PhD Course - AI & Business Research

Part I. Application and Methods

• AI Application in Empirical Research. (Timoshenko & Hauser, Mkt Sc 2019, Puranam, Kadiyali & Narayan, Mkt Sc 2021, Troncoso & Luo, Mkt Sc 2022)

• Econometric Challenges when using AI. [Hands-On Exercise] (Chen, Hong & Tamer 2005, Yang, Adomavicius & Burtch, ISR 2018, Qiao & Huang, ISR 2021)

• AI Methods for Business Applications (Liu, Mkt Sc 2023, Wang, Tao & Zhang, Mkt Sc 2025, Ye, Yoganarasimhan & Zheng, Mkt Sc 2025)

Part II. Agentic AI

• Design "Consumer" Agents for synthetic market research [Hands-On Exercise]

  • Resources: 1000 Agents for simulated consumers

• Design "Platform" Agent (RAG+LLM) for shopping. [Hands-On Exercise]

  • Resources: Open AI SDK, Agentic AI UC Berkeley course and paper Repository, WebShop for simulated shopping environment.

  • Analytical Work on Platform Strategy (Dukes & Liu, MS 2015, Hagiu & Wright, M 2024 and others)

• Design "Brand" Agent (Workflow) for setting prices and advertisement under competition [Hands-On Exercise]

  • Resources: LangChain and Flowise for Agent Workflows.

  • Analytical Work on Firm and Advertiser Strategy (Iyer, Soberman & Villas-Boas, Mkt Sc 2005 and others)

Thanks to many experts who helped in coming up with the course content: Pushpendre Rastogi (VizOps, ex-Google Deep Mind) on all things Agentic AI, Yuyan Wang (Stanford) on Methodological work at the intersection of AI and Marketing, Behnam Mohammadi (UT-Dallas) on synthetic market research, Kathleen Li (UT-Austin) on econometrics and Emaad Manzoor (Cornell) on Human-AI literature.

Special Thanks to course TA Liying Qiu (CMU) for exercise design and across the board expertise.