14th MIT-UAlbany System Dynamics Research Colloquium
Friday, May 4th, 2007
E51-063 & E51-085
MIT Sloan School of Management

Organizers: John Lyneis (MIT) and Ryan Taylor (UAlbany)

Time Presentation Speaker
9:15 AM Networking and Coffee   
9:40 AM Welcome and Opening Remarks  
9:45 AM Improving Hospital Operations Using Bar-Code Capture Data and System Dynamics Modeling Techniques Daniel Goldsmith
10:30 AM

Exploring the Relationship between Forecasting Skill and Decision Thresholds

Ryan Taylor
11:15 AM Dynamics of growth in the grid and off-grid power systems in Kenya Kate Steel
12:00 PM Lunch  
12:45 PM Economic Transition Management in the Iranian Cement Industry Navid Ghaffarzadegan
1:30 PM The End of Core: Should disruptive innovation in telecom invoke discontinuous regulatory response? Chintan Vaishnav
2:15 PM Maritime maquiladoras:  A system dynamics detective story on the tuna ranching industry in Mexico  Don Robadue & Raul del Moral Simanek
3:00 PM Networking and Coffee   
3:15 PM Supporting Transitions to Alternative Fuel Vehicle Markets: Policy Analysis Using a Dynamic Behavioral Spatial Model   Derek Supple
4:00 PM Closing Remarks and Table Function at Marriott   

 

Abstracts 

Improving Hospital Operations Using Bar-Code Capture Data and System Dynamics Modeling Techniques, Daniel Goldsmith

To better understand the factors that support or inhibit process improvement in a hospital setting, we conducted a study of one hospital’s attempt to implement a health information system (HIS) to reduce errors in medical treatment and manage material flows. Our analysis suggests that critical determinants of success in efforts to improve hospital efficiency include connections among key hospital staff, including doctors, nurses, and pharmacists, as well as patients. Building on these observations, we propose a dynamic model capturing the evolution of the interactions among the “physics” underling hospital operations, information technology (IT), and staff behavior.  We show that early success in one phase of process improvement can create unintended feedback in a later phase. We use a system dynamics model to examine losses in performance in these later phases. We then recommend management improvements in both materials and staff utilization and estimate the resultant cost-saving. As part of this analysis we explore opportunities to merge real-time operational data with feedback modeling to provide dynamic tools for hospital administration, risk management, and education and training. We believe that the major gains in HIS use will accompany new information gathering capabilities, as these capabilities result in collections of data that can be used to greatly improve patient safety, hospital operations, and medical decision support.

Exploring the Relationship between Forecasting Skill and Decision Thresholds, Ryan Taylor

This exploratory model is an initial step in modeling the relationship between forecasting skill and decision thresholds. It is hypothesized that components of forecasting skill (i.e. environmental uncertainty, knowledge, and reliability) affect the optimal decision threshold for a task.  Key concepts to be discussed are the Expanded Lens Model and components of forecasting skill, duality of error and decision thresholds.

Dynamics of growth in the grid and off-grid power systems in Kenya, Kate Steel

In many African countries there is a tension between grid and off-grid electric service provision and it is unclear whether a centralized or decentralized power system architecture will emerge.  This paper explores some of the dynamics of system development in Kenya, where poor grid infrastructure has resulted in a thriving private market for photovoltaic panels and a growing number of industries are investigating shifting to on-site generation.  The research is based on ethnographic interviews and observations in Kenya and uses System Dynamics modeling tools to analyze qualitative and quantitative feedback in the system.

Economic Transition Management in the Iranian Cement Industry, Navid Ghaffarzadegan

Last decade, a lot of countries managed a transition policy from centrally planned command economies to market economies, while experiencing different socio-economic side effects. After these years, it is still an important issue in the countries which are not completely adjusted to market economy style, to manage the transition process in order to experience less wild fluctuations in prices. This paper represents recommended policies for Iranian Cement Industry which will deal with economic transition in near future. Using a System Dynamics approach, this paper gives some insights into analyzing similar economic policy problems.

The End of Core: Should disruptive innovation in telecom invoke discontinuous regulatory response?, Chintan Vaishnav
             
In a highly abstracted conceptualization, both the public switched telephone network (PSTN) and the Internet consist of two components: the end-devices and the network that connects them. Traditional telecommunications regulation has assumed the presence of a network core that could be engineered to fulfill regulatory goals as well as a vertically-integrated industry structure that could meet regulatory obligations. In this proposal, we take the case of Voice over Internet Protocol (VoIP), the technology that enables voice communications over the Internet, and argue that disruptive trends in technology are eroding the control in the core that was traditionally assumed. This eroding control in the core has the potential to render the current VoIP regulation inadequate and unsustainable. We hypothesize that in the environment of eroding control in the network core (“The End of Core”), meeting regulatory objectives will require that future regulatory response be discontinuous from that of the past. We propose a system dynamics model to study the dynamic complexity surrounding the current VoIP regulation and to understand policy options for preventing undesirable outcomes. The model consists of four sectors: the consumer adoption sector for modeling demand, the industry structure sector for modeling supply, the regulatory compliance sector for modeling the level of compliance and the innovation sector for modeling innovation trends. The model endogenizes the technological change to the policy process.

Maritime maquiladoras:  A system dynamics detective story on the tuna ranching industry in Mexico, Don Robadue & Raul del Moral Simanek

Tuna ranching is a value-added economic activity along the coast of Baja California in Mexico involving the live capture and transport of migrating juvenile tuna to pens located near shore, where they are fed for a period of months then harvested and shipped fresh to Japan for the high-end sashimi market.  This is turn is nested within the entire global tuna fishery and processing business.  Little is known about the functioning of Mexican tuna ranching, compared to its Australian and controversial Mediterranean competitors, however it is thought to be sufficiently small scale and limited to be sustainable.  Our analysis and modeling exercise reveal no cause for complacency however.  There are several hidden factors and issues that might be equally or more important in determining whether the Mexican industry is sustainable than the lists of concerns found in popular descriptions of tuna ranching. A feedback perspective provided by both causal mapping and simulation is aiding a scientific assessment team to detect these vulnerabilities, reformulate its hypotheses and better target data gathering on industry performance and impacts.

Supporting Transitions to Alternative Fuel Vehicle Markets: Policy Analysis Using a  Dynamic Behavioral Spatial Model, Derek Supple

Designing public policy and/or industry strategy to bolster the transition to alternative fuel vehicles (AFVs) is a difficult challenge as demonstrated by historical failed attempts.  A broad-boundary system dynamics model with explicit spatial structure was previously developed to improve understanding of the most important hurdles faced in reaching a self-sustaining market. Using California as an illustrative testing ground, various entrant vehicle/fuel technology pairs are tested individually and in competition amongst each other.
Sensitivity analysis of endogenous feedback structure and a range of technical and behavioral parameters is presented to understand basic behavior and identify policy leverage opportunities or the need for further calibration. The simulation model is used to test the impacts of policies individually and then to identify synergistic multi-policy combinations for success.  Using plausible parameters, model simulations achieve successful AFV diffusion but require long time periods prior to significant penetration of the vehicle fleet.  Findings suggest difficulty and substantial cost in using policy to speed the AFV market beyond multiple tipping points. Yet several policy insights reinforce the importance of designing policy cognizant of the system structure underlying its behavior.


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

Last edited by NG 11/08/2010