• Feng Liu (刘锋), Ph. D.

    Associate Professor 副教授

    Business School, Shandong University, Weihai, China.

    Principal Investigator (PI) of Star-lights Research Team (星耀科研小组）

    Editorial Board: Small Business Economics (SSCI), Journal of Competitiveness (SSCI, 2021-2024), Humanities & Social Sciences Communications (SSCI), Information Resources Management Journal (EI), International Journal of Multinational Corporation Strategy, Journal of Smart Tourism

    Young Editorial Board: Data Science and Management

    Email address: liufeng@sdu.edu.cn


    September 2023 - Now: Associate Professor at the Business School, Shandong University, Weihai.

    March 2020 - August 2023: Assistant Professor at the Business School, Shandong University, Weihai.

    March 2017 - February 2020: PhD in Business (Major in Logistics, Service & Operations Management), Korea University Business School.

  • 与合作者携手并进，与学术圈同频共振，与国家共绘繁荣。

    Collaborate closely with our partners, engage harmoniously with the academic community, and contribute to the prosperity of our motherland.

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    个人简介

    刘锋博士(https://www.fengliu.net/) ，山东临沂人，现任山东大学商学院副教授、博士生导师、电子商务与物流系副系主任，入选山东哲学社会科学“111”领军人才培育项目（第三类人选）、山东大学（威海）青年学者未来计划，2020年获得高丽大学商学院博士学位。主要从事供应链管理与人工智能的交叉融合方向的研究，熟练掌握机器学习、深度学习、多模态融合等新兴技术，围绕数智化运营与供应链管理取得一系列研究成果，拓宽了供应链集中度、供应链透明度等相关理论，丰富了人工智能在经管学科的研究范式。在Journal of Management Information Systems, Journal of Business Ethics, International Journal of Production Economics, Decision Support Systems, Technological Forecasting and Social Change, Annalsof Operations Research, China Economic Review, Expert Systems with Applications, 《科学学研究》等SCI/SSCI/CSSCI来源刊物上发表论文50余篇，谷歌学术引用量3300余次，相关研究成果荣获山东省第三十七届社会科学优秀成果奖三等奖。聚焦国家战略需求开展针对性研究，为“AI+管理”的交叉融合提供坚实理论支撑，主持国家自然科学基金青年项目1项，教育部人文社科青年项目1项，担任Small Business Economics (SSCI), Humanities & Social Sciences Communications (SSCI)等多个期刊的编委以及Data Science and Management的青年编委。2020年获得了工业和信息部颁发的<大数据分析师高级证书>，具备大数据采集、分析、教学等专项技术水平。

    刘锋老师创建了“星耀科研小组”，聚焦人工智能与经济管理的交叉领域，手把手带领本科生开展科研训练，助力学生突破学术瓶颈、登上国际学术舞台，累计指导本科生以第一作者发表包括FT50期刊在内的SCI/SSCI高水平论文成果15篇，让普通学生成长为学术新秀，培养了一批具有科研素养和创新精神的优秀青年人才。小组成员卢灿同学，在他的悉心指导下，从科研入门的“新手”逐步成长为能独立开展研究的 “能手”，凭借扎实的研究基础和创新思路，成功获批山东大学第二届青年学生基础研究项目培育计划（“青苗” 专项）立项。目前，“星耀科研小组” 形成了勤学善思、互助共进、争先创优的优良学风，越来越多的青年学子在科研实践中锤炼本领、增长才干，真正实现了以研育人、以育促长，为培养高素质创新型青年人才注入青春动能。

    目前团队经费充足，研究基础扎实，代码积累丰富，技术方法熟练。

    欢迎有志于从事学术研究的，特别对供应链运营管理、数字治理、信息资源管理、大数据分析、机器学习与深度学习感兴趣的同学报考商学院的企业管理学术硕士和工业工程与管理专业硕士。

    Feng Liu (https://www.fengliu.net/) is an Associate Professor at the Business School, Shandong University, Weihai, China. He serves as the Principal Investigator of the Star-lights Research Team. He received his Ph.D. from the Department of Logistics, Service and Operations Management (LSOM) at Korea University Business School, Seoul, South Korea. His research focuses on operations management, information systems, and the intersection of artificial intelligence, particularly machine learning and deep learning. He currently serves on the editorial boards of Small Business Economics, Humanities & Social Sciences Communications, and Information Resources Management Journal. His research has been published in leading journals, including the Journal of Management Information Systems, Journal of Business Ethics, International Journal of Production Economics, and Decision Support Systems.

  • Team Overview 团队介绍

    科研追光，星耀山大！

    Star-lights Research Team

    星耀科研小组

    面向本科生的星耀科研小组已成功运营9期，累计指导山东大学本科生以第一作者身份发表国际高水平论文15项（具体成果详见下方图片）。参与小组科研的同学均获得了优质的保研升学机会，成功斩获包括北京大学在内的海内外知名高校录取资格，在学术道路上迈出了坚实的一步。

    小组前辈成员均熟练掌握机器学习、深度学习、图像分析、文本分析、多模态融合等核心科研技术。我们始终秉持“互助共进、薪火相传”的理念，鼓励成员间互帮互助、协同创新，通过“以老带新”的模式，不仅传递科研经验、传授专业技术，更传承严谨务实、求真务实的科研精神，助力每一位成员快速成长。

    第10期科研活动即将启动，小组目前聚焦三大核心研究方向：“社交媒体：重塑企业管理、金融经济与社会发展的新动能”、“Generative AI: 社交媒体场景下生成式人工智能的管理与应用”、“社交机器人的精准识别与规范化治理”。只要你秉持坚持不懈的毅力、坚守诚实可靠的品格、保持认真努力的态度，且对科研充满热情、乐于探索，欢迎准备好个人简历与研究计划，发送至邮箱liufeng@sdu.edu.cn，申请加入我们的科研团队！

    唯有步履不停，方能迈向更为辽阔的天地，勇攀学术高峰；

    唯有锐意进取，方能收获丰硕成果，书写青春华章。

    愿我们精诚合作、并肩前行，不断攻克科研难关，做科研路上的追光者；也期待每一位加入的成员，向山而行、勇攀高峰，携手取得更多更高质量的研究成果，在学术探索中实现自我成长！

    Star-lights Research Team: Pursuing Scientific Excellence, Shining Bright at Shandong University!

    The Star-lights Research Team has successfully operated 6 sessions, guiding Shandong University undergraduates in publishing over 10 SSCI/SCI papers. Among these, nine high-level international papers were published with the students as first authors. These accomplishments have opened doors for further academic opportunities, with students receiving offers from renowned domestic and international universities.

    The senior members of the team are proficient in technologies such as machine learning, deep learning, image analysis, text analysis, and multimodal fusion. The team fosters a collaborative environment, encouraging mutual support and collective progress. With a culture of “learning from the seniors", experience is passed down, technical skills are taught, and, most importantly, the team’s spirit is inherited!

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  • Publication Achievements 期刊成就

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    FT50

    • Journal of Business Ethics
    • Journal of Management Information Systems

    ABS3

    • International Journal of Production Economics (Twice)
    • Technological Forecasting and Social Change (Three times)
    • Annals of Operations Research
    • Decision Support Systems
    • Journal of Purchasing and Supply Management
    • Journal of Business Logistics

  • 1. Operations and Supply Chain Management

    (运营管理与供应链管理)

    本系列研究成果主要致力于：1. 扩宽供应链集中度的内涵，在客户集中度和供应商集中度的基础上引出地区集中度与产品集中度的概念；2. 探索HACCP运营管理体系的经济价值；3. 数字化转型与供应链运营管理的交叉融合。

    1. Liu, F., Chen, Z., Fang, M., Xiao, S. *, & Shi, Y. (2024). Legitimacy and Transparency in Dyadic Supply Chains: Does Competition Intensity Matter?. International Journal of Production Economics, 109397. https://doi.org/10.1016/j.ijpe.2024.109397
    2. Liu, F., Liu, C., Wang, X., Park, K., & Fang, M. * (2024). Keep concentrated and carry on: redesigning supply chain concentration in the face of COVID-19. International Journal of Logistics Research and Applications, 27(10), 1681–1704. https://doi.org/10.1080/13675567.2023.2175803
    3. Liu, F., Fang, M., Xiao, S.(S). *, & Shi, Y. (2024) Mitigating bullwhip effect in supply chains by engaging in digital transformation: the moderating role of customer concentration. Annals of Operations Research. https://doi.org/10.1007/s10479-024-05908-
    4. Liu, F., Yu, Y., Fang, Y., Zhu, M., Shi, Y., & Xiao, S. S. (2024). Lean strategy in SMEs: Inventory leanness, operational leanness, and financial performance. The Asian Journal of Shipping and Logistics, 40(2), 109-117. https://doi.org/10.1016/j.ajsl.2024.02.003
    5. Liu, F., Wang, Q., Zhang, Z., Fang, M. and Xiao, S.(S). *(2023). Lean inventory, fintech and financing: interactive influences on Chinese SMEs, Management Decision, 61(8), 2302-2321. https://doi.org/10.1108/MD-06-2022-0878
    6. Liu, F., Kim, B. C. *, & Park, K. (2022). Supplier-base concentration as a moderating variable in the non-linear relationship between R&D and firm value. Asian Journal of Technology Innovation, 30(2), 342-363. https://doi.org/10.1080/19761597.2020.1853576
    7. Liu, F., Rhim, H., Park, K., Xu, J., & Lo, C. K. * (2021). HACCP certification in food industry: Trade-offs in product safety and firm performance. International Journal of Production Economics, 231,107838. https://doi.org/10.1016/j.ijpe.2020.107838
    8. Liu, F., & Park, K. * (2021). Managing firm risk through supply chain dependence: an SME perspective, Journal of Business & Industrial Marketing, 36(12), 2231–2242. https://doi.org/10.1108/JBIM-05-2019-0229
    9. Liu, F., Fang, M., Park, K., & Chen, X. * (2021) Supply chain finance, performance, and risk: How do SMEs adjust their buyer-supplier relationship for competitiveness?. Journal of Competitiveness, 13(4), 78–95. https://doi.org/10.7441/joc.2021.04.05
    10. Chen, X., Liu, C., Liu, F. *, & Fang, M. (2021). Firm Sustainable Growth during the COVID-19 Pandemic: The Role of Customer Concentration. Emerging Markets Finance and Trade, 57(6), 1566-1577. https://doi.org/10.1080/1540496X.2021.190488
    11. Fang, M., Liu, F., Xiao, S., & Park, K.* (2023). Hedging the bet on digital transformation in strategic supply chain management: a theoretical integration and an empirical test. International Journal of Physical Distribution & Logistics Management. 53(4), 512-531.. https://doi.org/10.1108/IJPDLM-12-2021-0545
    12. Fang, M., Liu, F., & Park, K. * (2022). Is inventory performance helping to improve SME credit ratings? The moderating role of supply chain concentration. Applied Economics Letters, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1080/13504851.2022.215645
    13. Fang, M., Yu, Y., Park, K., Liu, F., Xiao, S. S., & Shi, Y. (2024). Supply chain relationship dependencies and circular economy performance: The contingency role of digitalization capability. Journal of Purchasing and Supply Management, 100902. https://doi.org/10.1016/j.pursup.2024.100902
    14. Fang, M., Liu, F., Xiao, S. *, Park, K., & Gao, Y. (2025). Navigating Ethical Dilemmas in Supply Chain Finance: The Interplay Between Digitalization and Cultural Congruence. Journal of Business Logistics, 46(3), e70027. https://doi.org/10.1111/jbl.70027
    15. Zhang, X., Liu, F., & Fang, M. * (2025). Who is acting unethically? The role of board diversity in corporate social responsibility decoupling. Corporate Social Responsibility and Environmental Management, 1–20. https://doi.org/10.1002/csr.70174 (星耀科研小组成果）
    16. Li, M., Liu, F., Fang, M., Xiao, S., & Shi, Y. (2025). Green innovation along the dyadic relationship: the moderating role of supply chain dependence. The International Journal of Logistics Management, 1-28. (星耀科研小组成果）

    2. Machine Learning and Deep Learning Applications （机器学习深度学习与经济管理的交叉融合）

    本系列研究成果主要是丰富机器学习、深度学习的研究范式，探索机器学习与深度学习研究方法在经济管理中的应用，指导本科生（星耀科研小组）在SCI/SSCI发表论文多篇。

    1. Liu, F., and Chen, Y., Ho, Y (Chad)., Dasgupta, S. & Fang, M.* . (2026). A Machine Learning Analysis of Emotional Appeals in Charity Crowdfunding. Journal of Management Information Systems, Forthcoming, Available at SSRN: http://dx.doi.org/10.2139/ssrn.5954374
    2. Liu, F., Wang, R. & Fang, M. *. (2024) Mapping green innovation with machine learning: Evidence from China, Technological Forecasting and Social Change, 200, 123107. https://doi.org/10.1016/j.techfore.2023.123107 (星耀科研小组成果）
    3. Liu, F., Huang, W., Zhang, J., & Fang, M. * . (2024). Corporate social responsibility in family business: Using machine learning to uncover who is doing good. Technology in Society, 102453. https://doi.org/10.1016/j.techsoc.2024.102453 (星耀科研小组成果）
    4. Liu, F., Long, X., Zhang, Z., Lin, Dong., and Fang, M. *(2023). What makes you entrepreneurial? Using machine learning to investigate the determinants of entrepreneurship in China, China Economic Review, 81, 102029. https://doi.org/10.1016/j.chieco.2023.102029 (星耀科研小组成果）
    5. Sun, R, Liu, F. * , Li, Y., Wang, R. & Luo, J (2024) Machine Learning for Predicting Corporate Violations: How Do CEO Characteristics Matter? Forthcoming, Journal of Business Ethics （FT50）https://doi.org/10.1007/s10551-024-05685-0 (星耀科研小组成果）
    6. Wang, H., Chen, Z. S., Fang, M., Wang, Y., & Liu, F. * (2025). Panoramic sales insight: Using multimodal fusion to improve the effectiveness of flash sales. Decision Support Systems, 114401. https://doi.org/10.1016/j.dss.2025.114401
    7. Xu, Q., Liu, C., Luo, J., & Liu, F. (2024). Using machine learning to investigate the determinants of loan default in P2P lending: Are there differences between before and during COVID-19?. Pacific-Basin Finance Journal, 102550. https://doi.org/10.1016/j.pacfin.2024.102550 (星耀科研小组成果）
    8. Sun, C., & Liu, F.* (2024). VSEM-SAMMI: An Explainable Multimodal Learning Approach to Predict User-Generated Image Helpfulness and Product Sales. International Journal of Computational Intelligence Systems, 17(1), 97. https://doi.org/10.1007/s44196-024-00495-8 (星耀科研小组成果）
    9. Gu, J., Zhang, S., Yu, Y., & Liu, F. * (2024). AB-LSTM-GRU: A Novel Ensemble Composite Deep Neural Network Model for Exchange Rate Forecasting. Computational Economics. https://doi.org/10.1007/s10614-024-10754-7 (星耀科研小组成果）
    10. Liu, C., Chen, X., Wang, Y., Xiao, S., Liu, C., & Liu, F. * (2024). Exploring the determinants of systematic risk through machine learning: evidence from Chinese listed companies. Applied Economics. https://doi.org/10.1080/00036846.2024.2431170 (星耀科研小组成果）
    11. Zhang, J., Zhu, M. & Liu, F. *. (2024) Find who is doing social good: using machine learning to predict corporate social responsibility performance. Operations Management Research. https://doi.org/10.1007/s12063-023-00427-3 (星耀科研小组成果）
    12. Liu, W., Liu, C., Luo, J., & Liu, F.* (2024). How does digital transformation promote total factor productivity? Strategy, technology, and application. Managerial and Decision Economics, 1–12. https://doi.org/10.1002/mde.4155 (星耀科研小组成果）
    13. Zhang, S., Luo, J., Wang, S., & Liu, F. *. (2023). Oil price forecasting: A hybrid GRU neural network based on decomposition–reconstruction methods. Expert Systems with Applications, 218, 119617. https://doi.org/10.1016/j.eswa.2023.119617 (星耀科研小组成果）
    14. Wang, M., Yu, Y., & Liu, F. * . (2023). Does Digital Transformation Curb the Formation of Zombie Firms? A Machine Learning Approach. Technology Analysis & Strategic Management, https://doi.org/10.1080/09537325.2023.2296007 (星耀科研小组成果）
    15. Liu, C., Li, Y., Fang, M., & Liu, F. * . (2023). Using machine learning to explore the determinants of service satisfaction with online healthcare platforms during the COVID-19 pandemic. Service Business, 17, 449–476. https://doi.org/10.1007/s11628-023-00535-x(星耀科研小组成果）
    16. Liu, C., Chen, Y., Huang, S., Chen, X., & Liu, F. * (2023). Assessing the Determinants of Corporate Risk-Taking Using Machine Learning Algorithms. Systems, 11(5), 263. https://doi.org/10.3390/systems11050263 (星耀科研小组成果）
    17. Yu, Y., Zhou, R., Jiang, R., & Liu, F. * (2025). Exploring the role of social bots in cryptocurrency manipulation: Machine learning insights from the LUNA crash. Electronic Markets, Forthcoming. https://doi.org/10.1007/s12525-025-00849-w (星耀科研小组成果）
    18. Qu, A., Luo, J., & Liu, F. * (2025). Who guards the guards? Exploring the role of CEO characteristics in internal control through machine learning. Financial Innovation, Forthcoming. (星耀科研小组成果）

    3. Technology, Innovation, Entrepreneurship, and SMEs （技术、创新、创业以及中小企业）

    本系列研究主要是探索中小企业的高质量发展以及技术、创新、创业等多个领域的热点话题。

    1. Liu, F., Dutta, D. K. *, & Park, K. (2020). From external knowledge to competitive advantage: absorptive capacity, firm performance, and the mediating role of labour productivity. Technology Analysis & Strategic Management, 33(1), 18-30. https://doi.org/10.1080/09537325.2020.1787373
    2. Liu, F. *, Shang, M., & Zhou, X. (2021). Toward street vending in post COVID-19 China: Social networking services information overload and switching intention. Technology in Society, 66, 101669. https://doi.org/10.1016/j.techsoc.2021.101669
    3. Xu, J., & Liu, F. *, & Shang, Y. (2020). R&D investment, ESG performance and green innovation performance: evidence from China, Kybernetes, 50(3), 737-756. https://doi.org/10.1108/K-12-2019-0793
    4. Wang, X., Wong, Y. D., Liu, F., & Yuen, K. F. (2023). Consumers' paradoxical motives of co-creation: From self-service technology to crowd-sourcing platform. Technological Forecasting and Social Change, 197, 122934. https://doi.org/10.1016/j.techfore.2023.122934
    5. Wang, X., Wong, Y. D., Liu, F., & Yuen, K. F. * (2021). A push–pull–mooring view on technology-dependent shopping under social distancing: When technology needs meet health concerns. Technological Forecasting and Social Change, 173, 121109. https://doi.org/10.1016/j.techfore.2021.121109
    6. Yu, W., Dai, S. *, Liu, F., & Yang, Y. (2022). Matching disruptive innovation paths with entrepreneurial networks: a new perspective on startups’ growth with Chinese evidence. Asian Business & Management, 22, 878–902. https://doi.org/10.1057/s41291-022-00177-3
    7. 余维臻,陈立峰 & 刘锋. (2020). 后发情境下创业企业如何成为“独角兽”——颠覆性创新视角的探索性案例研究. 科学学研究, https://doi.org/10.16192/j.cnki.1003-2053.20200924.006

  • 感谢所有的合作者、所有的学生们！

    Research is a lot like love, and the commitment to be a researcher is a lot like saying “I do”.

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