Hailiang Chen
Prof. Hailiang CHEN
创新及资讯管理学
Assistant Dean (Taught Postgraduate)
Professor in Innovation and Information Management

3917 0016

KK 840

Academic & Professional Qualification
  • PhD, Purdue University
  • MS, Purdue University
  • BM, Tsinghua University
Biography

Hailiang Chen is interested in the research areas of social media, fintech, artificial intelligence, business analytics, venture capital, entrepreneurship, mobile and social commerce, economics of information systems, and design science. His research has been published in elite business journals in information systems, finance, and management, including Information Systems Research (ISR), Journal of Financial Economics (JFE), Journal of Management Information Systems (JMIS), Management Science (MS), Review of Financial Studies (RFS), and Strategic Management Journal (SMJ). His research received media coverage in outlets such as Wall Street Journal, Forbes, New York Times, Reuters, Seeking Alpha, TechSpot, and so on.

Teaching
  • Business Analytics
  • Social Media
  • FinTech
  • Capstone Project
Selected Publications
  • Yu, Yinan, Liangfei Qiu, Hailiang Chen, Benjamin P. C. Yen. 2023. Movie Fit Uncertainty and Interplay between Traditional Advertising and Social Media Marketing. Marketing Letters 34(3) 429–448.
  • Xu, Ruiyun Rayna, Hailiang Chen, J. Leon Zhao. 2023. SocioLink: Leveraging Relational Information in Knowledge Graphs for Startup Recommendations. Journal of Management Information Systems 40(2) 655-682.
  • Chen, Hailiang, Yifan Dou, Yongbo Xiao. 2023. Understanding the Role of Live Streamers in Live-Streaming E-Commerce. Electronic Commerce Research and Applications 59, 101266.
  • Chen, Hailiang, Byoung-Hyoun Hwang. 2022. Listening in on Investors’ Thoughts and Conversations. Journal of Financial Economics 145(2) 426-444.
  • Yu, Yinan, Hailiang Chen, Chih-Hung Peng, Patrick Y.K. Chau. 2022. The Causal Effect of Subscription Video Streaming on DVD Sales: Evidence from a Natural Experiment. Decision Support Systems 157, 113767.
  • Clarke, Jonathan, Hailiang Chen, Ding Du, Yu Jeffrey Hu. 2021. Fake News, Investor Attention, and Market Reaction. Information Systems Research 32(1) 35-52.
  • Xie, Peng, Hailiang Chen, Yu Jeffrey Hu. 2020. Signal or Noise in Social Media Discussions: The Role of Network Cohesion in Predicting the Bitcoin Market. Journal of Management Information Systems 37(4) 933-956.
  • Chen, Hailiang, Yu Jeffrey Hu, Shan Huang. 2019. Monetary Incentive and Stock Opinions on Social Media. Journal of Management Information Systems 36(2) 391-417.
  • Chen, Hailiang, Yu Jeffrey Hu, Michael D. Smith. 2019. The Impact of E-book Distribution on Print Sales: Analysis of a Natural Experiment. Management Science 65(1) 19-31.
  • Akcura, Tolga, Kemal Altinkemer, Hailiang Chen. 2018. Noninfluentials and Information Dissemination in the Microblogging Community. Information Technology and Management 19(2) 89-106.
  • Lee, Joon Mahn, Byoung-Hyoun Hwang, Hailiang Chen. 2017. Are Founder CEOs more Overconfident than Professional CEOs? Evidence from S&P 1500 Companies. Strategic Management Journal 38(3) 751-769.
  • Chen, Hailiang, Prabuddha De, Yu Jeffrey Hu. 2015. IT-Enabled Broadcasting in Social Media: An Empirical Study of Artists’ Activities and Music Sales. Information Systems Research 26(3) 513-531.
  • Chen, Hailiang, Prabuddha De, Yu Jeffrey Hu, Byoung-Hyoun Hwang. 2014. Wisdom of Crowds: The Value of Stock Opinions Transmitted Through Social Media. Review of Financial Studies 27(5) 1367-1403.
  • Chen, Hailiang, Hongyan Liu, Jiawei Han, Xiaoxin Yin, Jun He. 2009. Exploring Optimization of Semantic Relationship Graph for Multi-relational Bayesian Classification. Decision Support Systems 48(1) 112-121.
Awards and Honours
  • Faculty Outstanding Researcher Award, Faculty of Business and Economics, The University of Hong Kong, 2022-23
  • INFORMS Information System Society (ISS) Sandra A. Slaughter Early Career Award, 2022
  • General Research Fund, Research Grants Council of Hong Kong, five consecutive years (2019, 2020, 2021, 2022, and 2023)
  • Essential Science Indicators’ (ESI) Highly Cited Paper (Top 1% in the field of Social Sciences, General), 2021
  • Association for Information Systems (AIS) Early Career Award, 2019
  • Essential Science Indicators’ (ESI) Highly Cited Paper (Top 1% in the field of Economics & Business), 2014
Service to the University / Community
  • Program Director, Master of Science in Business Analytics, HKU Business School, 2020-2023
  • Program Chair, International Conference on Smart Finance (ICSF), 2021 and 2022
  • Associate Editor, Journal of Management Information Systems (JMIS), Special Issue on Fake News, 2020
  • Associate Editor, MIS Quarterly, Special Issue on Managing AI, 2019
  • Associate Editor, Information Systems Research, Special Issue on FinTech, 2018
Recent Publications
倾听投资者的想法与对话

神经科学和社会心理学的大量文献指出,人类天生对别人如何看待自己很在意。在本文中,我们提出投资者的印象管理策略最终亦可以主导他们以口碑相传方式所传递的内容,并可能不经意间造成噪声的传播。我们分析来自美国最大的投资相关网站之一的伺服器日志档数据,发现结果与我们的见解一致,即投资者会更积极地分享适用于印象管理的文章,即使这些文章不太准确地预测回报。其他分析亦指出,高层次的此类分享会导致定价过高。

「客流计租」,汇纳科技与实体商业数字化转型新法则

汇纳科技正在为整个实体商业构建一个新的基础坐标系。 对商业地产来说,数字化转型早已是大势所趋且探索已久,而今年的疫情黑天鹅更使这一进程加快了。 一直以来,数字化转型最大的难度就是思想意识上的改变,疫情改变了这一现状。数字化好处在于,企业在面临疫情影响的时候,业务波动性会比较低。 疫情期间对居民外出的限制,为实体渠道带来严重冲击。如果说此前的数字化转型对商业地产来说是锦上添花,那如今已是迫在眉睫。商业地产开始思索这场危机给行业带来的改变。

社交媒体讨论中的信号或噪音:网络凝聚力在预测比特币市场中的作用

早期研究显示,社交媒体上的讨论有助于预测金融市场的价格走势。随着社交媒体数据量的不断增加,如何有效地从海量的杂讯中抽取有价值而相关的资料,是一门重要的课题。我们透过研究比特币市场,分析社交媒体的情绪与价格变化的关系以及网络凝聚力在此关系中所起的作用。由于网络凝聚力与讨论网络内的信息相关性相关,我们假设相对凝聚力较高的网络,凝聚力较低的社交媒体讨论网络更能准确预测翌日的回报。我们使用从Bitcointalk.org收集到的数据,以回归分析及模拟交易的方法,印证了我们的假设。透过分析社交媒体在金融市场所扮演的角色,我们的研究丰富了相关的文献,亦为根据社交媒体的信号作交易的投资者提供实用的见解。

The Impact of E-book Distribution on Print Sales: Analysis of a Natural Experiment

Digital distribution introduces many new strategic questions for the creative industries—notably, how the use of new digital channels will impact sales in established channels. We analyze this question in the context of e-book and hardcover sales by exploiting a natural experiment that exogenously delayed the release of a publisher’s new Kindle e-books in April and May 2010. Using new books released simultaneously in e-book and print formats in March and June 2010 as the control group, we find that delaying e-book availability results in a 43.8% decrease in e-book sales but no increase in print book sales on Amazon.com or among other online or offline retailers. We also find that the decrease in e-book sales is greater for books with less prerelease buzz. Together, we find no evidence of strong cannibalization between print books and e-books in the short term and no support for the sequential distribution of books in print versions followed by e-book versions.