Managing operational uncertainty in manufacturing with industry 4.0 and 5.0 technologies: a modified neo-configurational perspective - Mtotywa, Matolwandile Mzuvukile (Rhodes University, Faculty of Commerce, Rhodes Business School)
The manufacturing sector is a significant economic multiplier due to its strong connections to the economy's downstream and upstream output sectors. It supports the notion that manufacturing drives industrialisation and can serve as the primary engine for growth and employment creation. Despite its importance, the manufacturing sector has challenges associated with diminishing size and lack of competitiveness, especially in countries such as South Africa. These challenges are exacerbated by prevailing operational uncertainties that negatively impact manufacturing firms. Literature on operational uncertainty, fourth and fifth industrial revolution technologies and organisational learning show several interrelated theoretical and methodological gaps, highlighting three empirical and theoretical gaps as well as two methodological gaps. Six propositions were developed to investigate the research objectives. This was done using a multi-method quantitative design based on the post-positivist paradigm, with data collected from 22 experts (expert survey) and 262 firm representatives (firm survey). The results of the study confirmed that operational uncertainty is a multi-dimensional construct with a reflective model for dimensions and reflective-reflective for higher-order construct. This means that for the dimensions, the indicators can be added or excluded in the formation of the dimension. The same is also true for construct, operational uncertainty. The results of the present study also confirm that operational uncertainty is a norm in the manufacturing industry with a Manufacturing Operational Uncertainty Index (MOUI) = 0.752, indicating the range of futures. This posits that it is difficult to divide these futures into a discrete and exhaustive set of possibilities due to the complexity of conditions (variables) at play. Industry 4.0 and 5.0 technologies and their capabilities can manage the operational uncertainty dimensions with these technologies capable of scenario planning and supply chain integration (SPSI), flexible production and mass customisation (FPMC), real-time system and process monitoring and response (RPMR), root cause analysis and sustainable solutions (RCAS). These technologies are mainly artificial intelligence (AI), Internet of Things (IoT), big data analytics (BDA) and to a less extent advanced robotics (ARB), blockchain and augmented and virtual reality (ARVR). Organisation learning is also an effective causal condition to incorporate in managing operational uncertainty with Industry 4.0 and 5.0 technologies. The study has both theoretical and methodological contributions. In theory, it advanced the modified neo-configuration theory, while the methodology provided an Manufacturing Operational Uncertainty Index and integrated fsQCA with fuzzy decision-making trial and evaluation laboratory (DEMATEL), and structural equation modelling partial least square (PLS-SEM). This research study is important since the recognition and dissemination of subjects within the field of operations management hold great significance for firms, which is contingent upon their sector of operation. This research offers valuable insights for academia, policymakers, and the manufacturing sector. It helps with their activities to effect meaningful change in day-to-day business operations, allowing for more effective progress in the subject area, and promoting practical, real-world issue-solving.
Keywords: Industry 4.0; Industry 5.0; Operational risk; Organizational learning; Qualitative comparative analysis; Configurational analysis