Jan A. Van Mieghem

About

Jan A. Van Mieghem is the A. C. Buehler Professor and Professor of Operations at the Kellogg School of Management of Northwestern University. He received his Ph.D. in Business and MS in Electrical Engineering from Stanford University, and holds an electrical engineering degree from the University KU Leuven, Belgium. His research focuses on product, service, and supply chain operations, studying both strategy and execution. His methodologies include mathematical modeling, stochastic analysis, optimization, financial valuation, empirical estimation, and verification. Current research areas include the operations research of human interaction and collaboration, healthcare data-driven forecasting, and flexibility in dual sourcing. Van Mieghem teaches courses in operations management and operations strategy across MBA, Ph.D., and executive programs, and advises firms on these topics. He has authored over 50 academic articles published in leading international journals and has written two books on operations management and operations strategy. He has held various academic positions, including Deputy Dean since summer 2023, and has served as Director of the PhD program in operations and of non-degree executive programs. His professional experience includes consulting on global strategic sourcing and operations management for firms such as Moen, McKinsey & Company, and Career Builder. Van Mieghem is a distinguished fellow of the Manufacturing and Service Operations Management…

Research topics

• Computer Science
• Mathematics
• Economics
• Artificial Intelligence
• Operations management
• Operations research
• Marketing
• Mathematical optimization
• Finance
• Engineering

Selected publications

• Can Deep Reinforcement Learning Improve Inventory Management? Performance on Lost Sales, Dual-Sourcing, and Multi-Echelon Problems

  Manufacturing & Service Operations Management · 2022 · 171 citations

  Problem definition: Is deep reinforcement learning (DRL) effective at solving inventory problems? Academic/practical relevance: Given that DRL has successfully been applied in computer games and robotics, supply chain researchers and companies are interested in its potential in inventory management. We provide a rigorous performance evaluation of DRL in three classic and intractable inventory problems: lost sales, dual sourcing, and multi-echelon inventory management. Methodology: We model each…

  PublisherOA PDFDOI

• Predicting Human Discretion to Adjust Algorithmic Prescription: A Large-Scale Field Experiment in Warehouse Operations

  Management Science · 2021 · 150 citations

  Senior authorCorresponding

  Conventional optimization algorithms that prescribe order packing instructions (which items to pack in which sequence in which box) focus on box volume utilization yet tend to overlook human behavioral deviations. We observe that packing workers at the warehouses of the Alibaba Group deviate from algorithmic prescriptions for 5.8% of packages, and these deviations increase packing time and reduce operational efficiency. We posit two mechanisms and demonstrate that they result in two types of dev…

  PublisherDOI

• Dual Sourcing and Smoothing Under Nonstationary Demand Time Series: Reshoring with SpeedFactories

  Management Science · 2021 · 60 citations

  Senior authorCorresponding

  We investigate near-shoring a small part of the global production to local SpeedFactories that serve only the variable demand. The short lead time of the responsive SpeedFactory reduces the risk of making large volumes in advance, yet it does not involve a complete reshoring of demand. Using a break-even analysis, we investigate the lead time, demand, and cost characteristics that make dual sourcing with a SpeedFactory desirable compared with complete off-shoring. Our analysis uses a linear gene…

  PublisherOA PDFDOI

• Digital Lean Operations: Smart Automation and Artificial Intelligence in Financial Services

  Springer series in supply chain management · 2021-05-11 · 27 citations

  book-chapterSenior author
  PublisherDOI

• Volume Flexibility at Responsive Suppliers in Reshoring Decisions: Analysis of a Dual Sourcing Inventory Model

  Production and Operations Management · 2022-03-20 · 16 citations

  articleOpen accessSenior author

  We investigate how volume flexibility, defined by a sourcing cost premium beyond a base capacity, at a local responsive supplier impacts the decision to reshore supply. The buyer also has access to a remote supplier that is cheaper with no restrictions on volume flexibility. We show that with unit lead time difference between both suppliers, the optimal dual sourcing policy is a modified dual base‐stock policy with three base‐stock levels <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"…

  PublisherOA PDFDOI

Frequent coauthors

• Robert Boute

  47 shared

• Itai Gurvich

  Northwestern University

  30 shared

• Joren Gijsbrechts

  26 shared

• Stephen Michael Disney

  University of Exeter

  19 shared

• Daniel Diermeier

  Vanderbilt University

  14 shared

• Dennis Zhang

  Washington University in St. Louis

  11 shared

• Gad Allon

  University of Pennsylvania

  9 shared

• Lauren Xiaoyuan Lu

  8 shared

Labs

• OperationsPI

Education

• PhD, Graduate School of Business

  Stanford University

  1995

• MS, Electrical Engineering

  Stanford University

  1990

• Burgerlijk Ingenieur, Electrical Engineering

  KU Leuven

  1989

Awards & honors

• First MSOM Best Paper Award (2007)
• Wickham Skinner Award for Best Paper Published in POM (2014)
• NU Excellence in Research (2012)
• 2023 Student Paper Competition First Place, College of Suppl…
• 2020 Flexibility Excellence Award, Global Institute of Flexi…

Similar researchers at Northwestern University

• Dean Karlanh-97
• Mark Finnh-95
• Torben Gustav Andersenh-85