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The aim of this study reported in this paper was to explore the application of operational excellence methodologies in a global context.

A qualitative interview approach was used to understand the current state, benefits, challenges, success factors, tools and techniques of operational excellence methodology implementation with relevance to logistics companies worldwide. About 16 interviews were undertaken with practitioners working in leading companies and with leading academics in Asia, Europe, Africa, North America, South America and Australia.

The findings show that operational excellence methodologies including Lean, Six Sigma, Lean Six Sigma and Agile can apply in logistics firms to improve operations and productivity and save costs. Top management support and involvement play an important role in the success of operational excellence projects in the logistics service.

The findings will be of interest to top and middle managers and logistics practitioners, with a dual aim of improving logistics performance and saving costs.

The present study has been one of the first global study attempts to explore the implementation of operational excellence methodologies in the logistics sectors.

Since the advent of Industry 4.0, there has been a growing research interest in developing the Green Lean Six Sigma concept in the direction of achieving sustainable development, primarily aligned with Goal 12 of the agenda. Given that the concept is still in its early stages of exploration and requires further development through empirical validation, opportunities exist for innovative research. Yet, difficulties arise in adopting this green initiative due to an inadequate understanding of its strategic practices. Thus, this study aims to establish strategic practices facilitating its adoption in the Industry 4.0 era and develop a validated multi-item scale to measure the practices.

A three-phase methodological approach is designed to perform the techniques of exploratory and confirmatory analyses in the manufacturing context. To be a sound study, engineers have been involved since they play a pivotal role in the realm of manufacturing; however, the existing research on engineers' viewpoints on this subject is limited, emphasizing the need for further investigation.

Upon validation of the ultimate fallouts, the analyses demonstrated a confirmatory model with eighteen scales determining five practices: strategic integrity, human resource management, technologies and tools, eco-production, and eco-networks. The findings further revealed robust correlations among these core practices within the model.

The contribution of this study entails depicting and discussing a measurement model for future research since there is currently no empirically validated model available to measure this multidimensional green initiative.

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

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

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

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

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

The present study aims to identify the critical barriers of blockchain technology (BT) implementation in a manufacturing environment in context of developing countries.

In the present work, barriers of BT adoption have been investigated via literature review and screened them through expert’s input. Further, the interrelationships among screened barriers were framed using a modified total interpretive structural modelling (mTISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) approach. The mTISM aims to develop a contextual relationship-based performance model with the logic behind transitive links formation to explore the dominant barriers. The MICMAC approach categorizes the blockchain adoption barriers based on their driving and dependence power.

Based on the analysis, nine barriers of BT adoption in manufacturing environment were identified and finalized through statistically. The obtained results exhibit that lack of awareness about blockchain and poor training/human expertise on innovative technologies are the most critical barriers that hinder blockchain adoption. This study provides a roadmap and may facilitate manufacturing professional, consultant, governing bodies and policymakers in the preparation of active strategies to overcome challenges in adoption of BT in the running system.

Literature is full with analysis of barriers of BT adoption in the domain of supply chain, operation management and manufacturing in context of developed nation only. The present work is the first attempt to examine the BT adoption barriers in the manufacturing environment of developing economy and covered the mutual-interrelationship among them via modified TISM approach.

Smart manufacturing (SM) capitalizes on big data analytics (BDA) advancements by enhancing current capabilities such as defect identification and enabling supporting capabilities such as preventive maintenance (PM). The previous literature fails to investigate the comprehensive associations between SM, BDA and PM. Therefore, this study aims to investigate the relationship among SM, BDA and PM.

The present research implements a multi-analytical PLS-SEM-ANN approach to investigate the relationships among BDA, PM and SM.

This investigation indicates that BDA is an effective digital technology that positively affects the operations of SM and PM. Furthermore, the results suggest that PM has a positive influence on SM and that it also positively mediates the relationship between BDA and SM, where PM cannot be treated as an auxiliary practice and plays an important role in SM as a primary operation. Furthermore, implementing the BDA enhances the performance of SM and PM.

The role of PM in the context of BDA and SM has been ignored in past research, and this study offers novelty by examining this relationship.

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.

To investigate the transformative impact of soft skills on the career pathways of experts and students in the engineering domain.

The study adopts a comprehensive approach, combining a review of existing literature with primary data to analyse quantitative and qualitative empirical investigations. Data from 40 participants, who are engineering students and professionals, is analysed using descriptive statistics and advanced software tools like ATLAS.ti and Jamovi.

The findings underscore the indispensable nature of soft skills in elevating employability, emphasising the urgent need for mandatory soft skills education for engineering students and professionals. The research identifies the top five soft skills engineers need: communication, teamwork, time management, leadership and problem-solving.

The research contributes to understanding soft skills’ pivotal role in engineering professions, providing valuable insights for professionals and organisations aiming to enhance performance and competitiveness in the industry. The study advocates for a holistic approach that recognises the symbiotic relationship between technical proficiency and soft skills in shaping the success of engineering graduates in the 21st-century workforce.

The study recognises the current job market demands and asserts that engineers must combine technical expertise with soft skills to succeed in the technology-driven yet people-centric engineering profession.

This paper aims to provide empirical evidence regarding Lean Six Sigma (LSS) practices supported by Industry 4.0 (I4.0) technologies in heavy vehicle manufacturing processes.

A two-case study was performed involving LSS specialists, leaders and managers of two heavy vehicle manufacturers in Brazil. The data analysis procedure combined content analysis techniques, conceptual maps and network analysis.

The results provide consistent evidence of synergies between LSS and I4.0, including digital mistake-proofing, digital andon, e-kanban, statistical monitoring as well as process mapping aided by cyber-physical systems (CPS) and big data analytics (BDA). To enable such interactions, companies need to invest in automation architectures, system integration, human–machine interfaces and analytical skills.

This study relies on data from a two-case study carried out in two companies from a single manufacturing sector in Brazil. For this reason, the findings cannot be generalized to the entire automotive industry.

There is still a lack of comprehensive research on the application of digital technologies in LSS practices. This is the first study which provides empirical evidence regarding the LSS practices supported by I4.0 technologies used by heavy vehicle manufacturers.

Operational excellence (OpEx) is a proven philosophy focusing on continuous improvement in processes and systems for superior performance and efficiency. It plays a crucial role in the energy sector, acting as a catalyst for safety, customer satisfaction, sustainability and competitiveness. This research aims to assess OpEx methodologies in Oman’s energy sector, examining methods, approaches, motivations and sustainability.

This study applies qualitative analysis methodology, involving interviews with 18 industry experts, from the energy sector in a sizeable energy country.

The analysis revealed a growing demand, particularly, in the oil and gas industry, driven by emerging business needs. Qualitative data analysis has identified 10 themes such as implemented methodologies, motivation drivers, deployment approaches, sustainability factors, benefits and challenges. Additionally, new themes emerged, including influencers to start OpEx, resource requirements, enablers for successful OpEx and systems.

This research was limited to Oman and the findings drawn from Omani energy companies may have limited applicability to energy companies in other regions. Therefore, if these findings were to be used, the validation of the findings in relation to other countries should be conducted, to ensure the validity of the context and outcome.

These findings contribute to understanding OpEx dynamics in the Omani energy sector, offering valuable insights for effective utilisation and organisational goal achievement. Furthermore, the study offers valuable insights on how to effectively employ OpEx initiatives in the energy sector to achieve their goals and create value. It addresses the lack of knowledge, offers a framework for successful OpEx implementation, bridges the theory-practice gap and provides insights for optimal utilisation.

To the best of the authors’ knowledge, this is the first empirical study on assessing OpEx methodologies in the energy sector, and therefore it serves as a foundation for many future studies. The study provides a theoretical foundation for the OpEx methodologies in terms of organisational readiness for successful OpEx implementation.

Many organizations currently transition towards digitalized process design, execution, control, assurance and improvement, and the purpose of this research is to empirically demonstrate how data-based operational excellence techniques are useful in digitalized environments by means of the optimization of a robotic process automation deployment.

An interpretive mixed-method case study approach comprising both secondary Lean Six Sigma (LSS) project data together with participant-as-observer archival observations is applied. A case report, comprising per DMAIC phase (1) the objectives, (2) the main deliverables, (3) the results and (4) the key actions leading to achieving the presented results is presented.

Key findings comprise (1) the importance of understanding how to acquire and prepare large system generated data and (2) the need for better large system-generated database validation mechanisms. Finally (3) the importance of process contextual understanding of the LSS project lead is emphasized, together with (4) the need for LSS foundational curriculum developments in order to be effective in digitalized environments.

This study provides a rich prescriptive demonstration of LSS methodology implementation for RPA deployment improvement, and is one of the few empirical demonstrations of LSS based problem solving methodology in industry 4.0 contexts.