基于深度学习的生鲜电商物流服务质量评价——以“京东生鲜”为例  

Fresh Food E-commerce Logistics Service Quality Evaluation Based on Deep Learning——Take“JD Fresh”for Example

作　　者：侯扬 李江波 姜春林[2] HOU Yang;LI Jiang-bo;JIANG Chun-lin(Business School,Qingdao University,Qingdao 266061,China;WISE Lab,Institute of Science of Science and S&T Management,Dalian University of Technology,Dalian 116024,China)

机构地区：[1]青岛大学商学院,青岛266061 [2]大连理工大学科学学与科技管理研究所暨WISE实验室,大连116024

出　　处：《青岛大学学报(自然科学版)》2024年第4期59-67,共9页Journal of Qingdao University(Natural Science Edition)

基　　金：国家社会科学基金(批准号:21BTQ104)资助。

摘　　要：为推动物流服务质量评价方法的创新融合与发展,实现全面精准评价,以京东生鲜在线评论为研究对象,构建评价指标体系,采用双向长短期记忆网络(BiLSTM)结合注意力机制(ATT)模型对其展开情感分析。研究结果表明,京东生鲜的物流服务质量整体呈积极上升趋势,物流服务人员的专业程度具备显著优势,但包装质量的保障服务存在不足,评价指标体系与深度学习模型相结合的方法可以更全面地反映消费者对物流服务质量的满意程度。To promote the innovative integration and development of logistics service quality evaluation methods and achieve comprehensive and accurate assessments,an evaluation index system was constructed with JD fresh's online reviews as the research object,and sentiment analysis was performed using a bidirectional long short-term memory network(BiLSTM)combined with an attention mechanism(ATT)model.The results show a positive upward trend in the overall logistics service quality of JD Fresh.The professionalism of logistics personnel demonstrates significant strengths,while packaging quality assurance services exhibit deficiencies.The integration of the evaluation index system with sentiment scores allows for a more comprehensive reflection of consumer satisfaction with logistics service quality.

关 键 词：物流服务质量 深度学习 情感分析 双向长短期记忆网络 注意力机制 

分 类 号：F252[经济管理—国民经济] F713.36