CONSUMER PERCEPTION LINKED NOVEL SUPPLY-CHAIN MANAGEMENT (NCP-NSCM) ALGORITHM

Consumer sentiment has emerged as a central driver of supply chain management (SCM) in the modern competitive and dynamic market conditions. Conventional SCM systems hardly incorporate real-time consumer sentiment, resulting in inefficiencies, misplaced production, and lower customer satisfaction. While big data analytics (BDA) has been increasingly used to improve SCM operations, the majority of current models do not account for direct incorporation of consumer sentiment. Filling this gap, the present study introduces the Novel Consumer Perception-linked Supply-Chain Management (NCP-NSCM) algorithm. This algorithm formally integrates consumer perception information into supply chain decision-making to improve responsiveness, flexibility, and consumer focus. In contrast to earlier approaches, the NCP-NSCM framework produces improved demand forecasting, risk detection, and operational responsiveness by means of integrated sentiment analysis and SCM modeling. The effectiveness of the strategy is proven through performance measures like accuracy, precision, recall, and major operational gains such as lower lead time, cost reductions, and better order accuracy. The research presents new frontiers for supply chain design that dynamically synchronizes with changing customer expectations.