Collaborative Decision Optimization for Timely Order Fulfillment and Service Quality Enhancement in E-Commerce Supply Chains

Abstract

To address the decision-making complexity arising from the large order volume, long fulfillment chain, and high service requirements in e-commerce, this paper proposes a supply chain collaborative decision optimization method for e-commerce fulfillment scenarios. This method constructs a unified collaborative modeling framework based on multi-dimensional business information such as order processing, seller response, product attributes, customer region, and fulfillment execution. It integrates heterogeneous features through a state fusion mechanism, uses collaborative correlation analysis to characterize the intrinsic relationship between orders and fulfillment conditions, and combines seller embedding representations to enhance the supporting role of supply-side features in decision generation, ultimately forming a decision output that balances timeliness and service performance. Compared with traditional methods that only focus on local links or single rule allocation, the proposed method can more systematically describe the organizational relationships under the combined influence of multiple subjects, factors, and constraints in the order fulfillment process, thereby improving the integrity and coordination of the supply chain decision-making process. Comparative analysis of related methods shows that the proposed method has better overall performance in terms of on-time order delivery, fulfillment stability, service quality, and collaborative execution capabilities, indicating that it can effectively support order fulfillment organization and service management in e-commerce scenarios. The research results show that building a collaborative decision-making optimization framework around the fulfillment process can help improve the operational quality of the e-commerce supply chain and provide a methodological basis for intelligent decision-making modeling in relevant business scenarios.