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Previous research has identified factors that enable lean change to be sustained. What remains unknown is how the interaction effects amongst these factors vary as lean change programmes mature. When are particular factors at their most influential?

Using a data and investigator triangulated qualitative research strategy, this paper tests an a priori model of change sustainability factors. In phase one, the research reveals the influence and significance of the model's change sustainability factors within 13 manufacturers. In phase two, four factors (Leadership, Political, Individual and Managerial) were selected for in-depth case study analyses in three manufacturers.

These point to when in the lean change, certain factors have the most influence on its sustainability. The Leadership factor and political factor are essential at the beginning and remain influential throughout. Employees' individual commitment (Individual factor) is significant in sustaining the change but it is at its most influential in the later stages. The Managerial factor (management approach) is influential in the mature stages of the programme.

Recognising where to put maximum focus during a lean change programme as it matures is crucial for management.

Sustaining lean change has not been studied from the perspective of what factors need to be emphasised at different stages in the programme for successful maturity to occur. Through empirical validation, this study helps address this knowledge gap.

Interesting because – Researchers have found that the majority of lean implementations fail – changes to structures and working practices are made only to see the gains dissipate. Previous research has suggested that multiple factors including leadership, culture and politics influence the change towards a lean organisation. While studies have shown that such factors play a role, what has not been studied is the time, that is, when the factors influence the change process. This study investigated when 11 factors have the most influence on lean implementation. Theoretical value – The study extends the state-of-the-art understanding of implementation of lean in organisations by adding a time element. It is found that in order to have a change that is sustainable, that is, lasting at least 18 months, factors that indicate the importance to the organisation are influential during the entire implementation process. This includes how central the change is to the organisation, the influence of leadership that sets vision and goals, and the implementation methods. Factors that can set things in motion such as the influence of important stakeholders are important at the beginning of the implementation process but then decline in influence over time. While factors that seem to have to do more with how companies operate have less influence at the start but become more influential over time. These include employees' commitment, the managerial style and approach, the organisational policies and structure, and the organisational culture. Practical value – Introducing lean into an organisation and gaining its sustained benefits is often not successful. While factors have previously been identified that influence the success of lean implementation, this study provides additional practical insight. It helps manufacturers be more effective by pinpointing which factors should be focused on during the various stages of the implementation process.

The integration between the traditional lean management and Industry 4.0, namely called Lean 4.0, is under the spotlight of both academia and practitioners. While we agree on the benefits Lean 4.0 may bring to companies performance, we still lack a deep understanding of the characteristics of this paradigm, such as its effective application space. Recalling traditional lean better suits repetitive companies, we are keen to understand whether the anew Lean 4.0 will enlarge its application space.

We performed an exploratory study, using a quantitative analysis based on Bayesian network approach to investigate whether Lean 4.0 results to be as effective in repetitive companies as in non-repetitive ones, in terms of operational performance.

While our findings confirm that Lean 4.0 will enhance companies' performance regardless their production strategies, companies adopting a repetitive strategy do benefit from a much higher improvement. Our findings provide an insight on the true applicability space of Lean 4.0, which seems to be the same as the traditional lean.

We contribute to the ongoing debate of Lean 4.0 providing initial empirical evidence on how to improve the operational performance in non-repetitive companies, seeing that Lean 4.0 might not be the best choice in its current format.

Prior to managing a company’s processes in the presence of a combination of paradigms, there is a need to understand their underlying interaction. This paper systematically reviews the existing literature that discusses the interaction between lean production (LP) and the fourth industrial revolution (i.e. Industry 4.0). The study aims to understand how the interaction unfolds and whether it is synergistic.

The research relies on a systematic literature review of peer-reviewed articles from Scopus and Web of Science that discuss the interaction between the two paradigms. The final set of articles pertaining to the topic was analysed.

The article presents that the interaction between the two paradigms occurs through a representation of the pillars of the House of Lean (HoL) interacting with the nine technological pillars of Industry 4.0. There is a consensus on the synergistic nexus among the pillars and their positive impact on operational performance. We also demonstrate the weights of the interactions between the two paradigms and the areas of operations management where this interaction takes place through Sankey charts. Our research indicates that the largest synergistic interaction occurs between just-in-time and industrial Internet of Things (IIoT) and that companies should invest in IoT and cyber-physical systems as they have the greatest weight of interactions with the pillars of the HoL.

This research facilitates a deeper insight into the interaction between LP and Industry 4.0 by organising and discussing existing research on the subject matter. It serves as a starting point for future researchers to formulate hypotheses about the interaction among the various pillars of LP and Industry 4.0, apply these interactions and test them through empirical research.

It could serve as a guide for managers to understand with which interactions they should start the digitalisation process.

With the rise in discussions on the interaction between the two paradigms, there is still an opportunity to understand the specificity of this interaction. Compared to the initial seminal works on the subject, such as Buer et al. (2018b), which investigated the direction of interaction between the two paradigms, this research contributes to further investigating this specificity and gaining a better understanding of the relationship governing the interaction between LP and Industry 4.0 by delineating the interaction state among the pillars of the two paradigms and its relevant importance.

This paper aim to propose a methodological mapping approach for the evaluation of dissertations and theses of graduate programs in the area of environmental sciences in Brazil in relation to the UN sustainable development goals (SDGs).

The research is characterized as exploratory with qualitative/quantitative approach. The proposed model was developed as a computational algorithm with a pilot being adopted as a professional master in national network for teaching in environmental sciences (ProfCiAmb) comprising associated courses from nine Brazilian public universities. 230 dissertations completed between 2018 and 2020 were analyzed.

A total of 266 correlations were identified between the texts and descriptors of each SDG. Correlation values between 0.100 (minimum value – Vmin) and 0.464 (maximum value – Vmax) were observed. SDG 4 – Quality Education (Vmax = 0.399) and SDG 6 – Drinking Water and Sanitation (Vmax = 0.464) were those with the highest correlation values, followed by SDG 3 – Health and Well-Being (Vmax = 0.299) and SDG 17 – Partnerships and Means of Implementation (Vmax = 0.249).

The construction of the computational algorithm provided consistent quantitative analyses with potential to contribute to the improvement of the multidimensional evaluation of graduate studies, as well as to support public policies related to teaching and research and strategic planning of the programs.

The relevance of this study lies in the creation of a model that involves the creation of metrics and tools regarding the impact of graduate studies on society.

Industry 4.0 and Lean Production are a successful match in terms of performance improvement. While we understand the combined potential, there is still poor understanding of how companies should embrace digital transformation to make it successful and sustainable, and the role that lean plays in it. In this paper, we investigate how manufacturing companies embark upon digital transformation and how being lean might affect it.

We conducted multiple case studies with 19 manufacturing companies. We identified two clusters of companies according to their Lean maturity, and we assessed digital transformation patterns by analyzing insights coming both from cases and from the literature. Integrating cross-case analysis results, we developed a framework that shows two different digital transformation patterns according to companies’ commitment to Lean.

Our findings first and foremost show the significant role of lean in driving digital transformation. We identify two patterns, namely Sustaining digital transformation pattern, characterized by the pervasive role of lean culture with small and horizontal digital changes, involvement of people and willingness to maintain continuous process improvement, and Disruptive digital transformation pattern, characterized by few and large digital steps that imply a disruptive and radical change in the company system.

Empirical evidence supports the relevance of the proposed model and its practical usefulness. It can be used to design digital transformation, prepare properly the introduction of Industry 4.0 through a lean approach, and plan the future desired state, identifying the Industry 4.0 technologies that should be implemented.

It is widely recognized that the relationship between Industry 4.0 and lean is significant and positive, yet little evidence was presented to back that. We aim at bringing this debate forward by providing initial empirical evidence of the significant role that lean has on digital transformation, showing how lean drives the digital transformation pattern of companies.