电子商务生态下智能招聘体系构建与人才匹配效能提升研究

Research on the Construction of Intelligent Recruitment System and the Improvement of Talent Matching Efficiency in the E-Commerce Ecosystem

摘要: 电商产业在高速扩张过程中呈现出岗位结构多样、用工节奏紧凑、场景变化频繁等特征，传统招聘模式难以满足业务链路对时效性与匹配度的要求。智能技术在语义解析、行为预测与多维特征建模中的应用，为构建新型招聘体系创造了坚实基础。研究围绕场景驱动、数据治理与算法优化展开，探讨智能招聘体系在岗位识别、人才评估与匹配策略中的机制与成效，并通过行业实践验证体系在效率、质量与稳定性方面的提升作用。研究旨在为电商行业形成可持续、可扩展的人才配置模式提供方法依据。

Abstract: In the process of rapid expansion, the e-commerce industry presents characteristics such as diverse job structures, tight employment rhythms, and frequent scene changes. Traditional recruitment models are difficult to meet the requirements of timeliness and matching in the business chain. The application of intelligent technology in semantic parsing, behavior prediction, and multi-dimensional feature modeling has created a solid foundation for building a new recruitment system. The research focuses on scenario-driven, data governance, and algorithm optimization, exploring the mechanism and effectiveness of intelligent recruitment systems in job identification, talent evaluation, and matching strategies, and verifying the system’s role in improving efficiency, quality, and stability through industry practice. The research aims to provide methodological basis for the sustainable and scalable talent allocation model in the e-commerce industry.