Spring 2017 System Dynamics Student Colloquium

You are cordially invited to attend the spring 2017 SD student colloquium. The colloquium is an opportunity for students from New England universities to present their research involving system dynamics, and to receive feedback from leaders in the system dynamics community.

Event Information

Date and time:

Friday, May 19, 2017

10:00 am to 5:00 pm


MIT building E62, Room 450

100 Main Street,

Cambridge, MA 02142


To register please complete the form available at:


Maximum Likelihood Schedule


9:45 - Tea and coffee

10:00 - Welcome + Overview

10:10 - Sahar Hashmi, MIT: Systems of Adherence to Diabetes Treatment

10:50 - Mahdi Najafabadi, Albany: Modeling Open Data Ecosystem

11:30 - Helene Finidori, Hull: Pattern Literacy in support of Systems Literacy


12:00: Lunch

12:20 - Sergey Naumov, MIT

1:00 - Babak Bahaddin, Albany: Interacting Decision Biases in Personal Economic Planning

2:00 - Xin Zhang, MIT: Investment Dynamics of the Chinese Real Estate Market


2:40: Break and Group Photograph

3:00: Erik Landry, MIT: The Capability Trap: Prevalence in Human Systems

3:40: Yining Bai, New Mexico State University: The future of Acequia: the sustainability and mutualism of traditional irrigation community

4:20: Leo Barlach, MIT: Dynamics of Renewable Energy Adoption

4:50: Closing


Leo Barlach

Graduate student at the System Design and Management program at MIT, with a focus on industrial sustainability.


Renewable energy is one of the most important technologies for developing a carbon neutral society. However, their variable production nature creates unique challenges for the grid in how to provide constant supply that meets demand at all times at low cost. Several studies have shown how the marginal economic value of wind production decreases as wind penetration increases, and how variable energy production favors intermediate sources such as natural gas. Few of those studies, however, use dynamic modelling to understand how these effects interact with each other. For my thesis I developed a dynamic model of the electric system in Texas and mostly confirmed some of the expected behaviors, with the caveat that they are highly dependent on the learning curves for each technology.

Helene Finidori is a doctoral student at the University of Hull, Business School - Center for Systems Studies in the UK, a member of the Evolution, Complexity and Cognition Group at the VUB, Free University in Brussels, and  a senior research fellow at the Schumacher Institute.

Pattern Literacy in support of Systems Literacy

To understand and adapt to the world around us, and to address the challenges that we are faced with in our ever changing and uncertain environment, we must get a grasp of the inner workings of our ecological, socio-environmental and socio-technological systems, and of how change unfolds, not only in their ‘mechanical’ aspects, but also in their political, philosophical, psychological, emotional, existential, relational, anthropological, epistemological dimensions.

The skills that this requires may be thought of as Systems Literacy. Systems Literacy involves a set of ‘sensing’ and mediating capabilities and tools to (1) make sense of salient patterns and weak signals in growing volumes of information and knowledge, and (2) leverage agency and the complementarity of perspectives, knowledges, know-hows and technologies across the board, and help change agents to enter in resonance with each other and their environment.

My research explores the properties of patterns as versatile units of cognitive processing and how the development of pattern literacy could support the development of systems literacy. It lays the ground for a pragmatism which enables change agents and systems practitioners to inter­operate from where they are located, linkimg theory and praxis, with an eye on what is around and the evolving whole. It explores pathways on how communities involved in systems sciences and transdisciplinary interventions could work together to develop such a pragmatism

Yining Bai is a graduate student in NMSU Water science and management program. Her research applies system dynamics modeling to explore the water balance in a traditional irrigation community under water resource stress from climate changes and society structure changes.

The future of Acequia: the sustainability and mutualism of traditional irrigation community

There is evidence that traditional irrigation communities in New Mexico, United States, which are also known as acequias, benefit the state’s socio-economic-hydrology systems in many respects. However, despite their long-term resistance to their arid environment these communities are declining over time. This paper tries to capture dynamics of political economy responsible for this decline and investigates policy options that may help to turn the trend.

Mahdi M. Najafabadi is a PhD candidate in the Informatics department, University at Albany (State University of New York). He is interested in using systems thinking perspective to tackle complex information-related problems in governments and societies. Mahdi is also interested in leveraging the Information Technology (IT) to address the constant changing needs in modern organizations. Mahdi uses computer simulation to analyze long term policy impacts.


Modeling Open Data Ecosystem

The main idea behind opening government data is to allow entrepreneurs create value from government data by eliciting new information use out of released datasets. However, experience shows that just opening the datasets by the government is not likely to set the stone rolling for the use of open data benefits across the value-chain down to the beneficiaries in the society.

Thinking of the impacts of open data program in a macrocosm in which the government, the society, and the flow of open data exist, we can come up with a model that is composed of some actors at the governmental and at the societal levels interact and create value once the data is released by the government. This research aims to contribute to this line of thinking by employing computer simulation techniques, particularly system dynamics, to study the structure and characteristics of open government data ecosystems. My goal is to better understand what are the key factors and processes needed to promote an effective and sustainable open data ecosystem. I also aim to gain insights and identify both success and failure modes for open data initiatives.

Babak Bahaddin got his bachelor degree from Civil Engineering department at Sharif University of Technology. During his undergraduate studies, he took some courses from the university's business school, especially courses about System Dynamics. Since then, he has been working in this area mostly as a student, but sometimes as an instructor, as a consultant, or as a researcher. Currently, he is a third-year PhD student in the Informatics department of University at Albany, SUNY. His specialization is Data Analytics. Besides coursework, he works for the System Dynamics Society as a graduate assistant. Currently, he is more involved with studies on best strategies in water resource management in macro- and micro level.

Abstract: Behavioral Economics has a rich tradition of empirical studies involving the effects of personal decision biases involving trade-offs between future and present utility values. Although research in the area has identified several psychological biases in the decision making process, most research explores one bias at a time, given the computational complexity of considering more than one, among other reasons.  This program of research proposes to create a numerical platform for exploring the implications of how countervailing biases may interact to create unexpected outcomes when two or more biases are present at the same time.  It will use life-time savings decisions as a theoretical domain since both theory and empirical studies are well-developed. Our program of research involves five main stages: 1) analyzing the “Individual Utility Function” model in behavioral economics, 2) developing a simulation platform to explore strategies to maximize lifetime utility incorporating four biases widely-explored in the behavioral economics literature, 3) Using Platform to Explore Misperceptions of Parameters, 4) Elaborate the Platform to Explain the Four Biases, and 5) reflect on the process and results to contribute to the field of behavioral economics. In this paper, we introduce these five steps, and also discuss initial progress through the first three stages.

Erik Landry: Erik is a Master of Science candidate in MIT’s Technology and Policy Program and a candidate for the MIT Sloan School of Management’s Sustainability Certificate.  He has worked on organic photovoltaics at Argonne National Laboratory and on concentrated solar power and renewable grid integration at the United States Department of Energy’s Solar Energy Technologies Office.  He is now more broadly interested in corporate sustainability and the use of system dynamics in socio-technical systems to inform smart policy decisions.

The Capability Trap: Prevalence in Human System

What do abused children, the fatal collapse of the I-35 bridge connecting Minneapolis and St. Paul, and the United States health care system all have in common?  We suggest that these examples arise from systems caught in the capability trap, in which pressures to boost short-run system performance lead to greater work effort at the expense of investment in maintenance, process improvement, and learning.  As the organization’s capabilities erode, performance falls further, leading to even greater pressure to work harder and even lower investment in capabilities.  However, the theory of the capability trap (Repenning & Sterman, 2001, 2002) was originally formulated in the context of maintenance and process improvement in manufacturing and petrochemicals, and empirical work to date has centered on such systems.  We hypothesize here that the capability trap is more prevalent and maps equally well onto various social systems.  We provide an initial assessment on its operation in several domains – critical infrastructure such as water supplies, electric grids, and transportation, focusing on mass transit; social services, focusing on foster care; education, crime and  prisons; and healthcare.  Rather than providing definitive evidence for each case, we seek to encourage deeper research into these capability trap dynamics and how they can be overcome.

Sahar Hashmi, MD is a PhD Candidate at MIT with a focus on healthcare systems management.


Preventing the complications and improving the quality of life of patients with diabetes along with better strategies to save cost is a big challenge for the healthcare system. We reported in our previous study that the system of adherence, if practiced, leads to better quality of life in patients with diabetes and could reduce the emergency visits and hospitalizations. The insurance companies and the government payer programs play a key role in the system of management of patient with diabetes. The question is how can this system of adherence be made efficient enough over time to help reduce the number of emergency visits and hospitalizations in patients with diabetes? Our model evaluates the cost allocation policies of five different insurance plans and their impact on improving patients’ lives and saving millions of dollars of the healthcare system in the United States.


If you have any questions, please contact:

Jad Sassine: jsassine@mit.edu

James Houghton: houghton@mit.edu