• 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（个人主页：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年毕业于韩国高丽大学商学院，获管理学博士学位。主要研究方向为供应链管理与人工智能的交叉融合，重点关注数智化运营与供应链管理前沿问题，熟练掌握机器学习、深度学习与多模态数据融合等方法。在相关研究中，围绕供应链集中度、供应链透明度及企业数字化转型等议题开展系统性探索，拓展并丰富了供应链管理理论体系，并推动人工智能在工商管理学科中的方法论应用。

    截至目前，已在 Journal of Management Information Systems、Journal of Business Ethics、International Journal of Production Economics、Decision Support Systems、Technological Forecasting and Social Change、Annals of Operations Research、China Economic Review、Expert Systems with Applications 及《科学学研究》等 SCI/SSCI/CSSCI 来源期刊发表论文 50 余篇，Google Scholar 引用 3400 余次。相关成果获山东省第三十七届社会科学优秀成果奖三等奖。主持国家自然科学基金青年项目 1 项、教育部人文社会科学青年项目 1 项，长期服务国家数字经济与人工智能发展战略需求，致力于推动“AI+管理”的交叉融合研究。现担任 Small Business Economics（SSCI）、Humanities & Social Sciences Communications（SSCI）等期刊编委，并担任 Data Science and Management 青年编委。

    招生与研究方向说明：目前团队科研经费充足、研究基础扎实、代码与数据积累丰富，具备良好的科研训练与创新支撑条件。

    欢迎有志于从事学术研究的同学报考山东大学商学院企业管理学术博士/硕士、工业工程与管理专业硕士。重点招收对以下方向感兴趣的学生：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等交叉领域。

    Feng Liu (liufeng@sdu.edu.cn; https://www.fengliu.net/) is an Associate Professor at the Business School, Shandong University, Weihai, China. He leads the Star-lights Research Team as Principal Investigator. Dr. Liu earned his Ph.D. in Logistics, Service & Operations Management from Korea University Business School. His research centers on operations and supply chain management, information systems, and the integration of artificial intelligence—especially machine learning and deep learning. He serves on the editorial boards of Small Business Economics, Humanities & Social Sciences Communications, and Information Resources Management Journal. His work has appeared in leading journals including Journal of Management Information Systems, Journal of Business Ethics, International Journal of Production Economics, Decision Support Systems, and Technological Forecasting and Social Change.

  • Team Overview 团队介绍

    科研追光，星耀山大！

    Star-lights Research Team

    星耀科研小组

    刘锋老师2021年创建“星耀科研小组”，聚焦人工智能与经济管理的交叉前沿领域，面向本科生开展系统化科研训练与学术能力培养，致力于帮助学生突破科研入门瓶颈，走向国际学术舞台。在长期指导实践中，已累计培养本科生以第一作者身份发表包括 FT50 期刊在内的 SCI/SSCI 高水平论文 15 篇，实现了从科研“入门者”到“学术新秀”的跨越式成长。在导师的悉心指导下，小组成员卢灿同学从科研新手逐步成长为能够独立开展研究的科研骨干，并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，体现了小组系统化培养体系的显著成效。

    目前，“星耀科研小组”已成功运行 9 期，形成了勤学善思、互助共进、追求卓越的优良学术生态。参与学生在科研训练中不断提升问题意识与研究能力，实现了以研促学、以研促长的良性循环。多位成员凭借扎实的科研成果与学术能力，获得包括北京大学在内的国内外知名高校深造机会，在学术发展道路上迈出坚实步伐。

    小组前期成员已系统掌握机器学习、深度学习、图像分析、文本分析及多模态融合等核心研究方法，形成了良好的技术积累与传承机制。团队始终秉持“互助共进、薪火相传”的理念，通过“以老带新”的培养模式，不仅传授科研方法与技术工具，更注重学术规范与科学精神的塑造，推动成员实现全面成长。

    第 10 期科研项目即将启动，本期重点围绕三大研究方向展开：

    • 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

    唯有步履不停，方能抵达更辽阔的学术天地；
    唯    有锐意进取，方能书写属于青春的科研华章。

    愿我们并肩同行，在探索未知的道路上不断突破边界；也期待每一位加入者于科研实践中锤炼能力、实现成长，共同产出更多高质量学术成果，走向更高水平的学术舞台。

    我们诚挚欢迎具备以下特质的同学加入：具备坚持不懈的学习毅力、诚实守信的学术品格、认真严谨的科研态度，并对学术研究充满热情与探索精神。请准备个人简历与初步研究想法，发送至邮箱：liufeng@sdu.edu.cn，期待与你共同开启科研之旅。

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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. (2025) Mitigating bullwhip effect in supply chains by engaging in digital transformation: the moderating role of customer concentration. Annals of Operations Research, 344, 825–846. https://doi.org/10.1007/s10479-024-05908-7
    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.* (2024). Is inventory performance helping to improve SME credit ratings? The moderating role of supply chain concentration. Applied Economics Letters, 31(10), 880-884. https://doi.org/10.1080/13504851.2022.2156455
    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, 30(4), 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. * (2026). Who is acting unethically? The role of board diversity in corporate social responsibility decoupling. Corporate Social Responsibility and Environmental Management, 33(1), 169-188. 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. * (2026). Green innovation along the dyadic relationship: the moderating role of supply chain dependence. The International Journal of Logistics Management, 37(2), 340-367. https://doi.org/10.1108/IJLM-02-2025-0068 (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., Chen, Y., Ho, Y. C. (Chad), Dasgupta, S., & Fang, M. *.(2026). Machine Learning Analysis of Emotional Appeals in Charity Crowdfunding. Journal of Management Information Systems, 43(2), 621–653. https://doi.org/10.1080/07421222.2026.2647463 (星耀科研小组成果）
    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 星耀科研小组成果）
    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, 45(5), 2739–2750. 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, 35, 110. https://doi.org/10.1007/s12525-025-00849-w (星耀科研小组成果）
    18. Chen, Y., Sun, R., & Liu, F. * (2026). Decoding good bots in online communities: How textual sentiment and paralanguage drive positive social interactions. Journal of Electronic Commerce Research, 27(2). http://ojs.jecr.org/jecr/sites/default/files/2026vol27no2_Paper2.pdf (星耀科研小组成果）
    19. 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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