电子商务与大模型融合发展的核心瓶颈及解决路径研究

Core Bottlenecks and Solution Paths for the Integrated Development of E-Commerce and Large Language Models

摘要: 随着ChatGPT、文心一言等大模型技术的迭代成熟，其在电子商务领域的应用已从早期试水进入规模化价值兑现阶段，在智能推荐、供应链优化、用户服务等环节展现出显著赋能效应。然而，技术融合过程中暴露出的适配性不足、数据治理失序、商业落地受阻、伦理合规缺失等问题，严重制约了融合价值的充分释放。本文基于文献梳理与行业案例分析，系统识别电子商务与大模型融合过程中急需解决的四大核心问题：技术层面的场景适配与泛化能力不足、数据层面的质量管控与合规风险凸显、商业层面的中小企业落地门槛与价值兑现困境、伦理层面的算法偏见与内容可信性危机。在此基础上，结合最新技术进展与政策框架，从技术优化、数据治理、商业赋能、伦理监管四个维度提出针对性解决路径，构建“问题识别–成因分析–路径构建”的完整研究链条，为推动电子商务与大模型深度融合提供理论支撑与实践指引。

Abstract: With the iterative maturation of large language models (LLMs) such as ChatGPT and ERNIE Bot (Enhanced Representation through Knowledge Integration Bot), their applications in the e-commerce field have evolved from the early pilot phase to a stage of large-scale value realization, demonstrating significant enabling effects in links including intelligent recommendation, supply chain optimization, and user services. However, problems exposed in the process of technological integration—such as insufficient adaptability, disordered data governance, hindered commercial implementation, and lack of ethical and regulatory compliance—have seriously restricted the full release of integrated value. Based on a literature review and industry case analysis, this paper systematically identifies four core issues urgently requiring resolution in the integration of e-commerce and LLMs: insufficient scenario adaptability and generalization capability at the technical level, prominent quality control and compliance risks at the data level, high implementation thresholds for small and medium-sized enterprises (SMEs) and value realization dilemmas at the commercial level, and algorithmic bias and content credibility crises at the ethical level. Building on this, integrating the latest technological advancements and policy frameworks, the paper proposes targeted solutions from four dimensions—technological optimization, data governance, business empowerment, and ethical supervision—and establishes a complete research chain of “problem identification—cause analysis—path construction,” providing theoretical support and practical guidance for promoting the in-depth integration of e-commerce and LLMs.