15th MIT-UAlbany System Dynamics Research Colloquium
Friday, November 16th, 2007
Room E25-11

MIT Sloan School of Management

Organizers: John Lyneis (MIT) and Navid Ghaffarzadegan (UAlbany)

Time Presentation Speaker
10:00 AM Quality Improvement Dynamics Gokhan Dogan, MIT
10:45 AM Automated Model Generation Andy Whitmore, UAlbany
11:30 AM How to maintain a growing campus without spending: working in a world of deferred maintenance John Lyneis, MIT
12:15 PM Lunch  
1:00 PM Implementing Change in Organizations – Supporting and Limiting Factors Nici Zimmerman, UAlbany
1:45 PM Profit Cycles in the Airline Industry Kawika Pierson, MIT
2:30 PM Break   
2:45 PM Eliciting Maps from Qualitative Data: A Study of Federal Open Market Committee's Collective Judgment Building Process Hyunjung Kim, UAlbany
3:30 PM TBA Jason Jay, MIT
4:15 PM Closing Remarks and Table Function at Marriott   

 

Abstracts

Quality Improvement Dynamics
Gokhan Dogan, MIT

Product quality improvement process includes problem solving before and after the start of production. Using qualitative and quantitative data from a major manufacturer, we empirically investigate the dynamics of quality improvement process for multi-generation products. We then test alternative policies with a simulation model.

Automated Model Generation
Andy Whitmore, UAlbany

Over the last decade storage capacity and processing ability have increased dramatically in power while significantly falling in price.  At the same time organizations have come to understand the importance of maintaining and leveraging large quantities of electronic data whether it is to improve customer service and internal operations or to comply with applicable legislation.  These conditions are beginning to give rise to the possibility that some parts of the modeling process could be automated.  This presentation will demonstrate an application that is designed to filter through organizational databases, find model structure hidden within the data and output a simulating Vensim model.  The hope is that by automating the modeling process, or parts of it, System Dynamics models will be available to a wider audience, more grounded in data, and much quicker to construct for large systems.     

How to maintain a growing campus without spending: working in a world of deferred maintenance
John Lyneis, MIT

Much recent work in System Dynamics has emphasized the dynamics that can result when organizations are placed under significant time and budget pressure.  Here, I study one organization’s approach to the repair and maintenance of its buildings, and find evidence of a work culture that is highly reactive.  Attempts to improve operations have had some success, but in the presence of continued budget pressure management strategies are limited.  A simulation model is developed based on both qualitative and quantitative data and is used to test policy alternatives. 

Implementing Change in Organizations - Supporting and Limiting Factors
Nici Zimmermann, UAlbany

My dissertation focuses on organizational change. Within this area, human reactions to changes are of particular interest for me. I want to analyze how organizational changes create reactions on the human side, and how these reactions feed back to the organizational side. It will also be interesting to see how these relationships are influenced by pressures from outside, i.e. from the organization’s environment. The research will be supported by a case study of recent changes at the New York Stock Exchange where resistance reactions as well as tremendous pressures for change from outside can be observed.

Profit Cycles in the Airline Industry
Kawika Pierson

Expanding upon existing system dynamics work, this model aims to investigate the causes of profit cycles in the airline industry.  It adds several previously unexplored control mechanisms that modern airlines employ to stabilize their profits and briefly explores the implications of cyclical profits to the case where some carriers can maintain a lower cost structure than others.

Eliciting Maps from Qualitative Data: A Study of Federal Open Market Committee's Collective Judgment Building Process  
Hyunjung Kim, UAlbany

System Dynamics relies heavily on qualitative data to build simulation models, but there has not been much effort to systematically elicit model structures from qualitative data. The presentation focuses on a recent effort to incorporate conceptualization and validation practice from ethnography to System Dynamics so that we become theoretically and methodologically more robust in qualitative modeling. Using Federal Reserve's monetary policy making process a case and verbatim transcripts from the Federal Open Market Committee meetings as the data, the study describes a way to elicit causal loop diagram from raw qualitative data and generates a thick description of the collective judgment-building process.


[ Back to the previous MIT-Albany colloquia ] [ Home ]

Last edited by NG 11/08/2010