How Dynamic Capabilities in Maintenance Enable Metal Plants in the UAE Via Big Data Analytic Capabilities Towards Digital Twins Adoption? A Mediation and Moderation Analysis
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Date
2024-06
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The British University in Dubai (BUiD)
Abstract
The research employed a standardised survey to explore how Dynamic Capabilities (DCs) are influencing the adoption of Digital Twins (DTs) through Big Data Analytics Capabilities (BDAC) as a mediator variable. Furthermore, it also inspects the influence of Digital Leadership (DL) as a moderator variable in above relationship in terms of maintenance in metal plants in United Arab Emirates (UAE). This research reveals a correlation between above indicated variables based on practical responses from maintenance. Results will definitely support the improvement of maintenance performance in metal plants. Mediation and moderation analyses were conducted using SmartPLS4 to test four hypotheses based on data collected from 183 respondents, comprising managers, engineers and technicians from maintenance departments in various metal plants in UAE. As hypothesised, research findings suggest that BDAC plays a mediating role in relationship between DCs including seizing (SEZ) and transforming (TRF) and adoption of DTs. However, sensing (SEN) has neither a direct nor an indirect relationship with DTs. Additionally, low DL significantly strengthens moderation effect in terms of positive relationship between BDAC and adoption of DTs. These findings confirm need of this research's key predictor variable - DCs, BDAC and moderator variable DL - in driving organisational readiness toward digital transformation. The research is limited and should not be generalised given that it has only focused on analysing collected data from one sector - metal plants industry in the UAE. Future research should focus on analysing how applicable this framework is across other industries while investigating factors for adoption of DTs.
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Keywords
big data analytics capabilities, digital twins, digital leadership, overall performance, dynamic capabilities, sensing, seizing, transforming, resource-based view