中文
LI Xiong
Non-tenured Associate Professor
Department of Business Administration
Discipline: Accounting
Email:xliev@ustc.edu.cn
Joined University of Science and Technology of China in 2025

Academic & Professional Qualifications

  • PhD in Accounting, University of Hong Kong

  • Personal website:   https://alexli-xiong.github.io/

    • Biography

    • Dr. Li's research focuses on how financial reporting affects the supply and demand of trade credit, as well as the macroeconomic implications of trade credit networks. Dr. Li completed his undergraduate education in mainland China and his graduate studies in Hong Kong, China. Before pursuing his accounting degree, he was a graduate student in physical chemistry.


    • Research Interest

    • Supply Chain Finance, Disclosure and Reporting, Product Market, and Private Firms


    • Selected Working Papers 

    • ***Supply Chain Finance***

    • 1) Are Private Firms Disadvantaged vis-à-vis Public Firms in the Trade Credit Market? (solo-authored)

    • 2) Taxes and Non-debt Financing: Evidence from Trade Credit  (with Travis Chow)

    • 3)Does CEO Trust Substitute for Trade Credit as an Implicit Product Quality Warranty? (with Kayla Freeman, Yi Liu, Gerald Lobo, and Xingqiang Yin)

    • 4) Unraveling the Pooling Equilibrium: How the Introduction of ASC 842 Triggers a Reallocation of Trade Credit? (with Travis Chow, Doyeon Kim, and Guochang Zhang)


    • ***Supply Chain Risk, Debt Contracting, etc.***

    • 5) Proprietary Costs and Supply Chain Collaboration (with Wenzhi Ding, and Guochang Zhang)

    • 6) CEO Cultural Heritage and Buyer-Supplier Disruption (with Yangyang Chen, Cuili Qian)

    • 7) Filling the Monitoring Void: Lead Arranger Distraction and Borrower Disclosure (with Wenxuan Fu, Derrald Stice, and Christopher Williams)


Research Assistant Opportunity

I am seeking a full-time research assistant. This role provides hands-on experience across multiple stages of the research process, with a particular focus on data work—including collection, cleaning, organization, and empirical analysis.

Preferred qualifications:

  • Strong proficiency in data analysis software (e.g., Stata, Python, or similar tools).

  • Background or demonstrated interest in machine learning is an advantage.

Applicants are encouraged to include a sample of their code when applying.





<Updated 2025.09.23>