Managing Disruptive Industry 4.0 Technologies to Enhance Circular Performance Outcomes: An Emerging Economy Perspective

Abstract

Enhancing the circular performance of the supply chains is the utmost requirement of emerging economies nowadays. It is evident that disruptive actions of Industry 4.0 technologies have impacted firms to fasten their processes of transformation through disruptive technologies. In this context, Artificial Intelligence (AI) has led to improving transparency, traceability, adopting innovative business models, etc. To assess the disruptive action of AI, the current study has adopted an integrated approach of Best-Worst-Method (BWM) and Combined Compromise Solution (CoCoSo) methods for measuring the role of disruptive AI capabilities in the circular performance outcomes of firms. This study employs an integrated approach of the BWM and CoCoSo methods for evaluating the AI capabilities and identifying the most preferred outcome. The results from BWM analysis shows that circular product design is the AI capability that acts as the most impactful enabler to enhance the circular performance outcomes of firms, followed by innovative circular business models. From the CoCoSo application, it is observed that waste reduction and enhanced resource circularity is the most critical circular performance outcome realized by firms due to enabled AI capabilities. The Resource-Based View (RBV) theory has been considered to explore the relationship between resources and AI capabilities, suggesting firms to minimize resources.

Keywords: Disruptive Industry 4.0 technologies, Artificial Intelligence, Circular Performance Outcomes, Emerging economies.