Hazhir Rahmandad


Hazhir Rahmandad

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Hazhir Rahmandad is the Schussel Family Professor of Management Science and an Associate Professor of System Dynamics at the MIT Sloan School of Management.

Hazhir's research shows how complex organizational dynamics can lead to heterogeneity in organizational practices and outcomes. He has analyzed how organizations learn in the presence of delays between taking action and observing the results, and has shown through empirical data and simulations the resulting learning challenges. Hazhir's strategy research has explored the shape of organizational performance landscapes, capability development tradeoffs under competition, and erosion of organizational capabilities through adaptation traps. In another stream of work he has studied public health problems, including COVID-19, obesity and depression dynamics, and comparing different modeling methodologies in application to epidemics, among others. Hazhir also contributes to expanding the dynamic modeling toolbox through advancing parameter estimation and validation methods for dynamic models.

Hazhir has published in diverse journals including Management ScienceOrganization ScienceStrategic Management Journal, Strategy Science, Journal of Operations ManagementInternational Journal of Obesity, Lancet Planetary Health, and System Dynamics Review, among others. He has been a reviewer for over 30 NIH and NSF panels and over two dozen different journals, and his research has been funded by the National Science Foundation, National Institutes of Health, Department of Housing and Urban Development, and private sector firms.

Hazhir holds a BS in industrial engineering from Sharif University of Technology and a PhD in management with system dynamics concentration from MIT. Before joining MIT Sloan in 2015, Hazhir was an Associate Professor of Industrial and Systems Engineering at Virginia Tech.


Hazhir Rahmandad wins Jay Wright Forrester award


"Evolution and Reproducibility of Simulation Modeling in Epidemiology and Health Policy over Half a Century."

Jalali, Mohammad S., Catherine DiGennaro, Abby Guitar, Karen Lew, and Hazhir Rahmandad. Epidemiological Reviews. Forthcoming.

"Employer Practices and Worker Outcomes: A Landscape Report."

Erin L. Kelly, Hazhir Rahmandad, Nathan Wilmers, and Aishwarya Yadama. Washington, DC: June 2022.

"Enhancing Long-term Forecasting: Learning from COVID-19 Models."

Rahmandad, Hazir, Ran Xu, and Navid Ghaffarzadegan. PLoS Computational Biology Vol. 18, No. 5 (2022): 1-15.

"The Effect of Unstable Schedules on Unit and Employee Productivity."

Hashemian, Mahdi, Zeynep Ton, and Hazhir Rahmandad, MIT Sloan Working Paper 6056-19. Cambridge, MA: MIT Sloan School of Management, September 2021.

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Why there is no long-term tradeoff between lives and livelihoods in the pandemic

This counter-intuitive result emerges because countries actually have little choice in how much they must reduce contact levels to control the epidemic.

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No tradeoff between lives and livelihoods in the COVID-19 pandemic

Two studies by Prof. Hazhir Rahmandad, Prof. John Sterman, and PhD student Tse Yang Lim find that this apparent tradeoff is a false one.

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Global Executive Academy

This global executive program is a transformative learning experience designed to fit the time and language constraints of experienced executives from a wide variety of industries and countries. A new frontier in executive education, it extends MIT content to the non-English speaking world through a multilingual experience. Program topics include: general management, leadership, strategy, innovation, negotiation, analytics management, finance, and productivity.

  • Jul 12-21, 2022
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Business Dynamics

This systems thinking course provides an intensive, hands-on introduction to system dynamics, a unique framework for understanding and managing complex businesses and organizations. Participants are introduced to a variety of problem solving tools, including mapping techniques, simulation models, and MIT’s “management flight simulators” to help them understand the sources of persistent problems and how business decisions may result in complicated cause-and-effect loops.

  • Jun 12-16, 2023
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