Voice Over Internet Protocol (VOIP) is the fastest-growing market in the United States. VOIP technology provides telephone-like service without the restrictions of telecommunication regulations. State governments fear that more calls traveling over Internet protocol (IP) enabled phone services will impact on the heavily-taxed fixed line phone service, which means less tax revenue to support crucial public services. However, states are struggling with how to tax VOIP services and reduce the impact of VOIP development. In this paper, we build a system dynamics model to gain insight into interactions between the VOIP market, traditional phone market, and tax policy. Two tax policy tests reviewed in this paper show tax policy does not significantly affect market competition. In addition, we show government is able to collect sufficient funds when applying new tax policy. We believe the model can help policy makers find a better way to collect maximum tax revenue with less impact on the market.
Market and technology changes have brought about new characteristics of product development. One of the most significant changes from the traditional to the new paradigm is the change from sequential and collocated development processes to concurrent and distributed processes. Although some researchers have built models of development processes and product development performance, most of these studies are about collocated development projects where the coordination between tasks is not explicitly studied. Consequently, there is a need to model the relationships between development processes and project cycle time in the distributed context, with special attention to the coordination between tasks. With the support of a design company, we developed and validated the model with data from mobile phone projects.
Compared with many preventable epidemics, how did a relatively insignificant disease like SARS develop into an international scare? This article describes the application of system dynamics to understand the SARS epidemic in Beijing. The powersim model simulates the structure of transmission dynamics and factors that impact the epidemic. Here, the probable impacts of changes in the system delays, including delays to quarantine, delays of disease diagnose, and the authorities epidemic information transmitting delays, are discussed. The model aims to present detailed understanding of delayed feedback mechanisms inherent to eliminate the misperceptions of basic dynamics, and then to design high leverage policies for preventing SARS. The article concludes that an open and transparent public information system is the most powerful weapon to curb SARS panics. The governments prompt epidemic information feedback system and relatively instant strong quarantine policies have substantial impacts on containing SARS epidemic.
This article intends to conceptualize the problem of low interagency collaboration in implementing local social welfare policies into a system dynamics model. This conceptualized model is introduced to explore the possible factors facilitating and hindering interagency collaboration between Department of Social Welfare (DSW) of city government and Social Affairs Section (SAS) of district office in both Taipei City and Kaohsiung City of Taiwan. The model combines insights from policy implementation theory, qualitative data from interviews with DSW and SAS staffs, and system dynamics literatures. Although this model is not yet formulated, several insights have been obtained. This study finds that the institutional design has made cooperation between two agencies difficult. Such an interagency relationship is reluctant compliance rather than partnership. This article argues that a homogeneous realization of the cooperation pattern among implementation participants is necessary for building effective interagency relationships in policy implementation.
We are attempting to create an agent based System Dynamics model of sustainable organizational change. A framework is proposed for comparing the experience of sustainable organizational change as a means of gathering other experiences to help create the model. A significant sustainable organizational change was created at BP's Lima refinery using The Manufacturing Game that was created at DuPont using a System Dynamics model of manufacturing reliability. While this change at BP Lima has survived for over 10 years, two changes of ownership and four sets of management, the changes at DuPont and another BP asset only lived 7 years and 1 year before losing the momentum of the change. At the conclusion of this talk, we will have a panel discussion on the reasons for sustainability with audience participation.
By addressing the need for organizational change, The Manufacturing Game(r) has enabled manufacturing facilities around the world to vastly improve their reliability practices, resulting in enormous gains in a short period of time. Our unique, integrated approach, based on a System Dynamics model, helps organizations realize their full potential by encouraging front-line workers to better understand their role and take responsibility for their performance as it relates to the functionality of the entire plant. This bottom-up approach to organizational change has been effective at not only improving reliability, but more importantly, sustaining improvement. Over 27,000 people from companies like DuPont, BP, Honda, Whirlpool and ExxonMobil have used The Manufacturing Game(r) to reduce failures and lower costs. The game is a board game played with poker chips, play money, and dice. It is a fun way to learn as many have experienced playing the beer game.
A model of infectious diseases has been developed for integration within a larger simulation structure to assess the interdependencies of critical infrastructures. The model has been parameterized to model a disease outbreak a large metropolitan area. The model subsequently calculates the spread of the infection and the influence of vaccination policies, quarantine and isolation procedures. Consequences are deaths, illnesses, and a variety of economic costs. Sensitivity analysis is a statistical technique to investigate how uncertainty in the input variables affects the model outputs and which input variables tend to drive variation in the outputs. Such analysis can provide critical information for decision makers and public health officials who may have to deal with the realities of a virulent infectious disease. This paper presents the results of preliminary analyses of the effects of inputs to the infectious disease model on the calculated consequences.
The Critical Infrastructure Protection Decision Support System (CIP/DSS) simulates the dynamics of individual infrastructures and couples separate infrastructures to each other according to their interdependencies. For example, repairing damage to the electric power grid in a city requires transportation to failure sites and delivery of parts, fuel for repair vehicles, telecommunications for problem diagnosis and coordination of repairs, and the availability of labor. The repair itself involves diagnosis, ordering parts, dispatching crews, and performing work. The electric power grid responds to the initial damage and to the completion of repairs with changes in its operating characteristics. Dynamic processes like these are represented in the CIP/DSS infrastructure sector simulations by differential equations, discrete events, and codified rules of operation. Many of these variables are output metrics estimating the human health, economic, or environmental effects of disturbances to the infrastructures.
A generic representation of the telecommunications infrastructure in a metropolitan area designed to be integrated into a much larger simulation of the seventeen key infrastructures[1] has been implemented in Vensim[2]. This Critical Infrastructure Protection Decision Support System (CIP/DSS) is designed to provide insights for the Department of Homeland Security (DHS) in making decisions about investments related to critical infrastructure protection[3]. Although a system dynamics representation was well suited to representing the dynamics and interdependencies in this complex system of systems, it was recognized early on that collaborations with key infrastructure domain experts and organizations would be important to the success of the project. This paper summarizes the results of a collaborative effort with Bell Laboratories, Lucent Technologies to leverage a detailed switched network simulation to inform the telecommunications system dynamics model in CIP/DSS.