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This study aims to investigate the impact of traditional teaching and active learning methods in lean management (LM) on the development of both soft and hard skills.

Through a longitudinal study, team members from two different organisations (the administrative sector of a public higher education institution and a public teaching hospital), each adopting different teaching methods to support their LM trainings, were systematically examined at four moments during an 18-month period. How teaching methods impacted team members’ development and knowledge was then assessed using multivariate data analysis techniques.

Results indicated that LM trainings can provide significant impacts when a combination of traditional teaching methods and active learning is adopted. Traditional teaching methods can be a good choice for learning hard skills depending on resources’ availability. However, it is recommended to include active learning methods to assist in the comprehension of more complex and abstract LM concepts (soft skills).

Although there exists a large number of publications on the relationship between LM implementation and teaching methods, the number of studies that consider the development of both hard and soft skills is rather limited. This study complements the existing literature on LM by identifying which teaching methods can support the development of hard skills and which the development of soft skills. Such identification facilitates the work of both scholars wishing either to begin or to dig deeper into this sphere and practitioners pursuing the best outcomes from LM.

This paper aims at identifying the main contributions of Industry 4.0 (I4.0) technologies to the enhancement of knowledge management (KM).

A scoping review based on two stages was carried out. In the first stage, a numerical and descriptive analysis was conducted. In the second stage, the latent content of those papers was explored through a qualitative analysis, in which papers were assessed regarding the outcome of the implementation of ten I4.0 technologies on 14 KM abilities and 6 KM processes.

Six technologies (e.g. Internet of Things (IoT), big data, cloud computing, simulation, visualisation and industrial robot) were claimed to have a significant contribution on KM, especially for creation, organisation, dissemination and application processes. Overall, results indicated that technologies can significantly contribute to KM, although the extent of such contribution varies across technologies, learning levels, KM processes and abilities.

Existing studies in I4.0 fall short in exploring how embodied knowledge is articulated in practice, especially regarding opportunities to use new technological alternatives in favour of knowledge and learning development. This study complements the existing literature on I4.0 by identifying which technologies can contribute to KM. Also, a framework was proposed to examine the contribution of I4.0 technologies to KM at individual, team, and organisational levels.