Enhancing product selection in live-streaming E-commerce: A multi-criteria decision-making framework

Live-streaming e-commerce has emerged as a dynamic retail model that demands efficient and accurate product selection to maximize monetization. However, traditional e-commerce screening mechanisms often fall short in addressing the multi-criteria and collaborative nature of decision-making in LSE scenarios. This study constructs a decision-making framework based on the BWM-CRITIC-MULTIMOORA method. Firstly, a comprehensive evaluation system is established by integrating 11 criteria across four dimensions: compliance, data performance, supply chain quality, and user experience. To address the inherent uncertainty and complexity in the product selection process, the framework utilizes a BWM-CRITIC subjective-objective weight optimization model to determine the criteria weights. In the weight determination method, the trust relationships, effective distance, and influence between decision-makers are also incorporated into a consensus-reaching model to help them reach agreement on pairwise comparisons of decision criteria. Finally, the improved MULTIMOORA method is used for product selection. The research results show that the proposed framework performs well in product ranking consistency and validates the relationship between consensus levels and product selection outcomes through sensitivity analysis. This study not only provides an effective decision-making tool for live-stream e-commerce product selection but also makes a new contribution to theoretical research in this field.