信息管理与商业智能系学术讲座

时间：7月4日 13:00-14:30

地点：李达三楼104室（线下）；腾讯会议室908560841/密码123456（线上）

题目：An Integrated Perspective of External and Internal IT Governance: Examining IT-Related Analyst Challenges in Earnings Conference Calls

报告人：Ling Xue, Terry Alumni Board Distinguished Associate Professor ，Department of Management Information Systems,Terry College of Business,University of Georgia

主持人：信息管理与商业智能系张诚教授

摘要：

This paper develops an integrated information technology (IT) governance perspective to consider how IT governance is fulfilled by the joint efforts of both the internal (i.e., corporate executives) and external governance participants (e.g., financial analysts). We focus on the interactions between the internal and external governance participants during firms’ earnings conference calls, in which analysts raise IT-related questions to challenge firms’ IT decisions. We examine how analysts’ IT-related challenges drive executives to improve the transparency of IT strengths and enhance subsequent IT initiatives. We adopt a neural network dependency parsing approach to examine how executives express IT-related information in response to analyst challenges. Using a large sample of US public firms, we find that analysts’ IT-related challenges impel executives, especially those with superior IT competence, to respond with more information about IT strengths. Following analysts’ IT-related challenges, firms with superior executive IT competence launched IT initiatives that were associated with increased stock returns, suggesting that analysts’ challenges drive firms with advantageous internal IT governance capabilities to undertake more promising IT initiatives. Overall, our findings reveal how the interactions between the external IT governance participants and the internal IT governance participants help fulfill effective IT governance.

时间：7月4日 14:30-16:00

地点：李达三楼104室（线下）；腾讯会议室908560841/密码123456（线上）

题目：Use-inspired AI and Computational Design Science Research in Information Systems

演讲人：方晓博士University of Delaware

主持人：信息管理与商业智能系张诚教授

演讲者介绍：

Xiao Fang (方晓) is Tenured Associate Professor of MIS and JPMorgan Chase Fellow at the Lerner College of Business & Economics and Institute for Financial Services Analytics, University of Delaware. He is also affiliated with Departments of Computer Science and Electrical Engineering, University of Delaware. He studies business and social network analytics with research methods and tools drawn from reference disciplines including Management Science (e.g., Optimization) and Computer Science (e.g., Data Mining and Machine Learning). He has published in business journals including Management Science, Operations Research, MIS Quarterly, and Information Systems Research as well as computer science outlets such as ACM Transactions on Information Systems and IEEE Transactions on Knowledge and Data Engineering. Professor Fang currently serves as Associate Editor for MIS Quarterly and Decisions Sciences. He is the founding chair of the INFORMS Workshop on Data Science. Professor Fang is active in advising doctoral students. Doctoral students under his supervision have taken tenure-track positions at first-tier business schools in North America.

摘要：

The US National Science Foundation (NSF) classifies AI research into two categories: fundamental AI research and use-inspired AI research. The former aims to develop theory and methods that are independent of any particular domain of application whereas the latter seeks new methods and understanding in AI by situating the research in a domain of application to simultaneously inform progress in AI and solve particular use cases. NSF emphasizes that use-inspired AI is not applied AI because it develops novel AI algorithms and methods inspired by important business, societal, scientific, and engineering problems. Positioned at the intersection of technology and business, researchers in the field of Information Systems (IS) are well-suited to carry out use-inspired AI research. In particular, computational design science research, which is concerned with solving business and societal problems by developing novel computational algorithms and methods, is use-inspired AI research in the IS field. In this talk, I will discuss what computational design science research is and why it is unique (especially in comparison to machine learning research in the field of Computer Science). I will also illustrate computational design science research with an example.