Simin Li

Hi, I’m an Assistant Professor of Management Science at the Freeman School of Business, Tulane University. My research focuses on multi-channel service delivery and information sharing in online platforms and healthcare settings. More recently, I have developed an interest in how generative AI tools disrupt or augment information exchange and acquisition on these platforms. To explore these questions, I collaborate closely with industry partners.

I received my Ph.D. in Operations Management from the Kellogg School, Northwestern University in 2020. Prior to graduate school, I worked as a data scientist at Microsoft. Email me at sli41 at tulane dot edu. My Tulane page. My CV.

Research

Published and accepted papers

  1. “Is Full Price the Full Story When Consumers Have Time and Budget Constraints” with Achal Bassamboo and Martin A. Lariviere. Manufacturing & Service Operations Management, 26(1), 370–388, (January – February 2024).
  2. “No Call, No Show: Impact of No-Shows on Customer Attrition in Online-to-Offline Services” with Nil Karacaoglu. Manufacturing & Service Operations Management, Accepted, 2026.
  3. “Proximity Matters: The Impact of Urgent Care Centers on Emergency Department Arrivals” with Achal Bassamboo and Martin A. Lariviere. Production and Operations Management, Accepted, 2026.

Working papers

  1. “When Free Is Not Enough: Layered Network Effects and Platform Competition” with Campbell Clarkson, Necati Tereyagoglu, and Sriram Venkataraman. Major Revision for Manufacturing & Service Operations Management, 2025. (Manuscript Available Upon Request)
  2. “Expedited Service Promises: Evidence From a Food Ordering Platform with Self-Pickup” with Nil Karacaoglu and Luyi Yang. Reject and Resubmit for Manufacturing & Service Operations Management, 2025. 
  3. “Promotional Design for Small Businesses: The Operational Value of Online Deals” with Kejia Hu and Martin A. Lariviere. Major Revision for Management Science, 2021.
    • Finalist, IBM Service Science Best Student Paper Competition, 2019.
  4. “Generative AI shifts technical knowledge production toward recombinant novelty” with Neha Sharma. Under review, 2026. [Knowledge at Wharton]
  5. “Disintermediation Evidence From a Cleaning Platform” with Nil Karacaoglu and Ioannis Stamatopoulos. Under revision, 2025.

Teaching

  1. MGSC 3010, Introduction to Business Analytics. (Tulane University, undergraduate, Sp21, Sp22, Fa22, Fa23, Fa24, Fa25)
    • Optimization, simulation, forecasting, regressions
    • Spreadsheet modeling
  2. MGSC 7000, Business Analytics Practicum. (Tulane University, graduate, Master of Business Analytics, Fa22, Fa23, Fa24, Fa25)
    • GenAI-augmented R coding (e.g., agentic requests via Amazon Q)
    • Text analytics powered by GenAI
    • Data cleaning, data visualization, descriptive analysis
    • Experiential learning via field trips to local analytic employers, industry colloquium

Professional Experience

  • Data Scientist, Operating System Group, Microsoft, Redmond, WA.
  • Decision Analytics Intern, EXL Services, New York, NY.
  • Market Research Intern, British American Tobacco, Singapore.