This study addresses the ongoing challenge of concurrently integrating Lean and Industry 4.0, a critical need for companies striving to enhance operational capabilities in increasingly digital environments. While past research focused on sequential approaches or high-level conceptualizations, this research delves into the level of 'how', applying Dynamic Capabilities theory through a deductive, four-stage mixed-method design, focused on large German manufacturing firms. First, expert interviews underwent thematic analysis to identify strategies and courses of action for integration. Next, an exploratory survey refined these results statistically. Third, the findings were validated and triangulated via a Delphi study, from which a structured integration framework emerged. Finally, confirmatory composite analysis of 236 managerial responses confirmed the reliability and validity of the framework. The study presents 44 validated actions grouped into six dimensions: Initiating, Sensing, Seizing, Transforming, Resources and Capabilities. Notably, it introduces the new 'Initiating' dimension, expanding the Dynamic Capabilities theory. While the study's focus on large German manufacturers is a limitation, the resulting framework offers practical pathways for companies unable to pursue sequential integration due to time pressures. Ultimately, this research provides both theoretical advancement and practical tools for successfully managing the simultaneous transformation towards Lean and Industry 4.0.

This paper aims to study the effect of Zero Defect Manufacturing (ZDM) on Sustainability by analyzing the state-of-the-art and identifying patterns and gaps within the available literature. Sustainability encompasses three pillars (Triple Bottom Line): social (people), environmental (planet), and economic (profit) pillars. The original ideas of a number of quality gurus such as Deming, who states that quality improves productivity through the reduction of costs caused by non-value added activities, Feigenbaum, who planted the roots for the concept of Total Quality Management (TQM) as we know today, and Ishikawa, who defends company-wide quality, that is, the need for involvement of all employees and the utilization of people’s intelligence, served as leverage for this study. The Sand Cone model proposed by Ferdows and De Meyer in 1990 presents a hierarchy of four concepts in the form of a pyramid that starts with “quality” at its base, succeeded by “dependability,” “speed,” and finally, “cost efficiency.” This productivity theory underlines, as well, the importance of quality management and aims to convey how companies should primarily focus on quality to further improve costs. In this sense, a Rapid Literature Review on papers concerning ZDM, quality management, and Sustainability was conducted, followed by a thematic analysis of the selected documents. The results from the assessment show how ZDM is addressed in several types of studies, such as literature reviews on its technical approach, models, and frameworks in different industries. Nonetheless, the literature is still lacking papers focused on the effects of ZDM on Sustainability, therefore, this study aims to bridge this gap.

This viewpoint article develops an architected framework of learning in lean enterprises by integrating Fujimoto's evolutionary learning capabilities perspective, Imai's Kaizen model, and Argyris and Schön's organizational learning framework. Through theoretical synthesis, the paper reconceptualizes lean as a dynamic system of learning systems that supports stabilization, incremental improvement and strategic renewal. The resulting framework positions lean transformation as a recursive process that fosters generative change, cultural adaptation, and long-term competitiveness. This integrative perspective provides practitioners with a diagnostic and developmental tool for overcoming stagnation in lean initiatives and designing more robust learning architectures, advancing a holistic, capability-based view of sustained lean growth.

Industry 4.0 is reshaping manufacturing, with Zero Defect Manufacturing (ZDM) emerging as a cornerstone for competitiveness and sustainability. This paper introduces a readiness assessment framework that evaluates four critical dimensions — infrastructure, processes, personnel, and company culture — bridging technological capability with quality management. A structured questionnaire operationalizes these dimensions and was applied to five European firms in the automotive and semiconductor sectors. Results show that while technological infrastructure is relatively advanced, predictive analytics and workforce data literacy remain underdeveloped, limiting the realization of ZDM’s full potential. The findings highlight the importance of integrating human-centered factors such as training, culture, and risk awareness with advanced digital tools. By providing both a diagnostic baseline and actionable insights, the framework supports companies in benchmarking their progress and guiding strategic investments. Beyond individual firms, it also offers researchers and policymakers a foundation for advancing ZDM adoption as part of a sustainable, defect-free manufacturing ecosystem.

The manufacturing industry is undergoing a profound transformation driven by the twin transition, described as an intertwined shift towards digitalization and sustainability. As such, this study explores the socio-technical competencies necessary for organizations to successfully navigate this transition. Adopting a mixed-method design science research approach, we first use a rapid literature review and thematic analysis to construct a competence development framework for the twin transition encompassing five key dimensions: digitalization, sustainability, social, leadership and product & process technical skills. These insights then inform a multiple case study involving the collection of semi-structured interview data across two manufacturing companies, assessing managerial perceptions of their current competence levels. Findings indicate that while managers generally demonstrate strong social-, leadership- and product & process technical skills, significant gaps remain in digitalization and sustainability competencies. Notably, sustainability knowledge is inconsistently understood across hierarchical levels, and digitalization competencies vary widely among managers. These results underscore the need for structured competence development initiatives to equip organizations for the twin transition. The study contributes both theoretically and practically by offering a systematic framework for competence mapping, enabling firms to identify skill gaps and implement targeted workforce development strategies. Strengthening these competencies will be essential for companies striving to remain competitive and sustainable in the evolving industrial landscape.

Purpose – A positive organisational culture has a decisive influence on the success and resilience of an institution. Still, many cultural initiatives have little lasting impact since they are not implemented holistically. Such a holistic cultural change can be supported by the framework of Operational Excellence methods. The aim of our study is therefore to develop a practical and flexible roadmap for cultural change that uses Operational Excellence methods to achieve sustainable cultural change. Design/methodology/approach – The study used an action research approach and was conducted over a period of 18 months in a manufacturing company. The data was obtained by carrying out several successive Action Research cycles and a quantitative performance measurement. Findings –First, key areas of action were identified throughout the organisation. Clear organisational values were then defined, providing a target image and development direction. Tangible artefacts and continuous monitoring of operational implementation were derived for each organisational value. Finally, continuous improvement routines and team development workshops triggered by the monitoring processes were identified as key components at team level. Practical implications –We show that Lean methods can be successfully used to implement cultural change in organisations. The flexibility of our model allows the focus of the cultural change not to be limited to the core ideas of Lean, but to be oriented towards the respective needs of the organisation. Our model sussccessfully involves all levels of organisational members, allowing the development of a sense of self-efficacy and options for action and facilitates communication on cultural issues. Originality/value – Our roadmap provides an effective framework for cultural growth in interdisciplinary teams and complex organisations and therefore holds great potential for both industrial companies and higher education institutions. In particular, organisations that already apply Operational Excellence methods can use our roadmap to initiate a cultural change in an effective and resource-saving way.

Lean practices are shown to enable the optimization of production processes. However, the true meaning of Lean extends beyond the mere application of practices, emphasizing people’s involvement and respect and acting as a robust learning approach rooted in Gemba. It enhances creativity and autonomy in problem-solving. Nevertheless, the importance of the human-centred aspect of Lean in the era of Industry 5.0 often remains theoretical as many managers and practitioners focus solely on Lean practices to achieve immediate results, neglecting the role of operators’ learning. This paper presents a methodology that integrates continuous learning into production optimization through use of a Plan-Do-Check-Act improvement cycle, placing employee learning at its core. The case company ElecTech specializes in the manufacturing of electric pylons, involving multiple fabrication and assembly operations. The paper examines various production setup-time configurations and Single-Minute Exchange of Die applications at ElecTech, where operators’ roles and interventions differ across scenarios. The results underscore the critical role of employee engagement in enhancing Lean outcomes, demonstrating the significant impact of operators’ learning on reducing lead times during production changeovers in which workers were involved. This paper reinforces the concept that Lean is not just about optimization; it is more fundamentally about continuous improvement – through the continuous development of people.

Kongsberg Defence Aerospace – a Norwegian multinational company that develops and delivers innovative technologies to safeguard people and critical infrastructure – is experiencing a fast-growing order backlog and a growing need for production managers to ensure efficient, high-quality and competitive production processes in its factories around the world. Recognizing this need, and through the establishment of a professorship in production management at the University of South-Eastern Norway, the company is seeking to establish a world class education program in production and operations management to develop and strengthen education in the field. As such, this paper sets out to benchmark production and operations management programs across the member institutions of the IFIP working group 5.7: Advances in Production Management Systems. We analyze both bachelor and master programs in the fields of engineering and management from 16 institutions spanning twelve different countries: Norway, the Netherlands, Mexico, Italy, Brazil, France, Denmark, Sweden, Switzerland, Australia, the UK and the USA. We also present the findings of an industrial focus group initiative in which participants considered the results of the global benchmarking study and identified areas for development based on gaps in the current offerings. The findings can be used by member institutions to help navigate current and future geopolitical challenges.

Purpose The study is intended to explore the key deployment factors of lean startup (LS) methodology in terms of tools, pros, cons, critical success factors (CSFs), challenges and benefits of LS methodology, providing a global perspective on LS application. Additionally, the study aims to compare LS applications across startups and large corporations for company creation or development projects and in companies in developed and developing economies. Design/methodology/approach An exploratory survey was conducted using an online questionnaire with 117 practitioners globally. Data analysis employed descriptive statistics, the Friedman test, Kendall’s coefficient of concordance and the Mann–Whitney U test to rank and compare LS adoption factors. Findings The study presented an empirical and global assessment of key LS factors through the perception of LS experts. The results demonstrated that startups use LS tools more frequently than large companies. However, they have more difficulties structuring the use of LS. Few differences were observed between the application of LS in companies in developing and developed countries, with the predominant difficulty in obtaining competencies and skills related to LS in developing countries. There is more intensive use of LS tools by companies that used the methodology for their creation. Practical implications The study emphasises consumer involvement, training and top management support for LS implementation, giving entrepreneurs and managers actionable insights. It also suggests governments investigate how to promote LS use in varied organisations. Originality/value A complete empirical investigation of LS deployment determinants fills significant gaps in LS literature. It addresses organizational kinds and economic circumstances from a global viewpoint, improving theoretical knowledge and practical execution of the LS approach.

This paper provides an insight into the global state of Lean Industry 4.0 (LI4) with over 1,000 industry responses. The approach employs a rigorous qualitative open-response survey. Our findings indicate that there was no unified industry perspective of LI4 terminology. The evolution of I4 is taking a similar path to Lean and making the same mistakes by not focusing on leadership, engagement, competencies, and behaviours. Past academic research has perhaps over-emphasised the environment and supply chain. The benefits of LI4 application are largely in terms of efficiency, cost reduction, learning and engagement. This work contributes by highlighting research avenues: why a piecemeal approach has been taken by industry to LI4, why LI4 has not been more widespread, and more detailed studies around contingent factors). It also provides industry with lessons on how to implement LI4 and the mistakes to avoid such as seeing implementation as a purely technical exercise.

Operationalisation of supply chain learning (SCL) is a major challenge. Technologies such as artificial intelligence (AI) are expected to favour supply chain information sharing, collaboration, and coordination, hence, supporting SCL. This paper examines how organisations' perceptions about AI adoption influence SCL, exploring the relationship between AI's perceived usefulness and ease of use with the SCL dimensions. We performed an online survey-based investigation with 206 Brazilian practitioners from different organisations of several industry sectors, whose responses were examined using multivariate data techniques. Similar trends in results were observed regardless of whether the relationship was between the focal company and its suppliers or between the focal company and its customers. When the perception about AI's usefulness and ease of use are both low, captive SCL tends to occur; when both are high, SCL might occur in a distributed way. A consortium SCL prevails if only AI's perceived ease of use is high; a selective SCL occurs if only the perceived usefulness is high. Identifying how SCL is impacted by organisations' perceptions about AI adoption may help managers to prioritise their digitalisation efforts, adjusting them according to the expected type of knowledge to be created and shared across the supply chain.

This study investigates the transformation of a large industrial plant into a service operations workshop through the Plan-Do-Check-Act (PDCA) cycle, emphasizing continuous improvement and strategic adaptability. This transformation was initiated due to financial challenges and the need to capitalize on existing service portfolios. It marks a strategic change from manufacturing to service-oriented operations, with limited guidance for managers overseeing this change. Employing an action-based research methodology guided by the PDCA framework, the study addresses the complexities of organizational learning, culture, and mindset shifts essential for transitioning to a service workshop. It describes the journey of strategic adaptation, from planning and executing service-centric initiatives to evaluating and refining processes based on feedback and market demands. The case highlights the importance of stakeholder engagement, developing a service-oriented workforce, and aligning operational strategies with long-term business goals. By validating the PDCA cycle as a flexible tool for change management, the study contributes to the literature on servitization strategies and managerial roadmaps, offering insights into achieving sustainable growth and innovation in service operations. The findings advocate for the PDCA cycle's utility in fostering a culture of continuous adaptation, which is crucial for supporting the ongoing adaptations needed to support servitization.

This study aimed to understand the impact of digital culture on companies’ knowledge and constant commitment to digital transformation, as well as its impact on organizations as a whole. Secondly, it aimed to explore the impact of digital technology adoption on organizational performance and competitiveness. Finally, the study investigated the role of knowledge management during digital transformation. A quantitative study was developed using a descriptive design. A questionnaire was developed on pre-test was carried out withon 15 participants and since no doubts or difficulties were detected, it was made available on the internet between January and April 2022. A total of 291 questionnaires were collected and validated. Data were imported from Google Forms for analysis in SPSS, version 25.0, andSmartPLS® 4.0 software. The questionnaire revealed good internal consistency (α = 0.922). Ten of the twelve hypotheses were confirmed, that is, the existence of positive and significant relationships between digital culture (DC) and knowledge of digital transformation (KDT); DC and adoption of digital technologies (ADT); DC and knowledge management (KM); commitment (C) and KDT; C and productivity (P); KDT and ADT; ADT and KM; ADT and P; ADT and C; and P and C. The results of regression analyses showed that the variables that contributed to the model (“competitiveness of organizations”) were productivity, the adoption of digital technologies, commitment to digital technologies, and knowledge management. The variables CD and KDT (Knowledge of digital transformation) presented lower and non-significant values.

Purpose This paper aims to investigate how manufacturers can foster insights and improvements from real-time data among shop-floor workers by developing organisational “learning-to-learn” capabilities based on both the lean- and action learning principle of learning through problem-solving. Second, the purpose is to extrapolate findings on how action learning can enable the complementarity between lean and industry 4.0. Design/methodology/approach An insider action research approach is adopted to investigate how manufacturers can enable their shop-floor workers to foster insights and improvements from real-time data at VELUX. Findings The findings report that enabling shop-floor workers to use real-time data consist of developing three consecutive organisational building blocks of learning-to-learn, learning-to-learn using real-time data and learning-to-learn generating real-time data − and helping others to learn (to learn). Originality/value First, the study contributes to theory and practice by demonstrating that a learning-to-learn capability is a core construct for manufacturers seeking to enable shop-floor workers to use real-time data-capturing systems to drive improvement. Second, the study outlines how lean and industry 4.0 complementarity can be enabled by action learning. Moreover, the study allows us to deduce six necessary conditions for enabling shop-floor workers to foster insights and improvements from real-time data.

Though the term lean is by no means something new, its definition and research boundaries remain somewhat unclear (Hopp and Spearman, 2021).Lean production was first described by Krafcik (1988) as a means of achieving world-class quality and productivity in manufacturing and was later popularized in Womack et al. (1990) as a superior business system consisting of five integral parts: dealing with the customer, designing the product, running the factory, coordinating the supply chain, and managing the lean enterprise.Since then, lean has been described as the most popular and most misunderstood approach to business improvement of our generation (Netland and Powell, 2017).

Driven by the digital transformation currently pursued by organisations, artificial intelligence (AI) applications have become more frequent. Nevertheless, its impact on employees' behaviors and attitudes is still poorly known. As employees' engagement (EE) is a key element for a successful Lean Production (LP) implementation, there is the need to understand such AI's implications on EE in this scenario. This paper aims to investigate the impact of AI on EE in lean organisations. We performed a qualitative-empirical approach in which we first interviewed twelve academic experts to grasp the investigated problem. Then, we conducted a multi-case study in manufacturing organisations undergoing a LP implementation to refine such understanding based on the observation of real-world evidence. Identifying commonalities between these stages allowed the formulation of propositions for future theory testing and validation. Findings indicate that AI may positively impact EE dimensions (physical, cognitive, and emotional) in human-centred work environments, such as lean organisations, although not at the same extent. Results also suggest that employees' psychological conditions (safety, meaningfulness, and availability) are positively affected by the relationship between AI and EE. The demystification of AI's effect on EE helps practitioners anticipate potential issues that can impair the LP implementation in the Fourth Industrial Revolution era.

This paper reports the outcomes of a case study on evaluating the usability of AR-driven quality control solution conducted in real life production setting with highly complex, high value production characteristics. The AR solution has been evaluated by the production personnel from every organizational level, with main emphasis given to operators and process engineers. The results clearly indicate a significant usability of the solution in avoiding the quality defects in the assembly line driven by manual operations.

This research examines the application of Enterprise Resource Planning (ERP) systems in service shops, focusing on the specific challenges unique to these environments compared to those in the manufacturing sector. Service shops, distinguished by their smaller scale and variable demands, often need different functionalities in ERP systems compared to manufacturing facilities. Our analysis is based on detailed billing records and monthly cash flow data to deliver critical insights into businesses’ performance for service shop managers. This study analyses ERP data from 27 service shops over 35 months. It is based on detailed billing records and monthly cash flow data to deliver critical insights into businesses’ performance for service shop managers that support managerial decision making. Our findings emphasise the importance of incorporating additional contextual information to augment the effectiveness of ERP systems in service contexts. Our analysis shows that simple, standardised data mining methods can significantly enhance operational management decision making when supported with visuals to support understanding and interpretation of the data. Moreover, this study suggests potential directions for future research aimed at improving business analytics and intelligence practices to optimise the use of ERP systems in service industries. This research contributes to the academic discourse by providing empirical evidence on utilising ERP data in service shops and offers practical recommendations for ongoing operational improvements.