Mr Jason Xianghua Wu

Mr Jason Xianghua Wu

Senior Lecturer
Business School
School of Information Systems and Technology Management

Dr. Jason Xianghua Wu is a Lecturer (a.k.a Assistant Professor) at the School of Information Systems and Technology Management (ISTM), UNSW Business School. Jason received his Ph.D. degree in Management Science from University of Texas at Arlington. He got his master degree in Economics in Zhejiang University and his Bachelor in information and computing science. Jason is enthusiastic about exploring human's behavior and psychology under different technology and business settings, using interdiscinplinary methodologies. His research interests lie at the intersections of behavioral operations, business analytics and information systems, with a focus on artificial intelligence (AI), online auctions, and other emerging technologies and economies.

+61 2 9065 2344
School of Information Systems and Technology Management, UNSW Business School, Room 2117, Level 2, West Wing, Quadrangle Building (E15), UNSW SYDNEY 2052.
  • Journal articles | 2023
    Wu JX; Wu Y; Chen KY; Hua L, 2023, 'Building Socially Intelligent AI Systems: Evidence from the Trust Game Using Artificial Agents with Deep Learning', Management Science, 69, pp. 7236 - 7252,

Wu, J. X., Wu, Y., Chen, K. Y., & Hua, L. (2023). Building Socially Intelligent AI Systems: Evidence from the Trust Game Using Artificial Agents with Deep Learning. Management Science. Fast Track Paper,

Multi-dimensional Procurement Auction with Loss Averse Workers in Online Labor Markets (Under Revision). Joint with Shan Li, and Kay Yut Chen.

Building Socially Responsible AI Systems: A Study of Emergent Social Biases and Mitigation in Deep-Reinforcement-Learning-Based Agents. Under Review, Submitting. Joint with Diana Wu, Kay Yut Chen, Jennifer Zhang, and Jeff Hou. 

Bargaining on Supply Chain Contract in a Two-sided Network: An Experimental Investigation. Working Paper, Submitting, Joint with Lei Hua, Alper Nakkas, Kay-Yut Chen.

How Fairness Spillover into Altruism? --Evidence from LLM and Deep Reinforcement Learning AI Agents. Working in Progress. Joint with Kay-Yut Chen, Diana Wu, Jennifer Zhang, and Jeff Hou. 

Detecting Payoff Abnormality by Human-AI Collaborations. Working in Progress, Joint with Feiteng Huang and Meng Li. 

AI Collusive Bidding in Repeated Reverse Auctions. Working in Progress, Joint with Jingyi Tian and Meng Li. 

Designing Online Labor Markets with Planning Fallacy. Working in Progress, Joint with Meng Li and Kevin Hong. 











My Teaching

My teaching philosophy is “to be an inspirer, helper, and learner”.  

1) To be an inspirer. Interest is the best teacher. I believe the starting point of teaching is to inspire the students’ interest in the subject and thus engage them in an active and independent learning process.

2) To be a helper. Teaching is a meaningful activity to help the students succeed in their academic journey.  I enjoy helping students to overcome difficulties and achieve their goals.

3) To be a learner. Being a good learner is a prerequisite for being a good teacher. I learn and accumulate real examples and relevant stories through teaching. This can in turn help me inspire the student and illustrate the concepts and definitions in a more clear and intuitive way. More importantly, as modern technology develops rapidly, it is crucial to keep learning new things to effectively deliver courses in emerging technologies and economies.