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Natalie Epstein

Natalie Epstein

Doctoral Student

Doctoral Student

Natalie Epstein is a PhD Candidate in Technology and Operations Management at Harvard Business School. Her research focuses on service design strategies for on-demand operations. As the service industry accelerates, she is particularly interested in operations where speed is essential. While the literature has primarily focused on delivering service, she employs empirical methods and fosters collaborations with companies to focus on the design of such service, studying elements such as communication channels, locations, payments, and incentives, which are crucial in the field. She has explored this in the context of last-mile and on-demand delivery services.

Before starting her PhD, Natalie worked as a Business Analyst at McKinsey & Company and as a Research Associate at Universidad de Chile. She received a B.S. in Industrial Engineering and an M.S. in Operations Management from Universidad de Chile.

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Natalie Epstein is a PhD Candidate in Technology and Operations Management at Harvard Business School. Her research focuses on service design strategies for on-demand operations. As the service industry accelerates, she is particularly interested in operations where speed is essential. While the literature has primarily focused on delivering service, she employs empirical methods and fosters collaborations with companies to focus on the design of such service, studying elements such as communication channels, locations, payments, and incentives, which are crucial in the field. She has explored this in the context of last-mile and on-demand delivery services.

Before starting her PhD, Natalie worked as a Business Analyst at McKinsey & Company and as a Research Associate at Universidad de Chile. She received a B.S. in Industrial Engineering and an M.S. in Operations Management from Universidad de Chile.

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Natalie Epstein
Contact Information
Publications

Journal Articles
Journal Articles

  • Correa, Jose, Natalie Epstein, Rafael Epstein, Juan Escobar, Ignacio Rios, Nicolas Aramayo, Bastian Bahamondes, Carlos Bonet, Martin Castillo, Andres Cristi, Boris Epstein, and Felipe Subiabre. "School Choice in Chile." Operations Research 70, no. 2 (March–April 2022): 1066–1087. View Details
  • Escobar, Juan, Rafael Epstein, Jose Correa, Pamela Gidi, Jozsef Markovits, Natalie Epstein, Yerko Montenegro, and Abner Turkieltaub. "The 5G Spectrum Auction in Chile." Art. 102580. Telecommunications Policy 47, no. 7 (August 2023). View Details

Working Papers
Working Papers

  • Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "The Operational Impact of Customer Location in On-Demand Services." Working Paper, September 2024. View Details
  • Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "Operational Impact of Communication Channels: Evidence from Last-Mile Delivery Services." Working Paper, August 2024. View Details
  • Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, December 2021. View Details

Cases and Teaching Materials
Cases and Teaching Materials

  • Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021. (Click here to access this tutorial.) View Details
  • Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021. View Details
  • Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.) View Details
All Publications

Natalie Epstein is a PhD Candidate in Technology and Operations Management at Harvard Business School. Her research focuses on service design strategies for on-demand operations. As the service industry accelerates, she is particularly interested in operations where speed is essential. While the literature has primarily focused on delivering service, she employs empirical methods and fosters collaborations with companies to focus on the design of such service, studying elements such as communication channels, locations, payments, and incentives, which are crucial in the field. She has explored this in the context of last-mile and on-demand delivery services.

Before starting her PhD, Natalie worked as a Business Analyst at McKinsey & Company and as a Research Associate at Universidad de Chile. She received a B.S. in Industrial Engineering and an M.S. in Operations Management from Universidad de Chile.

Journal Articles
  • Correa, Jose, Natalie Epstein, Rafael Epstein, Juan Escobar, Ignacio Rios, Nicolas Aramayo, Bastian Bahamondes, Carlos Bonet, Martin Castillo, Andres Cristi, Boris Epstein, and Felipe Subiabre. "School Choice in Chile." Operations Research 70, no. 2 (March–April 2022): 1066–1087. View Details
  • Escobar, Juan, Rafael Epstein, Jose Correa, Pamela Gidi, Jozsef Markovits, Natalie Epstein, Yerko Montenegro, and Abner Turkieltaub. "The 5G Spectrum Auction in Chile." Art. 102580. Telecommunications Policy 47, no. 7 (August 2023). View Details
Working Papers
  • Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "The Operational Impact of Customer Location in On-Demand Services." Working Paper, September 2024. View Details
  • Epstein, Natalie, Santiago Gallino, and Antonio Moreno. "Operational Impact of Communication Channels: Evidence from Last-Mile Delivery Services." Working Paper, August 2024. View Details
  • Balakrishnan, M., MoonSoo Choi, and Natalie Epstein. "An Empirical Study of Time Allotment and Delays in E-commerce Delivery." Working Paper, December 2021. View Details
Cases and Teaching Materials
  • Toffel, Michael, and Natalie Epstein. Assessing Prediction Accuracy of Machine Learning Models. Harvard Business School Tutorial 621-706, February 2021. (Click here to access this tutorial.) View Details
  • Parzen, Michael, Natalie Epstein, Chiara Farronato, and Michael Toffel. T-tests: Theory and Practice. Harvard Business School Tutorial 621-707, February 2021. View Details
  • Toffel, Michael W., Natalie Epstein, Kris Ferreira, and Yael Grushka-Cockayne. "Assessing Prediction Accuracy of Machine Learning Models." Harvard Business School Technical Note 621-045, August 2020. (Revised September 2020.) View Details
Additional Information
  • Curriculum Vitae
  • Personal Website
  • Google Scholar
Area of Study
  • Technology and Operations Management
Areas of Interest
  • behavioral operations
  • digital economy
  • operations management
  • service operations
  • supply chain
Additional Information
Curriculum Vitae
Personal Website
Google Scholar

Area of Study

Technology and Operations Management

Areas of Interest

behavioral operations
digital economy
operations management
service operations
supply chain
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