use discrete-event simulation and lean healthcare to analyse patient flows, exploring multiple scenarios to improve both patient experience and operations management.

Researchers combined Lean principles with discrete-event simulation to model the entire patient flow through the ED and its interactions with other hospital departments. Various scenarios were simulated to explore potential improvements in resource allocation, inpatient admissions and reductions in non-urgent cases.

This study demonstrates that reducing wait times for inpatient admissions significantly decreases all ED patients’ average length of stay (ALOS). Furthermore, reducing the number of non-urgent patient admissions has a substantial impact on ED metrics, as these patients represent over 40% of admissions and consume significant resources. Overall, combining all improvements led to a reduction in ALOS by more than 30%.

This paper uses simulation to characterise ED operations and assess the influence of other hospital departments on patient flow. This approach provides a quantitative understanding of the role these departments play in ED overcrowding. In addition, this study compares different patient workflow characteristics and their effects, highlighting the importance of workflow decisions in shaping patient experiences.

Among the Critical Success Factors considered by companies, the pursuit of high standards of productivity and quality stands out. However, achieving the best performance often implies difficulties in selecting the most appropriate methodology to solve a specific problem. In this sense, choosing a method to boost competitiveness is essential. Two widely recognized methodologies, Lean and Six Sigma, still emerge as frequent options. The purpose of this study is to provide an updated analysis of the integrated use of these techniques in the automotive sector due to organizational dysfunction effects, through a survey and two case studies.

A questionnaire was sent to 80 automotive companies located in the state of Sao Paulo, Brazil, obtaining a response rate of 20%. In the first case study, a questionnaire was used as a data collection method. Meanwhile, the second case was approached regarding problem-solving through Lean or Six Sigma.

The results of this research revealed proposals in which, in some cases, Six Sigma was considered the most appropriate, in others Lean, and both were suggested. Nowadays, the results highlight Lean Six Sigma can expand the continuous improvement in automotive industry.

The main contribution of this work in filling the gap caused by the dysfunctions was to update the Lean Six Sigma integration with DMAIC-VSM, reorganization and leadership. In the case study, the employees in contact with the shop floor began to understand the need to obtain greater knowledge of the statistical concepts. This study could also help developing countries that are seeking sustainability.

The purpose of this study is to explore the association between total quality management (TQM) and green manufacturing practices (GMP).

The study used a rigorous methodology to investigate the association between TQM and GMP in small and medium-sized enterprises (SMEs) located in Bengaluru, India. A questionnaire method was used in this research. Data were collected from 448 participants working in SMEs in Bengaluru. Exploratory factor analysis, confirmatory factor analysis and Cronbach’s alpha values are used to validate the instrument, and the structural equation modelling (SEM) is used to check the relationship between TQM and green manufacturing.

SEM confirmed a significant and positive association among TQM and GMP. The identified factors within TQM, including customer focus (CF), human resource management, information and analysis, leadership styles, process management and strategic planning (SP), highlighted the multifaceted nature of TQM practices influencing green manufacturing. Factors identified within GMP included green management, green process and green production. These factors represent key dimensions in the adoption of environmentally accountable manufacturing practices.

The findings suggest that assimilating environmental sustainability into quality management frameworks, particularly in areas such as leadership, SP and CF, can catalyze the adoption of GMP initiatives in SMEs.

This study’s originality lies in its association of TQM and GMP in SMEs located in Bengaluru, India. The comprehensive validation process, identification of specific TQM and GMP factors and practical implications contribute to the unique insights presented, making it a distinctive contribution to the field.

The purpose of this study is to analyze the relationship between lean manufacturing and corporate environmental performance. Scholarly literature has extensively addressed the relationship between those two areas but empirical papers present mixed and inconsistent results, calling for further analysis to establish a clearer understanding of the actual relationship and to identify the causes of conflicting findings across studies. Given the importance of sustainable practices in the current business landscape, this paper aims to provide a comprehensive overview of this relationship through a meta-analysis of previous research, with a focus on integrating quantitative findings to shed light on the potential impact of lean manufacturing on environmental performance and report its intensity with Pearson’s correlation coefficient.

This paper analyzes the data from 29 primary studies published between 2001 and 2022 that have empirically measured the relationship between lean manufacturing and corporate environmental performance and that have been identified in the Web of Science and SCOPUS databases through an exhaustive review of the literature. To integrate previous empirical results and evaluate the evidence for the lean manufacturing’s influence on environmental performance, a meta-analytic methodology was adopted through the Hedges–Olkin random effect approach, based on correlations.

Main findings support the notion that a significant, positive, rather moderated, relationship exists between lean manufacturing and environmental performance, with an overall correlation coefficient $\overline{r}$ = 0.25. The result seems robust, as several tests confirm that publication bias is unlikely. Overall, various lean practices are correlated to varying degrees with different measures of environmental performance. The environmental efficiency of external lean practices is higher than that observed for internal practices and quality management has a more pronounced effect than other internal lean practices. The 2008 global crisis did not change these relationships and the impact of lean manufacturing on environmental performance does not seem to be moderated by the degree of environmental awareness of the country where applied.

The results conclude that a significant, positive relationship exists between lean manufacturing and environmental performance ($\overline{r}$ = 0.25). This study tests certain factors that exhibit varying effect sizes and moderate the overall outcome, highlighting that the environmental efficiency of external lean practices is higher than that observed for internal practices. In addition, it suggests a more pronounced effect of quality management among other internal lean practices.

This study provides companies with an opportunity to align their operational strategies with environmental sustainability goals. Understanding that various lean practices exhibit diverse levels of correlation with multiple measures of environmental performance, decision-makers can prioritize their efforts and apply the lean practices that have a stronger effect on the desired environmental outcomes to improve their environmental impact. Conversely, managers are aware that certain lean practices have a week relationship with some environmental performance so they can avoid overestimating environmental benefits of lean manufacturing. Finally, results underscore the importance of organizational commitment to environmental sustainability.

It is, to the best of the authors’ knowledge, the first meta-analytic study to investigate the strength of the association between lean manufacturing and environmental performance and to test whether various lean practices are correlated to different measures of environmental performance. It fills this gap in the literature and therefore it represents a valuable contribution to the field. In addition, this paper explores certain factors that moderate the overall outcome.

The purpose of this paper is to shed light on the studies regarding the influential elements that contribute to the sustainability of continuous improvement (CI) programs. It aims to define the notion of sustainability and to identify and explore the influential elements that could encompass such a definition.

A comprehensive literature review was conducted to categorise various interpretations of sustainability into distinct dimensions. This approach also identified 16 influential elements that have the potential to sustain CI programs. A self-assessment survey involving 80 French companies was used to evaluate these elements through the Plan, Do, Check, Act framework. In addition, a maturity-benchmark model is introduced to help evaluate the degree of maturity of the most influential elements of CI programs.

The results highlight the inherent paradox in sustaining CI programs, where robustness and adaptability must coexist. The study identifies a relationship between influential elements and organisational maturity levels, offering actionable insights to help companies advance through these stages. Human-centered elements, such as leadership and employee engagement, have the greatest impact on CI sustainability, emphasizing the importance of fostering a people-centric culture. Conversely, operational elements are less influential, suggesting a need for balanced strategies.

This paper discusses a topic that is rarely addressed, namely, how to sustain CI programs within a CI framework. This paper provides a novel synthesis of influential elements and their relationships to organisational maturity within a CI framework, challenging traditional static views of sustainability. By emphasizing the dynamic and evolving nature of CI programs, it bridges theory and practice, offering organisations a practical model for continuous reassessment and adaptation.

This study aims to optimise cheese production processes in a dairy company, focusing on reducing milk consumption, increasing production capacity and minimising process variability.

The define, measure, analyse, improve and control methodology of Six Sigma was carried out in a dairy company. The study analyses variables and operational factors with tools like analysis of variance, fishbone diagrams and brainstorming to optimise cheese production, reduce milk consumption and minimise process variability in a dairy company.

Casein content, humidity and fat content were identified as the primary factors influencing cheese weight variability. Redefining milk treatment according to the optimal casein fat content and optimising cheese placement in drying chambers had the most significant effects among the adjustments made. Operational improvements were implemented, including machine angle calibration and conformer size reduction. These improvements resulted in a 6.8% reduction in milk consumption, a 3.3% increase in production capacity and a 32.4% decrease in process variability.

This study serves as a compelling demonstration of the potential success of Lean Six Sigma (LSS) in the dairy industry, particularly in optimising resource utilisation for maximum yield in mass cheese production. The outcomes of this study have led to reduced costs and increased cheese yield for the company under investigation, offering a valuable reference for improving cheese production efficiency and enhancing overall product quality. Moreover, the findings of this study can be replicated and applied in other segments of the dairy sector, showcasing the broader applicability and benefits of LSS methodologies.

To the best of the authors’ knowledge, this study represents one of the few instances of applying LSS to a mass-production dairy producer in Portugal. While existing studies on LSS methodologies in the dairy industry have primarily concentrated on optimising cheese yield through variable manipulation, this study extends the application of LSS principles to broader operational enhancements within the mass production context. This study demonstrated the effectiveness of LSS methodologies in achieving operational efficiency and waste reduction in cheese production through operational improvements, quality control and standardised work.

This study examines the impact of lean production on operational performance and assesses the role of organizational culture as a critical contextual variable in this impact. The purpose of the study is to investigate how the dimensions of organizational culture (clan culture, adhocracy culture, hierarchy culture and market culture) regulate this effect by evaluating the impact of lean production on operational performance. It is emphasized that organizational culture is a determining factor in the relationship between lean production and operational performance and that this effect may differ depending on the cultural structure of the organization.

In this study, manufacturing organizations in Turkiye that are engaged in lean production were selected as the population. A total of 112 lean production companies from the manufacturing sector participated. The survey technique was used for data collection. The moderator effect analysis was conducted using structural equation modelling with the Analysis of Moment Structures 24 statistical package.

The results of the study show that organizational culture is an important factor for organizations to adopt and sustain lean production processes. In particular, organizations with hierarchical and market cultures can improve their operational performance by integrating lean practices according to their cultural structure. Hierarchical cultures promote disciplined and consistent lean implementation, while market cultures foster a competitive, results-driven environment that maximizes lean efficiency. These findings highlight the importance of adapting lean strategies to fit the organizational culture for performance improvements.

This study is limited by its cross-sectional design, which restricts causal inferences. In addition, the findings are based on survey data from Turkish manufacturing firms, which may limit generalizability. Future research could explore these relationships using longitudinal data and expand to different industry contexts.

The findings suggest that aligning lean production with a strong organizational culture, particularly hierarchical and market-oriented cultures, enhances operational efficiency. Managers should focus on cultural adaptation strategies to improve lean implementations and sustain performance improvements.

This study contributes to the limited literature on the moderating role of organizational culture in the relationship between lean production and operational performance. By examining different types of culture (clan, adhocracy, hierarchy and market) within the context of lean production practices, it offers an in-depth perspective on how cultural adaptation shapes the effectiveness of lean practices. The findings highlight the importance of aligning lean strategies with organizational culture, providing valuable insights into long-term performance improvement, and opening several avenues for future research.

This study aims to use Lean principles, including the traditional seven types of waste and four additional service-specific waste types, to identify and eliminate wasteful activities.

The study integrates existing literature to identify different types of waste and conducts a case study within the Malaysian Customs Administration. The application process flow for License Manufacturing Warehouse is examined, and waste is identified and eliminated using the principles of waste elimination in Lean.

The study identifies eight prevalent types of waste in service processes, with motion being the most common and duplication the least. The case study in the Malaysian Customs Administration reveals no instances of waste in communication and error categories, indicating commendable efficiency in these areas. These insights offer valuable benchmarks for organizations seeking to optimize processes and address specific types of waste.

This paper is crucial for showcasing the practical implementation of waste elimination theory in Lean across the service sector, focusing on the Malaysian Customs Administration. It offers targeted insights into tailoring these principles for real-world efficiency gains, contributing valuable strategies for waste reduction in a specific organizational context.