This paper discusses the benefits of having an interchange standard for system dynamics models, why XML is a good candidate on which to build such as standard, and how the development process may take place through community-wide participation. The paper also presents XMILE, a prototype model interchange standard, as a proof of the concept.
Most dynamic decision making tasks include assumptions which have a huge uncertainty attached to them. Organizations are inherently complex. The combination of uncertainty and complexity results often in a sub-optimal decision. This paper emphasises on the usage of probabilistic system dynamics (SD). The focus of probabilistic SD is to represent the behaviour of uncertain variables in a realistic manner. The information generated by probabilistic SD could produce complete information thereby improving the mental models of decision makers. Many SD models use deterministic values of variables. However, determinism is untrue for real business settings. In order to test the effectiveness of probabilistic SD on managerial decision making, this study aims at conducting a series of rigorous and controlled experiments. Specifically it tests the usefulness of (1) system dynamics itself, (2) model validation techniques and (3) probabilistic system dynamics on decision-making. Furthermore, these experiments are conducted in two settings (1) using a simple model and (2) using a complex model. It is hoped that probabilistic SD would be instrumental in producing relevant information that would help in improving managers mental models, especially in complex scenarios. This in turn will result in better decisions under uncertainty in complex business environments.
If junior doctors are to work significantly fewer hours in the future, how can they still receive full training and continue to provide necessary levels of medical service to patients? Historically, excessive hours have been a way of the life for junior doctors worldwide, but New Deal regulations, a revised junior doctor contract, and the EU Working Time Directive are changing this. A project at Derriford Hospital in Plymouth is researching the nature of quality and effective training, and constructing SD models to yield insights and eventually support operational decision-making. This has already yielded significant insights for those at Derriford wrestling with this seemingly impossible task, including, the circularity between junior doctor training, consultants service and their training-supervision role, and the quality of training provided, and the likely importance of recruiting outside the progression process in addressing service imbalances. It also highlights some of the special challenges in projects where there are many stakeholders, political agendas, and a continuously changing environment.
Extreme Events are low probability, high consequence events, often resulting in billions of dollars of damage each year in the United States. Natural hazard issues connect experts in the natural science and social science, which complicates the problem for policymakers who may have balance multiple objectives as well as short term and long term goals. The recent devolution revolution trend in government has made its way to natural hazard policy domains. There is more pressure on local communities to create and implement mitigation plans that will promote long term sustainable development at the local level. The conceptual model for this research project explores the primary mitigation policy alternatives and depicts the "false sense of security" trap, with endogenous explanations, in a stock and flow feedback structure.
Our paper presents a model of economic impacts arising from disruptions to critical infrastructures. This model is a component of the Critical Infrastructure Protection Decision Support System (CIP/DSS) which simulates the dynamics of a set of interconnected individual infrastructures. We use factors of production (such as energy, telecommunications, and labor) from the CIP/DSS model to estimate the effects of interruptions to these infrastructures. The system dynamics approach we use is compared to equilibrium-based approaches such as input-output modeling. This method allows an understanding of the economic benefits of various protective measures. We incorporate non-equilibrium dynamics that arise from these disruptions to provide values for various economic impacts such as lost revenues and lost sales. The results from a disruption due to an infectious disease outbreak are presented. We show that the effects of quarantine dominate the overall economic impacts in a number of cases.
Accounts of the real-world use of system dynamics as a policy evaluation tool in macro-economic management are relatively rare. This paper offers an overview of current research being undertaken for the government of the State of Sarawak in E. Malaysia where an SD model is being formulated to inform the States future economic and social planning to 2020. Although still a work-in-progress, enough has been achieved to enable an interim account of the research to be written. Positive engagement with State government officials at the highest level has put system dynamics on the map in this corner of SE Asia.
Distribution must make a decision regarding its role in the specialty contracting supply chain. It can continue its historical role as wholesale/retail combination and hope for profitability, or it can choose to manage the channel by providing low cost products and services.
Profitability can only come through system productivity. System productivity depends on recognition and elimination of waste in the current operations and can be further improved by operational process innovation.
The cost drivers (CDs) of distributors can be impacted by identifying and addressing internal inefficiencies, effects of customer interactions, and the impact of suppliers on price and delivery. By managing the following elements, distributors can improve their bottom line by better than 30%:
1. First-time pass yield of order taking and delivery
2. Identification and reduction of waste
3. Customer point of entry
This paper suggests a methodology for improving the system productivity through management of these elements.
We still know very little about the long-term learning patterns of organizations. Analysis tends to favor the more immediate factors over more distant ones. We focus on synchronic portrayals of the organization while ignoring diachronic representations.
The model presented here analyzes changes in the state of the organization over time. It describes and investigates the totality of forces and actions that generate the organization's dynamic. It offers a speeded-up aging of the organization intended to bring out, over time, the counter-intuitive effects of decisions. Moreover, it endeavors to identify the cost drivers that contribute to increasing or shrinking the firm's profits.
We have used the meta-model that we developed to derive an application model whose purpose is to reproduce the long-term life of an organization. Our simulation speeds up the aging of the organization, enabling us 1) to show the counter-intuitive effects of decisions over the long term versus the short term, and 2) to highlight the cost drivers that generate hidden costs. Through its decisions, the firm gives rise to its own factors of development and decline: its own actions eventually change both the organization's health and its properties.
Previous research has shown that individuals fail to understand the basic building blocks of complex systems such as stocks and flows, feedbacks, and time delays. This paper presents three empirical studies intended to understand why individuals misperceive the relationships between stocks and flows. We used problems that were quite familiar to the participants, interventions to motivate participants to think harder in the problem, simplifications of graphs and direction of attention to specific aspects of the graphs. The results seem to disclose some of the mechanisms that individuals use to make their inferences about the graphs. That is, individuals attend to the most salient features of the graphical representation to make their inferences about the stock in the task. Does this really imply a misunderstanding of stocks and flows? We believe the further research needs to address this problem in realistic presentations rather than graphical representations.
In this paper we discuss the way in which dynamic modeling can be used to deal with front-end, back-end and integration issues in current high-tech virtual supply chains (SC).
In a first part of the paper we review and propose dynamic modeling options to connect customer value to business targets. This is done by explaining how to characterize target market by formalizing what are often informal but deeply held beliefs about what drives their customers' purchase decisions. We explain how dynamic models may help to connect planned investments to expected improvements in the customer's perception of the product critical attributes and thus increase sales, revenue, and market share.
In a second part of the paper we review and discuss the operational and financial effectiveness of existing virtual tools used in supply chain integration. We discuss how dynamic modeling may help to obtain a comprehensive model of supply chain integration. A modeling effort that can be used for the analysis of the effectiveness of various levels of integration.
In a third part of the paper we discuss and explain experiences in modeling different types of supplier contracts to accomplish varying degrees of security and flexibility.