Zhi Chen

Employment

Assistant Professor, Department of Analytics and Operations, NUS Business School, National University of Singapore, July 2020 - now

Education

Ph.D. in Management (Decision Sciences), INSEAD, 2014-2020.

B.E. (1st Class Hons), Industrial and Systems Engineering, National University of Singapore, 2009-2013.

Research Interests

Innovation Sourcing, AI Development, Wisdom of Crowds

My research aims to tackle operational challenges in innovation-driven value chains.

• The first stream of work is concerned with issues in the R&D phase of new products. Specifically, I study how firms can best design the supplier base and informational policies to procure innovation from suppliers. Recently, I am also interested in understanding the impact of policies and regulations on the development of new AI-based products such as autonomous vehicles.  

• The second stream focuses on demand forecasting for new products. Due to the lack of historical data, companies rely on insights from diverse experts for their forecasts. I study how to aggregate these forecasts into a consensus (known as "Wisdom of Crowds") as well as quantify the underlying uncertainty through the obtained forecasts.

Published Papers

• Assessing Uncertainty from Point Forecasts (with Anil Gaba and Dana Popescu), Management Science, 2019, 65(1), 90—106.

• Sourcing Innovation: Integrated System or Individual Components? (with Jürgen Mihm and Jochen Schlapp), Manufacturing & Service Operations Management, 2022, 24(2), 1056--1073.

• The M5 Uncertainty competition: Results, findings and conclusions (with Spyros Makridakis, Evangelos Spiliotis, Vassilios Assimakopoulos, Anil Gaba, Ilia Tsetlin and Robert L Winkler), International Journal of Forecasting, 2022, 38(4), 1365-1385.

• Evaluating Quantile Forecasts in the M5 Uncertainty Competition (with Anil Gaba, Ilia Tsetlin and Robert L Winkler), International Journal of Forecasting, 2022, 38(4), 1531-1545.

• R&D Data Sharing in New Product Development (with Jussi Keppo), Manufacturing & Service Operations Management, 2025, 27(4), 1275–1294.

• Sourcing Innovation: When to Own and When to Control Your Supplier (with Jürgen Mihm and Jochen Schlapp), Manufacturing & Service Operations Management, 2025, 27(6), 1869-1888.

• Combining Forecasts from Multiple Experts for Multiple Variables (with Long Zhao), Management Science, 2025, forthcoming.

Working Papers

• Learning By Failing: The (Unintended) Consequence of Test Reporting on Autonomous Vehicle Training (with Wenjie Xue), Working Paper, 2023.

• Constructing Quantiles via Forecast Errors: Theory and Empirical Evidence (with Long Zhao), Working Paper, 2024.

• Sequential vs Parallel Search under Competition (with Zhenyu Hu and Yufei Zhu), Working Paper, 2025.

Teaching Experiences

Managerial Operations and Analytics (MBA Core Course), NUS Business School

•  Summer 2021, Fall 2022. Fall 2024

Decision Analytics Using Spreadsheets (Undergraduate Core Course), NUS Business School

•  Spring 2022, Fall 2023

Uncertainty, Data and Judgment (MBA Core Course) Tutorials, INSEAD

• Spring 2016, Spring 2017, Spring 2018, Spring 2019, Spring 2020.

Production and Operations Management (MBA Core Course) Tutorials, INSEAD

• Fall 2017.