系别：信管系
職稱：講師
E-mail: yuqi_2019@163.com
一、個人簡介
學習經曆
2017年9月 獲學士學位（電子商務專業，東北大學秦皇島分校）
2023年9月 獲博士學位（管理科學與工程專業，上海大學）
二、研究成果
主要承擔項目
1.“從“産品”到“場景”一一沉浸式場景化電商情景下消費者購買行為的影響機制及場景營銷策略研究（2025年度浙江省哲學社會科學規劃“高校基本科研業務費改革”專項課題,2024-2027）
論文
1. S. Li*, Y. Zhang, Z. Yu, F. Zhang, H. Lu, Predicting the influence of viral message for VM campaign on Weibo, Electronic Commerce Research and Applications. 36 (2019) 100875. (SSCI&SCI檢索，JCR Q1，FMS B級)
2. Y. Zhang, S. Li*, Z. Yu, F. Zhang, H. Lu, A 2020 perspective on “Predicting the influence of viral messages for VM campaigns on Weibo,” Electronic Commerce Research and Applications. 40 (2020) 100949. (SSCI&SCI檢索，JCR Q1，FMS B級)
3. S.G. Li, Y.Q. Zhang*, Z.X. Yu, F. Liu, Economical user-generated content (UGC) marketing for online stores based on a fine-grained joint model of the consumer purchase decision process, Electronic Commerce Research. 21 (2021) 1083–1112. (SSCI檢索, JCR Q3)
4. S.G. Li, F. Liu, Y.Q. Zhang*, Z.X. Yu, Lean persuasive design of electronic word-of-mouth (e-WOM) indexes for e-commerce stores based on fogg behavior model, Electronic Commerce Research. (2023). (SSCI檢索, JCR Q3)
5. S. Li*, Y. Zhang, Y. Li, Z. Yu, The user preference identification for product improvement based on online comment patch, Electronic Commerce Research. 21 (2021) 423–444. (SSCI檢索, JCR Q3)
6. S. Li, F. Liu, Y. Zhang*, B. Zhu, H. Zhu, Z. Yu, Text Mining of User-Generated Content (UGC) for Business Applications in E-Commerce: A Systematic Review, Mathematics. 10 (2022) 3554. (SCI檢索 JCR Q1)
7. S. Li, F. Liu, Y. Zhang*, K. Peng, Z. Yu, Research on Personalized Product Integration Improvement Based on Consumer Maturity, IEEE Access. 10 (2022) 39487–39501. (SCI檢索, JCR Q2)
8. S Li, B Zhu, Y Zhang, F Liu, Z Yu.，A Two-Stage Nonlinear User Satisfaction Decision Model Based on Online Review Mining: Considering Non-Compensatory and Compensatory Stages. Journal of Theoretical and Applied Electronic Commerce Research 19.1 (2024): 272-296. (SCI檢索)
三、教授課程
（1）數據結構思想與實現；（2）數據采集與可視化；（3）電子商務（英）
四、研究方向
（1）網絡消費者購買及評價行為；（2）商務數據挖掘
