A Paradigm for Measuring Sustainable Performance Through Big Data Analytics–Artificial Intelligence in Manufacturing Firms

The study has examined the role of big data analytics powered by artificial intelligence (BDA-AI) to improve sustainable performance through sustainable supply chain practices. Data was collected from 249 supply chain professionals. Hypotheses were tested through a quantitative method using PLS-SEM with the help of SmartPLS version 3.2.9 to validate the measurement model. This study identified that BDA-AI has a significant and positive effect on Environmental Process Integration (EPI), Green Supply Chain Collaboration (GSCC), and Sustainable Manufacturing (SM). Similarly, the results showed that EPI, GSCC, and SM have a significant and positive effect on Sustainable Performance (SP). Also, these constructs significantly mediated the relationship between BDA-AI and SP. This research evaluated a second-order model and tested the sustainable performance in conjunction with Dynamic capability theory in the manufacturing industry of Pakistan. Therefore, this research could be beneficial for the researchers, manufacturers, and policymakers to attain sustainable goals by implementing the BDA-AI in the supply chain