Crowd Control is a function generally associated with the police more than the military. However, the Canadian Forces are occasionally asked to intervene in riot situations either in Canada, in support to Federal, Provincial and Municipal Governments, or overseas, during Coalition operations. Thus, there is a need to understand crowd behaviour and to determine optimal intervention strategies for crowd control. The Canadian Forces have skills and resources that might be called upon if a situation gets out of control and must be prepared to deploy on short notice. A model has been developed that can be used to understand these events in the time dimension both inside the event and from event to event. The model has been developed theoretically and face validated using data from two case studies. The model is required to evaluate appropriate tactics such as the employment of non-lethal weapons, and as a training simulator for strategic and tactical commanders.
In the modern information based society, failure of software systems can have significant consequences. It has been argued that increased attention to testing activities during the software development process can mitigate the probabilities of system failure after implementation. However, in order to justify investments in improved testing, the economic impacts of improper testing should be identified. In this paper, we propose a systematic approach to the evaluation of the economic impacts of software testing. The main factors affecting software testing are identified, and a computer simulation model is developed to investigate different testing scenarios. Usefulness of the suggested approach is demonstrated through several exploratory simulations. The results prove the utility of the System Dynamics modelling approach in building better understanding of the impact of software testing. Implications for software development practitioners, researchers, customers of software products and software support organisations are also discussed.
In this paper, we propose a new approach to network bandwidth estimation based on System Dynamics modelling. The paper discusses existing approaches to bandwidth estimation and network capacity planning. Limitations of these approaches are presented and the case for using System Dynamics is made. Applicability of the proposed approach is demonstrated through a real world network planning project for a distributed logistics application. A practical computer simulation model was developed to predict bandwidth requirements for the projects network. This model provides system planners with the ability to test different possible scenarios in order to make informed decisions about the system architecture. We show through practical results of the simulation runs and the insights gained during the process that the System Dynamics approach offers an effective solution to the problem of network bandwidth estimation and system planning. The paper concludes with a review of the results and pointers for further research.
We will explore how to value using modern financial techniques the development of new alternative energy technologies (AETs) given uncertainty. Uncertainty in developing AETs derives from: (1) the reduction in installation cost of new generation capacity as experience with the technology is gained, i.e. the learning curve (2) oil and natural gas price cycles; and (3) other macroeconomic and geopolitical forces, particularly the behavior of national oil companies (Aramco, PDVSA, PEMEX, etc.). Evaluating a new AET properly requires representing these uncertainties as well as an investment valuation approach that works well under high uncertainty. In particular, we propose to adapt the real options methodology to value the potential return from developing AETs using stochastic system dynamics models representing the uncertainty in both the learning curve and the fossil fuel price cycles.
The complexity of modern networked systems has negative consequences in the form of intended and unintended security incidents. Information security is not the first field to grapple with such challenges. In safety, incident learning systems (ILS) have been used to control high risk environments. Many of these systems, such as NASA's Aviation Safety Reporting System, have demonstrated considerable success while others have failed. Prior to implementing ILS in information security, it is prudent to learn from experiences gained in safety. We use System Dynamics to investigate how factors such as management commitment, incentives, recriminations and resources affect a safety incident learning system. We find that the rate of incidents is not a suitable indicator of the state of the system. An increasing or decreasing incident rate may both be caused by either increased or decreased security. Other indicators, such as the severity of incidents, should be used.
Designing public policy and industry strategy to bolster the transition to alternative fuel vehicles (AFVs) is a formidable challenge as demonstrated by historical failed attempts. The transition occurs within a complex system with many distributed actors, long time delays, several feedback relationships, and multiple tipping points. A broad-boundary, behavioral, dynamic model with explicit spatial structure was previously developed to represent the most important AFV transition barriers. In this work, the integrated model is parameterized for various vehicle platforms. Structural and parametric sensitivity analyses are used to build understanding of system behavior and to identify policy leverage points. The qualitative impacts of policies are tested individually and then in combinations to find synergies. Under plausible assumptions and strong policies, successful AFV diffusion can occur but requires several decades. Findings indicate that some commonly suggested policies provide little leverage and are quite costly. The analysis demonstrates the importance of designing policy cognizant of the system structure underlying its dynamic behavior. To reach a self-sustaining market, coordinated portfolios of policy instruments must simultaneously foster the development of consumer familiarity, well-distributed fueling infrastructure, and vehicle manufacturer knowledge at similar rates and over long enough duration to surpass thresholds in these complementary assets.
Fifteen years ago, Jay Forrester laid the cornerstones for a more effective kindergarten through 12th grade (K-12) education based on system dynamics. In this paper, teachers and other educators who have been implementing system dynamics and systems thinking in schools across the United States reflect on their progress. Although all of the educators have been encouraged and inspired by student engagement and insight using system dynamics in their classrooms, wider adoption has encountered obstacles. Strategies to overcome them include: improving the quality and quantity of system dynamics curriculum materials and training opportunities for teachers, integrating the use of systems thinking tools with system dynamics simulation to give students the full benefit of both, seeking ways to work within the K-12 institution to effect change, and working together to learn from successes and mistakes.
Contrary to S-curve diffusion theory, historical introductions of alternative transportation fuels (ATFs) exhibit a variety of adoption patterns. Analysis of ATF introductions in the market place of natural gas in Argentina and New Zealand and ethanol in Brazil reveals that the aggregate dynamics cannot be traced back to a single dominant mechanism of change. ATF diffusion embodies several coevolutionary processes, including: the development of the vehicle installed base, consumer preferences and driver behavior, the evolution of technology and complementarities, such as a fueling infrastructure, and the transformation of fuel and automotive supply chains. Further, their diffusion is conditioned by institutional contexts. A behavioral dynamic model with a broad system boundary helps understanding failures and successes of ATF diffusion. While successful diffusion, such as promised by the Brazil case, is possible, the analysis reveals complex dynamics, requiring long periods of commitment and coordination across various types of actors. The paper develops initial steps towards a framework for studying the rich dynamics of socio-technical systems change. Central in such a process based framework are the mechanisms within interorganizational fields, capturing decisions and actions from consumers, organizations across industries and policymakers, and including the system-physiological aspects. We discuss implications for policy and strategy.
In various articles and books, Kaplan and Norton maintain that use of a Balanced Scorecard (BSC) will increase an organization's ability to execute its strategy and therefore ultimately improve its performance. They substantiate their hypothesis with numerous cases for which they report breakthrough performance. Nonetheless, published empirical evidence for the BSCs positive impact on performance is sparse.
This article aims to contribute to the empirical research on the BSCs performance impact describing a laboratory experiment. Using a computer-based feedback-rich micro-world, the subjects were placed in a top manager position. Their task was to implement a given strategy as best as they could, which meant to translate strategy into operational decisions over a period of 10 years. The experiment group was equipped with a BSC management cockpit that was carefully tailored to the strategy, while the control group had to rely on traditional reports as information source.
The experiment data are used to test the hypothesis that subjects provided with the BSC cockpit perform better than the control group. Statistical analysis shows that this hypothesis could not be rejected. The BSC cockpit indeed had a positive impact on performance. Some possible explanations for this finding are discussed and issues for further research are outlined.
The objective of this paper is to develop and evaluate a micro-economical microworld which will allow policy makers to gain more insight in parameters that influence the Belgian fishery fleet structure.
In a later stage, this microworld may contribute to the process of developing a long-term strategy for the Belgian fishery sector, serving as a laboratory for ex-ante evaluation of possible strategies. (Keys, Fulmer, and Stumpf 1996; De Geus 1997) By visualizing decisions and strategies (Morecroft 1999), it generates insights about fleet dynamics in response to a changing environment and policy changes.