The role of lean, agility and learning ambidexterity in Industry 4.0 implementations

Dilupa Nakandala, Arun Elias and Hilal Hurriyet

Technological Forecasting and Social Change, 2024, vol. 206, issue C

Abstract: There is an increasing interest in understanding the interdependencies between conventional lean and agile implementations and Industry 4.0 technology adoptions. Our knowledge of how they interact and enable Industry 4.0 implementations in learning organisations is still immature. Informed by the Strategic Momentum Theory and the contextual ambidexterity framework, this paper empirically investigates the effects of lean and agile implementations on Industry 4.0 technology adoptions with exploratory and exploitative learning as mediators. Using the data collected from an online survey of 166 Australian firms and analysed using the PLS-SEM method, we found that only lean practices have significant and positive direct effects on Industry 4.0 implementations, and exploitative learning partially mediates the relationship. We also found that agility does not have direct effects on Industry 4.0 implementations, and exploitative learning fully mediates their relationship. However, the mediating role of exploratory learning is not empirically confirmed. This study confirms several recent exploratory research studies that found evidence for the significant role lean implementations play in Industry 4.0 technology adoption. Agile practices need to first translate into exploitative learning. The findings inform practitioners that firms with investments in lean, agility and exploitative learning capability development will have advantages in technology implementations.

Keywords: Industry 4.0; Lean, agile; Learning; Exploratory; Exploitative; Operations; Innovation; Industry 4.0 adoption; Industry 4.0 technology implementations; Contextual ambidexterity; Strategic momentum (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:206:y:2024:i:c:s0040162524003299

DOI: 10.1016/j.techfore.2024.123533

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