Embracing the new normal: leveraging industry 4.0 for supply chain optimisation and carbon footprint reduction

The goal of satisfying global demand across the world has led to profit-oriented practices that usually ignore sustainability concerns and frequently come at the expense of long-term effects on society and the environment. Traditional approaches to managing these issues have proven ineffective, necessitating the adoption of new capabilities and practices that are both cost-effective andsustainable. In response to this concern, this study pioneers an investigation into the adoption of I4.0 technologies and their dual impact on both cost optimisation and carbon footprint reduction. This study develops a robust model for supply chain networks and seeks to delve into the impact and strategic adoption of I4.0 for cost optimisation and the reduction of scope 1, 2, and 3 carbon footprints. The proposed model is solved using genetic algorithm (GA), adaptive genetic algorithm (AGA), differential evolution (DE), and adaptive differential evolution (ADE) approaches. The finding of the study suggests that decision makers adopt I4.0 technologies by identifying the optimum stakeholder capacity ranges that would yield the highest value in terms of cost optimisation and sustainability. Furthermore, this study expands the theoretical scope of supply chain management by integrating sustainability and cost aspects of the supply chain network.