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.
Faculty
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 Science, Organization Science, Strategic Management Journal, Strategy Science, Journal of Operations Management, International 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.
Rahmandad, Hazhir, and Michael Shayne Gary. Organization Science. Forthcoming. Download Paper. Supplemental Materials.
Xu, Ran, Hazhir Rahmandad, Marichi Gupta, Catherine DiGennaro, Navid Ghaffarzadegan, Heresh Amini, and Mohammad S. Jalali. The Lancet: Planetary Health Vol. 5, No. 10 (2021): E671-E680.
Jalali, Mohammad S., Catherine DiGennaro, Abby Guitar, Karen Lew, and Hazhir Rahmandad. Epidemiological Reviews. Forthcoming.
Erin L. Kelly, Hazhir Rahmandad, Nathan Wilmers, and Aishwarya Yadama. Washington, DC: June 2022.
Rahmandad, Hazir, Ran Xu, and Navid Ghaffarzadegan. PLoS Computational Biology Vol. 18, No. 5 (2022): 1-15.
Hashemian, Mahdi, Zeynep Ton, and Hazhir Rahmandad, MIT Sloan Working Paper 6056-19. Cambridge, MA: MIT Sloan School of Management, September 2021.
This counter-intuitive result emerges because countries actually have little choice in how much they must reduce contact levels to control the epidemic.
Two studies by Prof. Hazhir Rahmandad, Prof. John Sterman, and PhD student Tse Yang Lim find that this apparent tradeoff is a false one.
A new paper by Prof. Rahmandad and co-authors details the application of relatively simple, nuanced variables to enhance modeling capabilities.
"The tradeoff framing really hurt the response. That framing was wrong from the beginning.”
"...even in low-cost service settings, paying higher wages and treating workers with respect and dignity can be profit-maximizing."
An MIT team suggests that global infections were 12 times higher and deaths 50% higher than officially reported.
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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.