Zhi Chen
Assistant Professor, NUS Business School
Assistant Professor, Department of Analytics and Operations, NUS Business School, National University of Singapore, July 2020 - now
Ph.D. in Management (Decision Sciences), INSEAD, 2014-2020.
B.E. (1st Class Hons), Industrial and Systems Engineering, National University of Singapore, 2009-2013.
Overseas exchange at Industrial and Systems Engineering (ISyE), Georgia Institute of Technology, Spring 2012.
Research internship at École Polytechnique, Palaiseau, France, May-Aug 2012.
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.
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.
Combining Forecasts from Multiple Experts for Multiple Variables (with Long Zhao), Management Science, 2025, forthcoming.
Sourcing Innovation: When to Own and When to Control Your Supplier (with Jürgen Mihm and Jochen Schlapp), Manufacturing & Service Operations Management, 2025, forthcoming.
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.
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.