From training to learning: Transition of a workplace for industry 4.0

Abstract

BACKGROUND: Transition into Industry 4.0 has had many significant impacts. Customization symbolizes leanness, flexibility, adaptability, and agility. A business operator needs to recognize the factors that contribute to better utilization of the talents of its workforce and more effective workplace learning. OBJECTIVE: The study aims to provide a construct which highlights effective workplace learning. In this context, a construct represents a broad view of various interrelated ideas and concepts which can point to academic and practical implications. METHODS: The study applies action research which is suitable when observing a transformative change. The study intends to observe and notice how the environmental factors have changed and try to predict their impacts on human capital development. To help verify the suitability of these impacts, a comparison with similar studies or findings is made. Focuses on literature reviews which look at the impacts from Industry 4.0 (on a need to tackle the waste of the talents in a workplace), recent developments of learning (on an emerging importance of informal learning), and survey’s data (on a shift in a workplace’s expectation on the workers). RESULTS: Workplace learning has gradually replaced training and education. The proposed construct can help tackle the underutilization of the talents in a workplace as the workers are nowadays expected to perform the tasks and learn at the same time. CONCLUSIONS: Sustaining learning in a workplace needs to understand behavior, motivation, emotion, and workplace engagement. Informal learning, which reflects the individualization of learning, can enable an organization to deal with workplace learning.

Traces of Technological Well-being: Digi-uplifters and Digi-downshifters

“…This may portray Digi-downshifters as enthusiastic about delegating their work to new and improving technologies. The finding is in line with prior studies of the benefits in continuous learning (Rassameethes et al 2021;Watson et al 2018), and the implication is that repeated technological changes at work are more about the joy of learning about new things and working methods than frustration about constant changes (Bernerth et al 2011). Reflecting this in the high presentation of Digi-downshifters in the arts and entertainment industry, this conclusion is further supported on the grounds that creativity is profoundly associated with the motivation of continuous learning (Venckutė et al 2020).…”

“…Continuous learning at work has been found to exclusively improve wellbeing rather than being a risk factor for it (Watson et al 2018). At the same time, engaged employees are also found to be the individuals most willing and motivated to learn (Rassameethes et al 2021).…”

Operationalizing Mass Customization in Manufacturing SMEs—A Systematic Literature Review

“…[3]. Finally, collaboration with a network of partners is a factor that was often identified as favourable for implementing mass customization in the context of Industry 4.0 [16,17,22].…”

“…Based on this need for agility, the literature discusses ways in which Industry 4.0 and distributed networks can operationalize the requirements of mass customization [16,17]. However, companies are not adequately equipped to undertake the shift to Industry 4.0 [5].…”