Track: Modeling and Simulation

Abstract

To address issues of environmental and social sustainability, this research study investigates how business analytics can be integrated into sustainable textile supply chains. It emphasizes how this integration can improve managerial performance. The textile sector is under growing pressure to implement sustainable practices; thus it is critical to comprehend how data-driven decision-making may enhance sustainability outcomes and optimize operations. In the framework of sustainable practices in textile supply chains, the main goal of this research is to investigate how business analytics might be used to improve management performance. The goal of the study is to shed light on the operational efficiencies that analytics can give, the implementation challenges, and the wider sustainability implications. The main issue addressed is the knowledge gap regarding the adaptation of managerial processes to fully utilize analytics for sustainable objectives. The study has utilized a qualitative research technique, drawing on secondary data gathered from industry reports, scholarly literature, and other publications. The main conclusions show that although business analytics greatly enhances operational effectiveness and decision-making, obstacles including poor data quality, a lack of analytical abilities, and change aversion prevent successful deployment. One of the limitations of the study is that it mostly focused on larger businesses, which left a need to better understand the particular difficulties small and medium-sized businesses confront. The theoretical ramifications point to the necessity for more thorough frameworks that take environmental factors and social sustainability measures into account. In practice, businesses are urged to make training and technology investments to cultivate a culture that values data-driven decision-making.