Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held on Friday, December 8^th from 12:30-2:00pm EST in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/98105285349 (Password: SDFA23). Our guest speaker will be Warren Farr (Informed Dynamic Solutions) presenting Document the Model! What about the Modeling Process? (see abstract and brief bio below, announcement and paper attached). Lunch will be provided to those attending in person and a reminder email will be sent out closer to the date.

If you would also like to schedule a 30-minute 1:1 meeting with him before or after the seminar, please fill out the following link by COB Friday, December 1^st and I will confirm times and location with a calendar invite: https://rallly.co/invite/CM6MpCN2rGWb. Please notify me if you need to meet over Zoom instead

Abstract:              Documenting the process of building a simulation model is different from documenting the simulation model itself. Good model-building practice includes the discovery of potentially large sets of multimedia data. Organizing and documenting data and the process of collecting it has several advantages including: tightly linking data to its source and the timing of its discovery; separating source data from researcher inference (allowing for independent inspection); maintaining an evolutionary timeline; and easily sharing source data among participants and researchers. The topic of documenting models has been widely discussed. In contrast, this article proposes a data structure and its methods for documenting the process of building a simulation model.

This talk will focus on the motivations for building DynamicVu, an online software for documenting the modeling process using the data structure proposed in the SDR paper. Participants will be asked to reflect on the pros and cons of documenting the modeling process leading to an interactive discussion about best practices for documenting the model and the modeling process. How can such practices be supported in future software tools?

Brief Bio:             Warren Farr holds an MS in System Dynamics from Worcester Polytechnic Institute and an MBA degree from Duke University. Warren is a seasoned business leader with over 35 years of experience. With a technical background, he focuses on how business opportunities change over time and the profitable use of technology. He has been using System Dynamics for the past 15 years to create succinct and engaging strategies that are successfully implemented. Warren is currently vice-chairman of Refrigeration Sales Corporation, a US regional distributor of heating, ventilating, air conditioning, and refrigeration equipment, parts, and supplies. He is also the president of Informed Dynamic Systems, where he creates database solutions and system dynamic simulation models and coaches others in the use of system dynamics. Warren has served on the Policy Council of the System Dynamics Society and is currently a member of its Stewardship Committee.

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held on Friday, November 17^th from 12:30-2:00pm EST in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/98105285349 (Password: SDFA23). Our guest speaker will be Michael Macy (Cornell University) presenting The Shallowness of Deep Division (see abstract and brief bio below, announcement attached). Lunch will be provided to those attending in person and a reminder email will be sent out closer to the date.

If you would also like to schedule a 30-minute 1:1 meeting with him before or after the seminar, please fill out the following Doodle poll by COB Monday, November 13^th and I will confirm times and location with a calendar invite: https://doodle.com/meeting/participate/id/bkoKOM6b. Please notify me if you need to meet over Zoom instead.

Abstract

Computational models reveal a tipping point in political polarization beyond which there is a potentially irreversible phase transition with two properties: 1) opinions become aligned across seemingly disparate political and cultural dimensions, and 2) existential threats to shared interests (like a lethal pandemic, catastrophic global warming, or aggression by a foreign adversary) have a divisive rather than unifying effect. This unraveling of the social fabric suggests partisan divisions that are deeply rooted in opposing ideologies. However, an online experiment suggests it may be the other way around. What appear to be irreconcilable differences in an increasingly polarized society may have arisen through a tipping dynamic that might just as easily have tipped the other way but for the luck of the draw among early movers. If so, the depth of the social fissure points to the shallowness of disagreements between tribal combatants whose vitriolic hostility is substantively unwarranted.

About the Presenter

Michael Macy is Distinguished Professor of Arts and Sciences at Cornell and Director of the Social Dynamics Lab. With support from the U.S. National Science Foundation, Google, Yahoo! Research, DARPA, IARPA, and the Korean National Research Foundation, his research team has used computational models, online laboratory experiments, and digital traces of device-mediated interaction to explore familiar but enigmatic social patterns, including network “wormholes,” circadian rhythms on Twitter and Spotify, racial discrimination on Airbnb, lifestyle politics, the polarization of science, network mobility, and partisan unpredictability. His research has been published in Science, PNAS, Science Advances, Nature Human Behaviour, American Journal of Sociology, American Sociological Review, and Annual Review of Sociology. 

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held on Friday, October 20^th from 12:30-2:00pm EST in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/98105285349 (Password: SDFA23). Our guest speakers will be Tom Fiddaman (Ventana Systems) and Angie Moon (MIT Civil & Environmental Engineering)  presenting If Vensim is the answer, what is the question? Reflecting on the future direction of the System Dynamics tool and user ecosystem (see abstract below, announcement attached). Lunch will be provided to those attending in person and a reminder email will be sent out closer to the date.

If you would also like to schedule a 30-minute 1:1 meeting with Tom before or after the seminar, please fill out the following Doodle poll by COB Tuesday, October 17^th and I will confirm times and location with a calendar invite: https://doodle.com/meeting/participate/id/e09LyWya.

Abstract

Once upon a time, data was scarce, simulation was nearly unheard of, there were few ways to build and use quality dynamic models, and models rarely gave direct input to decisions. This made it easy for tool builders and tool users to coevolve within their own disciplinary stovepipes. The scale of our problems, and hopefully our opportunities, means that isolation is no longer viable. System Dynamics modelers can increasingly benefit from new tools in data science, AI and machine learning, and many fields could benefit from SD knowledge guiding better dynamics, realistic behavior, and useful interaction with decision makers.

Our future could be bright, with AI assistants freeing modelers from boring tasks, raising the productivity of thinking about systems, and making model results accessible to users. Or, it could be dark, with “ChatMDL” rapidly generating the simulation equivalent of 3-legged chicken images, models with superficial validity but more propaganda value than predictive accuracy, faster than we can debunk them.

In this seminar, I’d like to explore the state of the System Dynamics tool portfolio and the requirements of modelers and model consumers. In passing, I will mention the near-term roadmap for Vensim, as well as the broader ecosystem of SD tools many of us use. But the real goal is to discuss the long-term vision for System Dynamics. How do we realize a future in which:

• it’s easy to make every model a Bayesian blend of structure and parameter priors from subject matter expertise and data likelihoods?
• aggregation is not a dark art, but automated in a flexible and principled way?
• every model run is a synthetic data experiment supporting decision making under uncertainty?
• support for exploration of the state space yields as much understanding as we get from analytical methods on simple models?
• we have the computing power to support these innovations, and
• we can explain what we’re doing to influence people to solve our biggest problems.

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held on Friday, October 13^th from 1:00-2:30pm EST (please note the time change) in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/98105285349 (Password: SDFA23). Our guest speaker will be Scott E. Page (University of Michigan) presenting Institutional Ensembles and Cultural Institutional Capacity (see abstract and brief bio below, announcement and paper attached). Lunch will be provided to those attending in person and a reminder email will be sent out closer to the date.

If you would also like to schedule a 30-minute 1:1 meeting with him before or after the seminar, please fill out the following Doodle poll by COB Friday, October 6^th and I will confirm times and location with a calendar invite: https://doodle.com/meeting/participate/id/dPYN5qAe. Please notify me if you need to meet over Zoom instead.

Abstract 

We construct a series of models within a systems framework to analyze the interdependence between a society’s composition of institutions and its cultural-institutional capacity: the knowledge, behaviors, beliefs, norms, and networks that enables institutions to operate. In our models, a society selects a mixture of institutions of various types to allocate resources and take actions. These include markets, hierarchies, democracies, community-based institutions, or even algorithms. These institutional choices contribute to the production of cultural-institutional capacity, and, conversely, cultural-institutional capacity influences how well each institutional type performs. Cultural-institutional capacity building can be self-reinforcing. Markets can produce greater capacity for markets. It can also be generic and improve all institutional types. Neither of these forms of capacity building necessarily produces efficient ensembles of institutions. Paradoxically, systems with both forms can result in the collapse of an institutional type that builds generic capacity.

About the Presenter

Scott E. Page is the John Seely Brown Distinguished University Professor of Complexity, Social Science, and Management at the University of Michigan, and the Williamson family Professor of Business Administration, professor of management and organizations, Stephen M. Ross School of Business; professor of political science, professor of complex systems, and professor of economics, LSA. In 2011, he was elected to the American Academy of Arts and Sciences. Read more here.

Please visit the MIT System Dynamics Seminars page for more information.

You are invited to attend the System Dynamics Seminar being held on Friday, October 6^th from 12:30-2:00pm EST in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/98105285349 (Password: SDFA23). Our guest speaker will be Jordan Tong (Wisconsin School of Business) presenting A Replication Study of Operations Management Experiments in Management Science (see abstract and brief bio below, announcement and paper attached). Lunch will be provided to those attending in person and a reminder email will be sent out closer to the date.

If you would also like to schedule a 30-minute 1:1 meeting with him before or after the seminar, please fill out the following Doodle poll by COB Friday, September 29^th and I will confirm times and location with a calendar invite: https://doodle.com/meeting/participate/id/dR1Wz7Eb. Please notify me if you need to meet over Zoom instead.

Abstract 

Over the last two decades, researchers in operations management have increasingly leveraged laboratory experiments to identify key behavioral insights. These experiments inform behavioral theories of operations management, impacting domains including inventory, supply chain management, queuing, forecasting, and sourcing. Yet, until now, the replicability of most behavioral insights from these laboratory experiments has been untested. We remedy this with the first large-scale replication study in operations management. With the input of the wider operations management community, we identify 10 prominent experimental operations management papers published in Management Science, which span a variety of domains, to be the focus of our replication effort. For each paper, we conduct a high-powered replication study of the main results across multiple locations using original materials (when available and suitable). In addition, our study tests replicability in multiple modalities (in-person and online) due to laboratory closures during the COVID-19 pandemic. Our replication study contributes new knowledge about the robustness of several key behavioral theories in operations management and contributes more broadly to efforts in the operations management field to improve research transparency and reliability.

About the Presenter

Jordan Tong is the Wisconsin Naming Partners Professor and Professor in the Department of Operations and Information Management at the Wisconsin School of Business.

Professor Tong’s research primarily employs mathematical modeling and experimental methods to investigate questions in operations management, analytics, and behavioral science. His research focuses on examining how human cognitive limitations interact with broader system dynamics to inform operations design. He has published in journals such as Management Science, Operations Research, Psychological Science, Manufacturing & Service Operations Management, and Production and Operations Management. He is currently an Associate Editor at Management Science and a Senior Editor at Production & Operations Management.

Professor Tong has taught undergraduate and Master’s-level courses in Operations Management, Operations Analytics, Supply Chain Management, Modeling & Optimization for Business Analytics, and the Psychology of Business Analytics. He received his PhD in Operations Management from the Fuqua School of Business at Duke University and his BA in Mathematics from Pomona College.

Please visit the MIT System Dynamics Seminars page for more information.

Attend the System Dynamics Seminar being held next Friday, September 29^th from 12:30-2:00 pm EST in the Jay W. Forrester conference room, E62-450, or via Zoom: https://mit.zoom.us/j/98105285349 (Password: SDFA23). Our guest speaker will be Jerker Denrell (University of Warwick) presenting Relative versus Absolute Aspirations (see abstract and brief bio below, announcement attached). Lunch will be provided to those attending in person.

If you would also like to schedule a 30-minute 1:1 meeting with him before or after the seminar, please fill out the following Doodle poll by COB tomorrow, September 22^nd and I will confirm times and location with a calendar invite: https://doodle.com/meeting/participate/id/eg2g48rd. Please notify me if you need to meet over Zoom instead.

Abstract 

Aspirations impact when managers search for new alternatives. Therefore, their level and adjustment to environmental conditions have important performance consequences. Past research has shown that higher aspiration leads to higher performance unless the environment is turbulent. When conditions can change quickly, long periods of search may not pay off. Using a simple and analytically tractable model, we show that when aspirations are defined in relative terms (being better than others), we get the opposite result: higher aspirations lead to higher performance. These contrasting outcomes are the result of externalities generated by relative aspirations: improvements by one agent can leave others unsatisfied. Our findings have interesting implications for goal setting for individuals and populations.

About the Presenter

Jerker Denrell grew up in Sweden, studied management, economics, philosophy and also some mathematics. He wrote a dissertation on game theory at Stockholm School of Economics but was converted by James March to think about learning and decision-making from a more behavioural perspective. He started his career at Stockholm School of Economics, worked at Stanford Business School, University of Oxford, and is now at University of Warwick. Jerker’s research focuses on learning processes and their implications. Instead of examining whether biases exist in how people process information, he has examined how the sample of experiences available to people can lead to systematic biases in choices and judgment. He also has a keen interest in how randomness impacts our lives and fortunes and how stochastic processes can explain what appears as regularities.